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good morning everybody thank you so much

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for agreeing to participate

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in this effort

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we are

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doing this as one of our workshops

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without walls which is a

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tradition here at nai we think we

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invented it and we have done it for a

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huge variety of topics and with great

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results so

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let me give you my own personal

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perspective on why astrobiology why now

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i am not a virologist although i

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appreciate viruses and i think i'm

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seeing them everywhere in my own work um

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but uh i hold the position that uh the

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late dr barry

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blumberg held and of course he was a

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nobel uh laureate uh winning uh

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virologist and chemist and uh who worked

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extensively of course with um hepatitis

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and various other

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uh aspects of medical virology but who

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was of course extremely passionate about

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astro

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director of the institute i now had

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we are in our 20th year and nai is going

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away as an entity and being replaced by

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a new way of organizing astrobiology

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within nasa

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but i have always felt since barry

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passed away and he was a good friend of

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astrobiology

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and a good friend of mine

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and at the time he passed away

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we were

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in the process of sort of pre-organizing

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an effort

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to do a field trip for the

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uh astrovirology focus group uh into

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caves to actually look at what the uh

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vyram situation might be in cave

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environments which is where i typically

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work and do primarily

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bacteriological and archaeal

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studies so when barry passed away

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of course the plans for that halted

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and so

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before we sunset the institute i would

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like to uh you know do something to

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honor his great work in that field and

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his passionate devotion to astrobiology

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and his faith in uh pursuing the

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astrovirological aspects of astrobiology

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which i think are extremely important

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and have not received the attention that

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many other areas of astrobiology have

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on top of that of course why now

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part of the reason is because

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for those of you not familiar with the

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nasa and its processes

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one of the things that governs what we

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choose to do in science and missions

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is a every 10-year

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so-called decadal study that happens

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within all of the four major science

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branches of nasa so nasa is comprised of

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a

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um

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advisory and assessment activity by the

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national academy of sciences

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so the nrc or whatever it's calling us

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itself this week the academies are the

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entity that actually does this

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assessment and produces a

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large and um very uh

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attention-getting document

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and by attention-getting i mean that uh

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congress pays attention to what

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the guidance is that we receive from the

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national academies and so

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one of the ways uh in fact one of the

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main ways to get attention for a

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particular field or a particular type of

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mission concept or whatever it might be

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that one is pitching is to produce a

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white paper for

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uh that process

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now the latest intel i have about this

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is that the letter of authorization from

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nasa has not yet been received

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by

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the national academy so we don't know

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exactly the um

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precise

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timing but word on the street has it

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that the

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white paper submission process will be

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opening in february and that it will

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close probably in the

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april to may time frame and then of

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course the

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panels that are constituted as part of

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the decadal process will then deliberate

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and so uh it is

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very timely for us to engage in this now

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this the middle of september

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uh that gives us october november

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december january february to about the

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middle of february so that's five months

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to really try to

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see whether we can produce a

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consensus white paper

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the good thing about the white papers is

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that they're very short the bad thing

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about the white papers is that they're

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very short and so it's very challenging

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to write them

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one of the things that is really

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important about white papers is that

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instead of a particular field or mission

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concept idea or planetary body for that

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matter

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having a zillion different papers

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all with a few authors on them what

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really has the most impact is a limited

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number of papers with a very large

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number of co-authors and co-signers or

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we make everybody a co-signer we do

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whatever we want there's there's no

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good template for writing these so they

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are all over the map the astrophysics

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ones that just came in because

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astrophysics is is about a year in

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advance of the planetary

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and so that's already well underway uh

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there were 940 white papers

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which is probably not a good thing that

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there were that many um

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and many of them had you know one or two

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authors not very ideal and of course

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their their formats were all over the

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place and so um

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that

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i think with the you know relatively

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small and intimate nature

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of the astrovirology community which i

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am not part exactly but i'm a fan girl

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and trying to promote

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that i think that we ought to be able to

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come up with

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uh

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one or at worst two documents that

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really promote

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aspects of astrovirology that we believe

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are germane to

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nasa's mission

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to

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understand the origins and evolution of

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life on earth

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and to extend that to other planets and

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to

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seek evidence of life elsewhere and then

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uh one of the third components that is

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often left out of the picture is the

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aspect of what is the future destination

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of life on our planet and beyond so

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really the big questions that nasa has

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scoped out are really all across this

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time spectrum and broadly across

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the life sciences as they apply to space

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and earth's deep time history

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so one of the things that i have

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suggested for the two other

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white paper groups that i'm working with

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is that a robust big review journal

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article

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to be submitted to the journal

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astrobiology be prepared

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previously to the white paper so what

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this allows us to do as a group is to

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really dig in and fully flesh out our

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current

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group thinking about the scope of

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astrobiology its

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its impact on the field of astrobiology

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what are the potentials for

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astrobiological

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observations

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or theorizing even

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as they apply to upcoming

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mission opportunities and of course i

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would not even though this is in the

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planetary decadal um some of you may not

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be aware that there are plans afoot to

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move space biology into the science

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mission directorate well if you're not a

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bureaucrat then you probably think who

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cares but it makes a big difference in

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terms of how money flows and how things

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get managed and so in terms of the

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impact on

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astrobiology and where it overlaps with

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space biology there is a big overlap

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that has been artificially separated for

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many decades within the way nasa does

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business and so clearly viruses

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because we know they play such a major

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role in us as entities us as astronauts

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um the environment the microbial

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environment of spacecraft and

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potentially human habitats on the moon

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and mars there is significant crossover

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as it applies i think to the

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virus

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concerns that we have about earth

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biology in the space context so i just

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want to set the scene for that i'm

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hoping that

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you guys will be enthusiastic about

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putting together a paper i'll do

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everything i can to facilitate it

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obviously since it's not my field i have

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little

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specific intellectual content to

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donate but i do have my understanding of

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the way nasa works and the way

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astrobiology works and i think i can

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help with how we can make the biggest

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impact with this and then my uh

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envisionment and the the the core group

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that i've been working with

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we're envisioning a distillation of the

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very high level messages from that

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paper construction

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process making it into the white paper

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and we're on a very short timeline as i

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said it would be nice if we had

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essentially

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the paper already completed and

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submitted to astrobiology

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the journal

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well in advance of february so that we

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can at least cite ourselves uh in the

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white paper if not anything more and

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also um i've been in talks with sherry

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katy who is the

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executive editor of astrobiology i

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have served forever on the as a senior

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editor for astrobiology so she knows

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that this and other relevant white

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papers are coming and is very

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enthusiastic about finding way to

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publish them in as timely a fashion as

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possible so that is the

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bureaucratic and political framework

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and uh and my personal interest

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the other folks on the core team that

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have been

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trying to put this together of course uh

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ken stedman who is on the screen and ken

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has been

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the fearless leader keeping

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astrovirology alive within

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the astrobiology realm uh through

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tireless and often unrewarded efforts

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over the years and hopefully we can

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change that

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and then my lovely young colleagues who

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are here in the room uh gary trouball

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and lawrence

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livermore sorry we have two lawrences

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here

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a wonderful virologist and kathy

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bywaters who has many talents in

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astrobiology and who is here at nasa

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ames as a scientist so with that let me

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turn it over to ken who has prepared

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some initial remarks

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welcome everybody and i'm delighted to

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see you and i plan to learn a whole lot

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hey thanks penny and welcome to

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everybody uh

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particular thanks again to gary um

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huge thanks to him in terms of really

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getting all of this together thanks to

287
00:12:25,190 --> 00:12:23,040
everybody else particularly the speakers

288
00:12:26,470 --> 00:12:25,200
i'm not sure how many of you are online

289
00:12:28,150 --> 00:12:26,480
already

290
00:12:31,030 --> 00:12:28,160
for

291
00:12:33,750 --> 00:12:31,040
agreeing to work with us on this a lot

292
00:12:36,790 --> 00:12:33,760
of this was really kind of last minute

293
00:12:38,550 --> 00:12:36,800
so again hugely appreciated

294
00:12:41,590 --> 00:12:38,560
to all of those people who are going to

295
00:12:44,310 --> 00:12:41,600
be participating later on today i think

296
00:12:47,430 --> 00:12:44,320
pretty much everybody knows that this is

297
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going to be recorded a couple of things

298
00:12:52,629 --> 00:12:50,240
about zoom and just generally how we're

299
00:12:55,269 --> 00:12:52,639
going to be organizing this some of you

300
00:12:57,670 --> 00:12:55,279
have already found the chat window

301
00:12:59,190 --> 00:12:57,680
which i have just opened up here on the

302
00:13:01,829 --> 00:12:59,200
side

303
00:13:03,030 --> 00:13:01,839
if anybody wants to go ahead and tweet

304
00:13:05,110 --> 00:13:03,040
this

305
00:13:07,350 --> 00:13:05,120
hashtag astrovirology let's see if we

306
00:13:10,629 --> 00:13:07,360
can get it trending or maybe get it to

307
00:13:12,870 --> 00:13:10,639
go viral as the case may be

308
00:13:16,150 --> 00:13:12,880
over the next couple of days that would

309
00:13:17,829 --> 00:13:16,160
be absolutely awesome um we shall see

310
00:13:19,030 --> 00:13:17,839
i'm not going to make any guarantees

311
00:13:21,030 --> 00:13:19,040
about that

312
00:13:22,790 --> 00:13:21,040
and i didn't pay them to support it

313
00:13:25,110 --> 00:13:22,800
either so

314
00:13:26,310 --> 00:13:25,120
um a couple of other things um given

315
00:13:28,870 --> 00:13:26,320
hopefully all of you have seen the

316
00:13:31,990 --> 00:13:28,880
schedule um we've scheduled a half hour

317
00:13:34,150 --> 00:13:32,000
for each speaker actually scheduled 20

318
00:13:35,910 --> 00:13:34,160
minutes for each speaker and then 10

319
00:13:38,870 --> 00:13:35,920
minutes for questions and there are a

320
00:13:41,030 --> 00:13:38,880
couple of reasons for that one is we

321
00:13:42,629 --> 00:13:41,040
want to give people lots of chances to

322
00:13:43,750 --> 00:13:42,639
ask questions

323
00:13:45,829 --> 00:13:43,760
number two

324
00:13:48,550 --> 00:13:45,839
um speaking for myself i know i have a

325
00:13:49,990 --> 00:13:48,560
nasty tendency to go over my time limit

326
00:13:51,509 --> 00:13:50,000
so that gives us a little bit of

327
00:13:53,269 --> 00:13:51,519
flexibility but only a little bit of

328
00:13:55,509 --> 00:13:53,279
flexibility

329
00:13:57,629 --> 00:13:55,519
the other thing is since we are trying

330
00:13:59,590 --> 00:13:57,639
to do this um as

331
00:14:01,430 --> 00:13:59,600
multinationally as possible that's

332
00:14:04,310 --> 00:14:01,440
partly why we're doing

333
00:14:06,550 --> 00:14:04,320
a half day this morning and a half day

334
00:14:08,949 --> 00:14:06,560
tomorrow afternoon is to allow people in

335
00:14:11,189 --> 00:14:08,959
different time zones to be able to get

336
00:14:13,189 --> 00:14:11,199
into this but part of that also means we

337
00:14:15,670 --> 00:14:13,199
really have to try and keep the time and

338
00:14:17,430 --> 00:14:15,680
so if people actually do end up

339
00:14:18,870 --> 00:14:17,440
finishing early

340
00:14:19,670 --> 00:14:18,880
shock horror

341
00:14:21,670 --> 00:14:19,680
or

342
00:14:24,230 --> 00:14:21,680
the question period doesn't go quite as

343
00:14:26,470 --> 00:14:24,240
long that gives everybody a

344
00:14:28,069 --> 00:14:26,480
physiology break for a couple of minutes

345
00:14:30,790 --> 00:14:28,079
you can go and grab some coffee you know

346
00:14:33,189 --> 00:14:30,800
whatever it is so we can start in each

347
00:14:36,629 --> 00:14:33,199
of the half hour windows to make sure

348
00:14:39,910 --> 00:14:36,639
that everything starts on time and then

349
00:14:42,870 --> 00:14:39,920
hopefully ends on time and the ending on

350
00:14:44,710 --> 00:14:42,880
time thing um hopefully marco will just

351
00:14:46,710 --> 00:14:44,720
you know completely cut everybody off

352
00:14:48,870 --> 00:14:46,720
after half an hour and switches over to

353
00:14:51,350 --> 00:14:48,880
whoever the next person is i will um

354
00:14:53,910 --> 00:14:51,360
i'll defer to him and say it's all the

355
00:14:56,629 --> 00:14:53,920
technical people's fault um rather than

356
00:14:59,269 --> 00:14:56,639
me being mr nasty and coming in and

357
00:15:02,150 --> 00:14:59,279
saying no um this is it we've got to cut

358
00:15:03,990 --> 00:15:02,160
everything off and so that's sort of i

359
00:15:05,990 --> 00:15:04,000
feel my role

360
00:15:08,710 --> 00:15:06,000
in terms of the

361
00:15:11,430 --> 00:15:08,720
questions anybody who's on zoom should

362
00:15:14,150 --> 00:15:11,440
be able to ask questions directly there

363
00:15:15,990 --> 00:15:14,160
but also you can type in a question into

364
00:15:17,990 --> 00:15:16,000
the chat and then

365
00:15:20,550 --> 00:15:18,000
one or other of us will then actually

366
00:15:22,949 --> 00:15:20,560
read it to whoever the speaker is and so

367
00:15:25,110 --> 00:15:22,959
they can answer those questions and so

368
00:15:26,870 --> 00:15:25,120
those are the kinds of ways that we'd

369
00:15:28,870 --> 00:15:26,880
like to try and

370
00:15:30,310 --> 00:15:28,880
keep this thing

371
00:15:32,470 --> 00:15:30,320
running

372
00:15:34,790 --> 00:15:32,480
bear with us particularly with me this

373
00:15:36,710 --> 00:15:34,800
is my first workshop without walls first

374
00:15:37,990 --> 00:15:36,720
sort of virtual meeting

375
00:15:40,949 --> 00:15:38,000
so

376
00:15:41,910 --> 00:15:40,959
let us know if stuff is working or not

377
00:15:44,150 --> 00:15:41,920
working

378
00:15:46,150 --> 00:15:44,160
etc if it's a technical thing maybe you

379
00:15:47,590 --> 00:15:46,160
could pop something into the chat

380
00:15:48,470 --> 00:15:47,600
hopefully somebody can help you with

381
00:15:49,590 --> 00:15:48,480
that

382
00:15:51,509 --> 00:15:49,600
if it's a

383
00:15:53,990 --> 00:15:51,519
non-technical thing things you like

384
00:15:56,710 --> 00:15:54,000
about this process you don't like about

385
00:15:58,790 --> 00:15:56,720
it please give us some feedback and so

386
00:16:01,910 --> 00:15:58,800
that we can think about how we can do

387
00:16:04,629 --> 00:16:01,920
this better in future and one of our

388
00:16:07,030 --> 00:16:04,639
presenters later on said that this is a

389
00:16:08,389 --> 00:16:07,040
really great way to

390
00:16:10,710 --> 00:16:08,399
lower our

391
00:16:12,230 --> 00:16:10,720
carbon footprint in terms of putting

392
00:16:14,790 --> 00:16:12,240
together meetings

393
00:16:17,110 --> 00:16:14,800
and again hopefully widen the audience

394
00:16:19,269 --> 00:16:17,120
make this a lot more accessible to lots

395
00:16:20,550 --> 00:16:19,279
of different people so any

396
00:16:23,590 --> 00:16:20,560
comments

397
00:16:26,069 --> 00:16:23,600
thoughts um etc along those lines we'd

398
00:16:29,430 --> 00:16:26,079
really greatly appreciate and as penny

399
00:16:32,470 --> 00:16:29,440
mentioned um hopefully we'll be able to

400
00:16:34,389 --> 00:16:32,480
lean on as many of you as possible in

401
00:16:37,829 --> 00:16:34,399
terms of trying to put together a review

402
00:16:40,069 --> 00:16:37,839
article putting together a white paper

403
00:16:43,829 --> 00:16:40,079
so that we can really kind of

404
00:16:46,629 --> 00:16:43,839
advance the field of astrovirology um

405
00:16:48,389 --> 00:16:46,639
beyond the four walls that you can see

406
00:16:51,189 --> 00:16:48,399
behind me right here

407
00:16:53,990 --> 00:16:51,199
and a few of my colleagues as far as

408
00:16:55,829 --> 00:16:54,000
that's concerned so before i have a

409
00:16:57,670 --> 00:16:55,839
little presentation i just wanted to

410
00:17:00,629 --> 00:16:57,680
open things up for

411
00:17:03,110 --> 00:17:00,639
any sort of technical general questions

412
00:17:05,429 --> 00:17:03,120
before we sort of move into the

413
00:17:07,189 --> 00:17:05,439
formal parts of the presentation so does

414
00:17:09,510 --> 00:17:07,199
anybody have anything

415
00:17:11,510 --> 00:17:09,520
uh that we want to try and clarify

416
00:17:14,309 --> 00:17:11,520
before we move into that otherwise i've

417
00:17:20,870 --> 00:17:14,319
got a couple of slides on the

418
00:17:24,230 --> 00:17:22,549
so i got a quick question on the chat

419
00:17:26,230 --> 00:17:24,240
group can we share the workshop link via

420
00:17:32,070 --> 00:17:26,240
twitter i think absolutely

421
00:17:35,270 --> 00:17:33,750
someone else on the chatroom says it's

422
00:17:35,830 --> 00:17:35,280
too late they've already done it so

423
00:17:39,190 --> 00:17:35,840
thank you

424
00:17:41,029 --> 00:17:39,200
[Laughter]

425
00:17:43,270 --> 00:17:41,039
yeah no the idea is to make this as as

426
00:17:45,990 --> 00:17:43,280
widespread as absolutely possible uh

427
00:17:49,110 --> 00:17:46,000
that's uh sort of proselytizing as much

428
00:17:51,830 --> 00:17:49,120
as as we possibly can

429
00:17:53,830 --> 00:17:51,840
okay any other sort of question kinds of

430
00:17:57,029 --> 00:17:53,840
things along these lines

431
00:17:57,990 --> 00:17:57,039
okay let me see if i can share my screen

432
00:18:00,950 --> 00:17:58,000
and

433
00:18:03,990 --> 00:18:00,960
give you a couple of slides on

434
00:18:08,310 --> 00:18:04,000
what we've thought about astrobiology

435
00:18:13,110 --> 00:18:08,320
in the past so let me see

436
00:18:16,310 --> 00:18:13,120
which one we've got here okay hopefully

437
00:18:19,430 --> 00:18:16,320
you see my screen here okay good so

438
00:18:21,669 --> 00:18:19,440
um this is um speaking of articles in

439
00:18:24,710 --> 00:18:21,679
astrobiology hopefully some of you have

440
00:18:26,390 --> 00:18:24,720
seen this i suspect very few of you have

441
00:18:27,190 --> 00:18:26,400
actually seen

442
00:18:29,190 --> 00:18:27,200
the

443
00:18:31,669 --> 00:18:29,200
cover picture because it seems that

444
00:18:34,630 --> 00:18:31,679
nobody looks at covers anymore

445
00:18:38,230 --> 00:18:34,640
but this is the article that aaron

446
00:18:39,430 --> 00:18:38,240
berliner um tomohiro mochizuki and i put

447
00:18:40,950 --> 00:18:39,440
together

448
00:18:42,710 --> 00:18:40,960
um basically a couple of years ago and

449
00:18:44,070 --> 00:18:42,720
it came out right at the beginning of

450
00:18:47,029 --> 00:18:44,080
2018

451
00:18:48,150 --> 00:18:47,039
and really sort of a

452
00:18:50,870 --> 00:18:48,160
i'd like to think of a sort of a

453
00:18:53,669 --> 00:18:50,880
backbone to think about astrovirology

454
00:18:54,870 --> 00:18:53,679
and how it could be fitting into

455
00:19:08,470 --> 00:18:54,880
a

456
00:19:12,710 --> 00:19:08,480
move

457
00:19:14,430 --> 00:19:12,720
slides forward there we go uh most of

458
00:19:17,270 --> 00:19:14,440
the press actually thought this is what

459
00:19:18,310 --> 00:19:17,280
astrovirology is

460
00:19:21,669 --> 00:19:18,320
so

461
00:19:24,390 --> 00:19:21,679
um i think this is one thing that we do

462
00:19:26,750 --> 00:19:24,400
need to be careful about whenever i talk

463
00:19:29,510 --> 00:19:26,760
to the general public about

464
00:19:32,549 --> 00:19:29,520
astrobiology the immediate thing is oh

465
00:19:34,070 --> 00:19:32,559
should we be scared now this particular

466
00:19:35,350 --> 00:19:34,080
one unfortunately

467
00:19:38,950 --> 00:19:35,360
in the original it's actually an

468
00:19:40,950 --> 00:19:38,960
animated gif where you have the uh

469
00:19:43,270 --> 00:19:40,960
quote viruses which actually look to me

470
00:19:45,350 --> 00:19:43,280
a lot more like macrophages bouncing

471
00:19:47,510 --> 00:19:45,360
back and forth against this background

472
00:19:49,190 --> 00:19:47,520
it's really um

473
00:19:51,510 --> 00:19:49,200
frightening i guess is

474
00:19:54,549 --> 00:19:51,520
one way in lots of different ways of

475
00:19:56,710 --> 00:19:54,559
thinking about the term so um

476
00:19:59,110 --> 00:19:56,720
i'd like to think much more about this

477
00:20:01,510 --> 00:19:59,120
in terms of astrobiology

478
00:20:03,110 --> 00:20:01,520
astrovirology excuse me rather than

479
00:20:05,750 --> 00:20:03,120
this um

480
00:20:07,750 --> 00:20:05,760
in terms of the killer alien viruses and

481
00:20:09,350 --> 00:20:07,760
thanks to penny for sort of bringing up

482
00:20:11,830 --> 00:20:09,360
the

483
00:20:15,750 --> 00:20:11,840
origins of sort of thinking about

484
00:20:19,110 --> 00:20:15,760
viruses in an astrobiology context this

485
00:20:21,350 --> 00:20:19,120
was really the brainchild of

486
00:20:23,909 --> 00:20:21,360
barry blumberg the late barry blumberg

487
00:20:27,110 --> 00:20:23,919
and it he actually founded

488
00:20:29,190 --> 00:20:27,120
the virus focus group um i believe

489
00:20:32,950 --> 00:20:29,200
remember correctly it was in 2002 so

490
00:20:37,830 --> 00:20:32,960
about 17 years ago now and the basic

491
00:20:39,669 --> 00:20:37,840
take home of the virus focus group was

492
00:20:42,390 --> 00:20:39,679
barry wanted people to think about

493
00:20:44,549 --> 00:20:42,400
viruses because he was really

494
00:20:45,990 --> 00:20:44,559
excited about viruses and

495
00:20:46,870 --> 00:20:46,000
so was i

496
00:20:49,990 --> 00:20:46,880
and

497
00:20:54,149 --> 00:20:50,000
then when barry actually asked me to be

498
00:20:55,029 --> 00:20:54,159
co-chair of the virus focus group um as

499
00:21:52,029 --> 00:20:55,039
a

500
00:21:54,230 --> 00:21:52,039
in the bigger picture of

501
00:21:55,510 --> 00:21:54,240
astrobiology but

502
00:21:57,110 --> 00:21:55,520
this also gets to the point of you what

503
00:21:59,110 --> 00:21:57,120
is astrobiology and you can sort of

504
00:22:01,590 --> 00:21:59,120
think about astrobiology i think also in

505
00:22:04,230 --> 00:22:01,600
the larger context is astrobiology is

506
00:22:06,630 --> 00:22:04,240
really kind of biology as well

507
00:22:08,710 --> 00:22:06,640
just with a little bit of an astro

508
00:22:12,630 --> 00:22:08,720
context that goes with it

509
00:22:15,190 --> 00:22:12,640
so until now the virus focus group has

510
00:22:18,390 --> 00:22:15,200
basically been putting together

511
00:22:21,110 --> 00:22:18,400
workshops symposia field trips and as i

512
00:22:23,750 --> 00:22:21,120
say unfortunately as penny mentioned

513
00:22:26,669 --> 00:22:23,760
we didn't get to do the

514
00:22:28,630 --> 00:22:26,679
underground workshop field trip in

515
00:22:31,110 --> 00:22:28,640
astrovirology which would have been i

516
00:22:34,310 --> 00:22:31,120
think absolutely fascinating

517
00:22:36,390 --> 00:22:34,320
but we really concentrated on sort of

518
00:22:39,750 --> 00:22:36,400
the things that we knew a little bit

519
00:22:42,710 --> 00:22:39,760
about and also trying to get people

520
00:22:44,950 --> 00:22:42,720
from different fields of virology

521
00:22:45,909 --> 00:22:44,960
to start thinking together

522
00:22:47,750 --> 00:22:45,919
about

523
00:22:50,149 --> 00:22:47,760
you know the bigger picture again

524
00:22:52,710 --> 00:22:50,159
astrovirology so this again completely

525
00:22:54,950 --> 00:22:52,720
ties into the idea of a white paper

526
00:22:57,750 --> 00:22:54,960
ties into the idea of putting together a

527
00:23:00,070 --> 00:22:57,760
review paper to try and start to tie

528
00:23:03,510 --> 00:23:00,080
together some of these strings

529
00:23:05,110 --> 00:23:03,520
which have been really very independent

530
00:23:06,110 --> 00:23:05,120
in terms of

531
00:23:08,549 --> 00:23:06,120
different

532
00:23:10,470 --> 00:23:08,559
virologists thinking about these things

533
00:23:13,110 --> 00:23:10,480
as yeah barry always used to say he

534
00:23:15,510 --> 00:23:13,120
wasn't really a virologist i always say

535
00:23:17,750 --> 00:23:15,520
i'm not really a virologist but i think

536
00:23:20,630 --> 00:23:17,760
most virologists would say well i'm a

537
00:23:21,510 --> 00:23:20,640
this or a that or whatever so

538
00:23:24,390 --> 00:23:21,520
you know

539
00:23:25,669 --> 00:23:24,400
actually what what is astrovirology and

540
00:23:27,669 --> 00:23:25,679
tying that together i think is a really

541
00:23:29,510 --> 00:23:27,679
important aspect about

542
00:23:32,549 --> 00:23:29,520
this whole point of a white paper and

543
00:23:34,070 --> 00:23:32,559
putting together a a review article so

544
00:23:35,110 --> 00:23:34,080
what we've mostly talked about before

545
00:23:37,750 --> 00:23:35,120
and again a lot of this is going to be

546
00:23:39,029 --> 00:23:37,760
coming back up today um evolution of

547
00:23:43,350 --> 00:23:39,039
viruses

548
00:23:44,710 --> 00:23:43,360
very few people even a lot of scientists

549
00:23:47,269 --> 00:23:44,720
even a lot of

550
00:23:49,350 --> 00:23:47,279
real virologists don't have a good

551
00:23:51,590 --> 00:23:49,360
handle on how absolutely ubiquitous

552
00:23:53,909 --> 00:23:51,600
viruses are

553
00:23:55,269 --> 00:23:53,919
the whole area of virus ecology is

554
00:23:57,510 --> 00:23:55,279
really taking off we're going to hear

555
00:24:01,029 --> 00:23:57,520
from a couple of speakers about what's

556
00:24:02,470 --> 00:24:01,039
going on in terms of viruses roles in

557
00:24:04,950 --> 00:24:02,480
ecology

558
00:24:06,630 --> 00:24:04,960
virus diversity particularly in terms of

559
00:24:08,870 --> 00:24:06,640
structure i'll talk a little bit about

560
00:24:10,230 --> 00:24:08,880
this in my talk at the very end

561
00:24:11,669 --> 00:24:10,240
and

562
00:24:13,350 --> 00:24:11,679
one of my favorite lines again

563
00:24:14,950 --> 00:24:13,360
particularly in terms of an outreach

564
00:24:19,110 --> 00:24:14,960
point of view is that viruses have a bad

565
00:24:22,549 --> 00:24:19,120
rap um i think there are lots of

566
00:24:23,909 --> 00:24:22,559
viruses that do good things so far all

567
00:24:25,830 --> 00:24:23,919
of the work in virology has been

568
00:24:29,190 --> 00:24:25,840
thinking about pathogenic viruses and

569
00:24:31,590 --> 00:24:29,200
the roles that those have vast majority

570
00:24:34,789 --> 00:24:31,600
and then finally the only sort of real

571
00:24:36,390 --> 00:24:34,799
direct connection to astro and space and

572
00:24:38,310 --> 00:24:36,400
again thanks to penny for bringing this

573
00:24:42,070 --> 00:24:38,320
up has been

574
00:24:43,750 --> 00:24:42,080
um the idea of how could viruses and

575
00:24:47,190 --> 00:24:43,760
very specifically actually the

576
00:24:50,549 --> 00:24:47,200
extracellular form of viruses or virions

577
00:24:52,950 --> 00:24:50,559
survive in a space environment

578
00:24:55,990 --> 00:24:52,960
and this brings all kinds of ideas about

579
00:24:57,990 --> 00:24:56,000
panspermia but also space environment in

580
00:25:00,070 --> 00:24:58,000
a much broader picture you know other

581
00:25:02,710 --> 00:25:00,080
extraterrestrial environments as well

582
00:25:04,390 --> 00:25:02,720
and this i think is an area and we can

583
00:25:05,750 --> 00:25:04,400
talk more about it in the next couple of

584
00:25:08,630 --> 00:25:05,760
half days

585
00:25:10,470 --> 00:25:08,640
is really i think a very open area for

586
00:25:12,950 --> 00:25:10,480
research and something that

587
00:25:16,230 --> 00:25:12,960
personally i think that the field should

588
00:25:18,470 --> 00:25:16,240
be doing a lot of more work on

589
00:25:21,190 --> 00:25:18,480
so i've got a couple more just really

590
00:25:22,310 --> 00:25:21,200
quick so fun things of what we have been

591
00:25:25,110 --> 00:25:22,320
able to do

592
00:25:27,510 --> 00:25:25,120
in the past um again a couple of

593
00:25:30,870 --> 00:25:27,520
workshops first workshop we had was here

594
00:25:33,190 --> 00:25:30,880
in portland um and hopefully you can see

595
00:25:35,029 --> 00:25:33,200
barry those of you who remember a

596
00:25:37,830 --> 00:25:35,039
newberry right here in the middle

597
00:25:40,390 --> 00:25:37,840
again very much the focus of this whole

598
00:25:42,310 --> 00:25:40,400
project some of you may recognize some

599
00:25:44,710 --> 00:25:42,320
of the other people here forced rower

600
00:25:47,669 --> 00:25:44,720
has been a real leader in virus ecology

601
00:25:50,149 --> 00:25:47,679
um when he um first came up and asked me

602
00:25:51,750 --> 00:25:50,159
where to find the nasa meeting i wasn't

603
00:25:54,070 --> 00:25:51,760
sure if he was supposed to be here or a

604
00:25:55,510 --> 00:25:54,080
lost guy at some rock concert um those

605
00:25:56,549 --> 00:25:55,520
of you know forrest would appreciate

606
00:25:59,510 --> 00:25:56,559
that

607
00:26:00,390 --> 00:25:59,520
and paul turner greek stewards a lot of

608
00:26:02,070 --> 00:26:00,400
the real

609
00:26:03,430 --> 00:26:02,080
leading people and then right here

610
00:26:06,070 --> 00:26:03,440
hiding at the back are not completely

611
00:26:07,750 --> 00:26:06,080
hiding of course is sherry cady

612
00:26:09,909 --> 00:26:07,760
we had an app cycon meeting this is one

613
00:26:11,510 --> 00:26:09,919
of my favorite astrovirology slides

614
00:26:14,230 --> 00:26:11,520
roger hendricks came up with this you

615
00:26:17,029 --> 00:26:14,240
know lining up all of the viruses end to

616
00:26:18,870 --> 00:26:17,039
end ends up being the viruses on earth

617
00:26:21,669 --> 00:26:18,880
ends up being something like

618
00:26:24,630 --> 00:26:21,679
a few million light years so a

619
00:26:26,470 --> 00:26:24,640
ridiculously large number of viruses

620
00:26:29,669 --> 00:26:26,480
we also had a really

621
00:26:31,110 --> 00:26:29,679
fun trip and workshop to mono lake um

622
00:26:32,870 --> 00:26:31,120
where the

623
00:26:35,190 --> 00:26:32,880
we were actually able to go out on mono

624
00:26:38,070 --> 00:26:35,200
lake itself visit pahoa island which has

625
00:26:40,870 --> 00:26:38,080
a number of very interesting hot springs

626
00:26:42,630 --> 00:26:40,880
very near there mammoth lakes the long

627
00:26:44,549 --> 00:26:42,640
valley caldera also has some really

628
00:26:46,950 --> 00:26:44,559
interesting hot springs so we were able

629
00:26:48,630 --> 00:26:46,960
to sample there again

630
00:26:50,549 --> 00:26:48,640
barry even though he said he was getting

631
00:26:53,110 --> 00:26:50,559
seasick seems to have really enjoyed

632
00:26:55,990 --> 00:26:53,120
this particular trip and mona lake is

633
00:26:58,549 --> 00:26:56,000
really flat very few waves and then our

634
00:26:59,990 --> 00:26:58,559
last field trip was to lassen volcanic

635
00:27:02,710 --> 00:27:00,000
national park which is one of the main

636
00:27:04,950 --> 00:27:02,720
field sites that i work in

637
00:27:07,190 --> 00:27:04,960
and also had the opportunity to go to

638
00:27:09,110 --> 00:27:07,200
the hat creek observatory

639
00:27:11,029 --> 00:27:09,120
and with jill tarter and talk a little

640
00:27:13,350 --> 00:27:11,039
bit about seti so it's really been a

641
00:27:14,789 --> 00:27:13,360
whole combination of

642
00:27:17,190 --> 00:27:14,799
different

643
00:27:19,350 --> 00:27:17,200
aspects of thinking about

644
00:27:20,630 --> 00:27:19,360
viruses in a bigger sense and the last

645
00:27:23,350 --> 00:27:20,640
thing i wanted to mention is that we've

646
00:27:24,870 --> 00:27:23,360
also been very involved in outreach and

647
00:27:26,870 --> 00:27:24,880
trying to reach a lot of other people

648
00:27:28,710 --> 00:27:26,880
and i'm noticing that it is now

649
00:27:30,950 --> 00:27:28,720
8 30 so

650
00:27:32,549 --> 00:27:30,960
in terms of keeping on time let's see if

651
00:27:34,630 --> 00:27:32,559
we can switch over to steve benner

652
00:27:36,470 --> 00:27:34,640
assuming that he is actually

653
00:27:38,710 --> 00:27:36,480
online here and i'll actually let steve

654
00:27:39,990 --> 00:27:38,720
introduce himself because i keep

655
00:27:42,789 --> 00:27:40,000
forgetting which institute he's

656
00:27:47,990 --> 00:27:42,799
associated with

657
00:27:52,549 --> 00:27:50,389
so steve is steve around

658
00:27:54,310 --> 00:27:52,559
yes yes he is

659
00:27:56,310 --> 00:27:54,320
good online

660
00:27:57,350 --> 00:27:56,320
you cannot all unmute your microphone

661
00:27:58,789 --> 00:27:57,360
there

662
00:28:02,870 --> 00:27:58,799
so steve we should be able to hear you

663
00:28:06,230 --> 00:28:02,880
now oh i was unmuted by the host okay um

664
00:28:08,710 --> 00:28:06,240
yeah i am unable to drop my s

665
00:28:10,870 --> 00:28:08,720
power presentation presentation onto the

666
00:28:13,190 --> 00:28:10,880
screen that i'm able to share in

667
00:28:15,669 --> 00:28:13,200
in zoom actually i'm not quite clear why

668
00:28:18,630 --> 00:28:15,679
that's the case but uh

669
00:28:21,190 --> 00:28:18,640
um can and then for some reason

670
00:28:23,669 --> 00:28:21,200
zoom has blocked out on the control

671
00:28:27,430 --> 00:28:23,679
panel i think so can you actually for me

672
00:28:31,269 --> 00:28:28,789
sure i will do that let me bring those

673
00:28:32,549 --> 00:28:31,279
up really quickly okay

674
00:28:35,029 --> 00:28:32,559
excellent

675
00:28:37,510 --> 00:28:35,039
i i don't i don't fit my talk that

676
00:28:40,070 --> 00:28:37,520
really does not fit into this uh

677
00:28:42,070 --> 00:28:40,080
session as i looked at all the other

678
00:28:43,909 --> 00:28:42,080
ways in which people were talking about

679
00:28:46,630 --> 00:28:43,919
things as i think has nothing to do with

680
00:28:49,350 --> 00:28:46,640
viruses unless you wanted to detect them

681
00:28:50,710 --> 00:28:49,360
on uh um unless you wanted to detect

682
00:28:52,789 --> 00:28:50,720
them on that

683
00:28:54,950 --> 00:28:52,799
on earth so um now am i going to say to

684
00:28:56,070 --> 00:28:54,960
you please change slide

685
00:29:00,149 --> 00:28:56,080
or why

686
00:29:05,350 --> 00:29:02,549
all right don't go back one slide um

687
00:29:07,669 --> 00:29:05,360
that first slide okay so uh keep in mind

688
00:29:09,510 --> 00:29:07,679
that nasa is very much interested in i

689
00:29:13,830 --> 00:29:09,520
mean well the public is interested in

690
00:29:16,389 --> 00:29:13,840
and the public is nasa's customer um

691
00:29:18,630 --> 00:29:16,399
is i mean obviously nasa provides to the

692
00:29:20,470 --> 00:29:18,640
educated elite the

693
00:29:23,190 --> 00:29:20,480
you know if you're not

694
00:29:24,630 --> 00:29:23,200
a high brow you watch world wrestling

695
00:29:26,950 --> 00:29:24,640
federation for your

696
00:29:28,870 --> 00:29:26,960
entertainment nasa provides a sense of

697
00:29:31,110 --> 00:29:28,880
mission a sense of entertainment and a

698
00:29:32,549 --> 00:29:31,120
sense of purpose to the general public

699
00:29:33,830 --> 00:29:32,559
those who are familiar with this kind of

700
00:29:35,990 --> 00:29:33,840
things and those are people who

701
00:29:38,070 --> 00:29:36,000
particularly knew carl sagan is

702
00:29:40,070 --> 00:29:38,080
the one question that is at the top of

703
00:29:42,310 --> 00:29:40,080
everybody's mind in the public when you

704
00:29:43,269 --> 00:29:42,320
do surveys is whether or not life is out

705
00:29:45,110 --> 00:29:43,279
there

706
00:29:46,389 --> 00:29:45,120
we don't know quite what life is but

707
00:29:48,549 --> 00:29:46,399
there's this concept of a

708
00:29:50,310 --> 00:29:48,559
self-sustaining chemical system capable

709
00:29:52,149 --> 00:29:50,320
of darwinian evolution

710
00:29:54,389 --> 00:29:52,159
and that is

711
00:29:56,149 --> 00:29:54,399
a theory definition of life that carl

712
00:29:58,870 --> 00:29:56,159
sagan was very much instrumental in

713
00:30:00,710 --> 00:29:58,880
pushing um and it's a theory definition

714
00:30:02,549 --> 00:30:00,720
i'm using the formulation of carol

715
00:30:04,789 --> 00:30:02,559
cleveland here who's was the

716
00:30:08,070 --> 00:30:04,799
astrobiology resident philosopher

717
00:30:09,830 --> 00:30:08,080
because it is a statement not only about

718
00:30:11,990 --> 00:30:09,840
sort of definitional terms which are

719
00:30:13,590 --> 00:30:12,000
very hard to pin down but it really is a

720
00:30:15,430 --> 00:30:13,600
statement that when we adopt this theory

721
00:30:17,590 --> 00:30:15,440
definition we are saying what we think

722
00:30:19,669 --> 00:30:17,600
is the only way to generate matter as

723
00:30:21,909 --> 00:30:19,679
organic matter or whatever and the

724
00:30:23,909 --> 00:30:21,919
properties of value in life and that

725
00:30:26,230 --> 00:30:23,919
only way to do it is by this darwinian

726
00:30:28,710 --> 00:30:26,240
process of replication with errors where

727
00:30:31,669 --> 00:30:28,720
the errors are themselves replicable and

728
00:30:34,149 --> 00:30:31,679
then natural selection does the rest so

729
00:30:37,110 --> 00:30:34,159
your goal right now is to go out and

730
00:30:38,310 --> 00:30:37,120
find systems capable of darwinian

731
00:30:40,950 --> 00:30:38,320
evolution

732
00:30:42,710 --> 00:30:40,960
chris chiba and various other people

733
00:30:45,029 --> 00:30:42,720
made the comment that this was not an

734
00:30:48,310 --> 00:30:45,039
operational definition because what were

735
00:30:50,070 --> 00:30:48,320
you going to do fly to you know mars

736
00:30:52,870 --> 00:30:50,080
land and then sit around and wait for

737
00:30:54,789 --> 00:30:52,880
something to evolve well that's not a

738
00:30:57,590 --> 00:30:54,799
correct way of looking at this right

739
00:30:59,669 --> 00:30:57,600
what you you don't have to wait for a

740
00:31:02,070 --> 00:30:59,679
rabbit to evolve when you have a rabbit

741
00:31:04,149 --> 00:31:02,080
in your possession to make or a pair of

742
00:31:05,590 --> 00:31:04,159
rabbits in any case

743
00:31:07,190 --> 00:31:05,600
to make the statement that they have the

744
00:31:09,350 --> 00:31:07,200
capability of evolution so what you're

745
00:31:10,950 --> 00:31:09,360
looking for is molecular structures that

746
00:31:12,149 --> 00:31:10,960
have that capability you're not looking

747
00:31:14,310 --> 00:31:12,159
for the actual

748
00:31:17,830 --> 00:31:14,320
evolution itself all right so the next

749
00:31:19,509 --> 00:31:17,840
um slide is going to say what darwinism

750
00:31:21,990 --> 00:31:19,519
needs

751
00:31:23,909 --> 00:31:22,000
as a by way of informational polymer and

752
00:31:25,590 --> 00:31:23,919
there are two criteria that are both

753
00:31:28,070 --> 00:31:25,600
extremely important one of them is the

754
00:31:29,110 --> 00:31:28,080
so-called schrodinger aperiodic crystal

755
00:31:31,830 --> 00:31:29,120
structure

756
00:31:34,630 --> 00:31:31,840
and that means that the genetic polymer

757
00:31:37,350 --> 00:31:34,640
must be able to change its information

758
00:31:38,950 --> 00:31:37,360
content without changing its structure

759
00:31:42,549 --> 00:31:38,960
because all the building blocks have got

760
00:31:44,070 --> 00:31:42,559
to fit into the same packed form

761
00:31:45,430 --> 00:31:44,080
there's a second

762
00:31:47,029 --> 00:31:45,440
requirement that is that the genetic

763
00:31:48,950 --> 00:31:47,039
biopolymers be able to keep its

764
00:31:50,149 --> 00:31:48,960
properties constant with changing

765
00:31:52,789 --> 00:31:50,159
information

766
00:31:54,789 --> 00:31:52,799
and so the next slide

767
00:31:57,110 --> 00:31:54,799
shows you the picture of erwin schweiner

768
00:31:59,269 --> 00:31:57,120
he wrote this book in 1943 what's

769
00:32:01,509 --> 00:31:59,279
remarkable about this book is that he

770
00:32:02,549 --> 00:32:01,519
did not know the structure of dna it was

771
00:32:04,870 --> 00:32:02,559
not to be

772
00:32:07,190 --> 00:32:04,880
a watson crick double helix only came

773
00:32:08,470 --> 00:32:07,200
out 10 years later but schrodinger was a

774
00:32:10,149 --> 00:32:08,480
physicist

775
00:32:13,669 --> 00:32:10,159
he was famous for the schrodinger

776
00:32:15,990 --> 00:32:13,679
equation in quantum mechanics by 1943 he

777
00:32:18,070 --> 00:32:16,000
was slumming by doing biology that's

778
00:32:19,110 --> 00:32:18,080
sort of what many physicists did at that

779
00:32:21,110 --> 00:32:19,120
time

780
00:32:23,750 --> 00:32:21,120
but and what he knew was that simple

781
00:32:25,669 --> 00:32:23,760
binding cannot guarantee

782
00:32:28,230 --> 00:32:25,679
faithful information transfer at least

783
00:32:30,389 --> 00:32:28,240
not the level that's needed for biology

784
00:32:32,630 --> 00:32:30,399
because a simple binding gives you a

785
00:32:34,630 --> 00:32:32,640
titration curve which has a classical

786
00:32:37,669 --> 00:32:34,640
sigmoidal shape which if you ever did

787
00:32:40,149 --> 00:32:37,679
any work like this in your biochemistry

788
00:32:42,230 --> 00:32:40,159
laboratory you're familiar with and what

789
00:32:45,029 --> 00:32:42,240
you need to do to get faith for

790
00:32:47,509 --> 00:32:45,039
replication is sharp phase transitions

791
00:32:49,669 --> 00:32:47,519
between a correct pairing and an

792
00:32:51,669 --> 00:32:49,679
incorrect pairing and

793
00:32:53,430 --> 00:32:51,679
for that schrodinger said we have to

794
00:32:55,990 --> 00:32:53,440
rely on what's called the physics of

795
00:32:58,070 --> 00:32:56,000
phase transition now i won't go into the

796
00:33:00,310 --> 00:32:58,080
physics of phase translations but the

797
00:33:02,230 --> 00:33:00,320
melting of a crystal is an example of

798
00:33:05,870 --> 00:33:02,240
this which everybody's familiar with so

799
00:33:08,950 --> 00:33:05,880
if you take ice at minus

800
00:33:11,830 --> 00:33:08,960
0.0001 degrees centigrade and then move

801
00:33:14,470 --> 00:33:11,840
it to plus a 0.00 or one degree celsius

802
00:33:16,870 --> 00:33:14,480
the entire ice cube goes from a solid to

803
00:33:19,509 --> 00:33:16,880
a liquid in a phase transition and by

804
00:33:21,830 --> 00:33:19,519
the way impurities in that ice crystal

805
00:33:24,789 --> 00:33:21,840
will cause that melting point to be

806
00:33:26,630 --> 00:33:24,799
lower and broader and so the physics of

807
00:33:29,909 --> 00:33:26,640
phase transition

808
00:33:32,389 --> 00:33:29,919
is what allows very precise exclusion of

809
00:33:34,710 --> 00:33:32,399
impurities from a crystal it also is

810
00:33:36,630 --> 00:33:34,720
what you're relying on in dna to exclude

811
00:33:38,549 --> 00:33:36,640
impurities as mismatches when you're

812
00:33:40,870 --> 00:33:38,559
doing dna replication

813
00:33:42,950 --> 00:33:40,880
and for that and this is the key point

814
00:33:45,830 --> 00:33:42,960
the exchangeable informational building

815
00:33:46,789 --> 00:33:45,840
blocks must all have the same size and

816
00:33:48,870 --> 00:33:46,799
shape

817
00:33:50,950 --> 00:33:48,880
they must all fit into

818
00:33:52,710 --> 00:33:50,960
obviously a crystal of ice all the water

819
00:33:54,389 --> 00:33:52,720
molecules are identical and so there's

820
00:33:56,310 --> 00:33:54,399
really no information in the crystal

821
00:33:58,470 --> 00:33:56,320
structure of ice but

822
00:34:00,789 --> 00:33:58,480
um what schrodinger said okay great what

823
00:34:03,909 --> 00:34:00,799
we can do is make the molecules that are

824
00:34:06,389 --> 00:34:03,919
in that crystal a little different

825
00:34:09,270 --> 00:34:06,399
therefore it's a periodic in terms of

826
00:34:11,829 --> 00:34:09,280
its placement of these building blocks

827
00:34:14,550 --> 00:34:11,839
the a periodicity is what contains the

828
00:34:16,470 --> 00:34:14,560
information the genetic information but

829
00:34:18,869 --> 00:34:16,480
in order for this to work at all all the

830
00:34:20,389 --> 00:34:18,879
building blocks have to fit into exactly

831
00:34:25,510 --> 00:34:20,399
the same structure

832
00:34:28,710 --> 00:34:26,710
um

833
00:34:31,270 --> 00:34:28,720
this is of course actually uh i wish i

834
00:34:33,589 --> 00:34:31,280
had control this i'm going to go to the

835
00:34:36,069 --> 00:34:33,599
next slide for me so i should put a put

836
00:34:37,750 --> 00:34:36,079
in here somewhere structure of dna

837
00:34:39,829 --> 00:34:37,760
um that's a perfectly good structure of

838
00:34:42,869 --> 00:34:39,839
dna on the left let's go to the next

839
00:34:42,879 --> 00:34:46,149
the next slide

840
00:34:51,669 --> 00:34:49,190
yeah there you go so i you know i've put

841
00:34:53,589 --> 00:34:51,679
here the gc

842
00:34:56,629 --> 00:34:53,599
a cg base pair in the upper left hand

843
00:34:58,870 --> 00:34:56,639
corner and the t a base pair the next

844
00:35:01,750 --> 00:34:58,880
one down as you can see these are

845
00:35:04,550 --> 00:35:01,760
essentially the same size and shape i've

846
00:35:06,390 --> 00:35:04,560
actually fixed for those of you who are

847
00:35:08,790 --> 00:35:06,400
going to take a test on this subject i

848
00:35:10,630 --> 00:35:08,800
have actually fixed the structure of a

849
00:35:13,030 --> 00:35:10,640
to put an amino group

850
00:35:15,030 --> 00:35:13,040
down to form a third hydrogen bond with

851
00:36:06,150 --> 00:35:15,040
t

852
00:36:07,829 --> 00:36:06,160
assembling and he was building a

853
00:36:09,990 --> 00:36:07,839
structure for dna which had three

854
00:36:13,589 --> 00:36:10,000
strands of

855
00:36:15,510 --> 00:36:13,599
dna not two strands and watson

856
00:36:17,030 --> 00:36:15,520
writes in his book how any biologist

857
00:36:19,430 --> 00:36:17,040
would know that the important thing

858
00:36:21,829 --> 00:36:19,440
number was two not three

859
00:36:25,750 --> 00:36:21,839
but when watson and crick finally got

860
00:36:26,550 --> 00:36:25,760
the structures of the gc pair correct

861
00:36:27,990 --> 00:36:26,560
which

862
00:36:29,910 --> 00:36:28,000
they were they were trying to build a

863
00:36:31,510 --> 00:36:29,920
model with an incorrect structure of g

864
00:36:33,430 --> 00:36:31,520
the first thing that they said when they

865
00:36:35,910 --> 00:36:33,440
looked at those base pairs was aha this

866
00:36:37,430 --> 00:36:35,920
fits um

867
00:36:39,109 --> 00:36:37,440
schrodinger's a periodic crystal

868
00:36:43,109 --> 00:36:39,119
structure that is we can exchange

869
00:36:46,230 --> 00:36:43,119
g pairs for a t pairs or c g pairs for t

870
00:36:48,310 --> 00:36:46,240
a pairs or c g pairs for gc pairs and

871
00:36:49,349 --> 00:36:48,320
not change the overall structure so

872
00:36:51,109 --> 00:36:49,359
that's the first thing that they

873
00:36:51,910 --> 00:36:51,119
recognize about their model was that it

874
00:36:54,470 --> 00:36:51,920
fits

875
00:36:56,790 --> 00:36:54,480
schrodinger's criteria for

876
00:36:58,630 --> 00:36:56,800
aperiodic crystal structures now the

877
00:37:00,630 --> 00:36:58,640
other structures on this pair are all

878
00:37:02,390 --> 00:37:00,640
synthetic biology structures these are

879
00:37:04,870 --> 00:37:02,400
molecules that we have made

880
00:37:07,030 --> 00:37:04,880
and you can see we are changing the

881
00:37:08,390 --> 00:37:07,040
hydrogen bond donor and acceptor

882
00:37:09,990 --> 00:37:08,400
patterns we've

883
00:37:12,550 --> 00:37:10,000
written on these structures blue

884
00:37:15,109 --> 00:37:12,560
hydrogens as hydrogen bond donors

885
00:37:17,670 --> 00:37:15,119
so c is a hydrogen bond donor acceptor

886
00:37:18,630 --> 00:37:17,680
acceptor pattern blue red red

887
00:37:23,589 --> 00:37:18,640
which

888
00:37:24,630 --> 00:37:23,599
acceptor donor donor hydrogen bonding

889
00:37:25,910 --> 00:37:24,640
pattern

890
00:37:28,230 --> 00:37:25,920
and

891
00:37:30,230 --> 00:37:28,240
t is a small thing with a

892
00:37:32,069 --> 00:37:30,240
red blue red hydrogen bond acceptor

893
00:37:33,109 --> 00:37:32,079
donor acceptor pattern which pairs with

894
00:37:35,430 --> 00:37:33,119
a big

895
00:37:37,349 --> 00:37:35,440
amino adenine blue red blue donor

896
00:37:38,710 --> 00:37:37,359
acceptor donor and the rest of the

897
00:37:40,710 --> 00:37:38,720
structures here is there eight more

898
00:37:42,550 --> 00:37:40,720
nucleotides none of them are actually

899
00:37:44,870 --> 00:37:42,560
natural as far as we know

900
00:37:48,069 --> 00:37:44,880
they shuffle the hydrogen bond donor and

901
00:37:49,430 --> 00:37:48,079
acceptor pairs but they keep the

902
00:37:50,870 --> 00:37:49,440
size

903
00:37:53,670 --> 00:37:50,880
of the hair

904
00:37:56,630 --> 00:37:53,680
uniform so that you can replace anything

905
00:37:59,990 --> 00:37:56,640
any pair any of the six pairs on that

906
00:38:02,150 --> 00:38:00,000
slide by any of the other

907
00:38:03,910 --> 00:38:02,160
five pairs or the six pairs in the

908
00:38:04,950 --> 00:38:03,920
reverse direction and not change the

909
00:38:06,710 --> 00:38:04,960
structure

910
00:38:09,589 --> 00:38:06,720
and this artificially expanded genetic

911
00:38:11,109 --> 00:38:09,599
information system is in fact perfectly

912
00:38:13,270 --> 00:38:11,119
capable of meeting the schrodinger

913
00:38:16,829 --> 00:38:13,280
aperiodic crystal structure

914
00:38:20,069 --> 00:38:16,839
so the next slide i think maybe

915
00:38:22,310 --> 00:38:20,079
has yeah there you go so these are

916
00:38:25,670 --> 00:38:22,320
crystal structures at the bottom

917
00:38:26,950 --> 00:38:25,680
you're seeing um uh

918
00:38:30,310 --> 00:38:26,960
b c

919
00:38:33,270 --> 00:38:30,320
d e plus c d and e are three different

920
00:38:35,910 --> 00:38:33,280
structures of three different

921
00:38:38,069 --> 00:38:35,920
dna duplexes built from

922
00:38:41,349 --> 00:38:38,079
in this particular case eight letters of

923
00:38:43,430 --> 00:38:41,359
genetic alphabet but all still fitting

924
00:38:46,069 --> 00:38:43,440
the schrodinger aperiodic crystal

925
00:38:47,109 --> 00:38:46,079
structure and the structures are all the

926
00:38:49,510 --> 00:38:47,119
same

927
00:38:51,589 --> 00:38:49,520
uh c d and e and if that doesn't it

928
00:38:53,510 --> 00:38:51,599
doesn't seem so for you the structure b

929
00:38:55,349 --> 00:38:53,520
has all of them placed on top of each

930
00:38:56,710 --> 00:38:55,359
other so let me just pause there and

931
00:38:58,630 --> 00:38:56,720
make sure everybody understands the

932
00:39:00,710 --> 00:38:58,640
schrodinger a periodic crystal structure

933
00:39:02,230 --> 00:39:00,720
that is to have a darwinian molecule you

934
00:39:05,109 --> 00:39:02,240
got to be able to replace the

935
00:39:06,230 --> 00:39:05,119
informational units without disrupting a

936
00:39:10,310 --> 00:39:06,240
crystal

937
00:39:15,670 --> 00:39:12,710
is anybody there

938
00:39:17,670 --> 00:39:15,680
you're good okay so that's the that's

939
00:39:22,470 --> 00:39:17,680
the first requirement okay next slide

940
00:39:26,870 --> 00:39:24,950
yeah and so there you go so the first

941
00:39:29,270 --> 00:39:26,880
thing is that darwinism needs is a

942
00:39:30,790 --> 00:39:29,280
genetic system able to change encoded

943
00:39:31,990 --> 00:39:30,800
information without changing its

944
00:39:33,829 --> 00:39:32,000
structure

945
00:39:35,670 --> 00:39:33,839
that's schrodinger and by the way

946
00:39:37,349 --> 00:39:35,680
homochirality

947
00:39:39,430 --> 00:39:37,359
which is sought by many of the

948
00:39:41,510 --> 00:39:39,440
life-detection missions that nasa is

949
00:39:44,150 --> 00:39:41,520
contemplating including for example the

950
00:39:45,670 --> 00:39:44,160
mission to europa is actually not a

951
00:39:47,990 --> 00:39:45,680
primary

952
00:39:48,790 --> 00:39:48,000
attribute of living systems

953
00:39:50,630 --> 00:39:48,800
it's

954
00:39:52,550 --> 00:39:50,640
it is a derivative

955
00:39:55,430 --> 00:39:52,560
of the schrodinger a periodic crystal

956
00:39:59,030 --> 00:39:55,440
structure and is absolutely required for

957
00:40:01,510 --> 00:39:59,040
the informational biopolymers but uh

958
00:40:03,430 --> 00:40:01,520
biological systems actually mix d and l

959
00:40:04,870 --> 00:40:03,440
amino acids all the time in fact

960
00:40:07,670 --> 00:40:04,880
gramocide and there's lots of

961
00:40:09,670 --> 00:40:07,680
antibiotics that do this um what you

962
00:40:12,470 --> 00:40:09,680
can't do is have that system be the

963
00:40:14,950 --> 00:40:12,480
evolvable system as an in an information

964
00:40:15,990 --> 00:40:14,960
sense of the term so if you went looking

965
00:40:18,390 --> 00:40:16,000
for

966
00:40:20,550 --> 00:40:18,400
homochirality on europa and you managed

967
00:40:22,950 --> 00:40:20,560
to land yourself in a pile of gramocidin

968
00:40:25,829 --> 00:40:22,960
you would not see that

969
00:40:27,349 --> 00:40:25,839
as a you would not see homochirality as

970
00:40:28,069 --> 00:40:27,359
a life detection

971
00:40:32,550 --> 00:40:28,079
uh

972
00:40:34,069 --> 00:40:32,560
gramocided as being the product of a

973
00:40:37,510 --> 00:40:34,079
biological

974
00:40:39,349 --> 00:40:37,520
processes but homochirona is what you're

975
00:40:41,190 --> 00:40:39,359
going to see in the informational

976
00:40:43,829 --> 00:40:41,200
biopolymer and so your problem when you

977
00:40:45,829 --> 00:40:43,839
do life detection in space or for that

978
00:40:48,069 --> 00:40:45,839
matter in antarctica

979
00:40:50,150 --> 00:40:48,079
you do need to know that you're looking

980
00:40:52,550 --> 00:40:50,160
at an informational

981
00:40:54,390 --> 00:40:52,560
biopolymer before you start looking for

982
00:40:55,990 --> 00:40:54,400
homochirality

983
00:40:58,150 --> 00:40:56,000
so that actually brings us the next

984
00:40:59,750 --> 00:40:58,160
system which is the genetic system

985
00:41:02,550 --> 00:40:59,760
not the the

986
00:41:04,870 --> 00:41:02,560
structures of the building blocks must

987
00:41:07,670 --> 00:41:04,880
not only be robust with respect to

988
00:41:10,230 --> 00:41:07,680
replacement so as to not disrupt a

989
00:41:12,470 --> 00:41:10,240
periodic crystal structure but changing

990
00:41:14,870 --> 00:41:12,480
encoded information also has to be

991
00:41:17,349 --> 00:41:14,880
possible without changing the physical

992
00:41:19,829 --> 00:41:17,359
chemical behavior of the informational

993
00:41:22,309 --> 00:41:19,839
polymer such as its solubility it's

994
00:41:23,829 --> 00:41:22,319
molecular recognition it's reactivity

995
00:41:26,230 --> 00:41:23,839
and one thing we know from terran

996
00:41:28,870 --> 00:41:26,240
biochemistry is that these systems are

997
00:41:31,910 --> 00:41:28,880
actually hard to find so in proteins for

998
00:41:34,390 --> 00:41:31,920
example and i've used sickle cell anemia

999
00:41:36,630 --> 00:41:34,400
here as an example

1000
00:41:38,870 --> 00:41:36,640
a single amino acid change in a protein

1001
00:41:40,870 --> 00:41:38,880
of 500 amino acids can cause that

1002
00:41:42,950 --> 00:41:40,880
protein to precipitate and that's in

1003
00:41:44,870 --> 00:41:42,960
fact what's forming sickle cells and

1004
00:41:47,030 --> 00:41:44,880
biological systems

1005
00:41:49,430 --> 00:41:47,040
so hey you know if you had your genetic

1006
00:41:51,910 --> 00:41:49,440
polymer where you changed a g to an a or

1007
00:41:54,710 --> 00:41:51,920
t to a c to try to get more fitness and

1008
00:41:55,589 --> 00:41:54,720
then the dna precipitated it would be a

1009
00:41:58,150 --> 00:41:55,599
really

1010
00:42:00,630 --> 00:41:58,160
difficult to evolve system so you've got

1011
00:42:03,990 --> 00:42:00,640
to be able to keep the reactivity more

1012
00:42:05,670 --> 00:42:04,000
or less constant so the next slide maybe

1013
00:42:07,430 --> 00:42:05,680
let's just see what i got here

1014
00:42:09,829 --> 00:42:07,440
yeah um so

1015
00:42:12,470 --> 00:42:09,839
the polyelectrolyte theory of the gene

1016
00:42:13,430 --> 00:42:12,480
says that what you need to have to give

1017
00:42:14,870 --> 00:42:13,440
that

1018
00:42:16,470 --> 00:42:14,880
stable

1019
00:42:18,470 --> 00:42:16,480
physical properties with respect to

1020
00:42:20,710 --> 00:42:18,480
information change that has had this

1021
00:42:24,309 --> 00:42:20,720
repeating charge in the backbone

1022
00:42:25,670 --> 00:42:24,319
and the reason for that is because

1023
00:42:27,910 --> 00:42:25,680
that

1024
00:42:29,270 --> 00:42:27,920
the same molecule is charged as the most

1025
00:42:30,390 --> 00:42:29,280
important thing you can say about a

1026
00:42:32,230 --> 00:42:30,400
molecule

1027
00:42:34,230 --> 00:42:32,240
right not only does it

1028
00:42:36,710 --> 00:42:34,240
describe its solubility in water which

1029
00:42:38,390 --> 00:42:36,720
of course is night and day or charge

1030
00:42:41,349 --> 00:42:38,400
versus not charged

1031
00:42:43,109 --> 00:42:41,359
it also dominates all other electronic

1032
00:42:45,670 --> 00:42:43,119
properties of a molecule so a molecule

1033
00:42:47,910 --> 00:42:45,680
can have a charge that is a monopole

1034
00:42:49,190 --> 00:42:47,920
and if it doesn't have a charge then you

1035
00:42:50,790 --> 00:42:49,200
can start saying well it doesn't have a

1036
00:42:53,990 --> 00:42:50,800
dipole

1037
00:42:56,069 --> 00:42:54,000
important thing you can say about a

1038
00:42:58,150 --> 00:42:56,079
molecule if you're like benzene and you

1039
00:42:59,510 --> 00:42:58,160
don't have a dipole or a charge then you

1040
00:43:01,430 --> 00:42:59,520
can go down and ask well does it have a

1041
00:43:03,670 --> 00:43:01,440
quadrupole which benzene actually has

1042
00:43:05,349 --> 00:43:03,680
and that becomes the most important

1043
00:43:06,710 --> 00:43:05,359
feature of the molecule that dominates

1044
00:43:08,950 --> 00:43:06,720
its behavior

1045
00:43:10,630 --> 00:43:08,960
how are we doing

1046
00:43:11,910 --> 00:43:10,640
so a charge is big

1047
00:43:14,550 --> 00:43:11,920
if you don't have a charge you can worry

1048
00:43:16,150 --> 00:43:14,560
about charge separation that is a dipole

1049
00:43:17,510 --> 00:43:16,160
if you don't have a dipole you can start

1050
00:43:19,589 --> 00:43:17,520
worrying about what higher order

1051
00:43:22,069 --> 00:43:19,599
structures but the point about a

1052
00:43:25,030 --> 00:43:22,079
polyelectrolyte is it lets you change

1053
00:43:26,950 --> 00:43:25,040
the bases without changing the behavior

1054
00:43:29,349 --> 00:43:26,960
of the molecule and so if you go to the

1055
00:43:31,190 --> 00:43:29,359
next slide i just show you

1056
00:43:33,750 --> 00:43:31,200
one of the empirical tests of this from

1057
00:43:35,510 --> 00:43:33,760
our laboratory we we tried to make

1058
00:43:37,910 --> 00:43:35,520
dna without

1059
00:43:39,910 --> 00:43:37,920
repeating charges and and i'm not going

1060
00:43:41,750 --> 00:43:39,920
to go into great detail but there's dna

1061
00:43:43,589 --> 00:43:41,760
on your left and there is a molecule

1062
00:43:46,069 --> 00:43:43,599
that we made at great expense and effort

1063
00:43:48,950 --> 00:43:46,079
on the right you'll see i've added a

1064
00:43:51,430 --> 00:43:48,960
proton to the phosphorus to make sulfur

1065
00:43:53,270 --> 00:43:51,440
that removes the backbone charges

1066
00:43:54,950 --> 00:43:53,280
and what you'll discover about this

1067
00:43:57,910 --> 00:43:54,960
molecule is that when you get rid of the

1068
00:44:02,470 --> 00:43:59,829
what now happens is this molecule has a

1069
00:44:04,790 --> 00:44:02,480
repeating dipole and instead of

1070
00:44:06,710 --> 00:44:04,800
behaving like a respectable

1071
00:44:09,829 --> 00:44:06,720
genetic biopolymer it starts behaving

1072
00:44:11,670 --> 00:44:09,839
like sickle cell hemoglobin right it

1073
00:44:13,109 --> 00:44:11,680
folds and actually the next slide shows

1074
00:44:15,589 --> 00:44:13,119
you just for fun

1075
00:44:17,190 --> 00:44:15,599
a folding unfolding thermodynamic

1076
00:44:18,870 --> 00:44:17,200
property right you have

1077
00:44:21,589 --> 00:44:18,880
you have i've got an eight

1078
00:44:23,910 --> 00:44:21,599
letter oligonucleotide a cell phone you

1079
00:44:26,710 --> 00:44:23,920
cell phone g cell phone g so phone use

1080
00:44:29,510 --> 00:44:26,720
cell phone c seven asophone u

1081
00:44:31,750 --> 00:44:29,520
and you're looking at here a plot of the

1082
00:44:34,069 --> 00:44:31,760
um ultraviolet

1083
00:44:35,910 --> 00:44:34,079
spectrum as a function of temperature

1084
00:44:38,069 --> 00:44:35,920
and you're looking at the unfolding of

1085
00:44:40,870 --> 00:44:38,079
this particular molecule because these

1086
00:44:43,349 --> 00:44:40,880
molecules fold like proteins well why

1087
00:44:45,670 --> 00:44:43,359
because unlike dna they do not have a

1088
00:44:48,069 --> 00:44:45,680
repeating negative charge and like

1089
00:44:50,150 --> 00:44:48,079
proteins they have a repeating dipole

1090
00:44:51,670 --> 00:44:50,160
and so they behave like proteins making

1091
00:44:53,670 --> 00:44:51,680
a single change

1092
00:44:54,870 --> 00:44:53,680
in the sequence of bases in that

1093
00:44:56,950 --> 00:44:54,880
molecule

1094
00:44:59,109 --> 00:44:56,960
will change his physical properties

1095
00:45:01,030 --> 00:44:59,119
including its solubility dramatically

1096
00:45:03,109 --> 00:45:01,040
and this therefore is not an adequate

1097
00:45:05,030 --> 00:45:03,119
molecule for

1098
00:45:07,750 --> 00:45:05,040
or darwinism

1099
00:45:12,470 --> 00:45:08,710
good

1100
00:45:16,309 --> 00:45:14,309
yeah and so i mean i just sort of

1101
00:45:18,150 --> 00:45:16,319
schematically put this out here so

1102
00:45:20,790 --> 00:45:18,160
you're looking at the repeating dipole

1103
00:45:22,790 --> 00:45:20,800
in peptides or in cell phones it's like

1104
00:45:23,589 --> 00:45:22,800
putting a bunch of magnets on a string

1105
00:45:25,270 --> 00:45:23,599
right

1106
00:45:26,710 --> 00:45:25,280
north poles in the south pole if you let

1107
00:45:29,030 --> 00:45:26,720
go of the ends of the string the whole

1108
00:45:30,470 --> 00:45:29,040
thing will collapse upon itself

1109
00:45:32,630 --> 00:45:30,480
but in contrast if you have a

1110
00:45:34,710 --> 00:45:32,640
polyelectrolyte that is a molecule with

1111
00:45:37,349 --> 00:45:34,720
a repeating charge here a repeating

1112
00:45:39,270 --> 00:45:37,359
negative charge but this also works

1113
00:45:41,829 --> 00:45:39,280
if the molecule has a repeating positive

1114
00:45:44,470 --> 00:45:41,839
charge that molecule doesn't fold and

1115
00:45:46,150 --> 00:45:44,480
therefore it can template and

1116
00:45:48,390 --> 00:45:46,160
the next thing i should mention is on

1117
00:45:50,390 --> 00:45:48,400
the next slide which is that

1118
00:45:52,790 --> 00:45:50,400
this if you get rid of that repeating

1119
00:45:55,270 --> 00:45:52,800
backbone charge you also lose

1120
00:45:56,950 --> 00:45:55,280
blocks and qrik rules so here's just a

1121
00:45:59,829 --> 00:45:56,960
structure of one of those cell phone

1122
00:46:00,950 --> 00:45:59,839
molecules which i've shown we have a uu

1123
00:46:04,309 --> 00:46:00,960
pair

1124
00:46:05,829 --> 00:46:04,319
um the next slide uh shows you a little

1125
00:46:08,470 --> 00:46:05,839
bit more graphically what's going on

1126
00:46:11,670 --> 00:46:08,480
here you've got two kinds of repulsion

1127
00:46:13,109 --> 00:46:11,680
right you have the repulsion at the top

1128
00:46:15,670 --> 00:46:13,119
of that structure where the

1129
00:46:18,230 --> 00:46:15,680
double-headed arrows are showing

1130
00:46:19,670 --> 00:46:18,240
repulsion between backbone phosphates of

1131
00:46:21,030 --> 00:46:19,680
a single strand

1132
00:46:23,750 --> 00:46:21,040
and that's of course what keeps the

1133
00:46:25,750 --> 00:46:23,760
molecule unfolded and then you'll notice

1134
00:46:28,710 --> 00:46:25,760
that the coulombic charge repulsion

1135
00:46:31,510 --> 00:46:28,720
between strands what that does is lets

1136
00:46:34,870 --> 00:46:31,520
the molecules

1137
00:46:36,630 --> 00:46:34,880
law

1138
00:46:38,390 --> 00:46:36,640
predicts of course that the backbones

1139
00:46:40,309 --> 00:46:38,400
repel in fact

1140
00:46:42,390 --> 00:46:40,319
as an experimental piece of evidence to

1141
00:46:45,030 --> 00:46:42,400
support that dna duplexes are more

1142
00:46:47,109 --> 00:46:45,040
stable in high salt where the backbone

1143
00:46:48,309 --> 00:46:47,119
charges are shielded from each other by

1144
00:46:50,870 --> 00:46:48,319
salt

1145
00:46:53,589 --> 00:46:50,880
um but what this backbone repeating

1146
00:46:55,589 --> 00:46:53,599
charge does is drives strand strand

1147
00:46:57,829 --> 00:46:55,599
interactions as far as possible from the

1148
00:47:00,390 --> 00:46:57,839
backbone and that's what gives watson

1149
00:47:02,390 --> 00:47:00,400
qrik rules get rid of the repeating

1150
00:47:04,309 --> 00:47:02,400
backbone charges is now many synthetic

1151
00:47:07,270 --> 00:47:04,319
biologists have done

1152
00:47:09,190 --> 00:47:07,280
that that those rules go away

1153
00:47:11,750 --> 00:47:09,200
okay so go to the next slide for me

1154
00:47:14,069 --> 00:47:11,760
please

1155
00:47:16,150 --> 00:47:14,079
yeah so the darwinian informational

1156
00:47:18,069 --> 00:47:16,160
biopolymers must be charged because

1157
00:47:20,790 --> 00:47:18,079
among uh in water at least because it

1158
00:47:22,630 --> 00:47:20,800
keeps the polymer dissolved tomorrow

1159
00:47:25,270 --> 00:47:22,640
these backbone backbone coulomb

1160
00:47:26,950 --> 00:47:25,280
repulsions force strand strand contacts

1161
00:47:29,270 --> 00:47:26,960
are the watson crick edges of the

1162
00:47:31,190 --> 00:47:29,280
nuclear bases that's what gives you the

1163
00:47:33,030 --> 00:47:31,200
rules that you memorize in middle school

1164
00:47:35,670 --> 00:47:33,040
a pairs with t and g

1165
00:47:37,510 --> 00:47:35,680
c and of course polyanionic structure

1166
00:47:39,829 --> 00:47:37,520
discourages folding and that's what lets

1167
00:47:41,030 --> 00:47:39,839
you do template

1168
00:47:45,109 --> 00:47:41,040
all right

1169
00:47:49,990 --> 00:47:47,990
and by the way synthesis

1170
00:47:52,470 --> 00:47:50,000
again tests as i did not mention this

1171
00:47:53,750 --> 00:47:52,480
when i put up all these slides of all

1172
00:47:55,990 --> 00:47:53,760
these structures that fit the

1173
00:47:57,270 --> 00:47:56,000
schrodinger aperiodic crystal structure

1174
00:47:59,910 --> 00:47:57,280
but everything that we do in this

1175
00:48:01,990 --> 00:47:59,920
molecule also

1176
00:48:04,549 --> 00:48:02,000
has that repeating charge phosphate in

1177
00:48:07,030 --> 00:48:04,559
the backbone so this is a perfectly good

1178
00:48:09,750 --> 00:48:07,040
evolvable genetic system with 12 letters

1179
00:48:13,030 --> 00:48:09,760
instead of four i'm not saying necessary

1180
00:48:15,990 --> 00:48:13,040
that life on europa or enceladus

1181
00:48:18,710 --> 00:48:16,000
or sub i know in the water ammonia ocean

1182
00:48:20,710 --> 00:48:18,720
beneath titan will have a 12 letter off

1183
00:48:23,430 --> 00:48:20,720
of it but they could because they meet

1184
00:48:25,670 --> 00:48:23,440
the two criteria of required for

1185
00:48:27,910 --> 00:48:25,680
darwinism and by the way these are

1186
00:48:29,750 --> 00:48:27,920
sufficient criteria we actually don't

1187
00:48:32,390 --> 00:48:29,760
have to have any other features of that

1188
00:48:34,230 --> 00:48:32,400
biopolymer it has to be a repeating

1189
00:48:35,109 --> 00:48:34,240
backbone charge that can be a positive

1190
00:48:36,549 --> 00:48:35,119
charge

1191
00:48:38,950 --> 00:48:36,559
and the building blocks must be

1192
00:48:41,430 --> 00:48:38,960
exchangeable without changing their

1193
00:48:42,710 --> 00:48:41,440
overall size and packing

1194
00:48:46,150 --> 00:48:42,720
all right

1195
00:48:49,109 --> 00:48:46,950
great

1196
00:48:51,829 --> 00:48:49,119
okay no one's either i've either killed

1197
00:48:53,990 --> 00:48:51,839
you all or

1198
00:48:56,710 --> 00:48:54,000
all right so the next slide says all

1199
00:48:57,750 --> 00:48:56,720
right great so this by the way just for

1200
00:48:59,349 --> 00:48:57,760
fun

1201
00:49:02,390 --> 00:48:59,359
i just put some stuff in here just to

1202
00:49:04,230 --> 00:49:02,400
show you how good a 12 genetic system is

1203
00:49:07,270 --> 00:49:04,240
as long as it keeps the schrodinger it

1204
00:49:08,630 --> 00:49:07,280
periodic crystal structure

1205
00:49:10,390 --> 00:49:08,640
in tow and

1206
00:49:12,230 --> 00:49:10,400
the repeating

1207
00:49:14,309 --> 00:49:12,240
bonding patterns we just published this

1208
00:49:17,030 --> 00:49:14,319
paper with an eight letter genetic

1209
00:49:19,030 --> 00:49:17,040
system where we measured hundreds of

1210
00:49:22,630 --> 00:49:19,040
melting temperatures of thermodynamic

1211
00:49:26,790 --> 00:49:22,640
properties of the formation of atgc sb

1212
00:49:29,589 --> 00:49:26,800
and zp pairs the sb and zp pairs you've

1213
00:49:32,390 --> 00:49:29,599
never seen in your middle school classes

1214
00:49:33,829 --> 00:49:32,400
but there they are structurally and

1215
00:49:36,390 --> 00:49:33,839
if you want to look at the predicted

1216
00:49:38,150 --> 00:49:36,400
melting temperatures on the right side

1217
00:49:40,549 --> 00:49:38,160
on the

1218
00:49:43,349 --> 00:49:40,559
x-axis and the experimental temperatures

1219
00:49:46,069 --> 00:49:43,359
on the y-axis

1220
00:49:48,150 --> 00:49:46,079
the correlation coefficient is uh r

1221
00:49:50,470 --> 00:49:48,160
square is about 0.87

1222
00:49:53,829 --> 00:49:50,480
this is just as good as with natural dna

1223
00:49:55,750 --> 00:49:53,839
and by the way the depends from this are

1224
00:49:58,630 --> 00:49:55,760
not the funny bases not the funny

1225
00:50:00,710 --> 00:49:58,640
nucleotides they outlier is a t

1226
00:50:03,589 --> 00:50:00,720
okay which as you know is joined by only

1227
00:50:05,270 --> 00:50:03,599
two hydrogen bonds and that creates no

1228
00:50:07,670 --> 00:50:05,280
ends of problems when you're trying to

1229
00:50:10,950 --> 00:50:07,680
design primers and probes

1230
00:50:13,349 --> 00:50:10,960
do biotechnology but the point is that

1231
00:50:15,510 --> 00:50:13,359
this is an evolvable system which is

1232
00:50:16,870 --> 00:50:15,520
just meeting two requirements

1233
00:50:19,829 --> 00:50:16,880
scrotinger's requirement and the

1234
00:50:21,990 --> 00:50:19,839
polyelectrolyte requirement and other

1235
00:50:23,990 --> 00:50:22,000
everything else can be changed in the

1236
00:50:25,910 --> 00:50:24,000
system including the hydrogen bonding

1237
00:50:27,430 --> 00:50:25,920
patterns the number of bases the side

1238
00:50:29,349 --> 00:50:27,440
chains depends on the basis the

1239
00:50:31,030 --> 00:50:29,359
functionality of the bases any of a

1240
00:50:32,950 --> 00:50:31,040
number of things so again i'm not

1241
00:50:34,470 --> 00:50:32,960
necessarily expecting to see this on

1242
00:50:37,109 --> 00:50:34,480
enceladus but

1243
00:50:38,710 --> 00:50:37,119
um you can see that the rules are

1244
00:50:40,470 --> 00:50:38,720
predictive in the sense that we can go

1245
00:50:42,870 --> 00:50:40,480
into the laboratory and make our own

1246
00:50:44,790 --> 00:50:42,880
darwinian systems just by following

1247
00:50:45,829 --> 00:50:44,800
these two rules

1248
00:50:49,430 --> 00:50:45,839
okay

1249
00:50:55,430 --> 00:50:51,750
yeah and i just am beating a dead horse

1250
00:51:00,790 --> 00:50:58,790
okay so okay now we want to use these

1251
00:51:03,510 --> 00:51:00,800
features to build a life detection

1252
00:51:05,190 --> 00:51:03,520
device and um

1253
00:51:06,390 --> 00:51:05,200
one of the things that's very important

1254
00:51:08,950 --> 00:51:06,400
to know is that if i have a

1255
00:51:11,270 --> 00:51:08,960
polyelectrolyte if i have it in dilute

1256
00:51:14,230 --> 00:51:11,280
solution it's very easy to concentrate

1257
00:51:15,990 --> 00:51:14,240
that from a dilute solution well how all

1258
00:51:17,829 --> 00:51:16,000
i have to well all i have to do is put

1259
00:51:20,150 --> 00:51:17,839
down a detector which is at the bottom

1260
00:51:21,589 --> 00:51:20,160
of the slide with a bunch of positive

1261
00:51:23,349 --> 00:51:21,599
charges on it

1262
00:51:25,430 --> 00:51:23,359
and that of course will absorb a

1263
00:51:27,910 --> 00:51:25,440
biopolymer from solution with a bunch of

1264
00:51:30,790 --> 00:51:27,920
negative charges on it and because of

1265
00:51:33,190 --> 00:51:30,800
what we call polyvalency

1266
00:51:36,950 --> 00:51:33,200
um the repeating negatively charged

1267
00:51:39,030 --> 00:51:36,960
backbone will displace

1268
00:51:41,190 --> 00:51:39,040
inorganic ions like bromide with a

1269
00:51:44,549 --> 00:51:41,200
single negative charge or sulfate with

1270
00:51:46,309 --> 00:51:44,559
two negative charges or perchlorate

1271
00:51:48,470 --> 00:51:46,319
which unfortunately has one negative

1272
00:51:49,430 --> 00:51:48,480
charge but never mind

1273
00:51:51,829 --> 00:51:49,440
that's

1274
00:51:53,430 --> 00:51:51,839
but so it's very easy if i take a dilute

1275
00:51:55,109 --> 00:51:53,440
solution

1276
00:51:56,309 --> 00:51:55,119
to concentrate

1277
00:52:05,190 --> 00:51:56,319
a

1278
00:52:08,710 --> 00:52:05,200
loop solution

1279
00:52:13,430 --> 00:52:11,510
and so you can imagine a device in fact

1280
00:52:15,190 --> 00:52:13,440
we wrote a paper about this two years

1281
00:52:15,990 --> 00:52:15,200
ago which you can read

1282
00:52:19,030 --> 00:52:16,000
where

1283
00:52:21,030 --> 00:52:19,040
you could put two plates okay

1284
00:52:22,710 --> 00:52:21,040
in and the two plates one of them has a

1285
00:52:24,549 --> 00:52:22,720
bunch of negative charges on it one of

1286
00:52:27,270 --> 00:52:24,559
them has a bunch of positive charges on

1287
00:52:29,030 --> 00:52:27,280
it the first one is supposed to capture

1288
00:52:31,430 --> 00:52:29,040
martian genetic polymers if the

1289
00:52:32,390 --> 00:52:31,440
repeating backbone charge happens have

1290
00:52:33,430 --> 00:52:32,400
the

1291
00:52:34,309 --> 00:52:33,440
positive

1292
00:52:36,150 --> 00:52:34,319
the

1293
00:52:38,549 --> 00:52:36,160
positively charged plate captures

1294
00:52:41,670 --> 00:52:38,559
martian dna if it's repeating backbone

1295
00:52:44,069 --> 00:52:41,680
unit charge is negative and so they will

1296
00:52:45,589 --> 00:52:44,079
concentrate this from dilute solution

1297
00:52:49,030 --> 00:52:45,599
and then the next point we should make

1298
00:52:51,270 --> 00:52:49,040
is that you want to be able to

1299
00:52:53,910 --> 00:52:51,280
then asks or query what is absorbed to

1300
00:52:56,230 --> 00:52:53,920
see whether it is fitting

1301
00:52:58,870 --> 00:52:56,240
schrodinger's requirement that's kind of

1302
00:53:01,109 --> 00:52:58,880
interesting because

1303
00:53:03,510 --> 00:53:01,119
if i take dna and its building blocks

1304
00:53:05,750 --> 00:53:03,520
each of the building blocks is chiral

1305
00:53:06,870 --> 00:53:05,760
and so they will rotate plain polarized

1306
00:53:09,589 --> 00:53:06,880
light

1307
00:53:11,910 --> 00:53:09,599
um but if i hook them all together the

1308
00:53:14,069 --> 00:53:11,920
chirality is bigger you have a super

1309
00:53:15,750 --> 00:53:14,079
chirality and that's because each of the

1310
00:53:19,190 --> 00:53:15,760
little building blocks was the same

1311
00:53:22,069 --> 00:53:19,200
chirality that is homochiron induces a

1312
00:53:24,630 --> 00:53:22,079
bigger chirality in this particular case

1313
00:53:27,349 --> 00:53:24,640
for example in your dna a right-handed

1314
00:53:29,829 --> 00:53:27,359
not a left-handed double helix and that

1315
00:53:31,030 --> 00:53:29,839
right-handed double helix has more

1316
00:53:33,190 --> 00:53:31,040
rotation

1317
00:53:35,670 --> 00:53:33,200
of the polarized light

1318
00:53:38,549 --> 00:53:35,680
it's more optically active

1319
00:53:40,829 --> 00:53:38,559
if you will it's super chiral because it

1320
00:53:42,710 --> 00:53:40,839
has amplified the

1321
00:53:44,470 --> 00:53:42,720
microscopic chirality of each of its

1322
00:53:46,710 --> 00:53:44,480
building blocks and that's actually

1323
00:53:49,030 --> 00:53:46,720
something that can be detected

1324
00:53:50,950 --> 00:53:49,040
by in this particular case making the

1325
00:53:53,270 --> 00:53:50,960
mole this thing that's absorbing the

1326
00:53:55,670 --> 00:53:53,280
molecules um

1327
00:53:57,270 --> 00:53:55,680
a waveguide and putting plane polarized

1328
00:53:58,390 --> 00:53:57,280
light through it

1329
00:54:00,549 --> 00:53:58,400
um so

1330
00:54:02,790 --> 00:54:00,559
if there is in fact a homochiropolymer

1331
00:54:05,510 --> 00:54:02,800
absorbed that well plain polarized light

1332
00:54:08,309 --> 00:54:05,520
will be much more rotating

1333
00:54:10,150 --> 00:54:08,319
rotated than if it's not

1334
00:54:14,309 --> 00:54:10,160
um

1335
00:54:18,230 --> 00:54:16,390
yeah and so you know then there's only

1336
00:54:20,470 --> 00:54:18,240
questions about sensitivity which i

1337
00:54:22,870 --> 00:54:20,480
won't go through here but obviously you

1338
00:54:24,549 --> 00:54:22,880
can just do a biacore surface plasma

1339
00:54:26,230 --> 00:54:24,559
resonance absorption to detect the

1340
00:54:28,710 --> 00:54:26,240
absorption of these things the

1341
00:54:30,150 --> 00:54:28,720
sensitivity is low the long path length

1342
00:54:31,829 --> 00:54:30,160
is required

1343
00:54:34,549 --> 00:54:31,839
and we don't actually know what the

1344
00:54:36,789 --> 00:54:34,559
refractive index is of martian dna so

1345
00:54:40,230 --> 00:54:36,799
you have a problem managing that so the

1346
00:54:43,109 --> 00:54:41,430
is of course you can look for the

1347
00:54:45,750 --> 00:54:43,119
ultraviolet absorption of the side

1348
00:54:47,589 --> 00:54:45,760
chains onto that waveguide

1349
00:54:49,829 --> 00:54:47,599
that's a more sensitive test but again

1350
00:54:51,109 --> 00:54:49,839
we don't know that martian dna absorbs

1351
00:54:53,510 --> 00:54:51,119
uv light

1352
00:54:55,270 --> 00:54:53,520
the next slide

1353
00:54:58,069 --> 00:54:55,280
is what i just mentioned this sort of

1354
00:55:00,470 --> 00:54:58,079
macro chirality we can look for rotation

1355
00:55:01,910 --> 00:55:00,480
of plane polarized light which will be

1356
00:55:04,309 --> 00:55:01,920
greater

1357
00:55:06,630 --> 00:55:04,319
for my polymer of homocurrent building

1358
00:55:07,829 --> 00:55:06,640
blocks than rotation of the monomers

1359
00:55:11,270 --> 00:55:07,839
collectively

1360
00:55:14,470 --> 00:55:12,789
and by the way none of this precludes

1361
00:55:16,470 --> 00:55:14,480
downstream analysis if you're building

1362
00:55:19,109 --> 00:55:16,480
your life detection instrument so you

1363
00:55:21,270 --> 00:55:19,119
know we can obviously collect the

1364
00:55:23,829 --> 00:55:21,280
allegedly darwinian polyelectrolyte

1365
00:55:26,230 --> 00:55:23,839
polymer and then displace it later to do

1366
00:55:28,950 --> 00:55:26,240
multi-mass effect or some information to

1367
00:55:31,030 --> 00:55:28,960
get some information about the detailed

1368
00:55:34,390 --> 00:55:31,040
structure of the polyelectrolyte next

1369
00:55:38,549 --> 00:55:36,230
yeah so i mean this is a complete

1370
00:55:41,109 --> 00:55:38,559
architecture it's a wonderful concept

1371
00:55:43,109 --> 00:55:41,119
you go to the martian polar ice cap or

1372
00:55:45,270 --> 00:55:43,119
for that matter you can go to antarctica

1373
00:55:46,549 --> 00:55:45,280
you dump ice in the top

1374
00:55:48,710 --> 00:55:46,559
um

1375
00:55:51,510 --> 00:55:48,720
you know the mars cap is nice because it

1376
00:55:53,750 --> 00:55:51,520
surveys the entire accessible surface by

1377
00:55:55,829 --> 00:55:53,760
dust storms so you don't have to do

1378
00:55:58,470 --> 00:55:55,839
caching or make correct guesses about

1379
00:56:00,549 --> 00:55:58,480
locales to sample you got to stall the

1380
00:56:03,190 --> 00:56:00,559
sample but you got to keep in mind that

1381
00:56:05,270 --> 00:56:03,200
as all the other steps that i'm doing

1382
00:56:07,910 --> 00:56:05,280
are using energy but that can all be

1383
00:56:09,910 --> 00:56:07,920
added to the budget for the thawing

1384
00:56:11,750 --> 00:56:09,920
budget for the energy of falling of the

1385
00:56:13,750 --> 00:56:11,760
material you got to disrupt cell

1386
00:56:15,910 --> 00:56:13,760
compartments now remember i'm going to

1387
00:56:18,630 --> 00:56:15,920
put this into a cyclonic sharpless

1388
00:56:20,150 --> 00:56:18,640
centrifuge and if i've got dust in there

1389
00:56:21,990 --> 00:56:20,160
in cells thus

1390
00:56:24,710 --> 00:56:22,000
the abrasive dust will

1391
00:56:26,710 --> 00:56:24,720
disrupt cells pretty much for free

1392
00:56:29,430 --> 00:56:26,720
this sharpless centrifuge

1393
00:56:32,789 --> 00:56:29,440
that central tube is spinning and so all

1394
00:56:34,710 --> 00:56:32,799
the minerals go to the outside surface

1395
00:56:35,910 --> 00:56:34,720
and some of those minerals maybe a lot

1396
00:56:37,670 --> 00:56:35,920
of them are chiral and they would

1397
00:56:39,430 --> 00:56:37,680
interfere with the optical activity

1398
00:56:40,870 --> 00:56:39,440
measurement so they're being

1399
00:56:42,789 --> 00:56:40,880
set out to the side you can actually

1400
00:56:45,510 --> 00:56:42,799
withdraw them for

1401
00:56:46,789 --> 00:56:45,520
if you want to to and analyze them and

1402
00:56:49,349 --> 00:56:46,799
then you pass the liquid through your

1403
00:56:51,030 --> 00:56:49,359
polyelectric like capture things and you

1404
00:56:52,710 --> 00:56:51,040
can sample any of these things

1405
00:56:54,950 --> 00:56:52,720
microscopically

1406
00:56:56,870 --> 00:56:54,960
or you can do mineralogical samples i'm

1407
00:56:58,230 --> 00:56:56,880
delighted to look at that cyclonic

1408
00:57:00,470 --> 00:56:58,240
filtrated minerals and see whether

1409
00:57:02,470 --> 00:57:00,480
there's orate there you can see

1410
00:57:04,710 --> 00:57:02,480
metabolites in the evaporated waste and

1411
00:57:06,789 --> 00:57:04,720
you can look at downstream analysis of

1412
00:57:08,950 --> 00:57:06,799
polyelectrolytes with there's really no

1413
00:57:10,150 --> 00:57:08,960
possibility here for false positives

1414
00:57:12,230 --> 00:57:10,160
because

1415
00:57:15,349 --> 00:57:12,240
there's no other way of getting a

1416
00:57:17,750 --> 00:57:15,359
polyelectrolyte building block uh

1417
00:57:19,430 --> 00:57:17,760
assembled assembly with a set of

1418
00:57:21,589 --> 00:57:19,440
building blocks that are homochiral

1419
00:57:22,870 --> 00:57:21,599
except by the influence of darwinism i

1420
00:57:23,829 --> 00:57:22,880
think

1421
00:57:25,589 --> 00:57:23,839
of course

1422
00:57:28,630 --> 00:57:25,599
false negatives are a matter of

1423
00:57:31,589 --> 00:57:28,640
sensitivity of the device

1424
00:57:34,950 --> 00:57:31,599
all right that's all i have right now um

1425
00:57:37,109 --> 00:57:34,960
i think there's no slide to follow right

1426
00:57:39,030 --> 00:57:37,119
yeah there you go so let me stop and

1427
00:57:40,309 --> 00:57:39,040
answer any questions you have

1428
00:57:43,750 --> 00:57:40,319
steve unfortunately we're running a

1429
00:57:46,789 --> 00:57:43,760
little short on time so maybe if people

1430
00:57:48,549 --> 00:57:46,799
um have a chance to ask you questions

1431
00:57:50,789 --> 00:57:48,559
maybe they can do that offline or maybe

1432
00:57:52,950 --> 00:57:50,799
in a chat window a little bit later on

1433
00:57:56,890 --> 00:57:52,960
if that would work for you no problem

1434
00:57:56,900 --> 00:58:01,750
[Applause]

1435
00:58:01,760 --> 00:58:06,829
okay we got arvind

1436
00:58:13,190 --> 00:58:09,670
online all right can everyone see the

1437
00:58:16,710 --> 00:58:14,150
either

1438
00:58:19,190 --> 00:58:16,720
uh thanks uh gary kathy

1439
00:58:20,710 --> 00:58:19,200
ken and penny for organizing this uh

1440
00:58:22,150 --> 00:58:20,720
virtual conference it's awesome to

1441
00:58:24,390 --> 00:58:22,160
listen to a variety of different things

1442
00:58:25,510 --> 00:58:24,400
already and some of the concepts put

1443
00:58:27,990 --> 00:58:25,520
forward

1444
00:58:30,150 --> 00:58:28,000
so today i'm kind of going to be talking

1445
00:58:32,390 --> 00:58:30,160
about some weird stuff that we've been

1446
00:58:33,829 --> 00:58:32,400
noticing with single-stranded dna

1447
00:58:36,150 --> 00:58:33,839
viruses and i'm going to take you into

1448
00:58:39,349 --> 00:58:36,160
the world of single-stranded dna viruses

1449
00:58:43,829 --> 00:58:39,359
in quite a complex system

1450
00:58:49,030 --> 00:58:46,470
all right so before i go into

1451
00:58:50,309 --> 00:58:49,040
the whole field of signals with dna

1452
00:58:52,309 --> 00:58:50,319
viruses i want to actually start

1453
00:58:54,549 --> 00:58:52,319
tackling a couple of things which i

1454
00:58:56,309 --> 00:58:54,559
think are very important and these are

1455
00:58:58,950 --> 00:58:56,319
concepts of evolution

1456
00:59:00,630 --> 00:58:58,960
and we all know that viruses evolved by

1457
00:59:02,470 --> 00:59:00,640
three main mechanisms

1458
00:59:04,789 --> 00:59:02,480
and one is basically nucleotide

1459
00:59:07,349 --> 00:59:04,799
substitutions where you basically get

1460
00:59:10,230 --> 00:59:07,359
mutations occurring or some of which are

1461
00:59:12,390 --> 00:59:10,240
identifiers some of which are beneficial

1462
00:59:15,030 --> 00:59:12,400
others are pretty much

1463
00:59:16,630 --> 00:59:15,040
neutral and then to repair mutations

1464
00:59:17,750 --> 00:59:16,640
that are deleterious

1465
00:59:18,950 --> 00:59:17,760
by

1466
00:59:20,630 --> 00:59:18,960
again

1467
00:59:22,870 --> 00:59:20,640
mutating those sites is actually very

1468
00:59:24,230 --> 00:59:22,880
complex and to fix them is a very very

1469
00:59:26,309 --> 00:59:24,240
slow process

1470
00:59:28,870 --> 00:59:26,319
however there are viruses that are very

1471
00:59:31,109 --> 00:59:28,880
good at fixing a variety of mutations by

1472
00:59:33,030 --> 00:59:31,119
a mechanism called recombination

1473
00:59:35,190 --> 00:59:33,040
and this usually happens when you have

1474
00:59:36,870 --> 00:59:35,200
two viral templates within

1475
00:59:38,630 --> 00:59:36,880
a cell

1476
00:59:40,069 --> 00:59:38,640
and what happens is there is template

1477
00:59:41,270 --> 00:59:40,079
swapping that takes place during

1478
00:59:43,270 --> 00:59:41,280
reputation

1479
00:59:46,309 --> 00:59:43,280
and in this mechanism you can generate

1480
00:59:48,390 --> 00:59:46,319
chimeric viruses numeric genomes and as

1481
00:59:50,950 --> 00:59:48,400
a consequence of that to repair a

1482
00:59:53,670 --> 00:59:50,960
deleterious mutation is actually very

1483
00:59:55,910 --> 00:59:53,680
very beneficial it's very efficient in

1484
00:59:56,870 --> 00:59:55,920
this kind of mechanism but at the same

1485
00:59:59,030 --> 00:59:56,880
time

1486
01:00:01,510 --> 00:59:59,040
if a virus is trying to explore sequence

1487
01:00:03,190 --> 01:00:01,520
landscapes then it is able to do this

1488
01:00:05,190 --> 01:00:03,200
very efficiently using these kind of

1489
01:00:06,950 --> 01:00:05,200
mechanisms

1490
01:00:08,870 --> 01:00:06,960
um and then

1491
01:00:11,190 --> 01:00:08,880
we have something that is very very

1492
01:00:13,349 --> 01:00:11,200
unusual but unique in the sense that we

1493
01:00:15,349 --> 01:00:13,359
have reassortment which takes place

1494
01:00:17,510 --> 01:00:15,359
which we commonly know in the field of

1495
01:00:19,910 --> 01:00:17,520
influenza where you have eight segments

1496
01:00:21,829 --> 01:00:19,920
that they can reassort over time and as

1497
01:00:23,990 --> 01:00:21,839
a result of that you get different

1498
01:00:26,789 --> 01:00:24,000
variations of at least the hemoglobin

1499
01:00:30,069 --> 01:00:26,799
and neuraminidase and as a consequence

1500
01:00:31,589 --> 01:00:30,079
we have immunizations every year to try

1501
01:00:33,030 --> 01:00:31,599
and combat the different variants that

1502
01:00:34,549 --> 01:00:33,040
come through through

1503
01:00:36,870 --> 01:00:34,559
reassortment

1504
01:00:39,030 --> 01:00:36,880
but what is less known is that there are

1505
01:00:41,670 --> 01:00:39,040
viruses which are segmented and

1506
01:00:42,789 --> 01:00:41,680
multipatient viruses as well where each

1507
01:00:45,109 --> 01:00:42,799
segment

1508
01:00:47,750 --> 01:00:45,119
or each genomic element that constitute

1509
01:00:50,230 --> 01:00:47,760
the entire genome is packaged into an

1510
01:00:52,150 --> 01:00:50,240
individual capsid and there as well you

1511
01:00:54,549 --> 01:00:52,160
get reassortment taking place so it's

1512
01:00:57,190 --> 01:00:54,559
almost like each chromosome is patched

1513
01:01:00,150 --> 01:00:57,200
into an individual virion and those all

1514
01:01:02,549 --> 01:01:00,160
have to act together within a system

1515
01:01:04,470 --> 01:01:02,559
um to actually create an active

1516
01:01:06,789 --> 01:01:04,480
infection

1517
01:01:08,870 --> 01:01:06,799
so if we kind of unpack all of this and

1518
01:01:11,750 --> 01:01:08,880
start looking at viruses in a general

1519
01:01:14,390 --> 01:01:11,760
context viruses are very unusual in the

1520
01:01:17,750 --> 01:01:14,400
sense that the genomic material can vary

1521
01:01:19,829 --> 01:01:17,760
from dna to rna and also in terms of

1522
01:01:22,150 --> 01:01:19,839
polarity and also whether they're

1523
01:01:24,069 --> 01:01:22,160
double-stranded or not there also is

1524
01:01:26,470 --> 01:01:24,079
topological differences whether they can

1525
01:01:28,390 --> 01:01:26,480
be circular or linear

1526
01:01:30,950 --> 01:01:28,400
the things that is really unique about

1527
01:01:33,589 --> 01:01:30,960
single-stranded dna viruses is

1528
01:01:35,349 --> 01:01:33,599
majority of their muscular viruses

1529
01:01:37,190 --> 01:01:35,359
however

1530
01:01:39,670 --> 01:01:37,200
there is something that is very amazing

1531
01:01:41,750 --> 01:01:39,680
is that they actually are able to infect

1532
01:01:43,510 --> 01:01:41,760
all donald trump

1533
01:01:45,750 --> 01:01:43,520
and you're able to infect archaea

1534
01:01:48,710 --> 01:01:45,760
bacteria we know viruses that infect

1535
01:01:50,950 --> 01:01:48,720
diatoms fungi a variety of invertebrates

1536
01:01:53,030 --> 01:01:50,960
plants and obviously

1537
01:01:55,670 --> 01:01:53,040
through metagenomic approaches we're

1538
01:01:57,109 --> 01:01:55,680
discovering viruses that we have no idea

1539
01:01:59,109 --> 01:01:57,119
what they infect

1540
01:02:00,789 --> 01:01:59,119
but within these single stranded dna

1541
01:02:02,150 --> 01:02:00,799
viruses they're different conformations

1542
01:02:04,789 --> 01:02:02,160
of genomic

1543
01:02:07,029 --> 01:02:04,799
systems where you could have monopod

1544
01:02:09,029 --> 01:02:07,039
site or multipartite

1545
01:02:10,789 --> 01:02:09,039
molecules so basically you could have

1546
01:02:13,829 --> 01:02:10,799
one single chromosome into which all the

1547
01:02:16,390 --> 01:02:13,839
genetic material is packaged or you have

1548
01:02:18,069 --> 01:02:16,400
multiple chromosomes that then carry

1549
01:02:20,549 --> 01:02:18,079
different genetic information and

1550
01:02:23,430 --> 01:02:20,559
they're all unique in that context

1551
01:02:25,510 --> 01:02:23,440
but one thing that we've really

1552
01:02:26,950 --> 01:02:25,520
focused on these viruses primarily is

1553
01:02:29,190 --> 01:02:26,960
because we're under keen on

1554
01:02:31,029 --> 01:02:29,200
understanding evolution of these viruses

1555
01:02:32,710 --> 01:02:31,039
and these viral genomes are relatively

1556
01:02:35,029 --> 01:02:32,720
small so we can actually sequence them

1557
01:02:37,109 --> 01:02:35,039
to completion and we can look at coding

1558
01:02:39,430 --> 01:02:37,119
and non-coding regions to figure out

1559
01:02:41,349 --> 01:02:39,440
what the variations are

1560
01:02:43,029 --> 01:02:41,359
now one of the unique thing about some

1561
01:02:46,069 --> 01:02:43,039
of these viruses single-stranded dna

1562
01:02:48,549 --> 01:02:46,079
viruses not all but a vast number of

1563
01:02:51,190 --> 01:02:48,559
them is that they have certain very very

1564
01:02:53,190 --> 01:02:51,200
unique properties and one of them is a

1565
01:02:55,750 --> 01:02:53,200
enzyme called replication initiator

1566
01:02:57,430 --> 01:02:55,760
protein which actually has two domains

1567
01:03:00,309 --> 01:02:57,440
it's got an endonuclease domain and a

1568
01:03:01,750 --> 01:03:00,319
helicase domain which initiate the whole

1569
01:03:03,589 --> 01:03:01,760
mechanism of replication of these

1570
01:03:04,390 --> 01:03:03,599
circular molecules

1571
01:03:06,470 --> 01:03:04,400
and

1572
01:03:09,109 --> 01:03:06,480
very very unique motifs which are very

1573
01:03:12,390 --> 01:03:09,119
recognizable across the system

1574
01:03:15,029 --> 01:03:12,400
but if we were to break those two motifs

1575
01:03:17,109 --> 01:03:15,039
and draw some phylogeny infer phylogeny

1576
01:03:19,190 --> 01:03:17,119
based on that based on all the single

1577
01:03:22,150 --> 01:03:19,200
stranded dna viruses that encode these

1578
01:03:24,549 --> 01:03:22,160
kind of proteins we notice that the

1579
01:03:26,710 --> 01:03:24,559
phylogeny is not congruent and that kind

1580
01:03:29,670 --> 01:03:26,720
of suggests to us that these viruses

1581
01:03:32,069 --> 01:03:29,680
have at some point exchanged material or

1582
01:03:33,990 --> 01:03:32,079
are recombinant even at a protein level

1583
01:03:35,589 --> 01:03:34,000
so some of this obviously we can't

1584
01:03:37,349 --> 01:03:35,599
detect at the nucleotide level we can

1585
01:03:39,829 --> 01:03:37,359
see it at a protein level because of

1586
01:03:41,510 --> 01:03:39,839
these variations

1587
01:03:43,510 --> 01:03:41,520
but the other thing that is staggering

1588
01:03:45,510 --> 01:03:43,520
about these viruses and these are

1589
01:03:48,069 --> 01:03:45,520
nucleotide substitution rates that we've

1590
01:03:49,510 --> 01:03:48,079
calculated other people have calculated

1591
01:03:51,670 --> 01:03:49,520
we've calculated based on lab

1592
01:03:53,270 --> 01:03:51,680
experiments we've made infectious clones

1593
01:03:56,870 --> 01:03:53,280
put them into a system

1594
01:03:59,349 --> 01:03:56,880
measured mutation rates over 15 years

1595
01:04:01,829 --> 01:03:59,359
in some cases see what's been going on

1596
01:04:04,230 --> 01:04:01,839
and if you look at them that all across

1597
01:04:06,309 --> 01:04:04,240
the theme of single-stranded dna viruses

1598
01:04:08,309 --> 01:04:06,319
it appears to be a theme that the

1599
01:04:10,309 --> 01:04:08,319
mutation rates are really high or the

1600
01:04:13,029 --> 01:04:10,319
substitution rates are really high and

1601
01:04:15,990 --> 01:04:13,039
in some cases they're as high as those

1602
01:04:18,309 --> 01:04:16,000
of rna viruses and this general

1603
01:04:20,950 --> 01:04:18,319
hypothesis has always been that rna

1604
01:04:23,349 --> 01:04:20,960
viruses are actually error prone because

1605
01:04:25,829 --> 01:04:23,359
they use low fidelity enzymes

1606
01:04:28,950 --> 01:04:25,839
whereas here you've got dna viruses

1607
01:04:31,190 --> 01:04:28,960
which are using host dna polymerases yet

1608
01:04:33,109 --> 01:04:31,200
they have such high mutation rates or

1609
01:04:34,870 --> 01:04:33,119
substitution rates so that's kind of

1610
01:04:37,270 --> 01:04:34,880
something that's really been

1611
01:04:39,750 --> 01:04:37,280
hugging a whole group of us

1612
01:04:41,510 --> 01:04:39,760
so now let's start dwelving into small

1613
01:04:43,829 --> 01:04:41,520
groups of viruses and take you through a

1614
01:04:46,150 --> 01:04:43,839
journey of what we've been discovering

1615
01:04:47,670 --> 01:04:46,160
in the single-stranded dna virus field

1616
01:04:49,510 --> 01:04:47,680
and so there are these viruses called

1617
01:04:51,589 --> 01:04:49,520
gemini viruses that infect plants and

1618
01:04:53,829 --> 01:04:51,599
they're unique in the sense that if you

1619
01:04:55,349 --> 01:04:53,839
look at the topology of the genomes even

1620
01:04:57,750 --> 01:04:55,359
though they're single stranded they

1621
01:04:59,510 --> 01:04:57,760
bi-directionally transcribe so that

1622
01:05:02,470 --> 01:04:59,520
means the complementary sense is

1623
01:05:04,870 --> 01:05:02,480
required to transl transcribe some of

1624
01:05:07,190 --> 01:05:04,880
the open reading frames but at the most

1625
01:05:09,430 --> 01:05:07,200
they encode about five

1626
01:05:11,910 --> 01:05:09,440
to six uh proteins

1627
01:05:13,829 --> 01:05:11,920
but within this group at the top right

1628
01:05:16,069 --> 01:05:13,839
and uh left-hand side you can see there

1629
01:05:17,990 --> 01:05:16,079
are some things called bengoma viruses

1630
01:05:19,670 --> 01:05:18,000
and they can assume two conformations in

1631
01:05:21,270 --> 01:05:19,680
the sense they can be monopartite or

1632
01:05:23,510 --> 01:05:21,280
both bioptych but they have two

1633
01:05:26,309 --> 01:05:23,520
different molecules which are roughly

1634
01:05:28,150 --> 01:05:26,319
the same size about 2.7 kb get packaged

1635
01:05:29,990 --> 01:05:28,160
into individual variants and they have

1636
01:05:31,829 --> 01:05:30,000
to work together

1637
01:05:33,430 --> 01:05:31,839
but when we start unpacking these things

1638
01:05:34,870 --> 01:05:33,440
and we look at the two main prominent

1639
01:05:37,029 --> 01:05:34,880
proteins that they encode which is the

1640
01:05:39,190 --> 01:05:37,039
replicationist initiative protein and

1641
01:05:41,670 --> 01:05:39,200
the capsid protein and we in further

1642
01:05:44,069 --> 01:05:41,680
phylogenies we notice that in a vast

1643
01:05:46,309 --> 01:05:44,079
number of cases those phylogenys are not

1644
01:05:48,630 --> 01:05:46,319
congruent and that straightaway tells us

1645
01:05:51,029 --> 01:05:48,640
that these viruses are very recombinant

1646
01:05:53,349 --> 01:05:51,039
in nature they recombine very

1647
01:05:55,270 --> 01:05:53,359
commonly and evolve through mechanisms

1648
01:05:56,950 --> 01:05:55,280
of recombination

1649
01:05:59,109 --> 01:05:56,960
so at one point we thought okay let's

1650
01:06:01,670 --> 01:05:59,119
study mechanisms of recombination in

1651
01:06:03,270 --> 01:06:01,680
these viruses so if you start looking at

1652
01:06:04,789 --> 01:06:03,280
viruses in general and you want to study

1653
01:06:07,430 --> 01:06:04,799
recombination

1654
01:06:09,270 --> 01:06:07,440
there are basic hypothetical things that

1655
01:06:11,190 --> 01:06:09,280
you can put forward you take two genomes

1656
01:06:13,670 --> 01:06:11,200
that are say ten percent batteries from

1657
01:06:16,390 --> 01:06:13,680
each other at a nucleotide level chop

1658
01:06:18,789 --> 01:06:16,400
them in half make reciprocal chimeras

1659
01:06:20,470 --> 01:06:18,799
and put them into a system into host

1660
01:06:22,150 --> 01:06:20,480
and your outcomes can be a simple

1661
01:06:24,549 --> 01:06:22,160
recombinant which is a two breakpoint

1662
01:06:26,069 --> 01:06:24,559
recombinant where a small piece inserts

1663
01:06:27,349 --> 01:06:26,079
or you can have complex recombinants

1664
01:06:29,190 --> 01:06:27,359
where you have lots and lots of

1665
01:06:30,150 --> 01:06:29,200
recombination events so you get a mosaic

1666
01:06:32,870 --> 01:06:30,160
pattern

1667
01:06:34,789 --> 01:06:32,880
across the genome on the other side you

1668
01:06:36,710 --> 01:06:34,799
can also have unique sub genomic

1669
01:06:39,349 --> 01:06:36,720
elements where you get deletion and

1670
01:06:41,670 --> 01:06:39,359
insertion of unknown sequences in most

1671
01:06:43,670 --> 01:06:41,680
cases could be even host nucleic acid

1672
01:06:45,190 --> 01:06:43,680
that gets integrated

1673
01:06:46,950 --> 01:06:45,200
and when you analyze all of these

1674
01:06:48,870 --> 01:06:46,960
genomes there are going to be fitness

1675
01:06:51,589 --> 01:06:48,880
tradeoffs and you can measure fitness

1676
01:06:54,470 --> 01:06:51,599
tradeoffs which genomes are

1677
01:06:56,069 --> 01:06:54,480
beneficial which ones are not so we set

1678
01:06:58,230 --> 01:06:56,079
an experiment together where we thought

1679
01:07:00,630 --> 01:06:58,240
okay let's take two viruses these are

1680
01:07:01,589 --> 01:07:00,640
two brass infecting viruses and mazes

1681
01:07:03,349 --> 01:07:01,599
across

1682
01:07:05,670 --> 01:07:03,359
and we found these in africa there were

1683
01:07:07,349 --> 01:07:05,680
a problem with within the industry so we

1684
01:07:09,750 --> 01:07:07,359
were working with this

1685
01:07:10,870 --> 01:07:09,760
and we took two viruses that were 10

1686
01:07:13,190 --> 01:07:10,880
different from each other at the

1687
01:07:14,710 --> 01:07:13,200
nucleotide level we chopped them in half

1688
01:07:16,630 --> 01:07:14,720
give the other half to the other

1689
01:07:17,829 --> 01:07:16,640
individual make right make reciprocal

1690
01:07:19,349 --> 01:07:17,839
primeras

1691
01:07:20,870 --> 01:07:19,359
and then we put them back into a maze

1692
01:07:23,029 --> 01:07:20,880
genotype

1693
01:07:25,990 --> 01:07:23,039
and the viruses were able to recombine

1694
01:07:28,710 --> 01:07:26,000
and find an optimal solution

1695
01:07:30,710 --> 01:07:28,720
which is found in nature today

1696
01:07:33,190 --> 01:07:30,720
within 30 days

1697
01:07:36,630 --> 01:07:33,200
so they were able to explore 10 sequence

1698
01:07:38,390 --> 01:07:36,640
diversity in 30 days and get to

1699
01:07:40,390 --> 01:07:38,400
where they needed to be and what is

1700
01:07:42,870 --> 01:07:40,400
present in nature today

1701
01:07:45,190 --> 01:07:42,880
as an optimal solution in 10 days

1702
01:07:46,069 --> 01:07:45,200
and if you change the variety of main so

1703
01:07:47,670 --> 01:07:46,079
basically

1704
01:07:49,750 --> 01:07:47,680
you've got some sort of genetic traits

1705
01:07:51,910 --> 01:07:49,760
that we embed into this selective

1706
01:07:54,789 --> 01:07:51,920
breeding what you notice is that the

1707
01:07:56,470 --> 01:07:54,799
maize plants are very very sensitive to

1708
01:07:59,190 --> 01:07:56,480
these kind of things so they have low

1709
01:08:01,029 --> 01:07:59,200
tolerance to the virus very susceptible

1710
01:08:03,510 --> 01:08:01,039
the viruses seem to be exploring a bit

1711
01:08:05,990 --> 01:08:03,520
of sequence space but still aggregating

1712
01:08:08,549 --> 01:08:06,000
to an area which is very very common

1713
01:08:09,990 --> 01:08:08,559
down here which is immediate solution

1714
01:08:11,910 --> 01:08:10,000
but if you put it into a resistant

1715
01:08:13,510 --> 01:08:11,920
variety pretty much everything goes to

1716
01:08:16,550 --> 01:08:13,520
that one solution that is required in

1717
01:08:18,390 --> 01:08:16,560
nature so this is very staggering that

1718
01:08:20,870 --> 01:08:18,400
in nature this evolution experiment has

1719
01:08:23,590 --> 01:08:20,880
taken place over 250 years

1720
01:08:24,950 --> 01:08:23,600
we've done it in 30 days in latin

1721
01:08:27,189 --> 01:08:24,960
experiment

1722
01:08:28,709 --> 01:08:27,199
but also we noticed there is some level

1723
01:08:31,030 --> 01:08:28,719
of genome plasticity within these

1724
01:08:33,590 --> 01:08:31,040
molecules these viruses so here is an

1725
01:08:34,870 --> 01:08:33,600
example of a gemini viruses myopathic

1726
01:08:36,470 --> 01:08:34,880
and you will notice that we've been

1727
01:08:38,550 --> 01:08:36,480
discovering these groups of viruses

1728
01:08:40,789 --> 01:08:38,560
where this entire segment has been

1729
01:08:43,110 --> 01:08:40,799
incorporated into this molecule to

1730
01:08:45,669 --> 01:08:43,120
generate a larger molecule and still in

1731
01:08:47,430 --> 01:08:45,679
expanse so one thing that we can't

1732
01:08:48,630 --> 01:08:47,440
figure out is whether this is an

1733
01:08:49,510 --> 01:08:48,640
acquisition

1734
01:08:51,269 --> 01:08:49,520
or

1735
01:08:53,749 --> 01:08:51,279
these molecules have been derived from a

1736
01:08:56,149 --> 01:08:53,759
deletion of assignment and that's how

1737
01:08:58,229 --> 01:08:56,159
these viruses evolve so there is a

1738
01:09:00,149 --> 01:08:58,239
variety of different things

1739
01:09:02,470 --> 01:09:00,159
and so within this context how do you

1740
01:09:03,590 --> 01:09:02,480
start pairing these molecules together

1741
01:09:06,229 --> 01:09:03,600
like

1742
01:09:07,669 --> 01:09:06,239
is this and this totally related we can

1743
01:09:09,910 --> 01:09:07,679
do that by there are these common

1744
01:09:11,910 --> 01:09:09,920
regions we can look at them and because

1745
01:09:13,829 --> 01:09:11,920
one is required to replicate the other

1746
01:09:15,829 --> 01:09:13,839
we're able to do this

1747
01:09:17,349 --> 01:09:15,839
but it's also very complicated so we're

1748
01:09:19,749 --> 01:09:17,359
trying to come up with new methods to

1749
01:09:21,430 --> 01:09:19,759
understand how we can put these pairings

1750
01:09:22,950 --> 01:09:21,440
together and some of them are based on

1751
01:09:24,630 --> 01:09:22,960
network analysis

1752
01:09:27,110 --> 01:09:24,640
but when we even start looking at

1753
01:09:28,630 --> 01:09:27,120
phylogenies of these spared molecules

1754
01:09:30,550 --> 01:09:28,640
there isn't any congruence they're

1755
01:09:32,630 --> 01:09:30,560
pretty much exchanging

1756
01:09:33,749 --> 01:09:32,640
uh or trading with each other very

1757
01:09:35,269 --> 01:09:33,759
openly

1758
01:09:36,789 --> 01:09:35,279
so that leads me to another group of

1759
01:09:39,030 --> 01:09:36,799
viruses which i think are very very

1760
01:09:41,349 --> 01:09:39,040
important because these are the

1761
01:09:43,269 --> 01:09:41,359
multi-component viruses again infecting

1762
01:09:45,990 --> 01:09:43,279
plants but we're discovering similar

1763
01:09:48,630 --> 01:09:46,000
viruses in eukaryotic systems

1764
01:09:50,870 --> 01:09:48,640
and these molecules are six to eight

1765
01:09:53,669 --> 01:09:50,880
molecules each one gets packaged into an

1766
01:09:56,470 --> 01:09:53,679
individual variant and each one encodes

1767
01:09:57,910 --> 01:09:56,480
one single protein so in this case here

1768
01:10:00,149 --> 01:09:57,920
at the top there is a protein that

1769
01:10:02,149 --> 01:10:00,159
initiates replication replicates all

1770
01:10:03,669 --> 01:10:02,159
these molecules here is the molecule

1771
01:10:05,590 --> 01:10:03,679
that encodes the capsid protein that

1772
01:10:07,830 --> 01:10:05,600
needs to encapsulate all of these so you

1773
01:10:09,430 --> 01:10:07,840
can imagine the shear dynamics of these

1774
01:10:10,790 --> 01:10:09,440
molecules having to interact with each

1775
01:10:12,870 --> 01:10:10,800
other other

1776
01:10:14,630 --> 01:10:12,880
and inside a cell system also the

1777
01:10:16,790 --> 01:10:14,640
delivery is also important because at

1778
01:10:18,870 --> 01:10:16,800
some point within a host you need to get

1779
01:10:20,709 --> 01:10:18,880
all of these into a

1780
01:10:22,790 --> 01:10:20,719
system so they can all cooperate and

1781
01:10:24,550 --> 01:10:22,800
produce progeny

1782
01:10:26,470 --> 01:10:24,560
so we started studying them in greater

1783
01:10:28,070 --> 01:10:26,480
detail and we started noticing that they

1784
01:10:29,910 --> 01:10:28,080
were reassuring

1785
01:10:31,510 --> 01:10:29,920
very much like influenza viruses they're

1786
01:10:34,550 --> 01:10:31,520
able to trade

1787
01:10:37,110 --> 01:10:34,560
molecules between each other very openly

1788
01:10:38,950 --> 01:10:37,120
and what was really staggering is that

1789
01:10:41,270 --> 01:10:38,960
when we look at individual molecules

1790
01:10:42,550 --> 01:10:41,280
between themselves they were recombining

1791
01:10:44,070 --> 01:10:42,560
very rapidly

1792
01:10:45,350 --> 01:10:44,080
we take these molecules they're all

1793
01:10:47,189 --> 01:10:45,360
different

1794
01:10:49,270 --> 01:10:47,199
we analyze them for recombination and

1795
01:10:50,709 --> 01:10:49,280
they're also recombining

1796
01:10:52,630 --> 01:10:50,719
in these common regions so they're

1797
01:10:54,630 --> 01:10:52,640
actually exploring sequence space at a

1798
01:10:56,310 --> 01:10:54,640
completely different league which is

1799
01:10:59,590 --> 01:10:56,320
really fascinating in the sense that

1800
01:11:01,590 --> 01:10:59,600
these viruses are just like

1801
01:11:03,590 --> 01:11:01,600
viruses around red bull and acid and

1802
01:11:04,630 --> 01:11:03,600
they just stop there to explore sequence

1803
01:11:06,390 --> 01:11:04,640
space and they're going to do it no

1804
01:11:08,390 --> 01:11:06,400
matter what

1805
01:11:11,270 --> 01:11:08,400
so the other thing that we were always

1806
01:11:13,830 --> 01:11:11,280
fascinated by is why are these viruses

1807
01:11:16,070 --> 01:11:13,840
single stranded because single-stranded

1808
01:11:17,830 --> 01:11:16,080
nucleic acid is not stable double-spread

1809
01:11:19,590 --> 01:11:17,840
and nucleic acid is stable

1810
01:11:21,350 --> 01:11:19,600
so we assumed that they would be forming

1811
01:11:23,350 --> 01:11:21,360
complex secondary structures within the

1812
01:11:24,630 --> 01:11:23,360
genomic elements when they're packaged

1813
01:11:27,590 --> 01:11:24,640
into genomes

1814
01:11:29,510 --> 01:11:27,600
so we took all we analyzed all the

1815
01:11:32,630 --> 01:11:29,520
sequences of single-stranded dna viruses

1816
01:11:34,709 --> 01:11:32,640
that were available in public databases

1817
01:11:36,790 --> 01:11:34,719
did folding analysis so basically in

1818
01:11:38,830 --> 01:11:36,800
sync analysis of folding and tried to

1819
01:11:41,189 --> 01:11:38,840
look for paired sites that we saw very

1820
01:11:43,030 --> 01:11:41,199
commonly and when we start looking at

1821
01:11:45,430 --> 01:11:43,040
these paid sites in

1822
01:11:47,510 --> 01:11:45,440
our in silico folding experiments what

1823
01:11:49,189 --> 01:11:47,520
we noticed is that purifying selection

1824
01:11:51,669 --> 01:11:49,199
is strongest at websites which is not

1825
01:11:53,590 --> 01:11:51,679
surprising we also notice synonymous

1826
01:11:56,470 --> 01:11:53,600
substitution rates are low at paid

1827
01:11:58,630 --> 01:11:56,480
genomic size not surprisingly

1828
01:12:00,790 --> 01:11:58,640
in our evolution experiments we notice

1829
01:12:03,350 --> 01:12:00,800
that mutations tend to accumulate in

1830
01:12:05,750 --> 01:12:03,360
unpaid sites makes sense now

1831
01:12:09,910 --> 01:12:05,760
but what was staggering is that we saw

1832
01:12:12,870 --> 01:12:09,920
evidence of complementarity of uh to

1833
01:12:13,470 --> 01:12:12,880
evolve base pairs so there is some sort

1834
01:12:15,510 --> 01:12:13,480
of

1835
01:12:18,229 --> 01:12:15,520
complementarity involved in it that if

1836
01:12:19,590 --> 01:12:18,239
one with one nucleotide here in a base

1837
01:12:21,910 --> 01:12:19,600
paired region

1838
01:12:23,669 --> 01:12:21,920
uh it mutates there is a compensatory

1839
01:12:25,189 --> 01:12:23,679
mutation that takes place to retain that

1840
01:12:27,350 --> 01:12:25,199
particular structure

1841
01:12:29,510 --> 01:12:27,360
so we started noticing that

1842
01:12:31,350 --> 01:12:29,520
these single-stranded genomes fall into

1843
01:12:33,189 --> 01:12:31,360
complex sacrifice structures those

1844
01:12:35,189 --> 01:12:33,199
complex secondary structures

1845
01:12:37,430 --> 01:12:35,199
are very unique that there is some sort

1846
01:12:38,709 --> 01:12:37,440
of co-evolution taking place of paid

1847
01:12:40,149 --> 01:12:38,719
sites

1848
01:12:41,910 --> 01:12:40,159
and so this had never been shown and

1849
01:12:43,990 --> 01:12:41,920
this was kind of really interesting and

1850
01:12:45,510 --> 01:12:44,000
this also suggests that the secondary

1851
01:12:46,709 --> 01:12:45,520
structure is highly likely very

1852
01:12:49,189 --> 01:12:46,719
important

1853
01:12:51,189 --> 01:12:49,199
for either regulatory mechanisms or

1854
01:12:54,870 --> 01:12:51,199
maintaining some sort of genomic

1855
01:12:56,310 --> 01:12:54,880
integrity within capsid proteins

1856
01:12:58,550 --> 01:12:56,320
and now i'm going to take you away from

1857
01:13:00,390 --> 01:12:58,560
the plant side of things and go into

1858
01:13:03,590 --> 01:13:00,400
area which i think is interesting

1859
01:13:06,149 --> 01:13:03,600
because it involves human activities

1860
01:13:08,470 --> 01:13:06,159
and here is a virus that i've worked

1861
01:13:09,430 --> 01:13:08,480
extensively with it's virus that infects

1862
01:13:13,669 --> 01:13:09,440
parrots

1863
01:13:15,990 --> 01:13:13,679
again a single-spreaded dna virus and

1864
01:13:19,350 --> 01:13:16,000
puts only two proteins it's about two

1865
01:13:21,350 --> 01:13:19,360
kilobase in size but it actually

1866
01:13:23,590 --> 01:13:21,360
induces physiological changes in an

1867
01:13:25,750 --> 01:13:23,600
animal it suppresses its immune system

1868
01:13:29,030 --> 01:13:25,760
the animal's response in a lot of ways

1869
01:13:31,189 --> 01:13:29,040
is feather loss anemia in severe cases

1870
01:13:33,270 --> 01:13:31,199
like this one here there's a sulphur

1871
01:13:35,990 --> 01:13:33,280
crested cockatoo that has pretty much

1872
01:13:38,310 --> 01:13:36,000
lost most of its feathers as well as its

1873
01:13:39,910 --> 01:13:38,320
beak and you know you have to give it to

1874
01:13:41,990 --> 01:13:39,920
the australians for writing beautiful

1875
01:13:43,590 --> 01:13:42,000
obituaries about the birds and this is

1876
01:13:46,310 --> 01:13:43,600
cocky bennett that traveled around the

1877
01:13:49,590 --> 01:13:46,320
world died at the age of roughly 120

1878
01:13:52,070 --> 01:13:49,600
years so parents do live that long

1879
01:13:54,149 --> 01:13:52,080
and spent the last 20 years in a pub and

1880
01:13:56,870 --> 01:13:54,159
that's what it looked like

1881
01:13:58,790 --> 01:13:56,880
and so the phylogenetic tree on the

1882
01:14:00,470 --> 01:13:58,800
right hand side kind of suggests some

1883
01:14:02,870 --> 01:14:00,480
very very unique things

1884
01:14:05,270 --> 01:14:02,880
that here what you have is some sort of

1885
01:14:08,149 --> 01:14:05,280
a pet trade system taking place that are

1886
01:14:10,870 --> 01:14:08,159
breeding facilities from which there are

1887
01:14:12,950 --> 01:14:10,880
pushing some of the

1888
01:14:14,950 --> 01:14:12,960
legal and illegal trafficking of animals

1889
01:14:17,350 --> 01:14:14,960
to different zones and then what you're

1890
01:14:19,590 --> 01:14:17,360
getting is establishment of new viruses

1891
01:14:20,630 --> 01:14:19,600
and new ecosystems that haven't been

1892
01:14:21,990 --> 01:14:20,640
before

1893
01:14:24,070 --> 01:14:22,000
and we've analyzed some of the

1894
01:14:25,990 --> 01:14:24,080
facilities in poland for example we've

1895
01:14:27,910 --> 01:14:26,000
worked with veterinarians there to look

1896
01:14:29,830 --> 01:14:27,920
at recombination beds in some of these

1897
01:14:31,590 --> 01:14:29,840
facilities and a variety of different

1898
01:14:33,270 --> 01:14:31,600
carrots they come in from different

1899
01:14:35,750 --> 01:14:33,280
parts of the world they're brought into

1900
01:14:37,750 --> 01:14:35,760
these aviaries the animals are stressed

1901
01:14:39,510 --> 01:14:37,760
and before unite

1902
01:14:41,750 --> 01:14:39,520
the virus is just circulating and being

1903
01:14:43,910 --> 01:14:41,760
exchanged and here we've got a genome of

1904
01:14:45,990 --> 01:14:43,920
the virus that is more than two-thirds

1905
01:14:48,630 --> 01:14:46,000
of recombinant that we identify in these

1906
01:14:50,390 --> 01:14:48,640
kind of systems so these legal and

1907
01:14:52,790 --> 01:14:50,400
illegal trade systems are also

1908
01:14:55,270 --> 01:14:52,800
facilitating the spread of these viruses

1909
01:14:56,550 --> 01:14:55,280
and evolution of these viruses at a much

1910
01:14:58,229 --> 01:14:56,560
rapid rate than people have thought

1911
01:14:59,990 --> 01:14:58,239
before

1912
01:15:01,590 --> 01:15:00,000
and now we go into genomics kind of

1913
01:15:03,270 --> 01:15:01,600
systems and we start realizing that

1914
01:15:05,350 --> 01:15:03,280
actually we know very little about

1915
01:15:07,030 --> 01:15:05,360
cellular standard dna viruses because

1916
01:15:09,430 --> 01:15:07,040
through metagenomic approaches we just

1917
01:15:11,510 --> 01:15:09,440
keep finding viruses a lot of which we

1918
01:15:13,110 --> 01:15:11,520
don't even know the hosts for and here's

1919
01:15:15,110 --> 01:15:13,120
a big group of viruses that we've

1920
01:15:17,030 --> 01:15:15,120
recently established as a family level

1921
01:15:19,270 --> 01:15:17,040
structure however

1922
01:15:21,669 --> 01:15:19,280
these viruses the first group of them

1923
01:15:24,070 --> 01:15:21,679
were found to infect fungi induce

1924
01:15:26,390 --> 01:15:24,080
hypovirulence but we find them in pretty

1925
01:15:28,070 --> 01:15:26,400
much all different systems you can see

1926
01:15:30,149 --> 01:15:28,080
all the different kind of

1927
01:15:32,390 --> 01:15:30,159
sample types that have been identified

1928
01:15:33,990 --> 01:15:32,400
and they've got a huge diversity and so

1929
01:15:35,430 --> 01:15:34,000
these things are really abundant in

1930
01:15:37,350 --> 01:15:35,440
nature

1931
01:15:39,669 --> 01:15:37,360
but what is staggering again about them

1932
01:15:41,990 --> 01:15:39,679
is that they encourage two proteins and

1933
01:15:43,350 --> 01:15:42,000
we try to draw the phylogenesis of the

1934
01:15:45,750 --> 01:15:43,360
capsid protein and the replication

1935
01:15:48,310 --> 01:15:45,760
initiated proteins and not congruent at

1936
01:15:50,070 --> 01:15:48,320
all these are highly recombinant viruses

1937
01:15:51,030 --> 01:15:50,080
that are present

1938
01:15:53,510 --> 01:15:51,040
but

1939
01:15:55,110 --> 01:15:53,520
we find related viruses in nature and

1940
01:15:57,990 --> 01:15:55,120
here is something we found in an ice

1941
01:16:00,790 --> 01:15:58,000
core this is kind of work from uh terry

1942
01:16:03,430 --> 01:16:00,800
young and eric kellwood's group that i

1943
01:16:05,669 --> 01:16:03,440
was involved with and it might roughly

1944
01:16:08,709 --> 01:16:05,679
just short of 200 meters left in an ice

1945
01:16:09,990 --> 01:16:08,719
core they identified the virus and

1946
01:16:12,470 --> 01:16:10,000
we kind of worked together to try and

1947
01:16:13,990 --> 01:16:12,480
figure out what the virus was and then

1948
01:16:15,270 --> 01:16:14,000
we looked at it and thought wow this

1949
01:16:17,030 --> 01:16:15,280
looks very very similar to a

1950
01:16:18,630 --> 01:16:17,040
plant-infected virus in terms of its

1951
01:16:21,910 --> 01:16:18,640
genomic elements

1952
01:16:23,990 --> 01:16:21,920
so with bob gilbertson at uc davis we

1953
01:16:25,270 --> 01:16:24,000
generated an infectious clone put it

1954
01:16:27,350 --> 01:16:25,280
into plants

1955
01:16:29,990 --> 01:16:27,360
and lo and behold this virus was able to

1956
01:16:32,310 --> 01:16:30,000
replicate and spread but we dated this

1957
01:16:34,870 --> 01:16:32,320
layer and was dated at about 700 years

1958
01:16:37,189 --> 01:16:34,880
old so we resurrected a virus that was

1959
01:16:39,189 --> 01:16:37,199
700 years old through reverse genetics

1960
01:16:41,270 --> 01:16:39,199
so this also suggests and should be a

1961
01:16:43,590 --> 01:16:41,280
quotient for us that

1962
01:16:45,189 --> 01:16:43,600
the climate change impacts are real in

1963
01:16:47,510 --> 01:16:45,199
the sense that we're melting permafrost

1964
01:16:49,350 --> 01:16:47,520
at a very very rapid rate and so there

1965
01:16:50,470 --> 01:16:49,360
are pathogens and organisms that are

1966
01:16:53,030 --> 01:16:50,480
trapped

1967
01:16:55,510 --> 01:16:53,040
in these ecosystems that are now being

1968
01:16:57,350 --> 01:16:55,520
uh released into environments and some

1969
01:16:59,030 --> 01:16:57,360
of these environments haven't dealt with

1970
01:17:00,390 --> 01:16:59,040
these these

1971
01:17:03,030 --> 01:17:00,400
organisms and so what are the

1972
01:17:05,590 --> 01:17:03,040
consequences going to be in future for

1973
01:17:08,310 --> 01:17:05,600
either uh displacing certain organisms

1974
01:17:09,830 --> 01:17:08,320
out of these ecosystems as these uh

1975
01:17:11,030 --> 01:17:09,840
permafrost layers

1976
01:17:13,350 --> 01:17:11,040
go

1977
01:17:15,350 --> 01:17:13,360
so if we take back a bigger picture and

1978
01:17:17,189 --> 01:17:15,360
go back a few steps and look right riots

1979
01:17:19,030 --> 01:17:17,199
we know all of these viruses

1980
01:17:21,189 --> 01:17:19,040
single-splinted viruses that encode the

1981
01:17:23,270 --> 01:17:21,199
replication initiative protein have

1982
01:17:25,830 --> 01:17:23,280
these two motifs but some of these

1983
01:17:28,630 --> 01:17:25,840
motifs we also identify in fungal

1984
01:17:29,430 --> 01:17:28,640
elements sorry in plasmids

1985
01:17:31,430 --> 01:17:29,440
and

1986
01:17:33,110 --> 01:17:31,440
so we can start building network like

1987
01:17:34,870 --> 01:17:33,120
analysis and if you just take the

1988
01:17:36,630 --> 01:17:34,880
helicase domain and we know helicase

1989
01:17:38,390 --> 01:17:36,640
domains are present in a lot of

1990
01:17:40,630 --> 01:17:38,400
different systems including replication

1991
01:17:42,950 --> 01:17:40,640
machinery and repair machinery we can

1992
01:17:44,630 --> 01:17:42,960
start building networks of similarity

1993
01:17:47,189 --> 01:17:44,640
and we start noticing that some of these

1994
01:17:48,950 --> 01:17:47,199
helicase domains are also found in other

1995
01:17:51,510 --> 01:17:48,960
groups of viruses which are

1996
01:17:53,750 --> 01:17:51,520
circular double-stranded dna viruses but

1997
01:17:55,189 --> 01:17:53,760
a variety of different plasmids as well

1998
01:17:57,350 --> 01:17:55,199
and from there we can start then

1999
01:17:59,430 --> 01:17:57,360
inferring concepts of where these

2000
01:18:01,990 --> 01:17:59,440
viruses have evolved from and you start

2001
01:18:03,510 --> 01:18:02,000
noticing that it's not just one system

2002
01:18:05,990 --> 01:18:03,520
there is multiple acquisition and

2003
01:18:08,310 --> 01:18:06,000
multiple events that have led to these

2004
01:18:09,910 --> 01:18:08,320
viruses evolving from each other and if

2005
01:18:12,229 --> 01:18:09,920
you look at it at a much more broader

2006
01:18:13,910 --> 01:18:12,239
perspective we start noticing that some

2007
01:18:15,669 --> 01:18:13,920
of these viruses

2008
01:18:18,550 --> 01:18:15,679
haven't just evolved in a one clear

2009
01:18:20,470 --> 01:18:18,560
lineage process there have been multiple

2010
01:18:23,110 --> 01:18:20,480
evolution processes from plasmids and

2011
01:18:26,070 --> 01:18:23,120
plasmid like ancestral sequences that

2012
01:18:29,189 --> 01:18:26,080
have led to emergence or evolution of

2013
01:18:31,350 --> 01:18:29,199
these viruses in nature

2014
01:18:32,630 --> 01:18:31,360
and then what you can start doing is

2015
01:18:34,790 --> 01:18:32,640
this is something that i've been

2016
01:18:36,870 --> 01:18:34,800
fascinated with is that viruses all have

2017
01:18:38,390 --> 01:18:36,880
capsule proteins the capsid proteins are

2018
01:18:40,550 --> 01:18:38,400
very important because they recognize

2019
01:18:41,430 --> 01:18:40,560
certain particular receptors to get into

2020
01:18:43,590 --> 01:18:41,440
cells

2021
01:18:45,350 --> 01:18:43,600
now

2022
01:18:47,110 --> 01:18:45,360
can and a variety of other people have

2023
01:18:48,630 --> 01:18:47,120
found that there are certain viruses

2024
01:18:51,110 --> 01:18:48,640
single-stranded hernia viruses that

2025
01:18:53,510 --> 01:18:51,120
encode capsid proteins that are much

2026
01:18:55,590 --> 01:18:53,520
more closely related to viruses

2027
01:18:58,550 --> 01:18:55,600
which are rna viruses that have similar

2028
01:19:00,870 --> 01:18:58,560
capsid proteins so here is an example is

2029
01:19:03,030 --> 01:19:00,880
chongus viruses are rna viruses their

2030
01:19:04,229 --> 01:19:03,040
capsid proteins are very similar to some

2031
01:19:06,390 --> 01:19:04,239
of the capsular proteins that are

2032
01:19:08,310 --> 01:19:06,400
encoded by single-stranded dna viruses

2033
01:19:10,470 --> 01:19:08,320
so where has this chimeric acquisition

2034
01:19:12,390 --> 01:19:10,480
taken place at a cdna level at some

2035
01:19:14,149 --> 01:19:12,400
point so these viruses

2036
01:19:16,790 --> 01:19:14,159
have some sort of a

2037
01:19:19,110 --> 01:19:16,800
proxy in terms of capsid fault space and

2038
01:19:21,430 --> 01:19:19,120
i think capsid fault space and mark

2039
01:19:23,590 --> 01:19:21,440
cuprof is a big proponent of this is

2040
01:19:25,830 --> 01:19:23,600
that capsid false space is limited and

2041
01:19:27,590 --> 01:19:25,840
as a consequence of it

2042
01:19:29,990 --> 01:19:27,600
is that there's only so much fault space

2043
01:19:32,310 --> 01:19:30,000
you can have at a protein capsid level

2044
01:19:33,910 --> 01:19:32,320
and some of these viruses are then

2045
01:19:35,430 --> 01:19:33,920
acquiring these

2046
01:19:37,590 --> 01:19:35,440
capsid like molecules from different

2047
01:19:39,270 --> 01:19:37,600
areas and so here are all the gemini

2048
01:19:41,110 --> 01:19:39,280
virus captured proteins that we know

2049
01:19:44,149 --> 01:19:41,120
about and what is interesting about

2050
01:19:46,070 --> 01:19:44,159
these is they actually have

2051
01:19:48,550 --> 01:19:46,080
a capsid fold

2052
01:19:49,990 --> 01:19:48,560
which is very similar to that of an rna

2053
01:19:52,310 --> 01:19:50,000
virus which is satellite tobacco

2054
01:19:53,350 --> 01:19:52,320
necrotic virus and you can see the vast

2055
01:19:55,669 --> 01:19:53,360
number of

2056
01:19:57,990 --> 01:19:55,679
unclassified circular dna viruses that

2057
01:19:59,910 --> 01:19:58,000
have this fold as well when you start

2058
01:20:01,750 --> 01:19:59,920
looking at network analysis so these

2059
01:20:04,310 --> 01:20:01,760
network analysis are becoming very very

2060
01:20:06,709 --> 01:20:04,320
important in the way we understand and

2061
01:20:09,189 --> 01:20:06,719
so yes complemented with phylogenetic

2062
01:20:11,270 --> 01:20:09,199
trees these are very very good ways of

2063
01:20:14,229 --> 01:20:11,280
pulling down

2064
01:20:16,830 --> 01:20:14,239
related sequences and understanding

2065
01:20:19,270 --> 01:20:16,840
more broader concepts of viral

2066
01:20:22,149 --> 01:20:19,280
evolution and so i want to kind of start

2067
01:20:23,990 --> 01:20:22,159
ending this with a bigger concept and

2068
01:20:25,590 --> 01:20:24,000
this is that if you look at

2069
01:20:27,510 --> 01:20:25,600
phallogenetic tree on the right hand

2070
01:20:29,430 --> 01:20:27,520
side you notice these are all single

2071
01:20:31,350 --> 01:20:29,440
stranded dna viruses and called

2072
01:20:33,590 --> 01:20:31,360
replication associated or initiative

2073
01:20:36,550 --> 01:20:33,600
proteins and the ones that are well

2074
01:20:39,510 --> 01:20:36,560
classified are in these little triangles

2075
01:20:41,110 --> 01:20:39,520
lapse branches uh labeled here

2076
01:20:43,669 --> 01:20:41,120
everything else that's on this

2077
01:20:46,229 --> 01:20:43,679
illustration here are texture that we've

2078
01:20:48,550 --> 01:20:46,239
identified in our research group now

2079
01:20:50,149 --> 01:20:48,560
everything that is in red is what we

2080
01:20:52,709 --> 01:20:50,159
have identified

2081
01:20:54,229 --> 01:20:52,719
right uh in the entire ecosystems

2082
01:20:57,030 --> 01:20:54,239
so to me

2083
01:20:58,950 --> 01:20:57,040
if i were to draw a plot of viruses that

2084
01:21:00,790 --> 01:20:58,960
exist on this planet in terms of what we

2085
01:21:02,950 --> 01:21:00,800
know about them today they would be

2086
01:21:05,430 --> 01:21:02,960
scattered on this plot on a 10 by 10

2087
01:21:07,270 --> 01:21:05,440
grid in various different places and if

2088
01:21:09,189 --> 01:21:07,280
i was to sum that up in terms of where

2089
01:21:11,830 --> 01:21:09,199
our current knowledge is it would be

2090
01:21:14,149 --> 01:21:11,840
less than one percent of all the viruses

2091
01:21:15,189 --> 01:21:14,159
we know on the planet so that means we

2092
01:21:17,270 --> 01:21:15,199
have

2093
01:21:19,510 --> 01:21:17,280
a lot of work to do in terms of if we

2094
01:21:22,709 --> 01:21:19,520
really want to understand virology

2095
01:21:25,510 --> 01:21:22,719
we're far from it we've only had a huge

2096
01:21:27,830 --> 01:21:25,520
bias to viruses that cause disease and

2097
01:21:30,470 --> 01:21:27,840
viruses that cause disease in organisms

2098
01:21:32,390 --> 01:21:30,480
that we dearly care about like plants

2099
01:21:34,709 --> 01:21:32,400
animals humans

2100
01:21:36,629 --> 01:21:34,719
everything else we've just neglected

2101
01:21:38,470 --> 01:21:36,639
and also as ken mentioned we've

2102
01:21:41,110 --> 01:21:38,480
completely looked at it from a disease

2103
01:21:42,629 --> 01:21:41,120
angle never from a beneficial angle and

2104
01:21:45,270 --> 01:21:42,639
we do know that viruses are most

2105
01:21:47,350 --> 01:21:45,280
abundant entity on the planet if they're

2106
01:21:48,870 --> 01:21:47,360
so abundant

2107
01:21:50,870 --> 01:21:48,880
they should be having beneficial roles

2108
01:21:52,470 --> 01:21:50,880
in ecosystems and we do know that in

2109
01:21:54,470 --> 01:21:52,480
marine ecosystems there are very very

2110
01:21:57,830 --> 01:21:54,480
important

2111
01:21:59,430 --> 01:21:57,840
for carbon sink and at the bottom here

2112
01:22:01,189 --> 01:21:59,440
is a very very unique paper which i

2113
01:22:03,350 --> 01:22:01,199
think is great and this is part of the

2114
01:22:05,750 --> 01:22:03,360
efforts of the tara oceans project and

2115
01:22:07,430 --> 01:22:05,760
if you look at in the uh epipelagic

2116
01:22:08,709 --> 01:22:07,440
samples that the water columns that

2117
01:22:10,390 --> 01:22:08,719
they've looked at

2118
01:22:12,950 --> 01:22:10,400
they've saturated

2119
01:22:14,950 --> 01:22:12,960
the amount of viruses they can find so

2120
01:22:17,030 --> 01:22:14,960
they've got to a level that doesn't

2121
01:22:17,990 --> 01:22:17,040
matter how much at that layer they

2122
01:22:19,510 --> 01:22:18,000
sample

2123
01:22:21,669 --> 01:22:19,520
they have got

2124
01:22:23,669 --> 01:22:21,679
a very good handle of sequence space in

2125
01:22:25,830 --> 01:22:23,679
the regions they've sampled but when you

2126
01:22:28,550 --> 01:22:25,840
go into different areas they're still

2127
01:22:30,550 --> 01:22:28,560
not close to it and i think with single

2128
01:22:32,470 --> 01:22:30,560
stranded dna viruses i think we're in

2129
01:22:35,189 --> 01:22:32,480
this stage that we're not even at all

2130
01:22:36,709 --> 01:22:35,199
close to having figured out everything

2131
01:22:38,390 --> 01:22:36,719
so with that i'd like to thank all of

2132
01:22:39,990 --> 01:22:38,400
the who have been involved in a lot of

2133
01:22:42,629 --> 01:22:40,000
the work that i do that have spent for

2134
01:22:45,430 --> 01:22:42,639
the last 15 20 years and there are

2135
01:22:48,229 --> 01:22:45,440
groups of people all around the world as

2136
01:22:50,229 --> 01:22:48,239
well as a whole lot of crew that have

2137
01:22:51,189 --> 01:22:50,239
you know students in my lab and are

2138
01:22:52,629 --> 01:22:51,199
still

2139
01:23:08,790 --> 01:22:52,639
staffing my research group thank you

2140
01:23:14,310 --> 01:23:10,790
questions anyone

2141
01:23:18,070 --> 01:23:14,320
hey arvin siobhan here hi siobhan

2142
01:23:20,310 --> 01:23:18,080
so i posted this to the chat but

2143
01:23:22,149 --> 01:23:20,320
what's the real risk of these viruses

2144
01:23:24,790 --> 01:23:22,159
being in infectious capsids as the

2145
01:23:26,550 --> 01:23:24,800
permafrost thaws i would worry about

2146
01:23:29,270 --> 01:23:26,560
things like the tabama viruses because

2147
01:23:30,870 --> 01:23:29,280
those things can withstand incineration

2148
01:23:33,430 --> 01:23:30,880
and all kinds of environmental

2149
01:23:35,030 --> 01:23:33,440
challenges but should we actually worry

2150
01:23:36,229 --> 01:23:35,040
about intact

2151
01:23:37,430 --> 01:23:36,239
virions

2152
01:23:38,790 --> 01:23:37,440
that could actually be infectious from

2153
01:23:40,390 --> 01:23:38,800
permafrost are we just going to keep

2154
01:23:42,950 --> 01:23:40,400
learning about

2155
01:23:44,229 --> 01:23:42,960
what was there hundreds of years ago and

2156
01:23:46,470 --> 01:23:44,239
we could resurrect these things with

2157
01:23:47,590 --> 01:23:46,480
reverse genetics that's very very cool

2158
01:23:49,030 --> 01:23:47,600
but they're not actually going to infect

2159
01:23:51,030 --> 01:23:49,040
our plants tomorrow

2160
01:23:52,470 --> 01:23:51,040
well they could in fact so

2161
01:23:54,470 --> 01:23:52,480
look at our pollution levels on the

2162
01:23:56,070 --> 01:23:54,480
planet microplastics are pretty much

2163
01:23:58,390 --> 01:23:56,080
everywhere a lot of these viruses will

2164
01:24:00,229 --> 01:23:58,400
bind to microplastics microflaxes

2165
01:24:01,510 --> 01:24:00,239
uh they seem to get into systems we've

2166
01:24:02,790 --> 01:24:01,520
got a lot of detergents in our

2167
01:24:04,870 --> 01:24:02,800
ecosystems

2168
01:24:07,270 --> 01:24:04,880
and so detergents mean you've got

2169
01:24:09,910 --> 01:24:07,280
actually a beautiful surfactant that can

2170
01:24:11,830 --> 01:24:09,920
deliver things straight into a variety

2171
01:24:14,390 --> 01:24:11,840
of different organisms especially single

2172
01:24:16,149 --> 01:24:14,400
cell organisms and we've got vectors

2173
01:24:17,910 --> 01:24:16,159
insects that are pretty much picking up

2174
01:24:19,590 --> 01:24:17,920
a lot of this material through the

2175
01:24:21,750 --> 01:24:19,600
foraging behavior and they will be

2176
01:24:25,110 --> 01:24:21,760
taking in and injecting it so the

2177
01:24:26,070 --> 01:24:25,120
plausibility of a scenario like this is

2178
01:24:29,510 --> 01:24:26,080
there

2179
01:24:31,910 --> 01:24:29,520
the frequency or how viable they are i

2180
01:24:32,790 --> 01:24:31,920
cannot kind of speak on that

2181
01:24:45,990 --> 01:24:32,800
but

2182
01:24:48,950 --> 01:24:47,590
arvind ken here

2183
01:24:51,510 --> 01:24:48,960
yes hi ken

2184
01:24:53,350 --> 01:24:51,520
uh just a quick question in terms of the

2185
01:24:55,590 --> 01:24:53,360
astrovirology and also put this in the

2186
01:24:57,030 --> 01:24:55,600
chat is and maybe mark's the right

2187
01:24:59,110 --> 01:24:57,040
person to ask this question of but do

2188
01:25:01,430 --> 01:24:59,120
you think that if there are limited

2189
01:25:04,550 --> 01:25:01,440
numbers of folds that you can use for

2190
01:25:07,270 --> 01:25:04,560
capsids um would that potentially be a

2191
01:25:09,750 --> 01:25:07,280
way that one could think about

2192
01:25:11,189 --> 01:25:09,760
virion detection techniques that maybe

2193
01:25:13,030 --> 01:25:11,199
you could put on a spacecraft or

2194
01:25:18,070 --> 01:25:13,040
something like that

2195
01:25:22,550 --> 01:25:19,510
don't forget

2196
01:25:23,590 --> 01:25:22,560
that protein sequence space is great all

2197
01:25:25,350 --> 01:25:23,600
right

2198
01:25:27,350 --> 01:25:25,360
sorry nucleotide sequence space is very

2199
01:25:29,189 --> 01:25:27,360
great then you get into protein sequence

2200
01:25:31,270 --> 01:25:29,199
space and you get into four space so you

2201
01:25:33,830 --> 01:25:31,280
can have the same fold

2202
01:25:35,669 --> 01:25:33,840
yet you could have 30 percent diversity

2203
01:25:37,910 --> 01:25:35,679
at a nucleotide level

2204
01:25:39,830 --> 01:25:37,920
so i think our detection in this kind of

2205
01:25:41,110 --> 01:25:39,840
system is unless we have initial

2206
01:25:47,669 --> 01:25:41,120
approaches

2207
01:25:49,590 --> 01:25:47,679
detecting fault are very poor even today

2208
01:25:52,550 --> 01:25:49,600
so i think one thing that we really need

2209
01:25:55,110 --> 01:25:52,560
to do is accelerate our crystal uh

2210
01:25:57,270 --> 01:25:55,120
structure solving programs all around

2211
01:26:00,310 --> 01:25:57,280
the world to solve structures of

2212
01:26:02,550 --> 01:26:00,320
proteins and once better databases we

2213
01:26:04,470 --> 01:26:02,560
can start threading through homology

2214
01:26:06,790 --> 01:26:04,480
modeling a variety of these protein

2215
01:26:09,430 --> 01:26:06,800
structures so that is one way but there

2216
01:26:11,830 --> 01:26:09,440
is a likelihood we might be able to come

2217
01:26:13,030 --> 01:26:11,840
up with ways of using ai based

2218
01:26:15,270 --> 01:26:13,040
techniques

2219
01:26:26,149 --> 01:26:15,280
to detect certain folds that we haven't

2220
01:26:26,159 --> 01:26:31,890
anyone else

2221
01:26:34,629 --> 01:26:33,189
[Music]

2222
01:26:36,950 --> 01:26:34,639
so i think we're gonna have to shift

2223
01:26:39,510 --> 01:26:36,960
over here quickly to brit so let's thank

2224
01:26:42,790 --> 01:26:39,520
arvind for um

2225
01:26:46,310 --> 01:26:42,800
whirlwind of single-stranded dna viruses

2226
01:26:46,320 --> 01:26:50,709
okay can everybody hear me

2227
01:26:56,390 --> 01:26:53,830
yes we can hear you great all right

2228
01:27:00,950 --> 01:26:56,400
and once i get this started let me know

2229
01:27:06,310 --> 01:27:03,590
is the powerpoint up for everyone else

2230
01:27:08,149 --> 01:27:06,320
it is we can see it all right terrific

2231
01:27:09,990 --> 01:27:08,159
i must admit this is my first virtual

2232
01:27:11,270 --> 01:27:10,000
workshop like this i like it a lot and i

2233
01:27:13,189 --> 01:27:11,280
imagine that there's going to be many

2234
01:27:14,950 --> 01:27:13,199
many more of these in the future

2235
01:27:16,310 --> 01:27:14,960
as we start decreasing our carbon

2236
01:27:17,270 --> 01:27:16,320
footprint so thanks for getting this

2237
01:27:18,470 --> 01:27:17,280
going

2238
01:27:20,470 --> 01:27:18,480
um

2239
01:27:22,790 --> 01:27:20,480
so that was i'm very pleased actually to

2240
01:27:24,709 --> 01:27:22,800
be talking just after arvin because

2241
01:27:27,669 --> 01:27:24,719
i don't actually spend much time on

2242
01:27:29,750 --> 01:27:27,679
viral evolution but it's hopefully now

2243
01:27:32,470 --> 01:27:29,760
you've been suitably convinced that it

2244
01:27:34,229 --> 01:27:32,480
happens rapidly and is important and

2245
01:27:36,629 --> 01:27:34,239
over longer time skills and so what

2246
01:27:38,550 --> 01:27:36,639
instead i'm going to talk about today is

2247
01:27:40,070 --> 01:27:38,560
co-evolution and why

2248
01:27:42,709 --> 01:27:40,080
interactions between

2249
01:27:44,390 --> 01:27:42,719
viruses and in particular bacteriophages

2250
01:27:47,350 --> 01:27:44,400
are important in shaping bacterial

2251
01:27:49,669 --> 01:27:47,360
populations and communities

2252
01:27:50,870 --> 01:27:49,679
and so just to bring everybody up to the

2253
01:27:53,189 --> 01:27:50,880
same page when we're talking about

2254
01:27:54,870 --> 01:27:53,199
coevolution of course the first question

2255
01:27:57,669 --> 01:27:54,880
is co-evolution between what type of

2256
01:27:59,510 --> 01:27:57,679
phage and there are generally speaking

2257
01:28:01,669 --> 01:27:59,520
three types of phages lytic phage

2258
01:28:03,270 --> 01:28:01,679
temperate phage or filamentous phage

2259
01:28:04,470 --> 01:28:03,280
here and see i'm going to ignore the

2260
01:28:06,149 --> 01:28:04,480
filamentous phage although i think

2261
01:28:07,350 --> 01:28:06,159
they're incredibly neat

2262
01:28:09,270 --> 01:28:07,360
um

2263
01:28:11,430 --> 01:28:09,280
and focus primarily on lytic phage for

2264
01:28:12,950 --> 01:28:11,440
this talk but i don't want to ignore all

2265
01:28:15,350 --> 01:28:12,960
of the incredible diversity that

2266
01:28:16,870 --> 01:28:15,360
temperate phage introduce and so i'm

2267
01:28:18,950 --> 01:28:16,880
just going to spend a second here before

2268
01:28:21,189 --> 01:28:18,960
shifting to my own work

2269
01:28:23,910 --> 01:28:21,199
and so for thinking about the impact

2270
01:28:26,070 --> 01:28:23,920
that bacteriophages have on bacterial

2271
01:28:28,149 --> 01:28:26,080
communities and populations one of the

2272
01:28:30,070 --> 01:28:28,159
obvious ones is through direct

2273
01:28:32,390 --> 01:28:30,080
horizontal gene transfer and the genes

2274
01:28:35,350 --> 01:28:32,400
that they introduce as they themselves

2275
01:28:37,270 --> 01:28:35,360
integrate into a bacterial genome and so

2276
01:28:39,750 --> 01:28:37,280
these temperate phages when they form

2277
01:28:42,149 --> 01:28:39,760
lysogens in bacteria can completely

2278
01:28:43,910 --> 01:28:42,159
change the bacterial phenotype and one

2279
01:28:45,830 --> 01:28:43,920
of the ways that we care about this is

2280
01:28:47,990 --> 01:28:45,840
if that happens to change bacterial

2281
01:28:50,070 --> 01:28:48,000
pathogenicity for example

2282
01:28:51,990 --> 01:28:50,080
but this is just an example and of

2283
01:28:54,310 --> 01:28:52,000
course there are many different axes

2284
01:28:56,470 --> 01:28:54,320
across which phenotype can change

2285
01:28:59,110 --> 01:28:56,480
potentially including colonization of

2286
01:29:00,629 --> 01:28:59,120
spaceships for example but here this is

2287
01:29:02,310 --> 01:29:00,639
a really nice study not from my group

2288
01:29:04,709 --> 01:29:02,320
but they looked specifically at this

2289
01:29:08,390 --> 01:29:04,719
emerging opportunistic pathogen they

2290
01:29:11,830 --> 01:29:08,400
compared 795 genomes of this pathogen

2291
01:29:14,709 --> 01:29:11,840
and found over 4 000 prophages

2292
01:29:16,310 --> 01:29:14,719
let me just move this here and so

2293
01:29:18,470 --> 01:29:16,320
of those prophages and i'm just showing

2294
01:29:21,430 --> 01:29:18,480
this beautiful phylogeny they created

2295
01:29:23,910 --> 01:29:21,440
they did it with the proteome as well

2296
01:29:25,430 --> 01:29:23,920
this diversity is important in part

2297
01:29:27,590 --> 01:29:25,440
because as i already said this is

2298
01:29:29,669 --> 01:29:27,600
generating diversity in the bacterial

2299
01:29:33,430 --> 01:29:29,679
population and community as well

2300
01:29:35,350 --> 01:29:33,440
they found that 78 of the genomes had uh

2301
01:29:37,830 --> 01:29:35,360
i'm sorry of the intact prophages so

2302
01:29:39,510 --> 01:29:37,840
these are prophages that are remain

2303
01:29:41,430 --> 01:29:39,520
capable of exercising again and

2304
01:29:44,709 --> 01:29:41,440
infecting a new host

2305
01:29:46,390 --> 01:29:44,719
70 78 of them encoded potential

2306
01:29:47,590 --> 01:29:46,400
virulence genes

2307
01:29:49,270 --> 01:29:47,600
and so

2308
01:29:50,709 --> 01:29:49,280
if you want to understand pathogenicity

2309
01:29:53,669 --> 01:29:50,719
and bacterial virulence this sort of

2310
01:29:55,110 --> 01:29:53,679
argues that ignoring prophages which

2311
01:29:59,990 --> 01:29:55,120
we quite often do especially in

2312
01:30:03,830 --> 01:30:02,229
let's see here there we go

2313
01:30:05,590 --> 01:30:03,840
so if we go back here for a moment as i

2314
01:30:07,830 --> 01:30:05,600
already said most of what i'm going to

2315
01:30:09,990 --> 01:30:07,840
be discussing today is lytic phages here

2316
01:30:11,910 --> 01:30:10,000
in a and these are phages that are

2317
01:30:13,830 --> 01:30:11,920
obligate killers of their host so they

2318
01:30:16,149 --> 01:30:13,840
inject their own dna or rna hijack the

2319
01:30:18,950 --> 01:30:16,159
machinery birth must burst the cell in

2320
01:30:20,470 --> 01:30:18,960
order to reproduce and infect new hosts

2321
01:30:22,550 --> 01:30:20,480
and of course this has obvious

2322
01:30:24,790 --> 01:30:22,560
ecological ramifications it's killing

2323
01:30:25,830 --> 01:30:24,800
bacteria this was why people got excited

2324
01:30:27,990 --> 01:30:25,840
about lytic phage when they were

2325
01:30:30,310 --> 01:30:28,000
discovered in the 20s because

2326
01:30:32,070 --> 01:30:30,320
this was before antibiotics a way to

2327
01:30:34,390 --> 01:30:32,080
kill bacteria

2328
01:30:37,110 --> 01:30:34,400
but they do far more than that and so if

2329
01:30:39,350 --> 01:30:37,120
we want to understand bacteriophage oh

2330
01:30:41,990 --> 01:30:39,360
i'm sorry here we go if we want to

2331
01:30:43,830 --> 01:30:42,000
understand bacteria phage co-evolution

2332
01:30:46,070 --> 01:30:43,840
one of the first parts of this is to

2333
01:30:47,750 --> 01:30:46,080
understand how bacteria evolve resistant

2334
01:30:49,270 --> 01:30:47,760
so these phages are there they're

2335
01:30:50,550 --> 01:30:49,280
obligate killers that already said so

2336
01:30:53,110 --> 01:30:50,560
they're putting a strong selection

2337
01:30:55,110 --> 01:30:53,120
pressure on their bacterial hosts and

2338
01:30:56,950 --> 01:30:55,120
this is just three very simple uh the

2339
01:30:59,350 --> 01:30:56,960
most simple examples and the potentially

2340
01:31:01,590 --> 01:30:59,360
the most common but bacterial resistance

2341
01:31:03,030 --> 01:31:01,600
mechanisms are constantly

2342
01:31:05,990 --> 01:31:03,040
being

2343
01:31:08,310 --> 01:31:06,000
discovered and so here on in a you have

2344
01:31:09,750 --> 01:31:08,320
a simple change in the receptor so

2345
01:31:11,270 --> 01:31:09,760
phages must bind to recognize a

2346
01:31:13,030 --> 01:31:11,280
bacterial cell and so of course the

2347
01:31:15,270 --> 01:31:13,040
bacteria can change that receptor and

2348
01:31:17,590 --> 01:31:15,280
instantly be resistant to that phage it

2349
01:31:18,390 --> 01:31:17,600
can no longer detect the bacterial cell

2350
01:31:19,990 --> 01:31:18,400
or

2351
01:31:22,470 --> 01:31:20,000
it could use these crispr cast

2352
01:31:24,870 --> 01:31:22,480
mechanisms so this is a mechanism by

2353
01:31:27,189 --> 01:31:24,880
which bacteria can recognize specific

2354
01:31:28,950 --> 01:31:27,199
sections of phage the phage genome and

2355
01:31:31,189 --> 01:31:28,960
block translation of that transcription

2356
01:31:34,229 --> 01:31:31,199
of that phage and then the last one here

2357
01:31:36,550 --> 01:31:34,239
in c is apoptosis or cell suicide the

2358
01:31:38,790 --> 01:31:36,560
idea that once a bacterial cell detects

2359
01:31:40,870 --> 01:31:38,800
phage infection it actually kills itself

2360
01:31:43,189 --> 01:31:40,880
before the phage can do that protecting

2361
01:31:46,229 --> 01:31:43,199
neighboring cells and likely in any

2362
01:31:47,830 --> 01:31:46,239
given microbiome or bacterial community

2363
01:31:50,950 --> 01:31:47,840
all of these mechanisms are happening

2364
01:31:54,470 --> 01:31:52,870
of course you wouldn't have co-evolution

2365
01:31:55,990 --> 01:31:54,480
without the flip side and you again you

2366
01:31:57,030 --> 01:31:56,000
already heard a nice talk about viral

2367
01:31:58,790 --> 01:31:57,040
evolution

2368
01:32:01,030 --> 01:31:58,800
in the case of phages here's just one

2369
01:32:02,790 --> 01:32:01,040
very nice example of how phages can

2370
01:32:05,830 --> 01:32:02,800
counter adapt against crispr cast

2371
01:32:08,149 --> 01:32:05,840
resistance crispr resistance and so here

2372
01:32:11,270 --> 01:32:08,159
what you're looking at is at low density

2373
01:32:13,189 --> 01:32:11,280
this crispr resistance is actually quite

2374
01:32:15,270 --> 01:32:13,199
effective and so this is not work from

2375
01:32:17,270 --> 01:32:15,280
my lab this is a work that was done in

2376
01:32:19,270 --> 01:32:17,280
two separate labs they find the same

2377
01:32:21,350 --> 01:32:19,280
result but actually if you get enough

2378
01:32:22,950 --> 01:32:21,360
phages infecting the same cell the

2379
01:32:25,590 --> 01:32:22,960
phages can essentially work together to

2380
01:32:27,030 --> 01:32:25,600
overcome crispr resistance and so this

2381
01:32:29,990 --> 01:32:27,040
is one

2382
01:32:31,110 --> 01:32:30,000
example of how phages counter adapt

2383
01:32:33,110 --> 01:32:31,120
of course if it's a receptor

2384
01:32:34,550 --> 01:32:33,120
modification a counter modification

2385
01:32:37,430 --> 01:32:34,560
would do the trick a change in the tail

2386
01:32:39,030 --> 01:32:37,440
fiber and so forth and so what i tend to

2387
01:32:41,669 --> 01:32:39,040
think about when i think about bacteria

2388
01:32:44,310 --> 01:32:41,679
and phage interacting is the constant

2389
01:32:46,870 --> 01:32:44,320
arms race as bacteria evolve resistance

2390
01:32:49,350 --> 01:32:46,880
and phage counter adapt and this in

2391
01:32:51,270 --> 01:32:49,360
theory can go on indefinitely now in

2392
01:32:53,270 --> 01:32:51,280
practice it's not clear phage genomes

2393
01:32:55,110 --> 01:32:53,280
are small and so there's probably our

2394
01:32:56,390 --> 01:32:55,120
cycles and there's going to be some sort

2395
01:32:57,990 --> 01:32:56,400
of finite

2396
01:32:59,350 --> 01:32:58,000
amount of evolution that can happen

2397
01:33:00,390 --> 01:32:59,360
before you're almost back where you

2398
01:33:02,709 --> 01:33:00,400
started

2399
01:33:04,790 --> 01:33:02,719
potentially

2400
01:33:07,270 --> 01:33:04,800
and so just to give you a few examples

2401
01:33:08,870 --> 01:33:07,280
of why we should care about coevolution

2402
01:33:09,910 --> 01:33:08,880
um this is beautiful work from steve

2403
01:33:10,790 --> 01:33:09,920
patterson

2404
01:33:13,510 --> 01:33:10,800
showing

2405
01:33:15,990 --> 01:33:13,520
that um co-evolution as opposed to just

2406
01:33:18,149 --> 01:33:16,000
evolution really speeds up the molecular

2407
01:33:20,470 --> 01:33:18,159
evolution and so this is a sort of in

2408
01:33:22,950 --> 01:33:20,480
vitro test tube experiment here where

2409
01:33:25,510 --> 01:33:22,960
they either allowed bacteria and phage

2410
01:33:29,030 --> 01:33:25,520
to co-evolve so these are the c one

2411
01:33:31,030 --> 01:33:29,040
through six or just evolve

2412
01:33:33,750 --> 01:33:31,040
okay in this case they keep one player

2413
01:33:35,350 --> 01:33:33,760
fixed and they allow the other to evolve

2414
01:33:36,870 --> 01:33:35,360
and what you can see here is that this

2415
01:33:39,030 --> 01:33:36,880
is just a phylogeny you can see that

2416
01:33:41,270 --> 01:33:39,040
there's far less or slower molecular

2417
01:33:42,709 --> 01:33:41,280
evolution when evolution happens when

2418
01:33:44,709 --> 01:33:42,719
you fix one of the players and don't

2419
01:33:46,790 --> 01:33:44,719
allow them to counter-adapt than if you

2420
01:33:48,470 --> 01:33:46,800
allow for co-evolution and the other

2421
01:33:50,470 --> 01:33:48,480
thing they were able to show here is

2422
01:33:53,270 --> 01:33:50,480
that this leads to rapid diversification

2423
01:33:55,189 --> 01:33:53,280
so rapid specificity and diversification

2424
01:33:56,310 --> 01:33:55,199
so here along the top and b you're

2425
01:33:58,470 --> 01:33:56,320
looking at

2426
01:34:00,709 --> 01:33:58,480
the different co-evolution lines and who

2427
01:34:03,189 --> 01:34:00,719
those phages can infect and you can see

2428
01:34:06,149 --> 01:34:03,199
that for example c4 is capable of

2429
01:34:07,430 --> 01:34:06,159
infecting a different set of hosts than

2430
01:34:09,430 --> 01:34:07,440
c6

2431
01:34:11,910 --> 01:34:09,440
and so this happened within a very short

2432
01:34:13,750 --> 01:34:11,920
period of time in the lab and really to

2433
01:34:15,669 --> 01:34:13,760
me emphasizes how

2434
01:34:17,270 --> 01:34:15,679
important co-evolution is both at the

2435
01:34:18,950 --> 01:34:17,280
molecular level and then at the

2436
01:34:21,350 --> 01:34:18,960
phenotypic level and this is work from

2437
01:34:22,950 --> 01:34:21,360
angus buckling now uh older work where

2438
01:34:27,110 --> 01:34:22,960
they just simply looked at bacterial

2439
01:34:29,030 --> 01:34:27,120
phenotype these different more

2440
01:34:31,350 --> 01:34:29,040
and they could show that if you look in

2441
01:34:33,270 --> 01:34:31,360
this sort of test tube experiment if you

2442
01:34:34,550 --> 01:34:33,280
allow phage co-evolution in a test tube

2443
01:34:36,709 --> 01:34:34,560
versus if you allow the bacteria to

2444
01:34:39,030 --> 01:34:36,719
evolve alone when the phages are present

2445
01:34:40,870 --> 01:34:39,040
the diversity the allopatric diversity

2446
01:34:43,189 --> 01:34:40,880
so how different two test tubes to

2447
01:34:45,910 --> 01:34:43,199
populate populations end up being from

2448
01:34:48,550 --> 01:34:45,920
one another is far higher when phages

2449
01:34:50,629 --> 01:34:48,560
are present than when they're absent

2450
01:34:52,709 --> 01:34:50,639
so rapid and molecular evolution rapid

2451
01:34:54,790 --> 01:34:52,719
phenotypic diversification hopefully

2452
01:34:56,870 --> 01:34:54,800
i've convinced you by this moment that

2453
01:34:58,070 --> 01:34:56,880
coevolution matters if you want to be

2454
01:35:00,070 --> 01:34:58,080
understanding

2455
01:35:01,830 --> 01:35:00,080
bacteria

2456
01:35:03,189 --> 01:35:01,840
and one of the ways that you can measure

2457
01:35:05,750 --> 01:35:03,199
coevolution and i would say the gold

2458
01:35:07,430 --> 01:35:05,760
standard way if you can do it is using a

2459
01:35:08,709 --> 01:35:07,440
time shift experiment so i'm just going

2460
01:35:10,470 --> 01:35:08,719
to spend a moment here because i'll show

2461
01:35:11,590 --> 01:35:10,480
you some data

2462
01:35:13,750 --> 01:35:11,600
using this but this is just a

2463
01:35:15,990 --> 01:35:13,760
theoretical model from a paper that

2464
01:35:17,510 --> 01:35:16,000
dieter ever put out a few years back

2465
01:35:19,669 --> 01:35:17,520
which is a great primer for anyone

2466
01:35:21,750 --> 01:35:19,679
interested in time shift experiments the

2467
01:35:24,470 --> 01:35:21,760
idea here is simply you would co-evolve

2468
01:35:25,750 --> 01:35:24,480
your populations and then freeze through

2469
01:35:27,510 --> 01:35:25,760
time or if you happen to have a

2470
01:35:29,030 --> 01:35:27,520
permafrost sample you know you can thaw

2471
01:35:31,430 --> 01:35:29,040
through time

2472
01:35:32,390 --> 01:35:31,440
and do a cross inoculation where you're

2473
01:35:34,390 --> 01:35:32,400
taking

2474
01:35:35,830 --> 01:35:34,400
bacteria let's say from one time point

2475
01:35:37,830 --> 01:35:35,840
and you're challenging that bacteria

2476
01:35:39,910 --> 01:35:37,840
with phages from the past

2477
01:35:41,750 --> 01:35:39,920
or phages from the future and you have a

2478
01:35:43,590 --> 01:35:41,760
clear prediction that they should be

2479
01:35:45,750 --> 01:35:43,600
more resistant

2480
01:35:48,149 --> 01:35:45,760
to phages from the past and less

2481
01:35:50,550 --> 01:35:48,159
resistant to phages from the future

2482
01:35:52,629 --> 01:35:50,560
as those phages have counter adapted to

2483
01:35:55,030 --> 01:35:52,639
any resistance mechanisms and this sort

2484
01:35:57,669 --> 01:35:55,040
of directionality is indicative of this

2485
01:36:00,149 --> 01:35:57,679
these arms race dynamics in a

2486
01:36:01,669 --> 01:36:00,159
co-evolving system

2487
01:36:03,189 --> 01:36:01,679
and you can do this in test tube

2488
01:36:05,350 --> 01:36:03,199
populations and this is a really nice

2489
01:36:07,590 --> 01:36:05,360
one from pauline scanlon

2490
01:36:09,270 --> 01:36:07,600
where you again take your bacteria in

2491
01:36:11,510 --> 01:36:09,280
this case pseudomonas fluorescens and a

2492
01:36:13,830 --> 01:36:11,520
phage allow them to co-evolve over time

2493
01:36:15,669 --> 01:36:13,840
and do a huge matrix cross where you

2494
01:36:17,189 --> 01:36:15,679
take bacteria here from different time

2495
01:36:18,709 --> 01:36:17,199
points and you cross them with phages

2496
01:36:20,790 --> 01:36:18,719
from different time points

2497
01:36:23,189 --> 01:36:20,800
and what this allows you to do is

2498
01:36:25,510 --> 01:36:23,199
actually measure you can show that over

2499
01:36:26,629 --> 01:36:25,520
time bacteria increase their resistance

2500
01:36:27,910 --> 01:36:26,639
to phage

2501
01:36:29,590 --> 01:36:27,920
through those mechanisms i already

2502
01:36:31,990 --> 01:36:29,600
described but that phages are

2503
01:36:33,750 --> 01:36:32,000
continually counter adapting to that and

2504
01:36:35,270 --> 01:36:33,760
in this particular case this is a true

2505
01:36:37,510 --> 01:36:35,280
arms race because

2506
01:36:39,830 --> 01:36:37,520
the bacteria are never in the course of

2507
01:36:41,109 --> 01:36:39,840
this experiment once again susceptible

2508
01:36:42,149 --> 01:36:41,119
to phages from the start of the

2509
01:36:44,310 --> 01:36:42,159
experiment

2510
01:36:46,470 --> 01:36:44,320
resistance continues to increase and

2511
01:36:47,990 --> 01:36:46,480
phage infectivity continues to increase

2512
01:36:49,910 --> 01:36:48,000
so they're chasing one another through

2513
01:36:51,350 --> 01:36:49,920
space

2514
01:36:53,510 --> 01:36:51,360
and again we know this happens very

2515
01:36:55,510 --> 01:36:53,520
rapidly in a test tube but what my lab

2516
01:36:57,590 --> 01:36:55,520
specifically focuses on is whether this

2517
01:36:58,790 --> 01:36:57,600
happens in the real world and whether

2518
01:37:00,629 --> 01:36:58,800
that matters

2519
01:37:02,390 --> 01:37:00,639
and we do that in in two different ways

2520
01:37:05,270 --> 01:37:02,400
we do that in terms of looking at

2521
01:37:07,350 --> 01:37:05,280
pairwise interactions between phages and

2522
01:37:08,950 --> 01:37:07,360
bacteria we focus on the plant pathogens

2523
01:37:10,870 --> 01:37:08,960
pseudomonas ring a

2524
01:37:12,070 --> 01:37:10,880
we have some new work as well on erwinia

2525
01:37:14,229 --> 01:37:12,080
and lavora

2526
01:37:16,070 --> 01:37:14,239
called the causal agent of fireblade and

2527
01:37:17,669 --> 01:37:16,080
then also just the role that phages play

2528
01:37:20,149 --> 01:37:17,679
in the broader microbiome in these

2529
01:37:22,629 --> 01:37:20,159
microbial communities and the system we

2530
01:37:24,790 --> 01:37:22,639
use is the phylosphere above ground

2531
01:37:26,629 --> 01:37:24,800
tissue of plants this is an incredibly

2532
01:37:29,750 --> 01:37:26,639
convenient system because the spatial

2533
01:37:31,830 --> 01:37:29,760
scale is very clear

2534
01:37:34,550 --> 01:37:31,840
and so i'm going to start by showing you

2535
01:37:37,109 --> 01:37:34,560
some work on the sort of more black boxy

2536
01:37:41,750 --> 01:37:37,119
community level and follow and finish

2537
01:37:46,229 --> 01:37:43,910
the first experiment i ever did when i

2538
01:37:47,990 --> 01:37:46,239
started to try to get a hold of what was

2539
01:37:50,070 --> 01:37:48,000
happening in a natural system the

2540
01:37:51,109 --> 01:37:50,080
phylosphere of a horse chestnut tree in

2541
01:37:53,590 --> 01:37:51,119
this case

2542
01:37:55,750 --> 01:37:53,600
is i went out and i just simply asked

2543
01:37:57,590 --> 01:37:55,760
what bacteriophages are in these leaves

2544
01:37:59,669 --> 01:37:57,600
and who are they infecting

2545
01:38:02,390 --> 01:37:59,679
and this is only focused on culturable

2546
01:38:03,990 --> 01:38:02,400
components of the microbial community

2547
01:38:06,390 --> 01:38:04,000
but nonetheless if you do that if you

2548
01:38:08,870 --> 01:38:06,400
culture bacteria from a given leaf and

2549
01:38:11,030 --> 01:38:08,880
then you filter that leaf juice and see

2550
01:38:12,709 --> 01:38:11,040
whatever viruses are in there and ask

2551
01:38:15,270 --> 01:38:12,719
who can they infect

2552
01:38:17,270 --> 01:38:15,280
you find that phages are far more

2553
01:38:19,350 --> 01:38:17,280
infective so this is a sympatric phage

2554
01:38:21,750 --> 01:38:19,360
from the same tree they're far more

2555
01:38:23,750 --> 01:38:21,760
infective to bacteria from that same

2556
01:38:25,109 --> 01:38:23,760
tree than they are to bacteria from a

2557
01:38:26,950 --> 01:38:25,119
neighboring tree

2558
01:38:28,550 --> 01:38:26,960
and this just is a nice starting place

2559
01:38:30,310 --> 01:38:28,560
it's an old paper now but it's a nice

2560
01:38:32,070 --> 01:38:30,320
starting place because it tells us that

2561
01:38:34,149 --> 01:38:32,080
in a natural system like the tree

2562
01:38:35,270 --> 01:38:34,159
phylosphere that phages are there

2563
01:38:37,189 --> 01:38:35,280
they're in high abundance they're

2564
01:38:40,550 --> 01:38:37,199
infecting about 15

2565
01:38:42,550 --> 01:38:40,560
of the bacteria in their local community

2566
01:38:44,070 --> 01:38:42,560
and that they're well adapted

2567
01:38:46,070 --> 01:38:44,080
and as soon as you have that evidence

2568
01:38:47,270 --> 01:38:46,080
for adaptation

2569
01:38:48,709 --> 01:38:47,280
that suggests that they should be

2570
01:38:51,669 --> 01:38:48,719
putting strong selection pressure on

2571
01:38:53,430 --> 01:38:51,679
their bacterial hosts for resistance

2572
01:38:55,189 --> 01:38:53,440
so how do we test that well i already

2573
01:38:57,590 --> 01:38:55,199
told you the gold standard way to test

2574
01:38:59,430 --> 01:38:57,600
it is with the time shift experiment

2575
01:39:01,109 --> 01:38:59,440
the downside of a black box approach

2576
01:39:04,550 --> 01:39:01,119
like this is you can't follow a single

2577
01:39:06,390 --> 01:39:04,560
lineage through time so we're sort of

2578
01:39:08,310 --> 01:39:06,400
glossing over we're making a broader

2579
01:39:10,070 --> 01:39:08,320
statement about evolution here as a

2580
01:39:11,990 --> 01:39:10,080
function of turnover between species

2581
01:39:14,229 --> 01:39:12,000
turnovers between strain as well as

2582
01:39:15,669 --> 01:39:14,239
mutation but nonetheless we can take a

2583
01:39:18,070 --> 01:39:15,679
similar approach

2584
01:39:19,270 --> 01:39:18,080
and we can ask again we take our leaves

2585
01:39:21,270 --> 01:39:19,280
from these trees and we put them into

2586
01:39:23,510 --> 01:39:21,280
the freezer you can then resurrect the

2587
01:39:25,430 --> 01:39:23,520
bacteria and the phage and say for a

2588
01:39:28,070 --> 01:39:25,440
given bacterial host let's say here's

2589
01:39:30,550 --> 01:39:28,080
just an illustrative example

2590
01:39:32,149 --> 01:39:30,560
a bacterium from july from tree number

2591
01:39:34,470 --> 01:39:32,159
two

2592
01:39:35,189 --> 01:39:34,480
and you can then challenge that bacteria

2593
01:39:37,590 --> 01:39:35,199
with

2594
01:39:38,790 --> 01:39:37,600
potential phage so this filtered leaf

2595
01:39:40,550 --> 01:39:38,800
juice

2596
01:39:43,270 --> 01:39:40,560
from earlier time points for example

2597
01:39:45,669 --> 01:39:43,280
june here uh the contemporary time point

2598
01:39:47,510 --> 01:39:45,679
july or later time points august and

2599
01:39:49,590 --> 01:39:47,520
september for example

2600
01:39:51,109 --> 01:39:49,600
so if we do that and we lump across our

2601
01:39:54,310 --> 01:39:51,119
the eight trees that i used in this

2602
01:39:59,189 --> 01:39:56,709
what we find is a similar result to what

2603
01:40:01,750 --> 01:39:59,199
pauline scanlan and others often find in

2604
01:40:02,709 --> 01:40:01,760
test tubes which is to say a directional

2605
01:40:04,470 --> 01:40:02,719
pattern

2606
01:40:06,870 --> 01:40:04,480
where in this case if we look at

2607
01:40:08,390 --> 01:40:06,880
bacterial resistance oh sorry about the

2608
01:40:10,229 --> 01:40:08,400
y-axis there something funny is going on

2609
01:40:11,669 --> 01:40:10,239
but the bacterial resistance on the

2610
01:40:14,149 --> 01:40:11,679
y-axis

2611
01:40:15,830 --> 01:40:14,159
we can say that bacteria are more

2612
01:40:17,750 --> 01:40:15,840
resistant to phages that they've

2613
01:40:19,510 --> 01:40:17,760
experienced previously in the season so

2614
01:40:22,070 --> 01:40:19,520
this is the past phage

2615
01:40:23,510 --> 01:40:22,080
okay so if they've been under selection

2616
01:40:25,270 --> 01:40:23,520
from that phage

2617
01:40:26,310 --> 01:40:25,280
they are more likely to be resistant to

2618
01:40:27,910 --> 01:40:26,320
it

2619
01:40:30,550 --> 01:40:27,920
the contemporary time point somewhere in

2620
01:40:32,310 --> 01:40:30,560
the middle and then future phages tend

2621
01:40:34,950 --> 01:40:32,320
to have counter-adapted and overcome

2622
01:40:36,470 --> 01:40:34,960
that resistance and so another way of

2623
01:40:38,149 --> 01:40:36,480
saying that is bacteria are least

2624
01:40:40,149 --> 01:40:38,159
resistant to phages that they have not

2625
01:40:42,149 --> 01:40:40,159
yet encountered phages that have likely

2626
01:40:43,750 --> 01:40:42,159
counter-adapted to that contemporary

2627
01:40:45,590 --> 01:40:43,760
resistance

2628
01:40:47,109 --> 01:40:45,600
i should say that the solid bar here is

2629
01:40:48,950 --> 01:40:47,119
just the average across the trees and

2630
01:40:51,109 --> 01:40:48,960
there is a lot of variation not every

2631
01:40:52,709 --> 01:40:51,119
tree is behaving in the same way but the

2632
01:40:54,790 --> 01:40:52,719
pattern is highly statistically

2633
01:40:56,950 --> 01:40:54,800
significant even if you pull out this

2634
01:41:00,310 --> 01:40:56,960
sort of super co-evolving population

2635
01:41:04,229 --> 01:41:01,590
okay

2636
01:41:06,790 --> 01:41:04,239
so so far i've told it told you that in

2637
01:41:08,629 --> 01:41:06,800
a natural system phages are present

2638
01:41:10,229 --> 01:41:08,639
they're highly prevalent

2639
01:41:11,510 --> 01:41:10,239
they should be they're obligate killers

2640
01:41:13,430 --> 01:41:11,520
so they should be putting selection on

2641
01:41:15,350 --> 01:41:13,440
their hosts and indeed it looks like

2642
01:41:16,950 --> 01:41:15,360
bacteria are becoming more resistant

2643
01:41:18,950 --> 01:41:16,960
through the season as they're

2644
01:41:21,189 --> 01:41:18,960
encountering these phages in a natural

2645
01:41:23,830 --> 01:41:21,199
system

2646
01:41:25,350 --> 01:41:23,840
what does that mean for diversity so

2647
01:41:27,189 --> 01:41:25,360
i've again given you some nice examples

2648
01:41:28,790 --> 01:41:27,199
from a test tube that we have clear and

2649
01:41:30,629 --> 01:41:28,800
we have clear theory the kill the winter

2650
01:41:33,189 --> 01:41:30,639
theory is a good example of that where

2651
01:41:36,070 --> 01:41:33,199
we expect that phages should as they

2652
01:41:37,590 --> 01:41:36,080
adapt to common bacterial types

2653
01:41:39,590 --> 01:41:37,600
they actually take

2654
01:41:41,750 --> 01:41:39,600
the fitness of common types down and

2655
01:41:44,070 --> 01:41:41,760
they should be increasing diversity of

2656
01:41:46,310 --> 01:41:44,080
the microbial population or community

2657
01:41:48,070 --> 01:41:46,320
but can we actually show that to be true

2658
01:41:49,910 --> 01:41:48,080
uh which is it's a bit of a challenge

2659
01:41:52,229 --> 01:41:49,920
and again as a first pass we took a

2660
01:41:53,990 --> 01:41:52,239
black box approach and by we here this

2661
01:41:55,750 --> 01:41:54,000
work was led by norma marella who's a

2662
01:41:56,709 --> 01:41:55,760
phd student in the lab who just recently

2663
01:41:58,629 --> 01:41:56,719
finished

2664
01:41:59,669 --> 01:41:58,639
um and so what she did was went out to

2665
01:42:01,990 --> 01:41:59,679
the field

2666
01:42:03,430 --> 01:42:02,000
sampled a whole microbiome so in this

2667
01:42:05,189 --> 01:42:03,440
case we used tomato it's a very

2668
01:42:07,430 --> 01:42:05,199
convenient model system

2669
01:42:09,270 --> 01:42:07,440
she was able to go out to fields sample

2670
01:42:11,669 --> 01:42:09,280
the whole tomato plant

2671
01:42:12,870 --> 01:42:11,679
wash off all of the bacteria and the

2672
01:42:15,990 --> 01:42:12,880
viruses

2673
01:42:17,750 --> 01:42:16,000
from the surface of leaves and then

2674
01:42:20,070 --> 01:42:17,760
through a series of filtration steps

2675
01:42:22,070 --> 01:42:20,080
separate that microbiome into two

2676
01:42:24,950 --> 01:42:22,080
components the microbial community the

2677
01:42:26,390 --> 01:42:24,960
bacteria and then the viral component

2678
01:42:29,350 --> 01:42:26,400
and the nice thing about that is then we

2679
01:42:31,590 --> 01:42:29,360
can either inoculate sterile plants with

2680
01:42:32,950 --> 01:42:31,600
either the bacterial community alone or

2681
01:42:34,950 --> 01:42:32,960
that bacterial community where the

2682
01:42:36,950 --> 01:42:34,960
phages have been recombined

2683
01:42:38,790 --> 01:42:36,960
and again a very black box approach but

2684
01:42:41,750 --> 01:42:38,800
it allows us to get a really nice

2685
01:42:43,830 --> 01:42:41,760
average of whether phages are generally

2686
01:42:46,550 --> 01:42:43,840
making a difference during initial

2687
01:42:48,950 --> 01:42:46,560
microbiome colonization in this case

2688
01:42:52,149 --> 01:42:48,960
and we use digital droplet pcr as a way

2689
01:42:54,950 --> 01:42:52,159
of quantifying absolute abundance

2690
01:42:56,790 --> 01:42:54,960
of our bacteria using 16s probe

2691
01:42:57,910 --> 01:42:56,800
and also for future studies that i'll

2692
01:43:00,629 --> 01:42:57,920
show you

2693
01:43:03,750 --> 01:43:00,639
specific bacteria as well

2694
01:43:05,270 --> 01:43:03,760
okay so she sprayed plants and replicate

2695
01:43:07,750 --> 01:43:05,280
with either the bacterial component

2696
01:43:10,629 --> 01:43:07,760
alone or the bacteria with it sympatric

2697
01:43:11,910 --> 01:43:10,639
the same phage from that

2698
01:43:13,669 --> 01:43:11,920
community

2699
01:43:16,390 --> 01:43:13,679
and the first thing to say is when we

2700
01:43:17,750 --> 01:43:16,400
look at the plants a day later so a day

2701
01:43:20,390 --> 01:43:17,760
after they're inoculated with this

2702
01:43:22,790 --> 01:43:20,400
diverse microbial community we can show

2703
01:43:25,669 --> 01:43:22,800
that the when you recombine with the

2704
01:43:28,709 --> 01:43:25,679
phage this orange bar here that overall

2705
01:43:30,550 --> 01:43:28,719
abundance so the ddpcr copy number

2706
01:43:32,149 --> 01:43:30,560
per leaf is lower

2707
01:43:34,790 --> 01:43:32,159
and this shouldn't surprise you these

2708
01:43:36,550 --> 01:43:34,800
phages are obligate killers but it is at

2709
01:43:38,790 --> 01:43:36,560
least suggesting that they really are

2710
01:43:40,950 --> 01:43:38,800
finding hosts and knocking them out in

2711
01:43:43,030 --> 01:43:40,960
this community

2712
01:43:45,189 --> 01:43:43,040
that effect on density goes away after

2713
01:43:47,189 --> 01:43:45,199
day seven although a lot changes on the

2714
01:43:48,310 --> 01:43:47,199
leaves carrying capacity is reached so

2715
01:43:50,149 --> 01:43:48,320
probably there's a lot of strain

2716
01:43:53,270 --> 01:43:50,159
switching here as the community is

2717
01:43:54,870 --> 01:43:53,280
establishing and stabilizing

2718
01:43:56,870 --> 01:43:54,880
the second thing we can do then is

2719
01:43:59,189 --> 01:43:56,880
sequence our microbial community and ask

2720
01:44:00,790 --> 01:43:59,199
what effect phages had on the whole

2721
01:44:02,149 --> 01:44:00,800
community composition

2722
01:44:03,510 --> 01:44:02,159
and i'll just show you one example of

2723
01:44:05,910 --> 01:44:03,520
that here

2724
01:44:08,390 --> 01:44:05,920
to say that again when you have phages

2725
01:44:11,350 --> 01:44:08,400
present there's a clear compositional

2726
01:44:12,790 --> 01:44:11,360
shift so this is a pcoa plot where we're

2727
01:44:14,870 --> 01:44:12,800
just looking at

2728
01:44:17,189 --> 01:44:14,880
community composition and beta

2729
01:44:19,270 --> 01:44:17,199
dissimilarity among them so all you need

2730
01:44:20,390 --> 01:44:19,280
to know here is if two points are

2731
01:44:22,229 --> 01:44:20,400
further apart

2732
01:44:23,990 --> 01:44:22,239
that means the community members have

2733
01:44:26,310 --> 01:44:24,000
less in common so the community is more

2734
01:44:27,750 --> 01:44:26,320
different

2735
01:44:29,910 --> 01:44:27,760
and so

2736
01:44:31,669 --> 01:44:29,920
again you can see that the bacteria and

2737
01:44:33,750 --> 01:44:31,679
phage replicates cluster out whether it

2738
01:44:35,750 --> 01:44:33,760
be day one or seven and the bacteria

2739
01:44:37,590 --> 01:44:35,760
only cluster out and the treatment

2740
01:44:39,910 --> 01:44:37,600
whether or not phage or that is there or

2741
01:44:42,070 --> 01:44:39,920
not explains 13 of the variation in

2742
01:44:43,270 --> 01:44:42,080
community composition and so again this

2743
01:44:45,270 --> 01:44:43,280
just suggests that if you're trying to

2744
01:44:47,350 --> 01:44:45,280
explain microbial microbiome diversity

2745
01:44:48,709 --> 01:44:47,360
whether it be a microbiome in a human

2746
01:44:51,430 --> 01:44:48,719
gut or in a

2747
01:44:53,430 --> 01:44:51,440
lake um ignoring the phages you're going

2748
01:44:56,629 --> 01:44:53,440
to miss this sort of explanatory power

2749
01:44:58,149 --> 01:44:56,639
of at least 13

2750
01:45:00,950 --> 01:44:58,159
and then the final thing she was able to

2751
01:45:02,390 --> 01:45:00,960
do using this same data set here the 16s

2752
01:45:04,950 --> 01:45:02,400
amplicon dataset

2753
01:45:06,790 --> 01:45:04,960
is ask what impacts phages had overall

2754
01:45:08,629 --> 01:45:06,800
on diversity and i've already given you

2755
01:45:10,390 --> 01:45:08,639
a theoretical reason why we expect

2756
01:45:11,750 --> 01:45:10,400
phages to maintain diversity i've

2757
01:45:13,750 --> 01:45:11,760
already shown you that this happens in a

2758
01:45:15,830 --> 01:45:13,760
test tube so hopefully this won't come

2759
01:45:17,910 --> 01:45:15,840
as a surprise although to me science is

2760
01:45:19,430 --> 01:45:17,920
always surprising when it

2761
01:45:21,109 --> 01:45:19,440
meets expectation

2762
01:45:22,310 --> 01:45:21,119
and so what you're looking at here is on

2763
01:45:24,550 --> 01:45:22,320
the left

2764
01:45:25,910 --> 01:45:24,560
alpha diversity so you can think about

2765
01:45:26,790 --> 01:45:25,920
this as

2766
01:45:28,950 --> 01:45:26,800
how many

2767
01:45:31,510 --> 01:45:28,960
otu or what the richness of species are

2768
01:45:33,189 --> 01:45:31,520
there and at day seven so we don't

2769
01:45:35,270 --> 01:45:33,199
really see an impact at day one which is

2770
01:45:36,629 --> 01:45:35,280
not particularly surprising but at day

2771
01:45:39,590 --> 01:45:36,639
seven once these communities have

2772
01:45:41,910 --> 01:45:39,600
established we find that indeed when

2773
01:45:44,229 --> 01:45:41,920
phages are present there are there's a

2774
01:45:46,070 --> 01:45:44,239
higher diversity of bacteria in these

2775
01:45:47,350 --> 01:45:46,080
microbiomes

2776
01:45:49,669 --> 01:45:47,360
and so

2777
01:45:51,590 --> 01:45:49,679
that fits beautifully with theory the

2778
01:45:53,350 --> 01:45:51,600
more surprising result for us although

2779
01:45:55,189 --> 01:45:53,360
again does fit with theory is on the

2780
01:45:57,430 --> 01:45:55,199
right here and what you're looking at is

2781
01:45:59,270 --> 01:45:57,440
the average ray curtis distances among

2782
01:46:01,990 --> 01:45:59,280
replicates and so another way of saying

2783
01:46:04,470 --> 01:46:02,000
that is how different is the microbiome

2784
01:46:06,709 --> 01:46:04,480
of two plants that received only

2785
01:46:08,629 --> 01:46:06,719
bacteria from one another or two plants

2786
01:46:11,990 --> 01:46:08,639
that received bacteria and phage from

2787
01:46:14,470 --> 01:46:12,000
one another so within treatment

2788
01:46:16,070 --> 01:46:14,480
but differences among individual plants

2789
01:46:17,830 --> 01:46:16,080
and what you can see here is no

2790
01:46:20,149 --> 01:46:17,840
significant differences at day one but

2791
01:46:22,550 --> 01:46:20,159
at day seven we actually have decreased

2792
01:46:24,149 --> 01:46:22,560
beta diversity in the presence of phage

2793
01:46:26,470 --> 01:46:24,159
and i think this is really neat because

2794
01:46:28,229 --> 01:46:26,480
it's suggesting that phages are really

2795
01:46:29,669 --> 01:46:28,239
moving the microbiome in this in the

2796
01:46:31,510 --> 01:46:29,679
same direction so they're sort of

2797
01:46:34,390 --> 01:46:31,520
raining in the microbiome in a similar

2798
01:46:37,669 --> 01:46:35,910
okay so i'm just going to finish up here

2799
01:46:40,390 --> 01:46:37,679
in the last

2800
01:46:41,270 --> 01:46:40,400
seven minutes or so by zooming in a bit

2801
01:46:51,270 --> 01:46:41,280
on

2802
01:46:54,550 --> 01:46:51,280
plant pathogen of broad host range and

2803
01:46:56,550 --> 01:46:54,560
we focus on tomato plants

2804
01:46:58,870 --> 01:46:56,560
and this work here is a recent paper

2805
01:47:01,189 --> 01:46:58,880
that's come out from kathy hernandez

2806
01:47:03,430 --> 01:47:01,199
and so the citations down there if

2807
01:47:05,990 --> 01:47:03,440
you're interested in the full story but

2808
01:47:08,310 --> 01:47:06,000
we became very interested in

2809
01:47:10,629 --> 01:47:08,320
the idea that co-evolution is likely to

2810
01:47:12,310 --> 01:47:10,639
be very different in a test tube from in

2811
01:47:14,709 --> 01:47:12,320
a plant and i've already shown you some

2812
01:47:17,109 --> 01:47:14,719
evidence that that's true but we wanted

2813
01:47:19,750 --> 01:47:17,119
a very specific test of this and so

2814
01:47:21,590 --> 01:47:19,760
because we know that we can grow our

2815
01:47:23,030 --> 01:47:21,600
strains on a tomato plant in very

2816
01:47:24,709 --> 01:47:23,040
controlled conditions

2817
01:47:26,870 --> 01:47:24,719
we thought this is a nice comparison to

2818
01:47:28,709 --> 01:47:26,880
a test tube so what i'm showing you here

2819
01:47:30,950 --> 01:47:28,719
is in our in vitro lines this is a

2820
01:47:33,350 --> 01:47:30,960
typical experimental evolution

2821
01:47:34,950 --> 01:47:33,360
setup where on the far left on the

2822
01:47:37,430 --> 01:47:34,960
bottom here the treatments we have

2823
01:47:39,109 --> 01:47:37,440
bacteria alone and the passage three is

2824
01:47:40,629 --> 01:47:39,119
the midpoint passage six is the end of

2825
01:47:42,629 --> 01:47:40,639
the experiment and you just look at

2826
01:47:44,629 --> 01:47:42,639
whether they evolved resistance or not

2827
01:47:46,470 --> 01:47:44,639
and the bacteria alone lines do not

2828
01:47:48,149 --> 01:47:46,480
involve resistance

2829
01:47:50,950 --> 01:47:48,159
and the um

2830
01:47:53,750 --> 01:47:50,960
the co-evolved or if you allow either of

2831
01:47:55,270 --> 01:47:53,760
them to evolve as a fixed against the

2832
01:47:57,590 --> 01:47:55,280
other one

2833
01:47:59,510 --> 01:47:57,600
so in other words phage can evolve to

2834
01:48:00,629 --> 01:47:59,520
fix bacteria or bacteria can evolve to

2835
01:48:03,109 --> 01:48:00,639
fix phage

2836
01:48:05,830 --> 01:48:03,119
in either of those cases we see

2837
01:48:07,189 --> 01:48:05,840
that resistance spreads and the two

2838
01:48:09,109 --> 01:48:07,199
different colored dots it's not really

2839
01:48:10,470 --> 01:48:09,119
important but that's ancestral phage or

2840
01:48:12,870 --> 01:48:10,480
the contemporary phage during

2841
01:48:13,590 --> 01:48:12,880
co-evolution or evolution

2842
01:48:15,189 --> 01:48:13,600
so

2843
01:48:16,950 --> 01:48:15,199
in a test tube

2844
01:48:19,590 --> 01:48:16,960
resistance evolves very quickly is the

2845
01:48:21,590 --> 01:48:19,600
take-home message from this slide

2846
01:48:23,750 --> 01:48:21,600
and that's not surprising what you can

2847
01:48:25,750 --> 01:48:23,760
then do is take resistant mutants and

2848
01:48:27,590 --> 01:48:25,760
susceptible mutants put them back in a

2849
01:48:30,870 --> 01:48:27,600
plant in the presence or absence of

2850
01:48:31,669 --> 01:48:30,880
phage and measure selection for that

2851
01:48:33,590 --> 01:48:31,679
type

2852
01:48:35,189 --> 01:48:33,600
and i'm just focusing here on the 24

2853
01:48:37,030 --> 01:48:35,199
hours so this is you inoculate the

2854
01:48:38,550 --> 01:48:37,040
plants and 24 hours later you can use

2855
01:48:40,709 --> 01:48:38,560
droplet digital pcr to measure

2856
01:48:42,229 --> 01:48:40,719
pseudomonas ring a and what i want you

2857
01:48:43,590 --> 01:48:42,239
to take away again this is in a test

2858
01:48:45,830 --> 01:48:43,600
tube is

2859
01:48:47,669 --> 01:48:45,840
when there are phage present in that

2860
01:48:49,830 --> 01:48:47,679
tube the bacterial density of

2861
01:48:51,669 --> 01:48:49,840
pseudomonas serine is lower for

2862
01:48:53,910 --> 01:48:51,679
susceptible mutants than resistant

2863
01:48:56,629 --> 01:48:53,920
mutants in other words selection should

2864
01:48:58,390 --> 01:48:56,639
favor resistance mutants and indeed

2865
01:49:00,550 --> 01:48:58,400
that's what we see resistance spreads in

2866
01:49:02,310 --> 01:49:00,560
a test tube very quickly

2867
01:49:04,629 --> 01:49:02,320
in most cases we see it happening in

2868
01:49:05,590 --> 01:49:04,639
under 48 hours

2869
01:49:07,510 --> 01:49:05,600
okay

2870
01:49:09,590 --> 01:49:07,520
so what happens in a plant

2871
01:49:11,590 --> 01:49:09,600
in this case she took the same strains

2872
01:49:13,669 --> 01:49:11,600
in the same experimental setup but now

2873
01:49:15,350 --> 01:49:13,679
put these bacteria in phage in a plant

2874
01:49:16,870 --> 01:49:15,360
and i'm showing you one example here but

2875
01:49:19,270 --> 01:49:16,880
she re-ran the experiment in many

2876
01:49:21,750 --> 01:49:19,280
different ways and many different mois

2877
01:49:24,470 --> 01:49:21,760
and what we found was that we did not

2878
01:49:26,550 --> 01:49:24,480
see the evolution of resistance and this

2879
01:49:28,390 --> 01:49:26,560
importantly and in contrast to what i've

2880
01:49:30,950 --> 01:49:28,400
just shown you from a whole microbe a

2881
01:49:33,109 --> 01:49:30,960
natural microbial community this is

2882
01:49:35,030 --> 01:49:33,119
resistance by mutation whereas

2883
01:49:37,270 --> 01:49:35,040
previously those resistance mechanisms

2884
01:49:39,910 --> 01:49:37,280
were open to strain replacement species

2885
01:49:42,470 --> 01:49:39,920
sorting etc if you're looking at

2886
01:49:45,270 --> 01:49:42,480
evolution by by mutation in this

2887
01:49:47,589 --> 01:49:45,280
particular system it seems like

2888
01:49:50,629 --> 01:49:47,599
we don't see the evolution of resistance

2889
01:49:53,270 --> 01:49:50,639
whereas we did rapidly in a test tube

2890
01:49:54,870 --> 01:49:53,280
okay so this blank figure should be

2891
01:49:56,550 --> 01:49:54,880
pretty convincing that it does not

2892
01:49:57,589 --> 01:49:56,560
happen rapidly

2893
01:49:59,350 --> 01:49:57,599
but why

2894
01:50:00,550 --> 01:49:59,360
and so we took that same approach that i

2895
01:50:02,390 --> 01:50:00,560
just showed you where we took our

2896
01:50:04,870 --> 01:50:02,400
resistant mutants and importantly these

2897
01:50:06,950 --> 01:50:04,880
are resistant mutants that were evolved

2898
01:50:07,990 --> 01:50:06,960
in vitro because we don't find them in

2899
01:50:11,669 --> 01:50:08,000
planta

2900
01:50:13,189 --> 01:50:11,679
ask how they grow in the presence or

2901
01:50:15,830 --> 01:50:13,199
absence of phage

2902
01:50:17,990 --> 01:50:15,840
and in total contrast to the figure i

2903
01:50:21,270 --> 01:50:18,000
showed you previously from in vitro in

2904
01:50:23,510 --> 01:50:21,280
this case in the presence of phage

2905
01:50:25,430 --> 01:50:23,520
there is no selective advantage to

2906
01:50:26,310 --> 01:50:25,440
resistance

2907
01:50:28,070 --> 01:50:26,320
okay

2908
01:50:29,750 --> 01:50:28,080
so that's not to say that phages aren't

2909
01:50:31,830 --> 01:50:29,760
doing anything because you can see if

2910
01:50:35,109 --> 01:50:31,840
you just look at the susceptible mutants

2911
01:50:36,790 --> 01:50:35,119
that their growth rate is is decreased

2912
01:50:38,310 --> 01:50:36,800
in the presence of phage relative to the

2913
01:50:41,510 --> 01:50:38,320
absence if you compare the blue and the

2914
01:50:43,430 --> 01:50:41,520
green bars there so phages are killing

2915
01:50:44,709 --> 01:50:43,440
their hosts in this environment and

2916
01:50:46,870 --> 01:50:44,719
they're not killing the resistant

2917
01:50:49,270 --> 01:50:46,880
mutants but the difference here is that

2918
01:50:50,870 --> 01:50:49,280
that strength of selection is not strong

2919
01:50:52,870 --> 01:50:50,880
enough to overcome the cost of

2920
01:50:54,790 --> 01:50:52,880
resistance and we've previously

2921
01:50:55,830 --> 01:50:54,800
demonstrated costs of resistance in this

2922
01:50:57,750 --> 01:50:55,840
system

2923
01:51:01,109 --> 01:50:57,760
the majority of resistance mutations

2924
01:51:03,830 --> 01:51:01,119
happen by via changes in the lps pathway

2925
01:51:06,390 --> 01:51:03,840
and we know that lps the lps receptor

2926
01:51:08,470 --> 01:51:06,400
that these phages use to bind changes in

2927
01:51:10,229 --> 01:51:08,480
that receptor can come at huge fitness

2928
01:51:12,310 --> 01:51:10,239
costs especially in the plant

2929
01:51:16,070 --> 01:51:12,320
environment and that was work previously

2930
01:51:20,550 --> 01:51:18,470
so the takeaway from this section is

2931
01:51:23,189 --> 01:51:20,560
that bacteriophage coevolution does

2932
01:51:25,350 --> 01:51:23,199
matter but the impact of it is going to

2933
01:51:27,189 --> 01:51:25,360
vary depending on the environment and we

2934
01:51:28,950 --> 01:51:27,199
need to be a little bit cautious moving

2935
01:51:31,430 --> 01:51:28,960
from test tube experiments to making

2936
01:51:33,270 --> 01:51:31,440
predictions about the real world

2937
01:51:35,109 --> 01:51:33,280
but you will notice that there's this

2938
01:51:37,270 --> 01:51:35,119
potential juxtaposition between what

2939
01:51:39,109 --> 01:51:37,280
i've shown happens rapidly in a natural

2940
01:51:40,709 --> 01:51:39,119
system and what's happening in this more

2941
01:51:43,350 --> 01:51:40,719
controlled system and i think there

2942
01:51:45,430 --> 01:51:43,360
remains a lot of work to be done as to

2943
01:51:47,589 --> 01:51:45,440
how much of what we see in terms of

2944
01:51:49,510 --> 01:51:47,599
phage mediated selection in nature is

2945
01:51:51,990 --> 01:51:49,520
the result of mutational change within a

2946
01:51:54,550 --> 01:51:52,000
lineage versus larger ecological

2947
01:51:56,790 --> 01:51:54,560
processes

2948
01:51:58,390 --> 01:51:56,800
and so to summarize um hopefully what

2949
01:52:00,310 --> 01:51:58,400
i've been able to convince you of is if

2950
01:52:03,270 --> 01:52:00,320
we're trying to understand microbial

2951
01:52:05,030 --> 01:52:03,280
communities which as a field we are very

2952
01:52:06,310 --> 01:52:05,040
interested in at the moment

2953
01:52:09,430 --> 01:52:06,320
we know that these communities are

2954
01:52:11,350 --> 01:52:09,440
complex um in terms of diversity and

2955
01:52:13,350 --> 01:52:11,360
across space they're very highly

2956
01:52:15,189 --> 01:52:13,360
variable so individuals host different

2957
01:52:17,189 --> 01:52:15,199
microbiomes different lakes etc have

2958
01:52:19,189 --> 01:52:17,199
different microbiomes they're dynamic

2959
01:52:21,109 --> 01:52:19,199
across time and if you're thinking about

2960
01:52:23,990 --> 01:52:21,119
a host associated microbiome they're

2961
01:52:25,510 --> 01:52:24,000
critical to shaping host phenotype and

2962
01:52:26,709 --> 01:52:25,520
through the series of

2963
01:52:28,310 --> 01:52:26,719
experiments i've just shown you

2964
01:52:30,390 --> 01:52:28,320
hopefully i've made a convincing

2965
01:52:32,550 --> 01:52:30,400
argument that phages are likely to be

2966
01:52:34,629 --> 01:52:32,560
important in all of these and through

2967
01:52:37,109 --> 01:52:34,639
this coevolutionary process they're

2968
01:52:39,109 --> 01:52:37,119
likely to shape composition

2969
01:52:40,550 --> 01:52:39,119
chain by adapting to local bacteria

2970
01:52:42,870 --> 01:52:40,560
potentially driving different

2971
01:52:44,390 --> 01:52:42,880
populations apart or in some cases

2972
01:52:46,870 --> 01:52:44,400
moving them together as i showed you

2973
01:52:49,109 --> 01:52:46,880
from the tomato plants

2974
01:52:49,990 --> 01:52:49,119
drive changes in composition over time

2975
01:52:51,750 --> 01:52:50,000
and

2976
01:52:54,550 --> 01:52:51,760
as i showed you in terms of prophages in

2977
01:52:56,390 --> 01:52:54,560
particular be important in shaping

2978
01:52:58,550 --> 01:52:56,400
their bacterial host phenotype which

2979
01:53:01,109 --> 01:52:58,560
could have important implications for

2980
01:53:03,510 --> 01:53:01,119
the eukaryotic host again if it's a host

2981
01:53:05,910 --> 01:53:03,520
associated microbe

2982
01:53:08,870 --> 01:53:05,920
and with that i will thank my my group

2983
01:53:15,900 --> 01:53:08,880
the organizers of today's and tomorrow's

2984
01:53:15,910 --> 01:53:19,990
[Applause]

2985
01:53:23,750 --> 01:53:22,149
thanks for that brett that was great uh

2986
01:53:29,270 --> 01:53:23,760
i just wanted to open up if anyone had a

2987
01:53:31,910 --> 01:53:30,070
i'll

2988
01:53:33,109 --> 01:53:31,920
ask the first question again uh hybrid

2989
01:53:35,270 --> 01:53:33,119
this guy

2990
01:53:37,109 --> 01:53:35,280
uh how much

2991
01:53:39,910 --> 01:53:37,119
uh how quickly are the bacteria

2992
01:53:43,430 --> 01:53:39,920
multiplying in planta because you've got

2993
01:53:45,589 --> 01:53:43,440
a difference in speed per unit of human

2994
01:53:47,910 --> 01:53:45,599
measured time can we adjust it at all to

2995
01:53:50,229 --> 01:53:47,920
bacterial generation time oh i would

2996
01:53:51,910 --> 01:53:50,239
love to know that answer um well we we

2997
01:53:54,790 --> 01:53:51,920
can get it a little bit with our droplet

2998
01:53:56,310 --> 01:53:54,800
digital pcr now we can look at

2999
01:53:58,790 --> 01:53:56,320
growth rates

3000
01:53:59,750 --> 01:53:58,800
and it's a good question

3001
01:54:01,430 --> 01:53:59,760
you know

3002
01:54:03,589 --> 01:54:01,440
i wonder

3003
01:54:05,350 --> 01:54:03,599
we could probably mine kathy's data set

3004
01:54:06,950 --> 01:54:05,360
a bit better to get an idea of that but

3005
01:54:08,870 --> 01:54:06,960
we're still measuring generally our

3006
01:54:11,990 --> 01:54:08,880
droplet digital pcr we're measuring

3007
01:54:13,510 --> 01:54:12,000
after 24 hours 48 hours 72 hours i think

3008
01:54:14,870 --> 01:54:13,520
we need a much more fine scale

3009
01:54:17,270 --> 01:54:14,880
resolution to

3010
01:54:19,589 --> 01:54:17,280
to not also then be averaging over death

3011
01:54:21,510 --> 01:54:19,599
and so forth um

3012
01:54:24,310 --> 01:54:21,520
but it's a it's a it's a good question

3013
01:54:29,990 --> 01:54:24,320
and i think we could potentially do it

3014
01:54:35,669 --> 01:54:32,470
perfect i'll ask the next question

3015
01:54:37,990 --> 01:54:35,679
um i was going back to the tomato plants

3016
01:54:39,750 --> 01:54:38,000
and viruses on them versus viruses added

3017
01:54:41,669 --> 01:54:39,760
to them this kind of a lock thinners

3018
01:54:43,910 --> 01:54:41,679
versus a toxinous approach you know in

3019
01:54:46,149 --> 01:54:43,920
california you can go several months

3020
01:54:48,550 --> 01:54:46,159
with no rain and this idea of watering

3021
01:54:50,310 --> 01:54:48,560
and this we're watering plants so

3022
01:54:52,310 --> 01:54:50,320
if you think we're watering plants for

3023
01:54:53,910 --> 01:54:52,320
the whole summer and we're adding a a

3024
01:54:55,189 --> 01:54:53,920
certain water source

3025
01:54:57,109 --> 01:54:55,199
and then

3026
01:54:58,790 --> 01:54:57,119
they maybe get used to those phages or

3027
01:55:01,109 --> 01:54:58,800
those viruses in the water source but

3028
01:55:03,109 --> 01:55:01,119
then we'll get rainfall

3029
01:55:04,470 --> 01:55:03,119
probably from the ocean that comes in

3030
01:55:07,030 --> 01:55:04,480
and we're adding these new types of

3031
01:55:08,470 --> 01:55:07,040
viruses so do you see impacts maybe or

3032
01:55:10,790 --> 01:55:08,480
have if you thought about that maybe

3033
01:55:12,629 --> 01:55:10,800
different water sources and this idea of

3034
01:55:14,229 --> 01:55:12,639
the community switches with the season

3035
01:55:17,430 --> 01:55:14,239
because of this

3036
01:55:18,709 --> 01:55:17,440
i think it's a great question um

3037
01:55:20,310 --> 01:55:18,719
i haven't thought about it within an

3038
01:55:21,669 --> 01:55:20,320
agricultural setting to be honest

3039
01:55:23,990 --> 01:55:21,679
especially irrigation water but i think

3040
01:55:26,470 --> 01:55:24,000
that's a really nice place to look where

3041
01:55:28,709 --> 01:55:26,480
we are doing that is i mentioned briefly

3042
01:55:31,030 --> 01:55:28,719
fire blight disease we've been sampling

3043
01:55:33,350 --> 01:55:31,040
pear trees for three years now monthly

3044
01:55:35,990 --> 01:55:33,360
in berkeley and

3045
01:55:38,470 --> 01:55:36,000
we we should be able to have once we do

3046
01:55:40,149 --> 01:55:38,480
the the metaviromics of that

3047
01:55:42,470 --> 01:55:40,159
we should be able to get an idea of

3048
01:55:44,870 --> 01:55:42,480
whether we see wholesale changes in the

3049
01:55:46,950 --> 01:55:44,880
the virum that's there

3050
01:55:48,390 --> 01:55:46,960
depending on rainfall and i think that

3051
01:55:50,070 --> 01:55:48,400
would be really neat but unfortunately

3052
01:55:51,270 --> 01:55:50,080
we're probably at least a year from that

3053
01:55:52,470 --> 01:55:51,280
answer

3054
01:55:53,669 --> 01:55:52,480
but i haven't thought about it doing it

3055
01:56:05,270 --> 01:55:53,679
in an agricultural field and i think

3056
01:56:09,109 --> 01:56:06,950
um i've actually got a follow-up

3057
01:56:11,189 --> 01:56:09,119
question on that so brits um just

3058
01:56:12,950 --> 01:56:11,199
thinking about it from generalists and

3059
01:56:14,470 --> 01:56:12,960
specialist viruses

3060
01:56:16,310 --> 01:56:14,480
and so leading on from the previous

3061
01:56:18,470 --> 01:56:16,320
question to me if you've got different

3062
01:56:20,709 --> 01:56:18,480
sources

3063
01:56:23,589 --> 01:56:20,719
that the hosts

3064
01:56:25,510 --> 01:56:23,599
are susceptible to different

3065
01:56:27,830 --> 01:56:25,520
varieties of viruses they're not very

3066
01:56:29,510 --> 01:56:27,840
unique so so that means the viruses the

3067
01:56:32,870 --> 01:56:29,520
phages that are infecting them are not

3068
01:56:34,790 --> 01:56:32,880
specialists but they're more generalists

3069
01:56:37,030 --> 01:56:34,800
so again that's a huge goal of our pair

3070
01:56:38,550 --> 01:56:37,040
project is to see whether that host

3071
01:56:40,149 --> 01:56:38,560
range changes over the course of the

3072
01:56:41,430 --> 01:56:40,159
season

3073
01:56:43,109 --> 01:56:41,440
but something just occurred to me that's

3074
01:56:44,470 --> 01:56:43,119
relevant to both of these questions

3075
01:56:46,149 --> 01:56:44,480
which is that if we're thinking about

3076
01:56:47,910 --> 01:56:46,159
this dispersal in immigration and

3077
01:56:50,229 --> 01:56:47,920
turnover as a function of rain for

3078
01:56:51,669 --> 01:56:50,239
example one of the critical and i think

3079
01:56:53,109 --> 01:56:51,679
unanswered questions that i would love

3080
01:56:54,870 --> 01:56:53,119
to hear from this community if there's

3081
01:56:57,430 --> 01:56:54,880
data out there that i don't know about

3082
01:56:59,430 --> 01:56:57,440
is the relative dispersal rates in the

3083
01:57:01,109 --> 01:56:59,440
environment of phage versus bacteria

3084
01:57:03,510 --> 01:57:01,119
because i think that's critical if we're

3085
01:57:05,270 --> 01:57:03,520
looking in rain you know how much of

3086
01:57:06,790 --> 01:57:05,280
course we know pseudomonas ring a our

3087
01:57:09,750 --> 01:57:06,800
focal pathogen moves through the water

3088
01:57:11,189 --> 01:57:09,760
cycle but we know much less about

3089
01:57:12,709 --> 01:57:11,199
phage movement

3090
01:57:15,109 --> 01:57:12,719
through the water cycle and so i would

3091
01:57:18,070 --> 01:57:15,119
be very keen to if anyone knows of good

3092
01:57:19,430 --> 01:57:18,080
data sets contrasting movement of phage

3093
01:57:21,430 --> 01:57:19,440
and bacteria

3094
01:57:22,950 --> 01:57:21,440
um we might not have time now but please

3095
01:57:24,709 --> 01:57:22,960
email me if you do have that i would

3096
01:57:27,350 --> 01:57:24,719
love to have that conversation a bit

3097
01:57:31,589 --> 01:57:29,830
or in marine systems for that matter

3098
01:57:33,189 --> 01:57:31,599
let's thank brit again i think this

3099
01:57:40,790 --> 01:57:33,199
might be a great transition to rachel so

3100
01:57:45,109 --> 01:57:44,149
um hi this is rachel did you want me to

3101
01:57:47,830 --> 01:57:45,119
just

3102
01:57:49,350 --> 01:57:47,840
start and share my screen or how does

3103
01:57:51,189 --> 01:57:49,360
that go

3104
01:57:53,589 --> 01:57:51,199
yeah can you start your

3105
01:57:55,510 --> 01:57:53,599
camera first

3106
01:57:57,750 --> 01:57:55,520
um so we can see you

3107
01:57:59,589 --> 01:57:57,760
there you go

3108
01:58:01,189 --> 01:57:59,599
yeah and then um click the share on the

3109
01:58:03,350 --> 01:58:01,199
button and share your screen and we

3110
01:58:06,709 --> 01:58:03,360
should be good to go so i should have my

3111
01:58:08,629 --> 01:58:06,719
um slides in like um view mode or

3112
01:58:10,229 --> 01:58:08,639
whatever

3113
01:58:13,109 --> 01:58:10,239
okay we're not seeing your screen share

3114
01:58:14,390 --> 01:58:13,119
yet but yeah you can go to the slideshow

3115
01:58:27,750 --> 01:58:14,400
mode

3116
01:58:32,629 --> 01:58:29,830
um

3117
01:58:36,470 --> 01:58:32,639
yeah we're seeing your desktop now

3118
01:58:38,310 --> 01:58:36,480
yeah so now i have to switch to

3119
01:58:46,790 --> 01:58:38,320
yeah on top

3120
01:58:46,800 --> 01:58:51,910
i don't know why i can't um i'm sorry

3121
01:58:55,750 --> 01:58:53,510
there

3122
01:59:00,830 --> 01:58:55,760
yep

3123
01:59:05,270 --> 01:59:03,030
um um

3124
01:59:07,109 --> 01:59:05,280
okay so um i

3125
01:59:08,870 --> 01:59:07,119
sorry i haven't gotten to participate in

3126
01:59:11,270 --> 01:59:08,880
the whole thing of this workshop it

3127
01:59:13,669 --> 01:59:11,280
seems really cool and i and it's very

3128
01:59:16,070 --> 01:59:13,679
awkward for me to be presenting without

3129
01:59:17,990 --> 01:59:16,080
having anybody to talk to i assume

3130
01:59:19,990 --> 01:59:18,000
there's people out there and i'm happy

3131
01:59:22,470 --> 01:59:20,000
to take questions whenever but i know

3132
01:59:25,669 --> 01:59:22,480
that's kind of awkward in this scenario

3133
01:59:27,830 --> 01:59:25,679
so um i guess i'll just talk through

3134
01:59:30,229 --> 01:59:27,840
um the way we're looking at viruses now

3135
01:59:32,149 --> 01:59:30,239
which is a little bit different than i

3136
01:59:34,790 --> 01:59:32,159
think probably i know at least the way

3137
01:59:37,990 --> 01:59:34,800
brit was was describing the ecology and

3138
01:59:39,189 --> 01:59:38,000
evolution um and i think that it's a

3139
01:59:41,830 --> 01:59:39,199
little bit different than the way people

3140
01:59:43,350 --> 01:59:41,840
think about it in microbes normally so

3141
01:59:45,189 --> 01:59:43,360
we're thinking about

3142
01:59:47,189 --> 01:59:45,199
viral symbiosis

3143
01:59:49,750 --> 01:59:47,199
and i wanted to kind of go back all the

3144
01:59:52,149 --> 01:59:49,760
way to the beginning because i'm really

3145
01:59:54,070 --> 01:59:52,159
interested in the origin of life

3146
01:59:55,910 --> 01:59:54,080
and we were in this

3147
01:59:58,149 --> 01:59:55,920
nasa astrobiology institute that was

3148
02:00:00,550 --> 01:59:58,159
looking at the processes of the origin

3149
02:00:02,790 --> 02:00:00,560
of life so i just want to remind you a

3150
02:00:04,950 --> 02:00:02,800
couple of things about that and then put

3151
02:00:05,750 --> 02:00:04,960
viruses in that context

3152
02:00:08,310 --> 02:00:05,760
so

3153
02:00:11,350 --> 02:00:08,320
of course you know this three domain

3154
02:00:14,790 --> 02:00:11,360
tree of life that was published

3155
02:00:17,030 --> 02:00:14,800
by carl rose in 1977

3156
02:00:19,589 --> 02:00:17,040
and i'm almost you know embarrassed to

3157
02:00:23,109 --> 02:00:19,599
put it up there um again because i hope

3158
02:00:25,430 --> 02:00:23,119
we all take this um now as a as a true

3159
02:00:27,430 --> 02:00:25,440
understanding of the way

3160
02:00:29,669 --> 02:00:27,440
life emerged even if we're not sure

3161
02:00:33,430 --> 02:00:29,679
exactly how the archaean eukaryotes are

3162
02:00:35,510 --> 02:00:33,440
related um as the trees are changing but

3163
02:00:37,669 --> 02:00:35,520
uh the same year

3164
02:00:40,149 --> 02:00:37,679
he also published a second paper which

3165
02:00:42,790 --> 02:00:40,159
was on the concept of cellular evolution

3166
02:00:45,109 --> 02:00:42,800
and people know less about that work but

3167
02:00:46,950 --> 02:00:45,119
i think it's really really important it

3168
02:00:48,950 --> 02:00:46,960
was less about the

3169
02:00:51,270 --> 02:00:48,960
relationships between the organisms and

3170
02:00:53,990 --> 02:00:51,280
more about the process of evolution and

3171
02:00:57,189 --> 02:00:54,000
how that changed in tempo and mode over

3172
02:00:59,350 --> 02:00:57,199
the um course of evolution so very

3173
02:01:02,390 --> 02:00:59,360
quickly what he said was that we know

3174
02:01:04,470 --> 02:01:02,400
that there's fossils of cyanobacteria

3175
02:01:07,189 --> 02:01:04,480
and i know these dates change around but

3176
02:01:08,550 --> 02:01:07,199
it's something like 3.5 billion years

3177
02:01:11,510 --> 02:01:08,560
ago

3178
02:01:13,350 --> 02:01:11,520
and by that time then if we believe

3179
02:01:15,750 --> 02:01:13,360
those fossils and those dates we would

3180
02:01:17,910 --> 02:01:15,760
have had an entire cell that was

3181
02:01:21,270 --> 02:01:17,920
functioning and doing oxygenic

3182
02:01:23,709 --> 02:01:21,280
photosynthesis which is a long way to go

3183
02:01:27,189 --> 02:01:23,719
if the earth started in

3184
02:01:30,550 --> 02:01:27,199
4.4.5 billion years ago so in that first

3185
02:01:34,229 --> 02:01:30,560
billion years we went all the way from

3186
02:01:36,950 --> 02:01:34,239
chemistry to full cell

3187
02:01:39,910 --> 02:01:36,960
biology and oxygenic photosynthesis

3188
02:01:42,149 --> 02:01:39,920
um whereas since then really in

3189
02:01:44,629 --> 02:01:42,159
comparison we've done very little we've

3190
02:01:47,189 --> 02:01:44,639
just kind of articulated on these things

3191
02:01:49,270 --> 02:01:47,199
and we still kind of function basically

3192
02:01:52,070 --> 02:01:49,280
as cells in the same way

3193
02:01:54,229 --> 02:01:52,080
so his question here is what changed and

3194
02:01:56,470 --> 02:01:54,239
what was different about

3195
02:01:58,790 --> 02:01:56,480
the pre-cellular

3196
02:02:02,390 --> 02:01:58,800
part of life and

3197
02:02:03,830 --> 02:02:02,400
the last 3.5 billion years and his idea

3198
02:02:05,830 --> 02:02:03,840
was that there was a change in

3199
02:02:07,270 --> 02:02:05,840
evolutionary mode and he called this

3200
02:02:10,310 --> 02:02:07,280
change in evolutionary mode the

3201
02:02:11,750 --> 02:02:10,320
darwinian transition because he thought

3202
02:02:15,750 --> 02:02:11,760
one of the things that made this

3203
02:02:19,189 --> 02:02:15,760
transition happen was that um we

3204
02:02:22,070 --> 02:02:19,199
the life changed from uh the form of

3205
02:02:26,070 --> 02:02:22,080
life he calls a progenote which is

3206
02:02:28,950 --> 02:02:26,080
not a cell um to a cellular form of life

3207
02:02:33,030 --> 02:02:28,960
and this mode of um

3208
02:02:36,470 --> 02:02:33,040
of of evolution that changes from this

3209
02:02:38,870 --> 02:02:36,480
progenode state to a cellular state is

3210
02:02:41,189 --> 02:02:38,880
what he called the darwinian transition

3211
02:02:43,109 --> 02:02:41,199
so let's think about what evolution is

3212
02:02:44,629 --> 02:02:43,119
like in a prognote state where there

3213
02:02:46,709 --> 02:02:44,639
aren't cells that are defining an

3214
02:02:49,189 --> 02:02:46,719
individual

3215
02:02:51,109 --> 02:02:49,199
and the cost of that or how that changed

3216
02:02:52,870 --> 02:02:51,119
the evolutionary mode he obviously

3217
02:02:54,629 --> 02:02:52,880
thought that it slowed things down and

3218
02:02:55,589 --> 02:02:54,639
that kind of makes sense when you think

3219
02:02:58,950 --> 02:02:55,599
about

3220
02:03:02,070 --> 02:02:58,960
the way horizontal gene transfer and

3221
02:03:04,709 --> 02:03:02,080
recombination shapes um the

3222
02:03:06,790 --> 02:03:04,719
way cells evolve today so the the

3223
02:03:09,189 --> 02:03:06,800
evolutionary mode of the progenote is

3224
02:03:11,510 --> 02:03:09,199
one that he thought was was getting the

3225
02:03:12,950 --> 02:03:11,520
relationship was just trying to put

3226
02:03:15,510 --> 02:03:12,960
together the relationship between

3227
02:03:17,510 --> 02:03:15,520
genotype and phenotype so there were no

3228
02:03:20,709 --> 02:03:17,520
cells it was this kind of super

3229
02:03:22,390 --> 02:03:20,719
molecular aggregate that kind of was

3230
02:03:24,390 --> 02:03:22,400
evolving as a pool

3231
02:03:26,310 --> 02:03:24,400
and that actually in classical

3232
02:03:28,870 --> 02:03:26,320
population genetics

3233
02:03:31,030 --> 02:03:28,880
allows selection to work more quickly

3234
02:03:34,390 --> 02:03:31,040
because it can work independently on

3235
02:03:37,830 --> 02:03:34,400
single pieces of keep single components

3236
02:03:40,070 --> 02:03:37,840
and optimize them specifically for the

3237
02:03:43,430 --> 02:03:40,080
specific conditions that the

3238
02:03:45,589 --> 02:03:43,440
uh protein is evolving um in

3239
02:03:47,669 --> 02:03:45,599
but and it also allows new components to

3240
02:03:49,830 --> 02:03:47,679
come together rather freely without the

3241
02:03:52,550 --> 02:03:49,840
constraints of having to interact or be

3242
02:03:57,750 --> 02:03:52,560
linked together but it comes at a cost

3243
02:04:02,629 --> 02:04:00,629
the way selection acts and you lose

3244
02:04:03,589 --> 02:04:02,639
diversity in that process

3245
02:04:07,189 --> 02:04:03,599
and so

3246
02:04:11,350 --> 02:04:07,199
um this kind of prevents the uh specific

3247
02:04:14,629 --> 02:04:11,360
evolution of a single context specific

3248
02:04:15,990 --> 02:04:14,639
um interaction between these molecules

3249
02:04:16,870 --> 02:04:16,000
so

3250
02:04:18,870 --> 02:04:16,880
um

3251
02:04:21,430 --> 02:04:18,880
he kind of i think based some of these

3252
02:04:24,310 --> 02:04:21,440
ideas on sol spiegelman um who was

3253
02:04:27,270 --> 02:04:24,320
thinking about the origin of cells as

3254
02:04:30,470 --> 02:04:27,280
well and thinking about why chromosomes

3255
02:04:33,030 --> 02:04:30,480
kind of consolidated at this darwinian

3256
02:04:35,189 --> 02:04:33,040
um threshold and so

3257
02:04:38,550 --> 02:04:35,199
he thinks that you know these com this

3258
02:04:40,709 --> 02:04:38,560
complexity and the size of the genome

3259
02:04:43,830 --> 02:04:40,719
was increasing

3260
02:04:47,030 --> 02:04:43,840
and possibly changing into a dna genome

3261
02:04:49,030 --> 02:04:47,040
for this reason to be able to have a

3262
02:04:51,430 --> 02:04:49,040
more complexity

3263
02:04:52,790 --> 02:04:51,440
and be able to solve more complicated

3264
02:04:55,589 --> 02:04:52,800
problems

3265
02:04:57,189 --> 02:04:55,599
but putting it together again has this

3266
02:04:59,270 --> 02:04:57,199
trade-off because now you have

3267
02:05:02,229 --> 02:04:59,280
everything linked together into one

3268
02:05:04,870 --> 02:05:02,239
chromosome inside one cell and all of

3269
02:05:07,270 --> 02:05:04,880
those things being linked prevents

3270
02:05:08,629 --> 02:05:07,280
selection from independently acting on

3271
02:05:10,950 --> 02:05:08,639
anyone

3272
02:05:12,790 --> 02:05:10,960
so this may be going a little far but

3273
02:05:14,950 --> 02:05:12,800
i'm just reminding you population

3274
02:05:16,310 --> 02:05:14,960
genetics that i hope you had a long time

3275
02:05:18,950 --> 02:05:16,320
ago

3276
02:05:22,069 --> 02:05:18,960
where if you have high linkage and the

3277
02:05:24,229 --> 02:05:22,079
selection acts on a particular gene it's

3278
02:05:26,790 --> 02:05:24,239
going to act on the whole region of that

3279
02:05:27,990 --> 02:05:26,800
and in clonal organisms that's the whole

3280
02:05:30,229 --> 02:05:28,000
chromosome

3281
02:05:32,709 --> 02:05:30,239
whereas if there's little pieces and

3282
02:05:34,950 --> 02:05:32,719
aggregates that are independent

3283
02:05:37,910 --> 02:05:34,960
selection can hack act on each one of

3284
02:05:40,950 --> 02:05:37,920
them independently so it decreases the

3285
02:05:43,189 --> 02:05:40,960
efficiency of selection

3286
02:05:47,189 --> 02:05:43,199
but increases the specificity of

3287
02:05:50,709 --> 02:05:47,199
selection to put to consolidate genomes

3288
02:05:54,390 --> 02:05:50,719
in through this darwinian

3289
02:05:56,629 --> 02:05:54,400
transition okay so in that context now

3290
02:05:58,550 --> 02:05:56,639
we can start to think about viruses and

3291
02:06:01,350 --> 02:05:58,560
how what we know about the way these

3292
02:06:03,910 --> 02:06:01,360
consolidated chromosomes all together

3293
02:06:05,910 --> 02:06:03,920
are evolving and i think that we all

3294
02:06:08,390 --> 02:06:05,920
know that um

3295
02:06:09,830 --> 02:06:08,400
by by comparative genomics with many

3296
02:06:11,750 --> 02:06:09,840
different strains and population

3297
02:06:13,910 --> 02:06:11,760
genomics that

3298
02:06:16,069 --> 02:06:13,920
there are still a lot of mobile genes

3299
02:06:18,550 --> 02:06:16,079
that are moving around so we haven't

3300
02:06:21,350 --> 02:06:18,560
fully crossed this threshold into

3301
02:06:23,270 --> 02:06:21,360
completely vertical transmission

3302
02:06:25,830 --> 02:06:23,280
instead there's components of every

3303
02:06:28,870 --> 02:06:25,840
genome that are coming and going

3304
02:06:32,790 --> 02:06:28,880
that have not passed this threshold and

3305
02:06:34,709 --> 02:06:32,800
they allow selection to act efficiently

3306
02:06:37,669 --> 02:06:34,719
and more specifically on those

3307
02:06:39,830 --> 02:06:37,679
components than otherwise

3308
02:06:42,550 --> 02:06:39,840
might happen

3309
02:06:45,669 --> 02:06:42,560
now the difference here is that these

3310
02:06:48,069 --> 02:06:45,679
are independent genetic units

3311
02:06:50,310 --> 02:06:48,079
most of the time i think they're viruses

3312
02:06:52,709 --> 02:06:50,320
and other mobile elements

3313
02:06:53,750 --> 02:06:52,719
that then get kind of co-opted by their

3314
02:06:55,750 --> 02:06:53,760
host

3315
02:06:57,750 --> 02:06:55,760
and so this is where the pangenome

3316
02:06:59,430 --> 02:06:57,760
concept comes in

3317
02:07:01,109 --> 02:06:59,440
which comes from looking at many

3318
02:07:03,030 --> 02:07:01,119
different microbial

3319
02:07:05,510 --> 02:07:03,040
genomes and seeing that there's a core

3320
02:07:08,149 --> 02:07:05,520
genome that evolves as you would think

3321
02:07:10,310 --> 02:07:08,159
it does by the rules of of population

3322
02:07:12,069 --> 02:07:10,320
genetics and the modern synthesis and

3323
02:07:14,149 --> 02:07:12,079
then there's this variable genome which

3324
02:07:15,510 --> 02:07:14,159
is a set of genes that come and go that

3325
02:07:16,709 --> 02:07:15,520
we're still trying to figure out the

3326
02:07:18,709 --> 02:07:16,719
rules on

3327
02:07:21,350 --> 02:07:18,719
and those are important genes that

3328
02:07:23,830 --> 02:07:21,360
encode really important traits we know

3329
02:07:25,910 --> 02:07:23,840
this mostly in pathogens where we've

3330
02:07:28,310 --> 02:07:25,920
seen toxins virulence factors and

3331
02:07:30,310 --> 02:07:28,320
antibiotic resistance moving around and

3332
02:07:32,550 --> 02:07:30,320
spreading on these

3333
02:07:34,310 --> 02:07:32,560
highly mobile genes

3334
02:07:35,750 --> 02:07:34,320
that makes sense in the context of

3335
02:07:38,069 --> 02:07:35,760
selection these things are more

3336
02:07:39,510 --> 02:07:38,079
efficiently under selection if they're

3337
02:07:43,109 --> 02:07:39,520
highly mobile

3338
02:07:45,830 --> 02:07:43,119
so um but if they're their own lifestyle

3339
02:07:48,149 --> 02:07:45,840
their own fitness viruses then we have

3340
02:07:50,790 --> 02:07:48,159
to start thinking about the interaction

3341
02:07:52,950 --> 02:07:50,800
between the chromosome and viruses as a

3342
02:07:56,950 --> 02:07:52,960
symbiosis and how they evolve

3343
02:07:57,669 --> 02:07:56,960
independently and separately um to um

3344
02:08:00,229 --> 02:07:57,679
to

3345
02:08:03,030 --> 02:08:00,239
in this mode of evolution that i think

3346
02:08:04,229 --> 02:08:03,040
is kind of beyond the darwinian

3347
02:08:06,310 --> 02:08:04,239
transition

3348
02:08:08,390 --> 02:08:06,320
that brings us into this more mobile

3349
02:08:10,149 --> 02:08:08,400
world

3350
02:08:12,310 --> 02:08:10,159
so what are the evolutionary rules we

3351
02:08:14,149 --> 02:08:12,320
need to start looking at um

3352
02:08:16,790 --> 02:08:14,159
at the different types of viruses there

3353
02:08:19,669 --> 02:08:16,800
are and i know that viruses are very

3354
02:08:20,950 --> 02:08:19,679
famous for their antagonistic

3355
02:08:24,629 --> 02:08:20,960
effects on

3356
02:08:27,189 --> 02:08:24,639
on communities and populations and

3357
02:08:29,189 --> 02:08:27,199
they certainly are changing dynamics and

3358
02:08:31,350 --> 02:08:29,199
microbiomes and and

3359
02:08:34,149 --> 02:08:31,360
um are really

3360
02:08:36,149 --> 02:08:34,159
important in that way but i think what's

3361
02:08:38,550 --> 02:08:36,159
often missed is the other forms of

3362
02:08:41,270 --> 02:08:38,560
viruses the ones that are latent that

3363
02:08:43,430 --> 02:08:41,280
are in the chromosome as pro viruses and

3364
02:08:45,990 --> 02:08:43,440
are being transmitted from generation

3365
02:08:48,310 --> 02:08:46,000
disgeneration vertically and co-evolving

3366
02:08:50,229 --> 02:08:48,320
with their host chromosome background

3367
02:08:53,189 --> 02:08:50,239
and then chronic viruses like the one

3368
02:08:55,589 --> 02:08:53,199
i'm going to talk about which like ssv

3369
02:08:59,350 --> 02:08:55,599
which doesn't kill its host and kill its

3370
02:09:01,589 --> 02:08:59,360
host as it um as it is transmitted but

3371
02:09:04,470 --> 02:09:01,599
buds from the host and so that allows

3372
02:09:06,709 --> 02:09:04,480
the symbiosis to possibly evolve towards

3373
02:09:09,589 --> 02:09:06,719
more of a mutualism between the virus

3374
02:09:11,830 --> 02:09:09,599
and the host chromosome

3375
02:09:13,830 --> 02:09:11,840
so i think we know very little about

3376
02:09:15,589 --> 02:09:13,840
viruses in general and their different

3377
02:09:18,629 --> 02:09:15,599
lifestyles because they're really hard

3378
02:09:20,550 --> 02:09:18,639
to study on a kind of a population level

3379
02:09:22,629 --> 02:09:20,560
and one of the breakthroughs that is

3380
02:09:25,589 --> 02:09:22,639
allowing us to do that is crispr cast

3381
02:09:27,910 --> 02:09:25,599
immunity so i don't need to talk about

3382
02:09:30,709 --> 02:09:27,920
the specifics of crispr cast immunity

3383
02:09:32,790 --> 02:09:30,719
and the elegant immune system that that

3384
02:09:34,550 --> 02:09:32,800
has evolved because i'm sure you all

3385
02:09:36,790 --> 02:09:34,560
know about that but i just want to

3386
02:09:38,870 --> 02:09:36,800
remind you that this also provides a

3387
02:09:41,109 --> 02:09:38,880
tool for evolutionary biologists to keep

3388
02:09:43,109 --> 02:09:41,119
track of virus host interactions over

3389
02:09:47,109 --> 02:09:43,119
time so the

3390
02:09:49,589 --> 02:09:47,119
in the process of acquiring immunity to

3391
02:09:53,189 --> 02:09:49,599
viruses through crisprs

3392
02:09:55,270 --> 02:09:53,199
um bacterial and archaeal cells add new

3393
02:09:57,910 --> 02:09:55,280
spacers onto their

3394
02:10:00,790 --> 02:09:57,920
on into their genome add a new component

3395
02:10:03,270 --> 02:10:00,800
a small component sequence piece of the

3396
02:10:05,830 --> 02:10:03,280
genome of the virus into their own

3397
02:10:07,430 --> 02:10:05,840
chromosome they record a memory of that

3398
02:10:10,310 --> 02:10:07,440
interaction

3399
02:10:12,629 --> 02:10:10,320
in the crispr cast immunity and that

3400
02:10:14,229 --> 02:10:12,639
allows us to look back at populations

3401
02:10:15,990 --> 02:10:14,239
and try to figure out what kind of

3402
02:10:18,470 --> 02:10:16,000
interactions are happening between

3403
02:10:20,790 --> 02:10:18,480
viruses and hosts and how this might be

3404
02:10:22,709 --> 02:10:20,800
impacting their evolution over time

3405
02:10:24,790 --> 02:10:22,719
because of the population signatures

3406
02:10:27,030 --> 02:10:24,800
that are in the crispr arrays or in the

3407
02:10:28,390 --> 02:10:27,040
immune diversity so we've been using

3408
02:10:30,149 --> 02:10:28,400
immune diversity

3409
02:10:32,149 --> 02:10:30,159
to link um

3410
02:10:34,550 --> 02:10:32,159
microbial cells to

3411
02:10:36,390 --> 02:10:34,560
their viruses and also to try to

3412
02:10:38,790 --> 02:10:36,400
understand how their interactions are

3413
02:10:41,669 --> 02:10:38,800
happening in natural populations

3414
02:10:44,069 --> 02:10:41,679
because this is really hard to do

3415
02:10:46,470 --> 02:10:44,079
so now i was just going to give a little

3416
02:10:49,109 --> 02:10:46,480
example of what we've learned by doing

3417
02:10:51,750 --> 02:10:49,119
this and how this uncovers aspects of

3418
02:10:53,350 --> 02:10:51,760
symbiosis that you might not um have

3419
02:10:55,109 --> 02:10:53,360
thought about

3420
02:10:57,350 --> 02:10:55,119
or that we that one might not think

3421
02:11:00,229 --> 02:10:57,360
about in any system

3422
02:11:03,430 --> 02:11:00,239
and that is to look at this population

3423
02:11:06,470 --> 02:11:03,440
of cell pholubus icelandicus um cell

3424
02:11:10,790 --> 02:11:06,480
pholipus is a g is a lives in geothermal

3425
02:11:11,830 --> 02:11:10,800
hot springs in meta populations and it

3426
02:11:15,510 --> 02:11:11,840
um

3427
02:11:17,750 --> 02:11:15,520
is a hyperthermophilic chronarchia

3428
02:11:18,950 --> 02:11:17,760
and acetophile

3429
02:11:20,629 --> 02:11:18,960
um and

3430
02:11:22,870 --> 02:11:20,639
because it evolves in these meta

3431
02:11:25,830 --> 02:11:22,880
populations we're looking at dynamics

3432
02:11:28,790 --> 02:11:25,840
across this like nested scale which is

3433
02:11:31,510 --> 02:11:28,800
how the virus interacts with the host

3434
02:11:33,430 --> 02:11:31,520
with its host with sulfolobis how that

3435
02:11:36,149 --> 02:11:33,440
interaction changes interactions with

3436
02:11:38,229 --> 02:11:36,159
other organisms in the hot spring and i

3437
02:11:40,229 --> 02:11:38,239
call this an island because it's very

3438
02:11:42,069 --> 02:11:40,239
clearly defined and so we can link

3439
02:11:44,790 --> 02:11:42,079
dynamics that are happening between

3440
02:11:48,550 --> 02:11:44,800
virus and host to this one relatively

3441
02:11:50,950 --> 02:11:48,560
well-defined ecosystem and compare the

3442
02:11:52,629 --> 02:11:50,960
different ecosystems to each other and

3443
02:11:54,950 --> 02:11:52,639
to understand the dynamics that are

3444
02:11:56,310 --> 02:11:54,960
specific within and between them and

3445
02:11:58,629 --> 02:11:56,320
then we're putting that into kind of a

3446
02:12:01,030 --> 02:11:58,639
whole big global context

3447
02:12:02,790 --> 02:12:01,040
although we don't see migration between

3448
02:12:05,990 --> 02:12:02,800
these different locations that we've

3449
02:12:07,510 --> 02:12:06,000
sampled for viruses or for hosts so

3450
02:12:09,830 --> 02:12:07,520
we've looked really closely at two

3451
02:12:11,669 --> 02:12:09,840
populations of sofolobis

3452
02:12:14,069 --> 02:12:11,679
one from yellowstone national park and

3453
02:12:15,830 --> 02:12:14,079
one from kamchatka russia

3454
02:12:18,149 --> 02:12:15,840
and

3455
02:12:19,990 --> 02:12:18,159
kind of looked at the dynamics that are

3456
02:12:23,030 --> 02:12:20,000
happening in those populations in their

3457
02:12:25,189 --> 02:12:23,040
genomes and what it told us was that the

3458
02:12:28,629 --> 02:12:25,199
dynamics are basically

3459
02:12:29,510 --> 02:12:28,639
driven by viruses and mobile elements um

3460
02:12:40,470 --> 02:12:29,520
the

3461
02:12:42,390 --> 02:12:40,480
factors like crisprs that

3462
02:12:45,030 --> 02:12:42,400
caught that mediate the interaction

3463
02:12:46,390 --> 02:12:45,040
between viruses and their hosts so we've

3464
02:12:49,669 --> 02:12:46,400
isolated

3465
02:12:51,669 --> 02:12:49,679
a 10 year time series of hosts and

3466
02:12:56,149 --> 02:12:51,679
viruses from these two independent

3467
02:12:57,990 --> 02:12:56,159
populations um and you can see here that

3468
02:12:59,830 --> 02:12:58,000
they're different between the different

3469
02:13:03,030 --> 02:12:59,840
populations so

3470
02:13:05,430 --> 02:13:03,040
in yellowstone we find mostly sirvs

3471
02:13:07,350 --> 02:13:05,440
which are lytic viruses while we also

3472
02:13:09,910 --> 02:13:07,360
find chronic

3473
02:13:11,669 --> 02:13:09,920
ssvs as well but we don't find them

3474
02:13:13,669 --> 02:13:11,679
plaquing as much and we find them

3475
02:13:16,870 --> 02:13:13,679
integrated into the chromosome in

3476
02:13:19,990 --> 02:13:16,880
kamtaka we find ssvs that that cause

3477
02:13:21,830 --> 02:13:20,000
plaques and no sirvs but we find a

3478
02:13:23,990 --> 02:13:21,840
couple other lytic viruses that we're

3479
02:13:27,589 --> 02:13:24,000
working on characterizing so we have the

3480
02:13:31,750 --> 02:13:27,599
same interaction between a single um

3481
02:13:34,229 --> 02:13:31,760
host type so the lubus type and

3482
02:13:36,629 --> 02:13:34,239
the same virus and two kind of different

3483
02:13:38,870 --> 02:13:36,639
ecosystems with other viruses around

3484
02:13:40,550 --> 02:13:38,880
them so we're trying to understand how

3485
02:13:44,550 --> 02:13:40,560
the co-evolution between the chronic

3486
02:13:46,229 --> 02:13:44,560
virus and its um sofalopus host is

3487
02:13:47,669 --> 02:13:46,239
changing in these different viral

3488
02:13:51,990 --> 02:13:47,679
contexts

3489
02:13:53,990 --> 02:13:52,000
okay so um lots of years of work by um

3490
02:13:55,990 --> 02:13:54,000
but mostly not done by me have

3491
02:13:59,189 --> 02:13:56,000
characterized the interactions between

3492
02:14:01,910 --> 02:13:59,199
sulfolobis and sirv

3493
02:14:03,270 --> 02:14:01,920
and also between cell pholubus endostate

3494
02:14:07,189 --> 02:14:03,280
virus and

3495
02:14:10,310 --> 02:14:07,199
um and sulfolubus and um

3496
02:14:12,629 --> 02:14:10,320
we know that this sirv is lytic it has

3497
02:14:15,910 --> 02:14:12,639
this amazing pyramids that cause that

3498
02:14:19,589 --> 02:14:15,920
cause the cells to lyse whereas uh so

3499
02:14:21,830 --> 02:14:19,599
ssv is a budding virus that is chronic

3500
02:14:23,669 --> 02:14:21,840
um we know that there are globally that

3501
02:14:25,990 --> 02:14:23,679
both the host and the viruses are

3502
02:14:27,910 --> 02:14:26,000
globally isolated so there's specific

3503
02:14:29,350 --> 02:14:27,920
genotypes income chaka that are

3504
02:14:31,669 --> 02:14:29,360
different from the ones that are in

3505
02:14:33,910 --> 02:14:31,679
yellowstone suggesting there might be

3506
02:14:36,310 --> 02:14:33,920
local adaptation between hosts and

3507
02:14:39,830 --> 02:14:36,320
viruses in these contexts and we've

3508
02:14:42,069 --> 02:14:39,840
looked most closely at the ssv and

3509
02:14:44,069 --> 02:14:42,079
islandic sulfur libous icelandicus

3510
02:14:46,950 --> 02:14:44,079
interaction in

3511
02:14:49,910 --> 02:14:46,960
kanchaka russia which is a large

3512
02:14:52,310 --> 02:14:49,920
population that's well mixed and pretty

3513
02:14:56,149 --> 02:14:52,320
stable over time meaning we've gone

3514
02:14:59,189 --> 02:14:56,159
there in 2000 and 2010 and seen the same

3515
02:15:01,990 --> 02:14:59,199
level of crispr diversity

3516
02:15:03,910 --> 02:15:02,000
main and virus diversity maintained over

3517
02:15:07,430 --> 02:15:03,920
time

3518
02:15:10,149 --> 02:15:07,440
and the maintenance of that large

3519
02:15:12,149 --> 02:15:10,159
large diversity of crispr alleles tells

3520
02:15:14,470 --> 02:15:12,159
us that there's some kind there's not

3521
02:15:17,109 --> 02:15:14,480
like selective sweeps of viruses that

3522
02:15:19,189 --> 02:15:17,119
are happening in these populations that

3523
02:15:20,790 --> 02:15:19,199
are clearing diversity at least immune

3524
02:15:23,990 --> 02:15:20,800
diversity out

3525
02:15:25,830 --> 02:15:24,000
so that's an interesting dynamic that is

3526
02:15:28,550 --> 02:15:25,840
i think we think is conferred by

3527
02:15:31,990 --> 02:15:28,560
crispers so the crispers kind of

3528
02:15:35,030 --> 02:15:32,000
influence allow this stable diversity in

3529
02:15:36,870 --> 02:15:35,040
crispr and the hosts um to evolve and

3530
02:15:38,870 --> 02:15:36,880
we've looked very

3531
02:15:40,629 --> 02:15:38,880
closely at this using modeling

3532
02:15:45,030 --> 02:15:40,639
approaches

3533
02:15:47,189 --> 02:15:45,040
to identify what aspects of the system

3534
02:15:50,069 --> 02:15:47,199
might allow it to

3535
02:15:51,589 --> 02:15:50,079
evolve this diversity and where if we

3536
02:15:54,390 --> 02:15:51,599
don't have this diversity what the

3537
02:15:55,510 --> 02:15:54,400
impact on the host and virus population

3538
02:15:56,709 --> 02:15:55,520
are

3539
02:15:59,109 --> 02:15:56,719
and so

3540
02:16:00,790 --> 02:15:59,119
this is an example an old example now we

3541
02:16:02,709 --> 02:16:00,800
have many more

3542
02:16:05,270 --> 02:16:02,719
complex examples that we've looked at

3543
02:16:08,149 --> 02:16:05,280
more closely now but

3544
02:16:10,470 --> 02:16:08,159
it's a simulation showing that this kind

3545
02:16:12,950 --> 02:16:10,480
of diversity can persist you can see

3546
02:16:15,350 --> 02:16:12,960
there's many colors of host in some of

3547
02:16:18,470 --> 02:16:15,360
these peaks and those colors mean that

3548
02:16:20,950 --> 02:16:18,480
you have many different crispr alleles

3549
02:16:23,830 --> 02:16:20,960
coexisting in a single population and

3550
02:16:26,629 --> 02:16:23,840
they all match the same virus but in

3551
02:16:29,270 --> 02:16:26,639
different ways so it's this the idea

3552
02:16:30,470 --> 02:16:29,280
that you can have a one to many one

3553
02:16:33,349 --> 02:16:30,480
viruses

3554
02:16:35,429 --> 02:16:33,359
virus matches many different immune

3555
02:16:38,950 --> 02:16:35,439
alleles that

3556
02:16:40,150 --> 02:16:38,960
controls the dynamics of this system

3557
02:16:41,910 --> 02:16:40,160
and so we've looked at what those

3558
02:16:43,910 --> 02:16:41,920
dynamics are and we see that when

3559
02:16:46,790 --> 02:16:43,920
there's a high diversity or what we call

3560
02:16:47,589 --> 02:16:46,800
distributed immunity the viruses are

3561
02:16:50,389 --> 02:16:47,599
have

3562
02:16:52,309 --> 02:16:50,399
difficulty persisting and

3563
02:16:54,950 --> 02:16:52,319
go extinct in the population probably

3564
02:16:57,830 --> 02:16:54,960
because they're at very low numbers

3565
02:17:00,389 --> 02:16:57,840
because they have to find a host and so

3566
02:17:01,990 --> 02:17:00,399
we see this in kamchatka

3567
02:17:04,629 --> 02:17:02,000
we see that there's

3568
02:17:07,349 --> 02:17:04,639
these ssvs that are persisting and yet

3569
02:17:10,950 --> 02:17:07,359
we see high distributed immunity to this

3570
02:17:13,190 --> 02:17:10,960
virus in this population and we don't

3571
02:17:14,389 --> 02:17:13,200
really were asked and we were asking how

3572
02:17:16,389 --> 02:17:14,399
this could be

3573
02:17:18,629 --> 02:17:16,399
because the virus shouldn't be able to

3574
02:17:20,309 --> 02:17:18,639
survive and persist in an environment

3575
02:17:23,190 --> 02:17:20,319
where there's this

3576
02:17:25,270 --> 02:17:23,200
really diversified crispr cast immunity

3577
02:17:27,429 --> 02:17:25,280
so we've calculated population

3578
02:17:28,870 --> 02:17:27,439
distributed immunity in the different

3579
02:17:31,270 --> 02:17:28,880
populations that we've looked at

3580
02:17:33,750 --> 02:17:31,280
relative to ssv and seen that it's

3581
02:17:36,070 --> 02:17:33,760
pretty high and that if you use these

3582
02:17:38,709 --> 02:17:36,080
calculations to try to predict whether

3583
02:17:41,349 --> 02:17:38,719
the virus should persist it's very

3584
02:17:44,790 --> 02:17:41,359
unlikely to invade and persist in this

3585
02:17:49,750 --> 02:17:44,800
ecosystem it's just really hard for any

3586
02:17:51,669 --> 02:17:49,760
ssv to find a host it can infect

3587
02:17:56,309 --> 02:17:51,679
so we tried to look at this in the lab

3588
02:17:57,349 --> 02:17:56,319
we took ssv the ssv9 which can isolated

3589
02:18:06,709 --> 02:17:57,359
and

3590
02:18:09,509 --> 02:18:06,719
establish a chronic infection in the lab

3591
02:18:11,270 --> 02:18:09,519
and we can see that the infected cells

3592
02:18:14,309 --> 02:18:11,280
grow as you would predict with a chronic

3593
02:18:16,309 --> 02:18:14,319
virus and produce viruses over time but

3594
02:18:18,549 --> 02:18:16,319
also we've been able to show that crispr

3595
02:18:20,469 --> 02:18:18,559
immunity works against this virus by

3596
02:18:22,870 --> 02:18:20,479
genetically engineering the system to

3597
02:18:26,070 --> 02:18:22,880
knock out crisprs and so that only in

3598
02:18:28,549 --> 02:18:26,080
the crispr knockouts can this virus

3599
02:18:30,549 --> 02:18:28,559
persist so there is this dynamic where

3600
02:18:33,190 --> 02:18:30,559
crisprs recognize

3601
02:18:35,750 --> 02:18:33,200
ssv and yet ssv persists in the

3602
02:18:37,589 --> 02:18:35,760
population so we had this question of

3603
02:18:39,669 --> 02:18:37,599
how this can happen and we tested this

3604
02:18:42,469 --> 02:18:39,679
question by

3605
02:18:45,429 --> 02:18:42,479
competing an infected strain against an

3606
02:18:46,870 --> 02:18:45,439
immune strain in the lab and this is

3607
02:18:49,349 --> 02:18:46,880
where we uncovered something that we

3608
02:18:52,709 --> 02:18:49,359
were kind of surprised to find

3609
02:18:55,110 --> 02:18:52,719
the ssv infection has a small cost to

3610
02:18:57,190 --> 02:18:55,120
the host so the persistent chronic

3611
02:18:59,509 --> 02:18:57,200
infection has a small cost to the host

3612
02:19:02,549 --> 02:18:59,519
we haven't been able to measure a cost

3613
02:19:04,709 --> 02:19:02,559
in the um of the immunity

3614
02:19:06,389 --> 02:19:04,719
but when we put the two cells together

3615
02:19:09,030 --> 02:19:06,399
the infected strain

3616
02:19:10,870 --> 02:19:09,040
wins every time so the top graph here

3617
02:19:14,230 --> 02:19:10,880
you see the competition between an

3618
02:19:15,750 --> 02:19:14,240
immune strain and an uninfected um

3619
02:19:18,070 --> 02:19:15,760
strain of

3620
02:19:20,629 --> 02:19:18,080
sulfolopus and you can see that they

3621
02:19:23,030 --> 02:19:20,639
they persist over the time scale that we

3622
02:19:25,750 --> 02:19:23,040
were looking at whereas if you put the

3623
02:19:27,990 --> 02:19:25,760
same background infected strain and

3624
02:19:30,870 --> 02:19:28,000
compete it with an immune strain the

3625
02:19:33,429 --> 02:19:30,880
infected strain wins and actually kills

3626
02:19:34,709 --> 02:19:33,439
off the rest of the

3627
02:19:37,669 --> 02:19:34,719
immune

3628
02:19:39,990 --> 02:19:37,679
and uninfected cells

3629
02:19:42,709 --> 02:19:40,000
so we've looked at this as

3630
02:19:45,750 --> 02:19:42,719
we think this is a mutualism it allows a

3631
02:19:48,070 --> 02:19:45,760
host to invade even when rare the host

3632
02:19:50,389 --> 02:19:48,080
cell if it's carrying a virus it can

3633
02:19:52,070 --> 02:19:50,399
invade a new population by killing off

3634
02:19:55,030 --> 02:19:52,080
competitors whether or not they're

3635
02:19:57,110 --> 02:19:55,040
immune and that helps the host and it

3636
02:19:58,790 --> 02:19:57,120
helps the virus because the virus

3637
02:20:00,790 --> 02:19:58,800
probably wouldn't be able to find any

3638
02:20:03,990 --> 02:20:00,800
hosts in that

3639
02:20:07,990 --> 02:20:04,000
very diverse crispr population

3640
02:20:10,550 --> 02:20:08,000
so we have this um idea that the chronic

3641
02:20:14,230 --> 02:20:10,560
virus has turned into this mutualist

3642
02:20:17,030 --> 02:20:14,240
conferring a very adaptive trait in a

3643
02:20:19,349 --> 02:20:17,040
competitive trait to the host which is

3644
02:20:22,230 --> 02:20:19,359
killing its competitors and in the

3645
02:20:26,469 --> 02:20:22,240
meanwhile also um

3646
02:20:28,790 --> 02:20:26,479
establishing its its own fitness um in a

3647
02:20:30,389 --> 02:20:28,800
a population that has very few

3648
02:20:34,230 --> 02:20:30,399
susceptible hosts

3649
02:20:37,510 --> 02:20:34,240
um so this is just an example i i it's

3650
02:20:39,670 --> 02:20:37,520
you know an idiosyncrasy perhaps but i

3651
02:20:42,309 --> 02:20:39,680
think it shows how

3652
02:20:44,710 --> 02:20:42,319
the virus host interaction can evolve

3653
02:20:47,429 --> 02:20:44,720
new traits for the host

3654
02:20:50,870 --> 02:20:47,439
that change its fitness in the in a

3655
02:20:52,790 --> 02:20:50,880
population and that is the kind of

3656
02:20:54,389 --> 02:20:52,800
selection we're talking about when we're

3657
02:20:56,950 --> 02:20:54,399
talking about

3658
02:20:58,630 --> 02:20:56,960
moving genes around and sometimes virus

3659
02:20:59,670 --> 02:20:58,640
infection really changes the traits of

3660
02:21:01,590 --> 02:20:59,680
the host

3661
02:21:03,590 --> 02:21:01,600
as it's evolving through

3662
02:21:06,389 --> 02:21:03,600
evolutionary time

3663
02:21:08,469 --> 02:21:06,399
so just don't forget i guess it's not it

3664
02:21:10,630 --> 02:21:08,479
goes without saying here that this these

3665
02:21:12,870 --> 02:21:10,640
types of interactions are happening

3666
02:21:16,870 --> 02:21:12,880
everywhere all the time

3667
02:21:20,550 --> 02:21:16,880
and maybe they're compensating for this

3668
02:21:23,990 --> 02:21:20,560
loss of flexibility that came

3669
02:21:26,630 --> 02:21:24,000
with the darwinian transition where we

3670
02:21:29,050 --> 02:21:26,640
transitioned to an individual cellular

3671
02:21:30,150 --> 02:21:29,060
vertical mode of evolution

3672
02:21:32,389 --> 02:21:30,160
[Music]

3673
02:21:33,270 --> 02:21:32,399
um so this is my

3674
02:21:35,990 --> 02:21:33,280
uh

3675
02:21:37,750 --> 02:21:36,000
lab the i chose two

3676
02:21:40,870 --> 02:21:37,760
different pictures that are actually out

3677
02:21:43,349 --> 02:21:40,880
of date now but because the work has has

3678
02:21:44,950 --> 02:21:43,359
been going forward through time

3679
02:21:46,790 --> 02:21:44,960
to highlight the people that actually

3680
02:21:48,790 --> 02:21:46,800
did the work

3681
02:21:52,550 --> 02:21:48,800
in the top picture

3682
02:21:54,550 --> 02:21:52,560
maria bautista really isolated the ssv

3683
02:21:55,910 --> 02:21:54,560
and made it tractable to work with in

3684
02:21:59,510 --> 02:21:55,920
the lab

3685
02:22:00,870 --> 02:21:59,520
in our model system changing did all the

3686
02:22:04,309 --> 02:22:00,880
genetics

3687
02:22:08,070 --> 02:22:04,319
that we needed to test crispr function

3688
02:22:10,469 --> 02:22:08,080
and the and samantha dwarf is has been

3689
02:22:13,110 --> 02:22:10,479
working on the interaction between

3690
02:22:14,710 --> 02:22:13,120
infected and uninfected cells

3691
02:22:17,670 --> 02:22:14,720
and we are

3692
02:22:19,750 --> 02:22:17,680
very collaborative with lots of labs all

3693
02:22:22,389 --> 02:22:19,760
around the world and that's really

3694
02:22:23,670 --> 02:22:22,399
important to note especially on this

3695
02:22:29,030 --> 02:22:23,680
work

3696
02:22:31,670 --> 02:22:29,040
the modeling and mark young

3697
02:22:34,230 --> 02:22:31,680
to do the virus isolation

3698
02:22:36,630 --> 02:22:34,240
and we're now working on new models with

3699
02:22:38,150 --> 02:22:36,640
mercedes pascal at the university of

3700
02:22:40,309 --> 02:22:38,160
chicago

3701
02:22:45,290 --> 02:22:40,319
and so i'd love to have any questions if

3702
02:22:45,300 --> 02:22:50,469
[Applause]

3703
02:22:56,070 --> 02:22:52,070
i guess let's open it up for questions

3704
02:22:56,080 --> 02:23:04,950
i have far too many but i'll wait

3705
02:23:10,469 --> 02:23:06,790
well maybe i'll start with one just uh

3706
02:23:12,710 --> 02:23:10,479
to fire things off um i do the killer

3707
02:23:14,070 --> 02:23:12,720
killer archaeas or the sharkayas i saw

3708
02:23:14,950 --> 02:23:14,080
your nice little image there in the

3709
02:23:18,389 --> 02:23:14,960
corner

3710
02:23:20,790 --> 02:23:18,399
um do you think that the

3711
02:23:23,030 --> 02:23:20,800
um this killer effect might also have

3712
02:23:25,670 --> 02:23:23,040
something to do with what maria found

3713
02:23:27,510 --> 02:23:25,680
again with the ssv9

3714
02:23:29,830 --> 02:23:27,520
and the

3715
02:23:31,349 --> 02:23:29,840
um dormancy effect do you think there

3716
02:23:34,790 --> 02:23:31,359
might be something there do you have any

3717
02:23:37,670 --> 02:23:34,800
ideas what might be going on there

3718
02:23:40,550 --> 02:23:37,680
yes and we're working on this um it is

3719
02:23:42,389 --> 02:23:40,560
the same we've identified the killer as

3720
02:23:44,870 --> 02:23:42,399
a toxin

3721
02:23:48,710 --> 02:23:44,880
it's a protein that's

3722
02:23:50,309 --> 02:23:48,720
produced by the cells exogenous

3723
02:23:54,630 --> 02:23:50,319
it

3724
02:23:59,190 --> 02:23:54,640
washed away

3725
02:24:00,550 --> 02:23:59,200
and persists in the environment then the

3726
02:24:04,230 --> 02:24:00,560
cells die

3727
02:24:06,710 --> 02:24:04,240
so i think um what the fact that she was

3728
02:24:07,830 --> 02:24:06,720
seeing with dormancy was that she would

3729
02:24:09,670 --> 02:24:07,840
um

3730
02:24:12,230 --> 02:24:09,680
she would challenge the cells with the

3731
02:24:13,190 --> 02:24:12,240
supernatant presumably with the toxin in

3732
02:24:18,070 --> 02:24:13,200
it

3733
02:24:21,030 --> 02:24:18,080
and so the dormancy was a reaction to

3734
02:24:22,870 --> 02:24:21,040
that um to seeing that toxin and then

3735
02:24:25,670 --> 02:24:22,880
being released from whatever effect it

3736
02:24:28,469 --> 02:24:25,680
was we're working on what happens in the

3737
02:24:31,190 --> 02:24:28,479
cell in response to this toxin and why

3738
02:24:33,270 --> 02:24:31,200
the infected cells don't get killed by

3739
02:24:34,870 --> 02:24:33,280
the toxin themselves and are resistant

3740
02:24:47,990 --> 02:24:34,880
to it

3741
02:24:51,750 --> 02:24:49,590
so if no one else will i'll keep going

3742
02:24:53,270 --> 02:24:51,760
on this too so um there as you well know

3743
02:24:55,349 --> 02:24:53,280
there are you know toxin antitoxin

3744
02:24:56,630 --> 02:24:55,359
systems also in in sulphur lowest but

3745
02:24:58,550 --> 02:24:56,640
many other organisms you think this is a

3746
02:25:00,870 --> 02:24:58,560
more generalizable thing you can start

3747
02:25:01,990 --> 02:25:00,880
thinking about toxin eddy toxins

3748
02:25:03,429 --> 02:25:02,000
as well

3749
02:25:05,190 --> 02:25:03,439
in these sort of you know not

3750
02:25:06,950 --> 02:25:05,200
necessarily killer archaea but you know

3751
02:25:07,830 --> 02:25:06,960
killer bacteria killer other kinds of

3752
02:25:10,469 --> 02:25:07,840
things

3753
02:25:12,950 --> 02:25:10,479
sure and i also think that um it's

3754
02:25:15,510 --> 02:25:12,960
actually good so one of the puzzling

3755
02:25:16,710 --> 02:25:15,520
pieces for a long time press was why

3756
02:25:18,630 --> 02:25:16,720
would uh

3757
02:25:21,670 --> 02:25:18,640
a virus want to kill

3758
02:25:24,150 --> 02:25:21,680
possible susceptible new hosts

3759
02:25:26,630 --> 02:25:24,160
and i think that the ant we think now

3760
02:25:27,830 --> 02:25:26,640
that the anti-toxin must be encoded on

3761
02:25:33,190 --> 02:25:27,840
the virus

3762
02:25:34,790 --> 02:25:33,200
n is not recognized by immunity then

3763
02:25:36,950 --> 02:25:34,800
those hosts live

3764
02:25:38,710 --> 02:25:36,960
so it's kind of a way of the virus

3765
02:25:41,349 --> 02:25:38,720
screening through

3766
02:25:44,389 --> 02:25:41,359
immune cells because you have to it's

3767
02:25:46,469 --> 02:25:44,399
like a addiction system but exogenous

3768
02:25:48,710 --> 02:25:46,479
right so you have to get infected in

3769
02:25:50,870 --> 02:25:48,720
order to resist the toxin

3770
02:25:53,510 --> 02:25:50,880
um which i think is really interesting

3771
02:25:55,270 --> 02:25:53,520
and seems pretty powerful so i would be

3772
02:25:57,349 --> 02:25:55,280
surprised if it hadn't

3773
02:26:07,590 --> 02:25:57,359
evolved elsewhere

3774
02:26:12,389 --> 02:26:09,510
i could keep asking questions about this

3775
02:26:15,590 --> 02:26:12,399
for ages as you know i'm a bit of a

3776
02:26:19,990 --> 02:26:17,270
um

3777
02:26:21,910 --> 02:26:20,000
in in the interests of everyone you know

3778
02:26:23,429 --> 02:26:21,920
needing physiology breaks and so on and

3779
02:26:25,110 --> 02:26:23,439
so forth and this is i think a great

3780
02:26:27,110 --> 02:26:25,120
lead-in to joshua vites who's actually

3781
02:26:29,910 --> 02:26:27,120
talking right after the break oh great

3782
02:26:31,270 --> 02:26:29,920
unless somebody else has any other

3783
02:26:32,870 --> 02:26:31,280
thoughts should we just go ahead and go

3784
02:26:35,270 --> 02:26:32,880
on break until

3785
02:26:36,870 --> 02:26:35,280
10 40 pacific

3786
02:26:38,389 --> 02:26:36,880
that work for everyone

3787
02:26:40,710 --> 02:26:38,399
i think that's a great idea i also

3788
02:26:42,469 --> 02:26:40,720
wanted to highlight if everyone has time

3789
02:26:44,389 --> 02:26:42,479
actually look at the comments that are

3790
02:26:46,790 --> 02:26:44,399
in zoom they're actually some great

3791
02:26:49,510 --> 02:26:46,800
engaging conversations and be great to

3792
02:26:51,349 --> 02:26:49,520
get more feedback from people or just

3793
02:26:53,590 --> 02:26:51,359
really think about it i really love the

3794
02:26:54,389 --> 02:26:53,600
discussion that's going on there also we

3795
02:26:56,950 --> 02:26:54,399
will

3796
02:26:58,950 --> 02:26:56,960
have that transcript available uh takes

3797
02:27:00,389 --> 02:26:58,960
maybe a couple days for us to figure out

3798
02:27:01,990 --> 02:27:00,399
how to do that

3799
02:27:03,590 --> 02:27:02,000
but we are recording everybody's

3800
02:27:05,429 --> 02:27:03,600
comments so

3801
02:27:07,990 --> 02:27:05,439
a lot of these topics

3802
02:27:09,190 --> 02:27:08,000
uh can be folded into our follow-on

3803
02:27:10,630 --> 02:27:09,200
discussions

3804
02:27:13,830 --> 02:27:10,640
you know in the process of putting

3805
02:27:16,389 --> 02:27:13,840
together a paper in the white paper

3806
02:27:17,670 --> 02:27:16,399
all right great time thank you

3807
02:27:19,910 --> 02:27:17,680
we're good to go

3808
02:27:21,830 --> 02:27:19,920
okay great thank you

3809
02:27:24,389 --> 02:27:21,840
thanks for having me here today this

3810
02:27:25,510 --> 02:27:24,399
virtual workshop my name is joshua weitz

3811
02:27:27,830 --> 02:27:25,520
and i'll be talking about viral

3812
02:27:30,469 --> 02:27:27,840
infection modes invasion fitness

3813
02:27:32,070 --> 02:27:30,479
across a continuum from lysis to latency

3814
02:27:33,830 --> 02:27:32,080
and i've hidden myself so i assume you

3815
02:27:35,190 --> 02:27:33,840
can see me and you can see these slides

3816
02:27:36,790 --> 02:27:35,200
is that right and you can hear my voice

3817
02:27:38,950 --> 02:27:36,800
someone get great

3818
02:27:41,030 --> 02:27:38,960
okay and let's see as long as i can

3819
02:27:42,870 --> 02:27:41,040
get it to advance that would be good so

3820
02:27:44,550 --> 02:27:42,880
we've heard a lot about viruses already

3821
02:27:47,110 --> 02:27:44,560
today i'm sure tomorrow is well and

3822
02:27:48,389 --> 02:27:47,120
usually when one thinks about viruses at

3823
02:27:50,230 --> 02:27:48,399
least in

3824
02:27:51,990 --> 02:27:50,240
a public setting it's often because one

3825
02:27:53,910 --> 02:27:52,000
is thinking about

3826
02:27:56,469 --> 02:27:53,920
see again if my buttons are clicking

3827
02:28:04,150 --> 02:27:59,270
sorry for the

3828
02:28:10,150 --> 02:28:06,469
let me see if we've

3829
02:28:12,469 --> 02:28:11,510
there we go

3830
02:28:14,550 --> 02:28:12,479
uh

3831
02:28:16,469 --> 02:28:14,560
we usually talk about viruses in public

3832
02:28:19,349 --> 02:28:16,479
context in terms of those viruses that

3833
02:28:21,429 --> 02:28:19,359
might cause uh mortality and morbidity

3834
02:28:22,790 --> 02:28:21,439
uh with respect to humans human diseases

3835
02:28:25,429 --> 02:28:22,800
like ebola

3836
02:28:27,429 --> 02:28:25,439
zika or influenza and i think it's fair

3837
02:28:29,349 --> 02:28:27,439
to say that this audience knows that

3838
02:28:31,270 --> 02:28:29,359
viruses infect organisms really across

3839
02:28:34,070 --> 02:28:31,280
the span of diversity of life from

3840
02:28:36,070 --> 02:28:34,080
humans mammals birds insects also plants

3841
02:28:38,710 --> 02:28:36,080
but crucially also microbes in other

3842
02:28:40,790 --> 02:28:38,720
words microbes get sick too and i've

3843
02:28:43,429 --> 02:28:40,800
given some examples and the prior talk

3844
02:28:45,349 --> 02:28:43,439
uh touched on one of those uh the sulfur

3845
02:28:47,190 --> 02:28:45,359
spindle viruses and other archaeal

3846
02:28:49,830 --> 02:28:47,200
viruses and also of course there are

3847
02:28:51,270 --> 02:28:49,840
viruses of bacteria amoeba and so on and

3848
02:28:52,550 --> 02:28:51,280
so i'm going to spend some time today

3849
02:28:54,469 --> 02:28:52,560
using these

3850
02:28:57,510 --> 02:28:54,479
virus and microbes particularly viruses

3851
02:28:59,510 --> 02:28:57,520
of bacteria as a means to think about

3852
02:29:02,550 --> 02:28:59,520
the ways in which infection mode might

3853
02:29:04,790 --> 02:29:02,560
differ and not necessarily

3854
02:29:06,790 --> 02:29:04,800
always be antagonistic to hosts so just

3855
02:29:07,830 --> 02:29:06,800
to get everyone on the same page

3856
02:29:10,790 --> 02:29:07,840
you're probably aware that when

3857
02:29:12,309 --> 02:29:10,800
bacterial viruses phage bacteria phage

3858
02:29:14,550 --> 02:29:12,319
or in the environment they might diffuse

3859
02:29:17,190 --> 02:29:14,560
until they're in contact with a target

3860
02:29:19,670 --> 02:29:17,200
cell inject their genetic material into

3861
02:29:21,190 --> 02:29:19,680
the host redirect cellular machinery in

3862
02:29:23,190 --> 02:29:21,200
order to make more

3863
02:29:25,830 --> 02:29:23,200
genetic material viral genetic material

3864
02:29:27,830 --> 02:29:25,840
which can self-assembles uh and into

3865
02:29:30,389 --> 02:29:27,840
these mature virions and through a time

3866
02:29:32,469 --> 02:29:30,399
process uh often there's a hole that's

3867
02:29:34,070 --> 02:29:32,479
made in the inner membrane

3868
02:29:36,309 --> 02:29:34,080
some cleavage in the cell wall and then

3869
02:29:37,750 --> 02:29:36,319
through a time process releases these

3870
02:29:39,750 --> 02:29:37,760
virus particles back into the

3871
02:29:41,349 --> 02:29:39,760
environment and so clearly for that

3872
02:29:44,230 --> 02:29:41,359
particular cell

3873
02:29:46,150 --> 02:29:44,240
that's the end of its uh its life but

3874
02:29:47,830 --> 02:29:46,160
that doesn't necessarily mean that the

3875
02:29:49,110 --> 02:29:47,840
death of one cell is the death of a

3876
02:29:50,630 --> 02:29:49,120
population

3877
02:29:52,870 --> 02:29:50,640
so because of this antagonistic

3878
02:29:54,309 --> 02:29:52,880
relationship the fact that this virus in

3879
02:29:57,110 --> 02:29:54,319
some ways

3880
02:29:58,550 --> 02:29:57,120
consumes or eats the hosts fajros from

3881
02:30:00,070 --> 02:29:58,560
to devour

3882
02:30:01,670 --> 02:30:00,080
the predator prey model has been the

3883
02:30:03,990 --> 02:30:01,680
basis for quite a lot of studies of

3884
02:30:06,630 --> 02:30:04,000
virus micro population dynamics how we

3885
02:30:09,190 --> 02:30:06,640
move from cellular level models up to

3886
02:30:11,270 --> 02:30:09,200
population level models and so here on

3887
02:30:13,110 --> 02:30:11,280
the left i've just given one variant of

3888
02:30:15,110 --> 02:30:13,120
a classic example and again my

3889
02:30:17,349 --> 02:30:15,120
background is theory and modeling and

3890
02:30:19,190 --> 02:30:17,359
here you have interaction between some

3891
02:30:21,670 --> 02:30:19,200
resources that are being flowed into the

3892
02:30:23,750 --> 02:30:21,680
system cells that take up those

3893
02:30:25,990 --> 02:30:23,760
resources and viruses that infect

3894
02:30:27,910 --> 02:30:26,000
reproduce and kill those cells and the

3895
02:30:29,750 --> 02:30:27,920
left-hand side denotes a non-linear

3896
02:30:31,510 --> 02:30:29,760
dynamical system where you have

3897
02:30:33,830 --> 02:30:31,520
resources are

3898
02:30:35,349 --> 02:30:33,840
bacteria and viruses v

3899
02:30:37,590 --> 02:30:35,359
and again the process of nutrient

3900
02:30:40,790 --> 02:30:37,600
consumption turns resources into cells

3901
02:30:43,270 --> 02:30:40,800
infection turns cells into more viruses

3902
02:30:45,750 --> 02:30:43,280
and with these simple ingredients

3903
02:30:48,870 --> 02:30:45,760
one can track the expected dynamics in

3904
02:30:51,030 --> 02:30:48,880
time and here on the right i've shown

3905
02:30:53,270 --> 02:30:51,040
time implicitly where prey is on the

3906
02:30:55,270 --> 02:30:53,280
x-axis and prayers on the y-axis and

3907
02:30:57,190 --> 02:30:55,280
what you see are these counterclockwise

3908
02:30:59,030 --> 02:30:57,200
cycles in other words when there are a

3909
02:31:00,950 --> 02:30:59,040
lot of prey around the viruses do well

3910
02:31:03,510 --> 02:31:00,960
increasing in abundance when there are a

3911
02:31:05,429 --> 02:31:03,520
lot of viruses they drive the prey down

3912
02:31:07,030 --> 02:31:05,439
when there are few prey then viruses go

3913
02:31:09,270 --> 02:31:07,040
down and because there are a few viruses

3914
02:31:11,429 --> 02:31:09,280
then bacteria can recover and these are

3915
02:31:12,870 --> 02:31:11,439
really lockable terror like dynamics so

3916
02:31:15,270 --> 02:31:12,880
for the same reasons you see these

3917
02:31:16,630 --> 02:31:15,280
oscillations within lynx hair systems

3918
02:31:18,230 --> 02:31:16,640
it's presumably the same reason you

3919
02:31:19,429 --> 02:31:18,240
might see them within virus microbe

3920
02:31:21,110 --> 02:31:19,439
systems

3921
02:31:23,349 --> 02:31:21,120
and there's experimental evidence that

3922
02:31:25,030 --> 02:31:23,359
these kinds of population cycles can be

3923
02:31:26,790 --> 02:31:25,040
observed in the laboratory these are

3924
02:31:28,950 --> 02:31:26,800
classic work brendan bohan and rich

3925
02:31:32,469 --> 02:31:28,960
lenski and their predator prey-like

3926
02:31:34,150 --> 02:31:32,479
cycles between phage t4 and e coli b

3927
02:31:35,830 --> 02:31:34,160
it's about a seven to eight day

3928
02:31:37,830 --> 02:31:35,840
experiment here

3929
02:31:39,910 --> 02:31:37,840
and you can see with time

3930
02:31:41,990 --> 02:31:39,920
oscillations of large magnitude and the

3931
02:31:44,550 --> 02:31:42,000
population densities of viruses and

3932
02:31:47,349 --> 02:31:44,560
hosts you can see at times virus to host

3933
02:31:49,429 --> 02:31:47,359
ratios don't just get to be one or ten

3934
02:31:50,309 --> 02:31:49,439
to one but can be a hundred to one or

3935
02:31:52,230 --> 02:31:50,319
more

3936
02:31:54,710 --> 02:31:52,240
and the oscillations are not because of

3937
02:31:56,469 --> 02:31:54,720
some exogenous driving of the system

3938
02:31:58,150 --> 02:31:56,479
it's not as if the system is being

3939
02:32:00,309 --> 02:31:58,160
driven by some oscillatory resource

3940
02:32:03,270 --> 02:32:00,319
input this is in a chemostat

3941
02:32:05,910 --> 02:32:03,280
with steady flow of minimal media and

3942
02:32:07,990 --> 02:32:05,920
nonetheless the feedback between virus

3943
02:32:10,230 --> 02:32:08,000
and microbes at the cellular level

3944
02:32:12,070 --> 02:32:10,240
translates into endogenous large scale

3945
02:32:14,389 --> 02:32:12,080
oscillations and they're shifted if you

3946
02:32:16,309 --> 02:32:14,399
notice the peaks of the virals

3947
02:32:18,950 --> 02:32:16,319
abundances are slightly shifted forward

3948
02:32:19,750 --> 02:32:18,960
in time with respect to bacterial peaks

3949
02:32:22,469 --> 02:32:19,760
okay

3950
02:32:23,590 --> 02:32:22,479
and so with that in mind

3951
02:32:25,670 --> 02:32:23,600
and i'm sorry that there's some

3952
02:32:27,830 --> 02:32:25,680
technical issues here

3953
02:32:31,030 --> 02:32:27,840
the sharing screen seems to forget that

3954
02:32:33,590 --> 02:32:31,040
i am here with a computer

3955
02:32:35,270 --> 02:32:33,600
so maybe

3956
02:32:37,670 --> 02:32:35,280
let me

3957
02:32:39,030 --> 02:32:37,680
go back is there any way i can do this

3958
02:32:40,469 --> 02:32:39,040
just by

3959
02:32:45,110 --> 02:32:40,479
zooming in it's the sharing of the

3960
02:32:51,270 --> 02:32:47,910
let's see if i go into that view

3961
02:32:54,950 --> 02:32:53,349
okay sorry about that delay this way at

3962
02:32:57,590 --> 02:32:54,960
least i can click on the new slide if i

3963
02:33:02,710 --> 02:32:59,590
and so these virus host interactions

3964
02:33:03,910 --> 02:33:02,720
modify the fit of cells on short time

3965
02:33:08,070 --> 02:33:03,920
scales

3966
02:33:09,830 --> 02:33:08,080
accept there to be oscillatory dynamics

3967
02:33:12,070 --> 02:33:09,840
and then once you start scaling this up

3968
02:33:14,389 --> 02:33:12,080
to ecosystems this effect of killing

3969
02:33:15,190 --> 02:33:14,399
individual cells and populations can

3970
02:33:16,790 --> 02:33:15,200
have

3971
02:33:18,230 --> 02:33:16,800
large ecosystem level effects

3972
02:33:20,309 --> 02:33:18,240
particularly we're insured often in

3973
02:33:22,389 --> 02:33:20,319
global oceans and part of the reason for

3974
02:33:24,950 --> 02:33:22,399
that is that the number of viruses

3975
02:33:27,030 --> 02:33:24,960
outnumber those of microbes largely

3976
02:33:29,510 --> 02:33:27,040
bacteria but some archaea anywhere from

3977
02:33:30,870 --> 02:33:29,520
about one to one to a hundred to one and

3978
02:33:33,349 --> 02:33:30,880
if you look on the axis here we're

3979
02:33:35,910 --> 02:33:33,359
talking about typical densities of 50

3980
02:33:37,830 --> 02:33:35,920
million 50 million uh viruses or

3981
02:33:39,990 --> 02:33:37,840
virus-like particles per milliliter

3982
02:33:41,349 --> 02:33:40,000
again in excess of those of bacteria so

3983
02:33:43,429 --> 02:33:41,359
all that lysis

3984
02:33:46,550 --> 02:33:43,439
presumably leads to big

3985
02:33:48,710 --> 02:33:46,560
changes in microbial densities

3986
02:33:50,389 --> 02:33:48,720
effects on microbial mortality as well

3987
02:33:52,469 --> 02:33:50,399
as the regeneration of carbon and other

3988
02:33:54,230 --> 02:33:52,479
nutrients back into the environment

3989
02:33:56,070 --> 02:33:54,240
but all the examples i've given thus far

3990
02:33:58,550 --> 02:33:56,080
really focuses on the effective viruses

3991
02:34:01,349 --> 02:33:58,560
as killing agents antagonistic

3992
02:34:02,710 --> 02:34:01,359
uh obligate intracellular parasites that

3993
02:34:04,710 --> 02:34:02,720
end up just killing the host in order to

3994
02:34:06,710 --> 02:34:04,720
make more of themselves so the question

3995
02:34:08,150 --> 02:34:06,720
i want to ask and really focus on

3996
02:34:10,150 --> 02:34:08,160
in my time today is do viruses and

3997
02:34:12,150 --> 02:34:10,160
microbes do more than kill

3998
02:34:14,230 --> 02:34:12,160
or prepare to kill

3999
02:34:16,790 --> 02:34:14,240
and the answer is yes and has been known

4000
02:34:19,670 --> 02:34:16,800
to be yes for quite a long time

4001
02:34:21,349 --> 02:34:19,680
and lysogeny and tempered phage

4002
02:34:23,030 --> 02:34:21,359
really provide a number of lessons from

4003
02:34:25,830 --> 02:34:23,040
a simple system going all the way back

4004
02:34:28,550 --> 02:34:25,840
to andre loft and others of

4005
02:34:30,469 --> 02:34:28,560
the pantheon of those who understood

4006
02:34:32,389 --> 02:34:30,479
viruses and tried to understand

4007
02:34:35,190 --> 02:34:32,399
the viral impacts on gene regulation and

4008
02:34:37,590 --> 02:34:35,200
molecular biology and the key idea

4009
02:34:39,349 --> 02:34:37,600
within tempered phage is that you have

4010
02:34:41,990 --> 02:34:39,359
the injection of the genetic material

4011
02:34:44,469 --> 02:34:42,000
into the host but then a genetic switch

4012
02:34:46,550 --> 02:34:44,479
really a decision between two

4013
02:34:49,030 --> 02:34:46,560
pathways one which is lysis which i've

4014
02:34:51,830 --> 02:34:49,040
already described and the other which is

4015
02:34:53,429 --> 02:34:51,840
integration of the viral genome into the

4016
02:34:55,910 --> 02:34:53,439
cellular genome

4017
02:34:58,389 --> 02:34:55,920
where it is termed a prophage and that

4018
02:35:00,870 --> 02:34:58,399
prophage that viral genome can then

4019
02:35:03,590 --> 02:35:00,880
terribly be passed on from mother to

4020
02:35:06,389 --> 02:35:03,600
daughter cell across the replication and

4021
02:35:09,270 --> 02:35:06,399
at some later point can be induced and

4022
02:35:12,710 --> 02:35:09,280
by induced i mean that the prophage

4023
02:35:14,630 --> 02:35:12,720
excises itself from the cellular genome

4024
02:35:16,150 --> 02:35:14,640
reinitiating the lytic cycle and then

4025
02:35:17,910 --> 02:35:16,160
heads out again

4026
02:35:19,750 --> 02:35:17,920
and although this is classic work

4027
02:35:22,070 --> 02:35:19,760
there's still quite a lot of activity

4028
02:35:25,190 --> 02:35:22,080
trying to understand these switches both

4029
02:35:28,070 --> 02:35:25,200
that switch in how to be temperate how

4030
02:35:30,150 --> 02:35:28,080
to make this decision after the virus

4031
02:35:32,150 --> 02:35:30,160
injects this genetic material and then

4032
02:35:33,830 --> 02:35:32,160
how the process of induction works this

4033
02:35:34,950 --> 02:35:33,840
is one example from the work of edo

4034
02:35:37,110 --> 02:35:34,960
golding

4035
02:35:38,870 --> 02:35:37,120
who is soon to be i believe at uiuc he's

4036
02:35:40,790 --> 02:35:38,880
been at baylor college of medicine for a

4037
02:35:43,429 --> 02:35:40,800
number of years and using a labeling

4038
02:35:46,710 --> 02:35:43,439
system is able you see in panel b

4039
02:35:49,030 --> 02:35:46,720
identify when i phage because the capsid

4040
02:35:52,150 --> 02:35:49,040
has been marked with this yfp has

4041
02:35:54,550 --> 02:35:52,160
attached excuse me to a cell and then

4042
02:35:57,030 --> 02:35:54,560
depending on the fate there's a reporter

4043
02:35:59,750 --> 02:35:57,040
system that those cells that have been

4044
02:36:01,270 --> 02:35:59,760
faded to lysogyny turn red so they're

4045
02:36:03,190 --> 02:36:01,280
normally growing and you can see them

4046
02:36:05,910 --> 02:36:03,200
actually divide and that red color pass

4047
02:36:08,070 --> 02:36:05,920
terribly between the two cells and those

4048
02:36:09,510 --> 02:36:08,080
cells that then produce new phages

4049
02:36:11,270 --> 02:36:09,520
produce these

4050
02:36:12,389 --> 02:36:11,280
again labeled phage

4051
02:36:15,270 --> 02:36:12,399
and the point i want to make here

4052
02:36:17,830 --> 02:36:15,280
although these are dichotomous outcomes

4053
02:36:18,710 --> 02:36:17,840
these decisions are probabilistic

4054
02:36:21,030 --> 02:36:18,720
meaning

4055
02:36:23,510 --> 02:36:21,040
it's not as if a particular

4056
02:36:24,790 --> 02:36:23,520
cell or particular virus encodes yes 100

4057
02:36:27,030 --> 02:36:24,800
of the time going this way and then

4058
02:36:29,030 --> 02:36:27,040
deterministically depending on the state

4059
02:36:30,950 --> 02:36:29,040
of the host it'll pop out

4060
02:36:32,150 --> 02:36:30,960
there is a relationship between cell

4061
02:36:34,230 --> 02:36:32,160
state

4062
02:36:36,550 --> 02:36:34,240
particularly if the cell is not in a

4063
02:36:38,309 --> 02:36:36,560
good state maybe a phage can detect that

4064
02:36:40,150 --> 02:36:38,319
and get out there's also a relationship

4065
02:36:41,910 --> 02:36:40,160
between multiplicity of infection other

4066
02:36:44,469 --> 02:36:41,920
factors and that is a long and

4067
02:36:45,990 --> 02:36:44,479
interesting topic maybe for another day

4068
02:36:49,270 --> 02:36:46,000
and all that revolves on how to be

4069
02:36:51,830 --> 02:36:49,280
tempered how does a virus regulate

4070
02:36:53,670 --> 02:36:51,840
detect what's going on in a cell in a

4071
02:36:55,190 --> 02:36:53,680
way that can change these probabilities

4072
02:36:56,950 --> 02:36:55,200
this initial decision switch and this

4073
02:36:58,630 --> 02:36:56,960
induction switch

4074
02:37:00,630 --> 02:36:58,640
but there's another question which is an

4075
02:37:02,870 --> 02:37:00,640
evolutionary question which is why to be

4076
02:37:04,550 --> 02:37:02,880
tempered in the first place

4077
02:37:06,710 --> 02:37:04,560
and frank stewart and bruce levin in the

4078
02:37:08,950 --> 02:37:06,720
mid 80s asked this question and they

4079
02:37:10,550 --> 02:37:08,960
proposed one of many uh a feast or

4080
02:37:12,309 --> 02:37:10,560
famine hypothesis

4081
02:37:13,349 --> 02:37:12,319
the idea that tempered phage do better

4082
02:37:15,030 --> 02:37:13,359
when there are a few hosts that are

4083
02:37:16,950 --> 02:37:15,040
available and the extracellular

4084
02:37:19,190 --> 02:37:16,960
mortality rate is high but but they did

4085
02:37:21,270 --> 02:37:19,200
offer a caveat and they said in spite of

4086
02:37:23,190 --> 02:37:21,280
the intuitive appeal of this low-density

4087
02:37:25,670 --> 02:37:23,200
hypothesis they're unable to find

4088
02:37:27,270 --> 02:37:25,680
solutions meaning they could impose

4089
02:37:29,429 --> 02:37:27,280
those conditions and that seemed to

4090
02:37:31,190 --> 02:37:29,439
favor the temperate phage

4091
02:37:33,030 --> 02:37:31,200
but it wasn't as if they understood the

4092
02:37:34,550 --> 02:37:33,040
principles by which that might happen so

4093
02:37:36,389 --> 02:37:34,560
the idea is that maybe when there are

4094
02:37:38,710 --> 02:37:36,399
fewer phages around it's better not to

4095
02:37:41,110 --> 02:37:38,720
kill off the last hosts but that has a

4096
02:37:43,990 --> 02:37:41,120
bit of a group selection or aspirational

4097
02:37:45,349 --> 02:37:44,000
level to the argument

4098
02:37:47,030 --> 02:37:45,359
though there is some evidence that this

4099
02:37:48,790 --> 02:37:47,040
is really what happens or at least that

4100
02:37:50,870 --> 02:37:48,800
had been the paradigm

4101
02:37:53,349 --> 02:37:50,880
in marine systems there was a notion of

4102
02:37:55,270 --> 02:37:53,359
seasonal time bombs the idea that in low

4103
02:37:57,349 --> 02:37:55,280
productivity low density environments

4104
02:37:58,630 --> 02:37:57,359
this is work by jennifer brum

4105
02:38:01,670 --> 02:37:58,640
and colleagues there are other similar

4106
02:38:03,830 --> 02:38:01,680
studies that when you look and use an

4107
02:38:05,750 --> 02:38:03,840
induction assay to try to pull out the

4108
02:38:08,710 --> 02:38:05,760
number of lysogens pull phage out that

4109
02:38:10,550 --> 02:38:08,720
are lysogens when over the winter or

4110
02:38:12,469 --> 02:38:10,560
spring there are less productivity and

4111
02:38:13,910 --> 02:38:12,479
fewer cells then in fact you see a lot

4112
02:38:15,910 --> 02:38:13,920
of lysogens and in the summer when

4113
02:38:18,309 --> 02:38:15,920
things are productive in a lot of cells

4114
02:38:19,590 --> 02:38:18,319
then you don't see many lysogens in

4115
02:38:21,990 --> 02:38:19,600
contrast when you look under the

4116
02:38:23,830 --> 02:38:22,000
microscope there's a higher fraction of

4117
02:38:24,790 --> 02:38:23,840
lytically infected cells

4118
02:38:26,469 --> 02:38:24,800
okay

4119
02:38:28,630 --> 02:38:26,479
and so that's the contrast here between

4120
02:38:30,230 --> 02:38:28,640
the top and the bottom panel and this

4121
02:38:32,870 --> 02:38:30,240
had been the paradigm until i would say

4122
02:38:35,030 --> 02:38:32,880
just a few years ago when an alternative

4123
02:38:36,710 --> 02:38:35,040
hypothesis was presented it's turned

4124
02:38:38,469 --> 02:38:36,720
piggy back the winner some of you may be

4125
02:38:40,469 --> 02:38:38,479
familiar with it the idea is really

4126
02:38:42,710 --> 02:38:40,479
quite the opposite the claim is that

4127
02:38:44,230 --> 02:38:42,720
misogyny is positively correlated with

4128
02:38:46,070 --> 02:38:44,240
increases in host density and

4129
02:38:47,990 --> 02:38:46,080
productivity in other words lytic

4130
02:38:49,429 --> 02:38:48,000
activity goes down as there's more

4131
02:38:51,429 --> 02:38:49,439
productive or

4132
02:38:52,950 --> 02:38:51,439
denser environments and there's a

4133
02:38:55,750 --> 02:38:52,960
background to why

4134
02:38:57,110 --> 02:38:55,760
this was of interest to the authors

4135
02:38:59,190 --> 02:38:57,120
and also

4136
02:39:01,270 --> 02:38:59,200
some additional context on density

4137
02:39:03,590 --> 02:39:01,280
relationships but there's some direct

4138
02:39:05,590 --> 02:39:03,600
evidence that they presented by looking

4139
02:39:08,150 --> 02:39:05,600
at a range of microbial densities and on

4140
02:39:10,950 --> 02:39:08,160
the y-axis here evidence from

4141
02:39:12,790 --> 02:39:10,960
metagenomics that there was some

4142
02:39:15,030 --> 02:39:12,800
increase in lysogen we have to use

4143
02:39:16,630 --> 02:39:15,040
proxies here by looking environments

4144
02:39:19,030 --> 02:39:16,640
they look for things like the percent of

4145
02:39:20,230 --> 02:39:19,040
pro virus like reeds things that might

4146
02:39:23,110 --> 02:39:20,240
indicate

4147
02:39:25,270 --> 02:39:23,120
the potential for latency

4148
02:39:27,750 --> 02:39:25,280
and despite claims in the paper i would

4149
02:39:29,830 --> 02:39:27,760
argue as you see here that there's not a

4150
02:39:33,590 --> 02:39:29,840
really strong relationship between the y

4151
02:39:35,590 --> 02:39:33,600
and the x-axis for pro-virus-like reads

4152
02:39:38,710 --> 02:39:35,600
there's not a strong relation between

4153
02:39:40,870 --> 02:39:38,720
the y and x-axis for integrases

4154
02:39:43,670 --> 02:39:40,880
nor for excision agents and these are

4155
02:39:45,190 --> 02:39:43,680
all indicators of things that look like

4156
02:39:46,790 --> 02:39:45,200
they have the potential getting in and

4157
02:39:48,389 --> 02:39:46,800
getting out

4158
02:39:49,750 --> 02:39:48,399
so the takeaway at least from my

4159
02:39:51,349 --> 02:39:49,760
perspective is that at the moment

4160
02:39:53,429 --> 02:39:51,359
there's an absence of evidence for a

4161
02:39:55,510 --> 02:39:53,439
positive correlation between lysogenic

4162
02:39:57,590 --> 02:39:55,520
proxies and cell density

4163
02:39:59,750 --> 02:39:57,600
and what can be more about that there's

4164
02:40:02,070 --> 02:39:59,760
other ways to look for these proxies by

4165
02:40:03,510 --> 02:40:02,080
looking directly at ratios of viruses to

4166
02:40:06,150 --> 02:40:03,520
microbes as a proxy i think there are

4167
02:40:08,230 --> 02:40:06,160
other issues there but nonetheless i do

4168
02:40:10,150 --> 02:40:08,240
think that this paper and to some of

4169
02:40:12,389 --> 02:40:10,160
this you know debate and back and forth

4170
02:40:14,070 --> 02:40:12,399
has raised perhaps even a more important

4171
02:40:15,510 --> 02:40:14,080
question which is what are the

4172
02:40:17,190 --> 02:40:15,520
environmental conditions that should

4173
02:40:19,349 --> 02:40:17,200
favor lysogeny

4174
02:40:21,830 --> 02:40:19,359
over lysis i don't think that question

4175
02:40:24,710 --> 02:40:21,840
has been resolved and i'm going to try

4176
02:40:26,790 --> 02:40:24,720
to begin to address that question today

4177
02:40:29,190 --> 02:40:26,800
by turning to an old lesson that some of

4178
02:40:30,550 --> 02:40:29,200
you probably know and it turns out that

4179
02:40:31,670 --> 02:40:30,560
there are different

4180
02:40:33,030 --> 02:40:31,680
ways of saying this in different

4181
02:40:34,710 --> 02:40:33,040
languages and cultures the one i'm

4182
02:40:36,710 --> 02:40:34,720
familiar with is a bird in the hand is

4183
02:40:39,190 --> 02:40:36,720
worth two in the bush

4184
02:40:41,429 --> 02:40:39,200
the idea you have something now

4185
02:40:43,429 --> 02:40:41,439
and you might trade it for something in

4186
02:40:44,790 --> 02:40:43,439
the future but you better trade up

4187
02:40:46,309 --> 02:40:44,800
because you're not certain of how much

4188
02:40:48,389 --> 02:40:46,319
you're going to get

4189
02:40:50,469 --> 02:40:48,399
and so i claim that this relates to a

4190
02:40:52,469 --> 02:40:50,479
puzzle that we should be asking

4191
02:40:54,070 --> 02:40:52,479
which is a virus in the cell's worth and

4192
02:40:55,910 --> 02:40:54,080
in the bloom

4193
02:40:58,630 --> 02:40:55,920
but what is n

4194
02:41:01,030 --> 02:40:58,640
right the virus has the cell right now

4195
02:41:03,990 --> 02:41:01,040
sure it could put out a whole bunch of

4196
02:41:06,790 --> 02:41:04,000
virus or virus particles back into the

4197
02:41:09,269 --> 02:41:06,800
environment but how many is worth

4198
02:41:11,269 --> 02:41:09,279
sending back out versus the one cell

4199
02:41:13,510 --> 02:41:11,279
that you have right now

4200
02:41:16,150 --> 02:41:13,520
and so i want to make this comparison

4201
02:41:18,070 --> 02:41:16,160
more direct by talking about the notion

4202
02:41:20,309 --> 02:41:18,080
of viral proliferation

4203
02:41:21,910 --> 02:41:20,319
and thinking about what really is the

4204
02:41:23,349 --> 02:41:21,920
fitness of these different viral

4205
02:41:24,870 --> 02:41:23,359
strategies when we view them at the

4206
02:41:26,950 --> 02:41:24,880
individual level

4207
02:41:28,870 --> 02:41:26,960
and i'll start with the typical idea of

4208
02:41:30,630 --> 02:41:28,880
lytic viruses where you have this virus

4209
02:41:32,950 --> 02:41:30,640
it encounters

4210
02:41:36,389 --> 02:41:32,960
a cell infects the cell i'm going to

4211
02:41:38,550 --> 02:41:36,399
call that the mother virus as opposed to

4212
02:41:40,389 --> 02:41:38,560
the mother cell

4213
02:41:42,469 --> 02:41:40,399
and it eventually will lyse and produce

4214
02:41:44,710 --> 02:41:42,479
100 virus particles i'm going to make

4215
02:41:47,670 --> 02:41:44,720
the claim that that is not its fitness

4216
02:41:49,590 --> 02:41:47,680
a hundred is not how many uh

4217
02:41:52,550 --> 02:41:49,600
the offspring that particular mother

4218
02:41:54,309 --> 02:41:52,560
virus has because 97 of those virus

4219
02:41:55,830 --> 02:41:54,319
particles might never find a new

4220
02:41:58,309 --> 02:41:55,840
susceptible cell

4221
02:41:59,910 --> 02:41:58,319
they might decay be unstable or so on

4222
02:42:01,429 --> 02:41:59,920
and in this particular example only

4223
02:42:04,550 --> 02:42:01,439
three

4224
02:42:06,870 --> 02:42:04,560
find encounter and successfully infect

4225
02:42:08,790 --> 02:42:06,880
into a new cell and we'll call those

4226
02:42:10,710 --> 02:42:08,800
daughter viruses and so therefore i

4227
02:42:12,469 --> 02:42:10,720
would claim that in this case the

4228
02:42:13,910 --> 02:42:12,479
fitness at the individual level the

4229
02:42:15,590 --> 02:42:13,920
number of offspring over the course of

4230
02:42:16,630 --> 02:42:15,600
the lifetime of this mother virus is

4231
02:42:17,750 --> 02:42:16,640
three

4232
02:42:19,990 --> 02:42:17,760
and they've

4233
02:42:22,230 --> 02:42:20,000
been obtained horizontally

4234
02:42:25,269 --> 02:42:22,240
via horizontal transmission from one

4235
02:42:27,830 --> 02:42:25,279
cell to other cells in the environment

4236
02:42:30,469 --> 02:42:27,840
on the other hand latent viruses also

4237
02:42:33,269 --> 02:42:30,479
have a way of reproducing

4238
02:42:36,389 --> 02:42:33,279
the mother virus might divide

4239
02:42:38,150 --> 02:42:36,399
and therefore produce progeny daughters

4240
02:42:40,070 --> 02:42:38,160
and daughter viruses that they will

4241
02:42:41,990 --> 02:42:40,080
count their own fitness on their own and

4242
02:42:43,349 --> 02:42:42,000
if the mother cell divides three times

4243
02:42:44,870 --> 02:42:43,359
before it dies whether because it's

4244
02:42:47,030 --> 02:42:44,880
grazed or

4245
02:42:49,349 --> 02:42:47,040
sticks to something or lyses for some

4246
02:42:51,269 --> 02:42:49,359
other reason now just in vertical

4247
02:42:52,550 --> 02:42:51,279
transmission alone it's also possible to

4248
02:42:54,389 --> 02:42:52,560
have the same

4249
02:42:56,150 --> 02:42:54,399
fitness okay

4250
02:42:58,150 --> 02:42:56,160
so the point i'm trying to make here is

4251
02:42:59,910 --> 02:42:58,160
that two vastly different strategies can

4252
02:43:02,070 --> 02:42:59,920
lead to the same notion or calculation

4253
02:43:04,309 --> 02:43:02,080
of fitness at the individual level

4254
02:43:05,750 --> 02:43:04,319
and from an ecological perspective it

4255
02:43:08,389 --> 02:43:05,760
would be good to know how this depends

4256
02:43:09,750 --> 02:43:08,399
on cell densities and other factors if

4257
02:43:11,349 --> 02:43:09,760
we're beginning to understand which of

4258
02:43:13,670 --> 02:43:11,359
these particular strategies might be

4259
02:43:16,150 --> 02:43:13,680
favored or continuum of these strategies

4260
02:43:18,870 --> 02:43:16,160
might be favored in the environment

4261
02:43:20,389 --> 02:43:18,880
so to do that what my group has done in

4262
02:43:23,349 --> 02:43:20,399
collaboration with

4263
02:43:25,349 --> 02:43:23,359
rachel whitaker with some folks uh uh

4264
02:43:28,150 --> 02:43:25,359
in my group juan lin lia student and

4265
02:43:29,910 --> 02:43:28,160
mike cortez uh a former postdoc now

4266
02:43:33,030 --> 02:43:29,920
faculty and hirea google deck also

4267
02:43:35,269 --> 02:43:33,040
former osaka now faculty is take this

4268
02:43:37,670 --> 02:43:35,279
individual perspective and translate it

4269
02:43:38,950 --> 02:43:37,680
into a population perspective

4270
02:43:40,870 --> 02:43:38,960
so i've given you the example on the

4271
02:43:41,990 --> 02:43:40,880
bottom left of what happens for the

4272
02:43:44,710 --> 02:43:42,000
individual

4273
02:43:46,630 --> 02:43:44,720
the top is meant to be a box model

4274
02:43:49,910 --> 02:43:46,640
describing susceptible cells that can

4275
02:43:52,389 --> 02:43:49,920
become infected that generate offspring

4276
02:43:54,710 --> 02:43:52,399
various virus particles these viruses

4277
02:43:56,950 --> 02:43:54,720
then re-effect and start the cycle and

4278
02:43:59,269 --> 02:43:56,960
the right-hand side is the translation

4279
02:44:00,870 --> 02:43:59,279
of those into a dynamical system

4280
02:44:02,389 --> 02:44:00,880
and i just want to point out here that

4281
02:44:04,389 --> 02:44:02,399
this last equation the change in the

4282
02:44:06,950 --> 02:44:04,399
number of virus particles goes up

4283
02:44:09,110 --> 02:44:06,960
because of lysis so every time at a rate

4284
02:44:10,710 --> 02:44:09,120
ada that the cell is lysed it produces

4285
02:44:13,429 --> 02:44:10,720
beta offspring

4286
02:44:15,990 --> 02:44:13,439
and virus particles are lost because

4287
02:44:17,190 --> 02:44:16,000
they're removed due to infection or due

4288
02:44:18,469 --> 02:44:17,200
to decay

4289
02:44:20,309 --> 02:44:18,479
and i'm not going to go into all the

4290
02:44:22,550 --> 02:44:20,319
details today

4291
02:44:24,230 --> 02:44:22,560
other than to say that one can calculate

4292
02:44:25,830 --> 02:44:24,240
instead of that number three a generic

4293
02:44:28,469 --> 02:44:25,840
description of how

4294
02:44:30,150 --> 02:44:28,479
many offspring

4295
02:44:31,910 --> 02:44:30,160
the virus might have in terms of this

4296
02:44:34,070 --> 02:44:31,920
complete cell cycle from an infected

4297
02:44:36,150 --> 02:44:34,080
cell to new infected cells

4298
02:44:37,670 --> 02:44:36,160
in terms of these details here but i'll

4299
02:44:38,630 --> 02:44:37,680
just translate them

4300
02:44:40,389 --> 02:44:38,640
which is

4301
02:44:42,710 --> 02:44:40,399
the number of virus particles produce

4302
02:44:44,710 --> 02:44:42,720
you start with 100

4303
02:44:46,710 --> 02:44:44,720
a fraction of those

4304
02:44:49,190 --> 02:44:46,720
reach a new uh

4305
02:44:50,710 --> 02:44:49,200
cell before they decay and only a

4306
02:44:52,389 --> 02:44:50,720
certain fraction of them are going to

4307
02:44:54,150 --> 02:44:52,399
lyse before they wash out so that's the

4308
02:44:56,710 --> 02:44:54,160
complete cycle the virus gets into a

4309
02:44:58,870 --> 02:44:56,720
cell it has a probability of releasing

4310
02:45:00,870 --> 02:44:58,880
beta particles and only a fraction of

4311
02:45:03,429 --> 02:45:00,880
those make it to the new cell and that

4312
02:45:05,190 --> 02:45:03,439
then becomes the horizontal fitness

4313
02:45:07,269 --> 02:45:05,200
and when one looks then at the relation

4314
02:45:09,590 --> 02:45:07,279
between susceptible population some

4315
02:45:11,110 --> 02:45:09,600
ecological trait and a viral trait one

4316
02:45:13,190 --> 02:45:11,120
finds that it's not inevitable that

4317
02:45:15,269 --> 02:45:13,200
viruses can invade if there aren't

4318
02:45:17,510 --> 02:45:15,279
enough hoes or if their traits are not

4319
02:45:19,670 --> 02:45:17,520
sufficiently favorable for that host and

4320
02:45:22,550 --> 02:45:19,680
there's a lot of examples of viruses uh

4321
02:45:25,030 --> 02:45:22,560
infecting hosts that may not be uh the

4322
02:45:26,710 --> 02:45:25,040
optimal host in the environment then you

4323
02:45:28,230 --> 02:45:26,720
get the extinction or decay of that

4324
02:45:29,590 --> 02:45:28,240
particular phage on that one host

4325
02:45:31,510 --> 02:45:29,600
whereas the better the virus is that

4326
02:45:33,510 --> 02:45:31,520
exploiting the host the more susceptible

4327
02:45:35,670 --> 02:45:33,520
hosts there are the easier it is for the

4328
02:45:37,269 --> 02:45:35,680
virus to spread

4329
02:45:39,269 --> 02:45:37,279
and the takeaway here is that ecological

4330
02:45:40,870 --> 02:45:39,279
conditions with more susceptible cells

4331
02:45:43,030 --> 02:45:40,880
and viral traits that are more efficient

4332
02:45:47,750 --> 02:45:43,040
infection and also can survive longer in

4333
02:45:52,790 --> 02:45:49,590
now in contrast we can do the same thing

4334
02:45:55,349 --> 02:45:52,800
with the latent virus case but here

4335
02:45:57,429 --> 02:45:55,359
rather than necessarily looking at the

4336
02:46:00,710 --> 02:45:57,439
horizontal transmission i'm going to

4337
02:46:02,070 --> 02:46:00,720
focus on just the case where fitness is

4338
02:46:03,590 --> 02:46:02,080
passed vertically

4339
02:46:05,590 --> 02:46:03,600
and again i won't go through some of the

4340
02:46:08,630 --> 02:46:05,600
mathematics here other than to say that

4341
02:46:10,309 --> 02:46:08,640
one can calculate this vertical fitness

4342
02:46:13,269 --> 02:46:10,319
and reduce it down to this simple

4343
02:46:15,349 --> 02:46:13,279
equation which is how long the cell

4344
02:46:16,870 --> 02:46:15,359
lives for multiply by its division rate

4345
02:46:19,590 --> 02:46:16,880
which gives you the average number of

4346
02:46:21,269 --> 02:46:19,600
offspring and if that's greater than one

4347
02:46:22,950 --> 02:46:21,279
then there are more daughter virus than

4348
02:46:26,230 --> 02:46:22,960
there are mother viruses and therefore

4349
02:46:28,790 --> 02:46:26,240
they are going to proliferate etc etc

4350
02:46:31,510 --> 02:46:28,800
so again here this is an example as we

4351
02:46:33,590 --> 02:46:31,520
increase susceptible populations the red

4352
02:46:35,750 --> 02:46:33,600
line is the horizontal fitness and i've

4353
02:46:38,630 --> 02:46:35,760
shown three blue lines

4354
02:46:40,950 --> 02:46:38,640
which shows how this vertical fitness

4355
02:46:42,950 --> 02:46:40,960
changes with susceptible cell density

4356
02:46:45,269 --> 02:46:42,960
notably it goes down

4357
02:46:47,110 --> 02:46:45,279
because if you infect a susceptible cell

4358
02:46:49,990 --> 02:46:47,120
and there are many other competitors you

4359
02:46:51,750 --> 02:46:50,000
have to face all those competitors

4360
02:46:53,670 --> 02:46:51,760
in the same niche so essentially there's

4361
02:46:55,190 --> 02:46:53,680
increasing niche competition

4362
02:46:57,110 --> 02:46:55,200
nonetheless if there are benefits of

4363
02:46:59,190 --> 02:46:57,120
lysogen in other words if the fitness of

4364
02:47:00,950 --> 02:46:59,200
the infected cell is better than that of

4365
02:47:04,070 --> 02:47:00,960
the uninfected cell then there's a

4366
02:47:06,790 --> 02:47:04,080
larger domain in which as you see to

4367
02:47:08,389 --> 02:47:06,800
presumably very high densities of cells

4368
02:47:10,790 --> 02:47:08,399
it actually might be better to be a

4369
02:47:12,150 --> 02:47:10,800
lysogen than to kill the cell and try to

4370
02:47:13,830 --> 02:47:12,160
find others

4371
02:47:15,110 --> 02:47:13,840
so the takeaway here is that ecological

4372
02:47:17,510 --> 02:47:15,120
conditions with reduced niche

4373
02:47:19,750 --> 02:47:17,520
competition direct cell benefits or low

4374
02:47:23,110 --> 02:47:19,760
variant survivorship all favor latent

4375
02:47:27,190 --> 02:47:25,349
and there's also

4376
02:47:29,750 --> 02:47:27,200
things in between these dichotomous

4377
02:47:31,269 --> 02:47:29,760
outcomes so here's an example in which a

4378
02:47:33,429 --> 02:47:31,279
cell is infected

4379
02:47:34,550 --> 02:47:33,439
and it can both

4380
02:47:36,389 --> 02:47:34,560
divide

4381
02:47:38,710 --> 02:47:36,399
generating progeny that are themselves

4382
02:47:41,269 --> 02:47:38,720
infected but through a budding process

4383
02:47:43,910 --> 02:47:41,279
rather than a lytic process release

4384
02:47:46,389 --> 02:47:43,920
progeny and therefore the chronic viral

4385
02:47:48,630 --> 02:47:46,399
fitness is a combination between the

4386
02:47:50,630 --> 02:47:48,640
horizontal fitness and the vertical

4387
02:47:52,630 --> 02:47:50,640
fitness and here in this particular

4388
02:47:54,950 --> 02:47:52,640
example in the lower left

4389
02:47:57,349 --> 02:47:54,960
there's one division event and two of

4390
02:47:59,510 --> 02:47:57,359
the uh butted off viruses that find new

4391
02:48:02,870 --> 02:47:59,520
cells so the total fitness remains three

4392
02:48:04,309 --> 02:48:02,880
even though it's through distinct modes

4393
02:48:06,630 --> 02:48:04,319
and so the point i'm making here is that

4394
02:48:08,230 --> 02:48:06,640
then when we think about chronic viruses

4395
02:48:10,469 --> 02:48:08,240
and their fitness it becomes an

4396
02:48:12,150 --> 02:48:10,479
aggregation of both the horizontal and

4397
02:48:13,590 --> 02:48:12,160
the vertical components

4398
02:48:15,030 --> 02:48:13,600
and

4399
02:48:17,030 --> 02:48:15,040
the point i'll make here i've already

4400
02:48:19,349 --> 02:48:17,040
told you what those are based on is that

4401
02:48:22,070 --> 02:48:19,359
we increase uh susceptible densities we

4402
02:48:24,230 --> 02:48:22,080
can compare all three strategies finding

4403
02:48:26,070 --> 02:48:24,240
that maybe at lower cell densities the

4404
02:48:27,590 --> 02:48:26,080
vertical mode is dominant at very high

4405
02:48:29,110 --> 02:48:27,600
cell densities the horizontal mode and

4406
02:48:30,469 --> 02:48:29,120
there can be a mix mode that can be

4407
02:48:32,230 --> 02:48:30,479
dominating between

4408
02:48:34,710 --> 02:48:32,240
though the precise position of these can

4409
02:48:36,950 --> 02:48:34,720
change the more that the cell is

4410
02:48:38,710 --> 02:48:36,960
benefited by the viral infection that

4411
02:48:41,110 --> 02:48:38,720
blue line can go up and start to move

4412
02:48:43,190 --> 02:48:41,120
over to the right in cell densities

4413
02:48:45,030 --> 02:48:43,200
so again the takeaway here is that

4414
02:48:46,469 --> 02:48:45,040
temperate and chronic modes are favored

4415
02:48:47,910 --> 02:48:46,479
when susceptible populations are

4416
02:48:49,349 --> 02:48:47,920
relatively low

4417
02:48:51,590 --> 02:48:49,359
lysosomes have a relative growth

4418
02:48:54,230 --> 02:48:51,600
advantage or extracellular decay rates

4419
02:48:55,910 --> 02:48:54,240
are high so in fact some of these early

4420
02:48:58,550 --> 02:48:55,920
predictions by steward 11 really are

4421
02:49:00,309 --> 02:48:58,560
recapitulated but here rather than

4422
02:49:02,550 --> 02:49:00,319
trying to figure out how to balance

4423
02:49:04,550 --> 02:49:02,560
virus particles with inspected cells

4424
02:49:06,950 --> 02:49:04,560
answering that question of how many

4425
02:49:08,630 --> 02:49:06,960
uh in the bloom we should count by

4426
02:49:10,790 --> 02:49:08,640
calculating fitness

4427
02:49:13,990 --> 02:49:10,800
in terms of these viral life cycles we

4428
02:49:15,269 --> 02:49:14,000
get a direct answer to this question

4429
02:49:17,429 --> 02:49:15,279
and you can read more in this virus

4430
02:49:19,030 --> 02:49:17,439
evolution paper it came out

4431
02:49:20,950 --> 02:49:19,040
earlier this year

4432
02:49:22,469 --> 02:49:20,960
so to answer this question i think that

4433
02:49:23,670 --> 02:49:22,479
we should be thinking about unified

4434
02:49:24,710 --> 02:49:23,680
metrics

4435
02:49:27,110 --> 02:49:24,720
and thinking

4436
02:49:29,990 --> 02:49:27,120
maybe alternatively to the predator prey

4437
02:49:31,269 --> 02:49:30,000
paradigm to use an epidemiological

4438
02:49:32,550 --> 02:49:31,279
paradigm

4439
02:49:33,910 --> 02:49:32,560
which is the

4440
02:49:35,429 --> 02:49:33,920
something referred to as the basic

4441
02:49:37,429 --> 02:49:35,439
reproduction number

4442
02:49:39,429 --> 02:49:37,439
the average number of new infected cells

4443
02:49:41,990 --> 02:49:39,439
produced by a single typical infected

4444
02:49:44,469 --> 02:49:42,000
cell and it's progeny varions in an

4445
02:49:46,469 --> 02:49:44,479
otherwise susceptible population right

4446
02:49:48,710 --> 02:49:46,479
and using this perspective we can in an

4447
02:49:51,269 --> 02:49:48,720
apples to apples way compare both the

4448
02:49:53,429 --> 02:49:51,279
horizontal mode which produces varions

4449
02:49:55,349 --> 02:49:53,439
but doesn't necessarily go vertically

4450
02:49:57,750 --> 02:49:55,359
and the latent mode even if it doesn't

4451
02:49:59,750 --> 02:49:57,760
make a virus particle it still can have

4452
02:50:01,830 --> 02:49:59,760
fitness in the sense of having newly

4453
02:50:04,230 --> 02:50:01,840
infected cells

4454
02:50:05,750 --> 02:50:04,240
and the last thing i want to do here

4455
02:50:07,990 --> 02:50:05,760
i've probably moved a little bit too

4456
02:50:09,990 --> 02:50:08,000
quickly as others have noted it's hard

4457
02:50:12,230 --> 02:50:10,000
to know what the feedback is but i'm

4458
02:50:14,710 --> 02:50:12,240
happy to take questions which is in

4459
02:50:15,990 --> 02:50:14,720
calculating

4460
02:50:18,389 --> 02:50:16,000
these

4461
02:50:20,550 --> 02:50:18,399
values of are not i've assumed

4462
02:50:21,670 --> 02:50:20,560
dichotomous outcomes

4463
02:50:24,469 --> 02:50:21,680
either

4464
02:50:26,230 --> 02:50:24,479
lysis or latency it turns out

4465
02:50:28,550 --> 02:50:26,240
technically it gets much harder i'd say

4466
02:50:31,830 --> 02:50:28,560
conceptually gets much harder when there

4467
02:50:32,790 --> 02:50:31,840
can be a mix between modes and we know

4468
02:50:34,230 --> 02:50:32,800
that

4469
02:50:36,870 --> 02:50:34,240
phage lambda

4470
02:50:38,870 --> 02:50:36,880
temperphage in general latent viruses

4471
02:50:41,030 --> 02:50:38,880
can go out of the latent mode and then

4472
02:50:42,230 --> 02:50:41,040
initiate uh lysis and it's been quite

4473
02:50:44,469 --> 02:50:42,240
hard for us to figure out how to do

4474
02:50:47,030 --> 02:50:44,479
these calculations until recently

4475
02:50:48,150 --> 02:50:47,040
so i'm gonna now just in one slide

4476
02:50:49,670 --> 02:50:48,160
highlight something that's on the

4477
02:50:51,750 --> 02:50:49,680
bioarchive

4478
02:50:54,790 --> 02:50:51,760
which is we've been able to come up this

4479
02:50:56,870 --> 02:50:54,800
is a graphical way of depicting what we

4480
02:50:58,550 --> 02:50:56,880
think the right way to think about

4481
02:51:00,630 --> 02:50:58,560
fitness is

4482
02:51:03,030 --> 02:51:00,640
and there's a lot of diagrams here we

4483
02:51:06,630 --> 02:51:03,040
actually use these diagrams to calculate

4484
02:51:08,550 --> 02:51:06,640
the idea of the top line

4485
02:51:10,710 --> 02:51:08,560
is that this is a model in which e

4486
02:51:13,269 --> 02:51:10,720
stands for exposed the virus i is

4487
02:51:16,309 --> 02:51:13,279
actively infected via the virion and s

4488
02:51:19,190 --> 02:51:16,319
is a susceptible cell l is a lysogen

4489
02:51:21,510 --> 02:51:19,200
so p1 that first diagram says the cell

4490
02:51:23,269 --> 02:51:21,520
is exposed it goes infected makes a

4491
02:51:25,670 --> 02:51:23,279
virus that viruses

4492
02:51:27,910 --> 02:51:25,680
contacts a new susceptible cell and

4493
02:51:30,469 --> 02:51:27,920
makes a cycle the black to black says a

4494
02:51:33,269 --> 02:51:30,479
cycle is created horizontally we call

4495
02:51:34,870 --> 02:51:33,279
that a lytic loop but we also have a

4496
02:51:37,670 --> 02:51:34,880
lysogenic loop which is there's a

4497
02:51:40,150 --> 02:51:37,680
lysogen it doubles so the offspring is

4498
02:51:42,070 --> 02:51:40,160
the lysogen stills the virus that's

4499
02:51:44,469 --> 02:51:42,080
a lysogenic loop

4500
02:51:48,230 --> 02:51:44,479
but we can have something which is a

4501
02:51:50,630 --> 02:51:48,240
lysolytic loop which is the exposed cell

4502
02:51:53,429 --> 02:51:50,640
integrates the prophage comes out into

4503
02:51:56,790 --> 02:51:53,439
an active infection produces viruses and

4504
02:51:59,110 --> 02:51:56,800
goes back to e but passes through the

4505
02:52:01,110 --> 02:51:59,120
lysogenic loop

4506
02:52:02,550 --> 02:52:01,120
those numbers then we can calculate the

4507
02:52:03,830 --> 02:52:02,560
fitness associated with each we have to

4508
02:52:05,190 --> 02:52:03,840
add them up

4509
02:52:06,950 --> 02:52:05,200
but it turns out when we do the

4510
02:52:09,190 --> 02:52:06,960
calculations and to really understand

4511
02:52:11,590 --> 02:52:09,200
them once you start to mix loop we have

4512
02:52:13,110 --> 02:52:11,600
to think through two generations

4513
02:52:15,590 --> 02:52:13,120
but because we have to think through two

4514
02:52:17,670 --> 02:52:15,600
generations you can mix these modes and

4515
02:52:19,190 --> 02:52:17,680
they're all these diagrams here and also

4516
02:52:21,190 --> 02:52:19,200
explains why there's the power of one

4517
02:52:23,110 --> 02:52:21,200
half at the end we have to discount the

4518
02:52:24,790 --> 02:52:23,120
fact that we've looked over two

4519
02:52:25,750 --> 02:52:24,800
generations and we have to compare that

4520
02:52:28,630 --> 02:52:25,760
back

4521
02:52:30,309 --> 02:52:28,640
to the one generation case this might

4522
02:52:32,710 --> 02:52:30,319
seem a little complicated though it's

4523
02:52:35,349 --> 02:52:32,720
kind of appealing in certain ways

4524
02:52:37,349 --> 02:52:35,359
the advantage of it has been is that

4525
02:52:39,030 --> 02:52:37,359
irrespective of the population dynamic

4526
02:52:41,590 --> 02:52:39,040
model you write down

4527
02:52:43,590 --> 02:52:41,600
whether this exposed infected virus

4528
02:52:45,750 --> 02:52:43,600
model there's work by thomas byrne

4529
02:52:47,670 --> 02:52:45,760
gruber recently on a resource implicit

4530
02:52:49,429 --> 02:52:47,680
model with implicit infections and the

4531
02:52:51,110 --> 02:52:49,439
steward 11 model which is resource

4532
02:52:53,030 --> 02:52:51,120
explicit

4533
02:52:55,429 --> 02:52:53,040
all of these models it turns out have

4534
02:52:57,429 --> 02:52:55,439
the exact same formula but the

4535
02:52:59,590 --> 02:52:57,439
quantitative values differ depending on

4536
02:53:01,670 --> 02:52:59,600
particular details but these are the

4537
02:53:03,590 --> 02:53:01,680
combinations of ways in which you can

4538
02:53:05,030 --> 02:53:03,600
have these life cycles

4539
02:53:06,710 --> 02:53:05,040
and it turns out you can make

4540
02:53:08,950 --> 02:53:06,720
predictions they look more or less the

4541
02:53:10,790 --> 02:53:08,960
same when viewed in this way

4542
02:53:12,389 --> 02:53:10,800
so the takeaway here is

4543
02:53:13,590 --> 02:53:12,399
um if you're interested in having talked

4544
02:53:14,550 --> 02:53:13,600
more and you can read more on the

4545
02:53:16,389 --> 02:53:14,560
archive

4546
02:53:18,469 --> 02:53:16,399
that a loop-based approach decomposes

4547
02:53:19,990 --> 02:53:18,479
viral fitness into lytic lysogenic and

4548
02:53:21,510 --> 02:53:20,000
lysolytic loops so we really have

4549
02:53:23,830 --> 02:53:21,520
mechanisms that we can think about

4550
02:53:25,429 --> 02:53:23,840
rather than just a long algebraic mess

4551
02:53:27,349 --> 02:53:25,439
we can think about ways in which these

4552
02:53:29,429 --> 02:53:27,359
loops are contributing to viral fitness

4553
02:53:31,429 --> 02:53:29,439
which transcends model details and i

4554
02:53:33,990 --> 02:53:31,439
hope reveals some generic mechanisms for

4555
02:53:35,910 --> 02:53:34,000
the benefits of latency

4556
02:53:38,309 --> 02:53:35,920
and then the last thing i'll ask is what

4557
02:53:39,830 --> 02:53:38,319
is a virus i think the this project

4558
02:53:42,309 --> 02:53:39,840
collaboration previously with rachel

4559
02:53:44,550 --> 02:53:42,319
wood or mark young and the ongoing work

4560
02:53:46,230 --> 02:53:44,560
has has for me at least raised some new

4561
02:53:48,710 --> 02:53:46,240
questions which is i used to think of a

4562
02:53:50,630 --> 02:53:48,720
virus as a capsid

4563
02:53:52,550 --> 02:53:50,640
containing genetic material and

4564
02:53:54,150 --> 02:53:52,560
obligated intracellular parasite

4565
02:53:55,910 --> 02:53:54,160
but then you might think well maybe it's

4566
02:53:57,750 --> 02:53:55,920
the virus cell right a little infected

4567
02:53:59,190 --> 02:53:57,760
cell or maybe it's a lysosome

4568
02:54:00,870 --> 02:53:59,200
and i would actually say now that it's

4569
02:54:02,309 --> 02:54:00,880
really all of the above

4570
02:54:04,150 --> 02:54:02,319
that viral fitness in the environment

4571
02:54:06,309 --> 02:54:04,160
depends on measuring the present and

4572
02:54:08,070 --> 02:54:06,319
long-term value of infection but we have

4573
02:54:10,150 --> 02:54:08,080
to start thinking i think about the

4574
02:54:12,309 --> 02:54:10,160
entire viral life cycle whether it's

4575
02:54:14,230 --> 02:54:12,319
inside or outside hosts and i think

4576
02:54:16,389 --> 02:54:14,240
it'll take some time to figure this out

4577
02:54:17,750 --> 02:54:16,399
whether through theory experiments as

4578
02:54:19,830 --> 02:54:17,760
well as field work

4579
02:54:21,590 --> 02:54:19,840
and so with that i'll wrap up i think i

4580
02:54:23,030 --> 02:54:21,600
just have a few minutes left

4581
02:54:24,790 --> 02:54:23,040
again acknowledging some of the folks

4582
02:54:26,469 --> 02:54:24,800
here georgia tech

4583
02:54:28,230 --> 02:54:26,479
collaborators former postdocs michael

4584
02:54:30,230 --> 02:54:28,240
cortez and haria gulbadak who have their

4585
02:54:33,349 --> 02:54:30,240
own groups and mathematics at florida

4586
02:54:36,150 --> 02:54:33,359
state and you all lafayette uh

4587
02:54:38,309 --> 02:54:36,160
also at montana uh state university mark

4588
02:54:39,910 --> 02:54:38,319
young and ui you see rachel whitaker if

4589
02:54:41,910 --> 02:54:39,920
you want to read about the latest work

4590
02:54:44,070 --> 02:54:41,920
it's on the archive and there's probably

4591
02:54:45,910 --> 02:54:44,080
a lot more to see we have a

4592
02:54:47,830 --> 02:54:45,920
website twitter and also code data

4593
02:54:50,290 --> 02:54:47,840
information on the github site so thank

4594
02:55:03,830 --> 02:54:50,300
you for your attention

4595
02:55:06,309 --> 02:55:05,110
okay i don't know if there's time left

4596
02:55:07,429 --> 02:55:06,319
there's probably very little time left

4597
02:55:09,269 --> 02:55:07,439
for questions maybe just one or two

4598
02:55:13,590 --> 02:55:09,279
minutes

4599
02:55:17,190 --> 02:55:15,830
hey

4600
02:55:18,630 --> 02:55:17,200
go for it

4601
02:55:20,550 --> 02:55:18,640
all right thanks

4602
02:55:23,269 --> 02:55:20,560
josh i was just wondering about

4603
02:55:25,670 --> 02:55:23,279
situations where the lysogen becomes

4604
02:55:27,429 --> 02:55:25,680
inactivated during sort of one of these

4605
02:55:28,950 --> 02:55:27,439
infection loops and how you might

4606
02:55:30,950 --> 02:55:28,960
account for its fitness in that

4607
02:55:33,030 --> 02:55:30,960
situation like is it still a virus is it

4608
02:55:34,630 --> 02:55:33,040
no longer a virus

4609
02:55:36,710 --> 02:55:34,640
yeah so i mean there's lots of examples

4610
02:55:39,030 --> 02:55:36,720
of these defunct prophage and that's one

4611
02:55:41,670 --> 02:55:39,040
of the risks of staying in too long

4612
02:55:43,030 --> 02:55:41,680
and that certainly decreases if even

4613
02:55:44,550 --> 02:55:43,040
though we are counting fitness

4614
02:55:46,150 --> 02:55:44,560
vertically

4615
02:55:47,910 --> 02:55:46,160
there is a presumption here that at some

4616
02:55:50,150 --> 02:55:47,920
point the virus could still

4617
02:55:52,389 --> 02:55:50,160
get out and disentangle its fate and

4618
02:55:53,910 --> 02:55:52,399
when that stops happening we can have

4619
02:55:54,950 --> 02:55:53,920
that argument at what point that is and

4620
02:55:56,950 --> 02:55:54,960
maybe other people here are going to

4621
02:55:58,630 --> 02:55:56,960
talk about it that it stops being a

4622
02:56:00,790 --> 02:55:58,640
virus and maybe becomes some other kind

4623
02:56:03,190 --> 02:56:00,800
of genetic element but at least in our

4624
02:56:07,269 --> 02:56:03,200
case that would be a loss

4625
02:56:09,269 --> 02:56:07,279
because it's another way of losing the

4626
02:56:11,269 --> 02:56:09,279
viral genome and its ability to have

4627
02:56:13,190 --> 02:56:11,279
both routes at that point and then the

4628
02:56:14,870 --> 02:56:13,200
calculations we could modify but that i

4629
02:56:16,309 --> 02:56:14,880
would view not as positive for viral

4630
02:56:17,750 --> 02:56:16,319
fitness and siobhan might have something

4631
02:56:19,990 --> 02:56:17,760
to say about that

4632
02:56:21,910 --> 02:56:20,000
uh i i think there's a great pairing of

4633
02:56:24,950 --> 02:56:21,920
uh talks but i was actually thinking the

4634
02:56:27,510 --> 02:56:24,960
same thing that uh lewis was um

4635
02:56:29,510 --> 02:56:27,520
do you need to model the loss of uh

4636
02:56:31,110 --> 02:56:29,520
intact viruses due to

4637
02:56:33,110 --> 02:56:31,120
you know defunct prophages or is that

4638
02:56:35,030 --> 02:56:33,120
not uh important because you're not

4639
02:56:37,349 --> 02:56:35,040
modeling uh

4640
02:56:39,510 --> 02:56:37,359
inactive variants you know defunct

4641
02:56:40,630 --> 02:56:39,520
defective variants in the model yeah so

4642
02:56:42,550 --> 02:56:40,640
i mean at least at this point there

4643
02:56:43,349 --> 02:56:42,560
would be probably another level to do

4644
02:56:44,630 --> 02:56:43,359
but

4645
02:56:47,510 --> 02:56:44,640
within the

4646
02:56:49,990 --> 02:56:47,520
the lysogenic the lysogenic phase there

4647
02:56:52,230 --> 02:56:50,000
is a loss term so i view that as an

4648
02:56:54,230 --> 02:56:52,240
additional loss term whether or not that

4649
02:56:56,710 --> 02:56:54,240
still confers immunity is that cell now

4650
02:56:59,510 --> 02:56:56,720
susceptible is it you know maybe it's

4651
02:57:01,670 --> 02:56:59,520
immune but it can't transmit we haven't

4652
02:57:03,510 --> 02:57:01,680
gone into that level of detail and i

4653
02:57:05,750 --> 02:57:03,520
agree that that is a nice challenge to

4654
02:57:07,190 --> 02:57:05,760
think about but at least we i think we

4655
02:57:09,830 --> 02:57:07,200
should think of that as a loss in terms

4656
02:57:16,469 --> 02:57:09,840
of the the average fitness that it's

4657
02:57:16,479 --> 02:57:27,910
okay i think what a time thank you

4658
02:57:32,230 --> 02:57:30,469
i guess we'll move on to you siobhan now

4659
02:57:34,070 --> 02:57:32,240
okay i've got zoom open i'm trying to

4660
02:57:45,510 --> 02:57:34,080
share screen

4661
02:57:48,469 --> 02:57:46,710
am i sharing the screen and i don't

4662
02:57:50,790 --> 02:57:48,479
think i am

4663
02:57:52,790 --> 02:57:50,800
now if you

4664
02:57:54,630 --> 02:57:52,800
mouse over the bottom of the screen

4665
02:57:57,510 --> 02:57:54,640
there should be a share button that's

4666
02:57:59,670 --> 02:57:57,520
green and you click on that oh sorry i

4667
02:58:11,269 --> 02:57:59,680
was doing it from my zoom app that was

4668
02:58:15,429 --> 02:58:12,710
all right

4669
02:58:16,630 --> 02:58:15,439
do you guys see a screen

4670
02:58:19,429 --> 02:58:16,640
yes we do

4671
02:58:21,349 --> 02:58:19,439
okay

4672
02:58:23,750 --> 02:58:21,359
all right so i do think that uh

4673
02:58:25,429 --> 02:58:23,760
thematically it works very well uh to go

4674
02:58:26,870 --> 02:58:25,439
from josh's talk to this one because

4675
02:58:31,030 --> 02:58:26,880
it's about

4676
02:58:33,030 --> 02:58:31,040
what a virus chooses to do not in a um

4677
02:58:35,269 --> 02:58:33,040
you know philosophical

4678
02:58:38,710 --> 02:58:35,279
uh human choice way but genetically what

4679
02:58:41,670 --> 02:58:40,710
and a virus need not

4680
02:58:50,150 --> 02:58:41,680
uh

4681
02:58:55,510 --> 02:58:52,710
a virus if it's replicating in a host is

4682
02:58:57,190 --> 02:58:55,520
already doing a pretty good job

4683
02:58:58,870 --> 02:58:57,200
it's making children it can have a

4684
02:59:00,950 --> 02:58:58,880
pretty good life if there are a lot of

4685
02:59:02,469 --> 02:59:00,960
uh hosts around

4686
02:59:05,110 --> 02:59:02,479
there's no need for a virus to think

4687
02:59:08,309 --> 02:59:05,120
about having an expanded host range it

4688
02:59:11,190 --> 02:59:08,319
wouldn't be relevant in its life

4689
02:59:12,870 --> 02:59:11,200
however um when viruses do think of

4690
02:59:14,710 --> 02:59:12,880
changing their host range sometimes they

4691
02:59:16,389 --> 02:59:14,720
spill over into humans

4692
02:59:18,630 --> 02:59:16,399
and then they become headline grabbing

4693
02:59:20,230 --> 02:59:18,640
viruses

4694
02:59:21,990 --> 02:59:20,240
a lot of what we know about host range

4695
02:59:23,349 --> 02:59:22,000
evolution comes from human infecting

4696
02:59:24,790 --> 02:59:23,359
viruses because we've studied them

4697
02:59:27,510 --> 02:59:24,800
intensively

4698
02:59:29,590 --> 02:59:27,520
intriguingly most emergent viruses in

4699
02:59:31,990 --> 02:59:29,600
humans need a host range mutation but

4700
02:59:33,670 --> 02:59:32,000
generally only about one point mutation

4701
02:59:35,349 --> 02:59:33,680
to be able a new host to infect new

4702
02:59:36,550 --> 02:59:35,359
hosts

4703
02:59:38,550 --> 02:59:36,560
uh the

4704
02:59:42,389 --> 02:59:38,560
human infecting viruses i'm showing here

4705
02:59:44,309 --> 02:59:42,399
are rna-based this is not a fluke rna

4706
02:59:46,950 --> 02:59:44,319
viruses are the most emergent

4707
02:59:49,429 --> 02:59:46,960
pathogens in humans in part because rna

4708
02:59:51,670 --> 02:59:49,439
viruses have high mutation rates

4709
02:59:53,510 --> 02:59:51,680
and sometimes those mutations will have

4710
02:59:55,269 --> 02:59:53,520
an effect on host range

4711
02:59:57,590 --> 02:59:55,279
so i'm showing you a figure here

4712
02:59:59,269 --> 02:59:57,600
that has on the y-axis mutation rate in

4713
03:00:00,469 --> 02:59:59,279
per site in the genome per genomic

4714
03:00:03,349 --> 03:00:00,479
replication

4715
03:00:05,110 --> 03:00:03,359
and along the x-axis genome size in log

4716
03:00:06,309 --> 03:00:05,120
of kilobases

4717
03:00:08,389 --> 03:00:06,319
and i have

4718
03:00:10,710 --> 03:00:08,399
a stock art representing different kinds

4719
03:00:13,030 --> 03:00:10,720
of organisms a mouse for mammals

4720
03:00:15,190 --> 03:00:13,040
bacteria a phage for big double-stranded

4721
03:00:17,910 --> 03:00:15,200
dna viruses some

4722
03:00:20,389 --> 03:00:17,920
of arvin's uh presented beautifully on

4723
03:00:22,790 --> 03:00:20,399
the small single-stranded dna viruses

4724
03:00:24,710 --> 03:00:22,800
here rna viruses do have a range that's

4725
03:00:26,950 --> 03:00:24,720
why we have a lengthy ebola showing a

4726
03:00:28,630 --> 03:00:26,960
range of rna virus mutation rates and up

4727
03:00:29,830 --> 03:00:28,640
here we have a viroid which is not viral

4728
03:00:31,910 --> 03:00:29,840
so we're not going to talk about it

4729
03:00:33,750 --> 03:00:31,920
today

4730
03:00:35,590 --> 03:00:33,760
rna viruses have high mutation rates

4731
03:00:38,309 --> 03:00:35,600
sometimes those mutations are going to

4732
03:00:41,269 --> 03:00:38,319
infect host range

4733
03:00:42,710 --> 03:00:41,279
what are the advantages of having

4734
03:00:44,469 --> 03:00:42,720
mutations that affect host range in your

4735
03:00:47,030 --> 03:00:44,479
population what are the constraints of

4736
03:00:49,830 --> 03:00:47,040
having a host range mutation i've been

4737
03:00:52,070 --> 03:00:49,840
studying this in a model rna virus

4738
03:00:53,750 --> 03:00:52,080
system but there are a number of groups

4739
03:00:56,870 --> 03:00:53,760
have studied this even in some human

4740
03:00:58,870 --> 03:00:56,880
infecting systems generally host range

4741
03:01:03,110 --> 03:00:58,880
has been studied in the modern era in

4742
03:01:06,230 --> 03:01:03,120
rna viruses more than in dna viruses

4743
03:01:09,190 --> 03:01:06,240
there's an obvious relationship between

4744
03:01:11,510 --> 03:01:09,200
uh host range in viruses which is a a

4745
03:01:14,870 --> 03:01:11,520
good proxy for the resource niche breath

4746
03:01:18,309 --> 03:01:14,880
of viruses and how many virus

4747
03:01:20,790 --> 03:01:18,319
progeny that we expect viruses to make

4748
03:01:22,550 --> 03:01:20,800
uh in each given host i'm not going

4749
03:01:24,550 --> 03:01:22,560
quite as detailed back into the

4750
03:01:26,070 --> 03:01:24,560
mathematical literature as josh but this

4751
03:01:27,910 --> 03:01:26,080
model that a jack of all trades is a

4752
03:01:29,670 --> 03:01:27,920
master of none has been articulated in

4753
03:01:31,910 --> 03:01:29,680
the ecological literature including

4754
03:01:35,190 --> 03:01:31,920
mathematically since the 60s that

4755
03:01:37,269 --> 03:01:35,200
basically if you are a a virus whose

4756
03:01:39,670 --> 03:01:37,279
niche is being illustrated by the red

4757
03:01:42,070 --> 03:01:39,680
line you're necessarily we're going to

4758
03:01:43,830 --> 03:01:42,080
call you a specialist because you infect

4759
03:01:46,230 --> 03:01:43,840
a narrow range of hosts and you're

4760
03:01:47,990 --> 03:01:46,240
better at infecting those hosts than the

4761
03:01:49,990 --> 03:01:48,000
pink virus whose we're calling the

4762
03:01:51,429 --> 03:01:50,000
generalist these are relative terms you

4763
03:01:52,550 --> 03:01:51,439
can't possibly

4764
03:01:54,070 --> 03:01:52,560
call something a specialist or

4765
03:01:56,070 --> 03:01:54,080
generalist without having another one to

4766
03:01:59,750 --> 03:01:56,080
compare it to there's no objective

4767
03:02:00,710 --> 03:01:59,760
definition for specialism or journalism

4768
03:02:11,349 --> 03:02:00,720
i

4769
03:02:13,030 --> 03:02:11,359
there's a

4770
03:02:15,510 --> 03:02:13,040
similar amount of fitness under each

4771
03:02:18,710 --> 03:02:15,520
curve in total

4772
03:02:20,389 --> 03:02:18,720
my pop culture metaphor for our uh the

4773
03:02:22,630 --> 03:02:20,399
jack of all trades is the master of none

4774
03:02:25,030 --> 03:02:22,640
is aging if anyone has suggestions uh

4775
03:02:27,269 --> 03:02:25,040
for a more updated 2000 and teens or

4776
03:02:28,389 --> 03:02:27,279
beyond uh metaphor please put them in

4777
03:02:29,910 --> 03:02:28,399
chat

4778
03:02:32,550 --> 03:02:29,920
what i tend to think about it is if you

4779
03:02:34,710 --> 03:02:32,560
are specializing on a very specific uh

4780
03:02:36,790 --> 03:02:34,720
kind of prey you can be very very good

4781
03:02:38,309 --> 03:02:36,800
at catching it and uh keeping your

4782
03:02:40,070 --> 03:02:38,319
narrow focus in the short time period

4783
03:02:42,469 --> 03:02:40,080
that that prey may be around

4784
03:02:44,630 --> 03:02:42,479
but a generalist isn't necessarily

4785
03:02:46,469 --> 03:02:44,640
tracking down one particular way of

4786
03:02:48,070 --> 03:02:46,479
getting points the generalist is aware

4787
03:02:49,670 --> 03:02:48,080
that there are lots of ways to get

4788
03:02:51,110 --> 03:02:49,680
points in the pac-man game and so

4789
03:02:52,630 --> 03:02:51,120
they're not uh

4790
03:02:54,309 --> 03:02:52,640
going to necessarily catch as many

4791
03:02:55,429 --> 03:02:54,319
ghosts but they're going to get perhaps

4792
03:02:56,710 --> 03:02:55,439
more points

4793
03:03:01,349 --> 03:02:56,720
by

4794
03:03:07,269 --> 03:03:04,630
in viruses as i uh had said verbally

4795
03:03:08,950 --> 03:03:07,279
before the specialist we expect has more

4796
03:03:10,309 --> 03:03:08,960
offspring from each infected host when

4797
03:03:12,469 --> 03:03:10,319
they get into a host they're more

4798
03:03:13,429 --> 03:03:12,479
productive they get more fitness out of

4799
03:03:14,550 --> 03:03:13,439
it

4800
03:03:16,870 --> 03:03:14,560
uh the

4801
03:03:18,950 --> 03:03:16,880
pink generalist we say

4802
03:03:20,870 --> 03:03:18,960
has a different set of advantages it

4803
03:03:22,630 --> 03:03:20,880
doesn't have to wait until it finds a

4804
03:03:24,150 --> 03:03:22,640
suitable host and have reduced search

4805
03:03:25,750 --> 03:03:24,160
time it can come across lots of

4806
03:03:28,150 --> 03:03:25,760
different hosts and have offspring in

4807
03:03:29,190 --> 03:03:28,160
them but we expect it not to have as

4808
03:03:30,710 --> 03:03:29,200
many

4809
03:03:32,309 --> 03:03:30,720
offspring in each host

4810
03:03:34,550 --> 03:03:32,319
i'm going to talk about three stories

4811
03:03:36,150 --> 03:03:34,560
today the first is a blast from the past

4812
03:03:37,349 --> 03:03:36,160
part of my thesis work which actually

4813
03:03:38,550 --> 03:03:37,359
looked at this

4814
03:03:40,950 --> 03:03:38,560
in

4815
03:03:43,030 --> 03:03:40,960
an rna experimental system does a larger

4816
03:03:45,030 --> 03:03:43,040
host range in and of itself reduce the

4817
03:03:46,469 --> 03:03:45,040
fitness on the usual host do we see that

4818
03:03:48,710 --> 03:03:46,479
just the acquisition of a host range

4819
03:03:50,070 --> 03:03:48,720
mutation brings your fitness down and

4820
03:03:53,030 --> 03:03:50,080
puts you on the generalist curve

4821
03:03:54,950 --> 03:03:53,040
compared to the specialist curve

4822
03:03:57,349 --> 03:03:54,960
so the system i work with is the rna

4823
03:03:59,269 --> 03:03:57,359
phage 56 which is a fantastic

4824
03:04:00,870 --> 03:03:59,279
model system in experimental evolution

4825
03:04:02,870 --> 03:04:00,880
it's incredibly popular because even

4826
03:04:05,349 --> 03:04:02,880
though it is a bacteriophage

4827
03:04:08,469 --> 03:04:05,359
it looks like a eukaryotic virus it has

4828
03:04:10,550 --> 03:04:08,479
a lipid coat very only physics and its

4829
03:04:13,670 --> 03:04:10,560
relatives and family sister verde have a

4830
03:04:16,870 --> 03:04:13,680
lipid code only cystiviruses have a

4831
03:04:18,389 --> 03:04:16,880
segmented genome there is a three

4832
03:04:20,150 --> 03:04:18,399
tripartite

4833
03:04:21,670 --> 03:04:20,160
segmented genome

4834
03:04:24,070 --> 03:04:21,680
segmentation was thought to evolve to

4835
03:04:25,750 --> 03:04:24,080
deal with eukaryotic cellular machinery

4836
03:04:27,670 --> 03:04:25,760
and their preferences so it doesn't make

4837
03:04:29,030 --> 03:04:27,680
a lot of sense that a tripartite genome

4838
03:04:31,750 --> 03:04:29,040
would have evolved in prokaryotic

4839
03:04:34,870 --> 03:04:31,760
viruses and in terms of phylogenetic

4840
03:04:37,269 --> 03:04:34,880
evidence uh the rna-dependent rna

4841
03:04:39,590 --> 03:04:37,279
polymerase which is the only shared gene

4842
03:04:41,670 --> 03:04:39,600
across all rna viruses when you do the

4843
03:04:43,670 --> 03:04:41,680
phylogenetics of that gene five six

4844
03:04:46,389 --> 03:04:43,680
groups with eukaryote infecting rio

4845
03:04:48,389 --> 03:04:46,399
viruses and not with other rna phages

4846
03:04:50,630 --> 03:04:48,399
it's got a pretty small genome

4847
03:04:53,910 --> 03:04:50,640
and it has a high mutation rate compared

4848
03:04:56,469 --> 03:04:53,920
to the double-stranded dna viruses that

4849
03:04:58,630 --> 03:04:56,479
uh were being envisioned in josh's talk

4850
03:05:00,870 --> 03:04:58,640
but because it's a double-stranded rna

4851
03:05:05,990 --> 03:05:00,880
virus perhaps it has the lowest measured

4852
03:05:09,750 --> 03:05:07,510
physics is a phage it infects

4853
03:05:12,389 --> 03:05:09,760
pseudomonas bacteria i have a phylogeny

4854
03:05:14,790 --> 03:05:12,399
here of the very broad pseudomonas

4855
03:05:17,670 --> 03:05:14,800
phylogeny outgroup rooted with e coli

4856
03:05:19,670 --> 03:05:17,680
there are roughly uh five fairly

4857
03:05:22,150 --> 03:05:19,680
distinct groups that and i've given you

4858
03:05:23,670 --> 03:05:22,160
a uh characteristic species name to

4859
03:05:25,910 --> 03:05:23,680
represent each of them

4860
03:05:28,309 --> 03:05:25,920
five sixes normal hosts are found in the

4861
03:05:30,790 --> 03:05:28,319
serengeti clay it was isolated as a

4862
03:05:32,950 --> 03:05:30,800
potential bio-control agent or agent for

4863
03:05:34,710 --> 03:05:32,960
piecering pathomarphasiolicola the cause

4864
03:05:37,750 --> 03:05:34,720
of halo bean blight

4865
03:05:38,870 --> 03:05:37,760
uh you can easily get physics to infect

4866
03:05:41,269 --> 03:05:38,880
other

4867
03:05:43,190 --> 03:05:41,279
uh cp's ringy pathobars

4868
03:05:45,349 --> 03:05:43,200
when they have host range mutations and

4869
03:05:48,710 --> 03:05:45,359
there's one other known alternative host

4870
03:05:51,190 --> 03:05:48,720
you can use for 56 it is called

4871
03:05:53,670 --> 03:05:51,200
pseudomonas pseudoalkalogenesis era that

4872
03:05:55,349 --> 03:05:53,680
stands for east river isolate a it was

4873
03:05:57,830 --> 03:05:55,359
dredged up from the east river in the

4874
03:05:59,349 --> 03:05:57,840
1970s by molecular biologists working on

4875
03:06:02,230 --> 03:05:59,359
physics and we don't know much about its

4876
03:06:07,910 --> 03:06:05,030
so a long time ago i isolated host range

4877
03:06:10,950 --> 03:06:07,920
mutants uh on two piece ring pathobars

4878
03:06:14,150 --> 03:06:10,960
um atrophosians and tomato and on era

4879
03:06:16,550 --> 03:06:14,160
and i sequenced using sanger sequencing

4880
03:06:18,150 --> 03:06:16,560
to find that each one of my mutants had

4881
03:06:20,630 --> 03:06:18,160
one of nine different mutations in the

4882
03:06:23,750 --> 03:06:20,640
same protein in 5 6 this

4883
03:06:25,510 --> 03:06:23,760
p3 host attachment protein so it was

4884
03:06:28,710 --> 03:06:25,520
already a target that we would have

4885
03:06:29,830 --> 03:06:28,720
expected and had been known for 30 years

4886
03:06:32,710 --> 03:06:29,840
was a place where you could get host

4887
03:06:35,590 --> 03:06:32,720
range mutants for 5 secs

4888
03:06:37,590 --> 03:06:35,600
of the 9 distinct mutations i found

4889
03:06:39,830 --> 03:06:37,600
three of them enabled physics to infect

4890
03:06:42,150 --> 03:06:39,840
atrophasians and dra

4891
03:06:45,269 --> 03:06:42,160
five allowed it to infect tomato and dra

4892
03:06:46,870 --> 03:06:45,279
and one allowed it to infect era alone

4893
03:06:49,269 --> 03:06:46,880
i then measured their fitness on the

4894
03:06:51,110 --> 03:06:49,279
original host p serinki patho aphasia

4895
03:06:52,870 --> 03:06:51,120
licola to see if carrying these

4896
03:06:54,710 --> 03:06:52,880
mutations already

4897
03:06:57,269 --> 03:06:54,720
led to a fitness cost

4898
03:06:59,990 --> 03:06:57,279
and i measured fitnesses as a 24-hour

4899
03:07:01,830 --> 03:07:00,000
paired growth assay where the wild-type

4900
03:07:02,790 --> 03:07:01,840
virus and the host range mutant could

4901
03:07:05,030 --> 03:07:02,800
grow

4902
03:07:06,550 --> 03:07:05,040
side by side and we could see which one

4903
03:07:08,790 --> 03:07:06,560
of them left more descendants after that

4904
03:07:10,950 --> 03:07:08,800
much time

4905
03:07:12,630 --> 03:07:10,960
and in this figure the y-axis is the

4906
03:07:14,870 --> 03:07:12,640
fitness on the original host pseudomonas

4907
03:07:16,469 --> 03:07:14,880
serenity path of our phaseolicula the

4908
03:07:18,950 --> 03:07:16,479
fitness of the wild type ancestor is

4909
03:07:20,790 --> 03:07:18,960
shown by the dotted line at one

4910
03:07:22,150 --> 03:07:20,800
across the x-axis you have the nine

4911
03:07:24,309 --> 03:07:22,160
different mutations

4912
03:07:25,990 --> 03:07:24,319
in p3 that i found in that study the

4913
03:07:29,750 --> 03:07:26,000
color coding tells you what the host

4914
03:07:32,230 --> 03:07:29,760
range of the descendant of viruses are

4915
03:07:35,429 --> 03:07:32,240
red for infecting tomato and era blue

4916
03:07:37,269 --> 03:07:35,439
for atrophos black for era

4917
03:07:39,910 --> 03:07:37,279
what should be clear from here is that

4918
03:07:41,750 --> 03:07:39,920
most of the time but not all of the time

4919
03:07:43,750 --> 03:07:41,760
we see that there is an immediate loss

4920
03:07:45,670 --> 03:07:43,760
in fitness on the original host just for

4921
03:07:47,429 --> 03:07:45,680
carrying a host range mutation there's

4922
03:07:49,429 --> 03:07:47,439
been no ecological history there's been

4923
03:07:51,910 --> 03:07:49,439
no time for a lot of natural selection

4924
03:07:54,389 --> 03:07:51,920
to occur in a novel host but just having

4925
03:07:56,309 --> 03:07:54,399
that flexibility in being able to attach

4926
03:07:58,710 --> 03:07:56,319
and infect a couple of different hosts

4927
03:08:00,950 --> 03:07:58,720
already is giving you an immeasurable

4928
03:08:03,030 --> 03:08:00,960
fitness cost on your original host two

4929
03:08:06,469 --> 03:08:03,040
of our nine mutations did not have a

4930
03:08:09,110 --> 03:08:06,479
statistically detectable uh cost in

4931
03:08:11,349 --> 03:08:09,120
on the original host as other people

4932
03:08:13,269 --> 03:08:11,359
have done similar studies in other

4933
03:08:15,590 --> 03:08:13,279
systems including human viruses we see

4934
03:08:17,429 --> 03:08:15,600
the same pattern most of the time we see

4935
03:08:19,990 --> 03:08:17,439
a cost an explicit antagonistic

4936
03:08:22,309 --> 03:08:20,000
cliotropy but there seem to be a couple

4937
03:08:24,150 --> 03:08:22,319
of ways that viruses can do this

4938
03:08:26,710 --> 03:08:24,160
where we don't detect a cost in the lab

4939
03:08:29,110 --> 03:08:26,720
of having carrying around an extra

4940
03:08:30,469 --> 03:08:29,120
ability to have a wider host range

4941
03:08:32,550 --> 03:08:30,479
i'm going to take two of these

4942
03:08:35,030 --> 03:08:32,560
particular host range mutations further

4943
03:08:37,750 --> 03:08:35,040
into the next study uh one from the

4944
03:08:40,710 --> 03:08:37,760
n-terminal end of uh the p3 protein one

4945
03:08:43,510 --> 03:08:40,720
from closer to the c-terminal end

4946
03:08:46,309 --> 03:08:43,520
ehe and g515s is what i won't refer to

4947
03:08:49,830 --> 03:08:48,070
so now we know that having a host range

4948
03:08:51,670 --> 03:08:49,840
mutation in and of itself can cause a

4949
03:08:54,550 --> 03:08:51,680
fitness effect but how does having a

4950
03:08:56,550 --> 03:08:54,560
host stream mutation affect a virus's

4951
03:08:58,950 --> 03:08:56,560
ability to jump into another novel host

4952
03:09:00,309 --> 03:08:58,960
how does it affect serial host shifting

4953
03:09:02,710 --> 03:09:00,319
so we have two

4954
03:09:06,150 --> 03:09:02,720
mutants that infect uh

4955
03:09:07,670 --> 03:09:06,160
are phaseolicula tomato and era a wild

4956
03:09:09,670 --> 03:09:07,680
type that only infects the original host

4957
03:09:11,830 --> 03:09:09,680
phaseolicula and we studied them in a

4958
03:09:14,230 --> 03:09:11,840
couple of different ways to measure the

4959
03:09:16,469 --> 03:09:14,240
mutational spectrum of how each of these

4960
03:09:18,150 --> 03:09:16,479
three strains can get into a third host

4961
03:09:19,590 --> 03:09:18,160
atrophasians

4962
03:09:21,990 --> 03:09:19,600
uh the way i'm going to show you results

4963
03:09:24,710 --> 03:09:22,000
from is from illumina sequencing we grew

4964
03:09:26,870 --> 03:09:24,720
up a high tider lysate of the virus on

4965
03:09:29,030 --> 03:09:26,880
the last host it had experienced so

4966
03:09:30,550 --> 03:09:29,040
either the original host or

4967
03:09:31,510 --> 03:09:30,560
in this case host tomato and those two

4968
03:09:32,389 --> 03:09:31,520
strains

4969
03:09:34,550 --> 03:09:32,399
uh

4970
03:09:36,630 --> 03:09:34,560
that was our before population we then

4971
03:09:39,750 --> 03:09:36,640
took a sample of that put the rest of it

4972
03:09:41,750 --> 03:09:39,760
onto a plate of atrophasians and uh let

4973
03:09:43,349 --> 03:09:41,760
it grow and whatever plaques grew up we

4974
03:09:45,910 --> 03:09:43,359
harvested them and isolated their

4975
03:09:47,830 --> 03:09:45,920
genomes we now had two uh populations of

4976
03:09:49,910 --> 03:09:47,840
viruses before and after exposure to

4977
03:09:52,309 --> 03:09:49,920
atrophasians and we threw that onto

4978
03:09:54,790 --> 03:09:52,319
aluminum i seek

4979
03:09:56,950 --> 03:09:54,800
and the results we got are shown here on

4980
03:09:59,670 --> 03:09:56,960
the y-axis i'm showing you the change in

4981
03:10:02,150 --> 03:09:59,680
shannon entropy so what i'm showing you

4982
03:10:04,229 --> 03:10:02,160
is the amount of polymorphism at the

4983
03:10:06,870 --> 03:10:04,239
different sites in this case in the m

4984
03:10:09,750 --> 03:10:06,880
segment this is representing 4 000 ish

4985
03:10:10,630 --> 03:10:09,760
bases in the m segment

4986
03:10:13,910 --> 03:10:10,640
the

4987
03:10:15,670 --> 03:10:13,920
after exposure atrophasians minus uh

4988
03:10:17,429 --> 03:10:15,680
prior to exposure to atrophos so

4989
03:10:19,670 --> 03:10:17,439
anything you're seeing above the zero

4990
03:10:21,429 --> 03:10:19,680
line which is represented by most of the

4991
03:10:23,910 --> 03:10:21,439
genome that those are mutations that

4992
03:10:26,790 --> 03:10:23,920
were over represented in the after

4993
03:10:28,389 --> 03:10:26,800
atrophasians exposure rather than before

4994
03:10:30,790 --> 03:10:28,399
i've given you a bit of shading to show

4995
03:10:33,110 --> 03:10:30,800
you where the p3 host attachment protein

4996
03:10:34,870 --> 03:10:33,120
is on the medium segment

4997
03:10:37,110 --> 03:10:34,880
the first thing you should see is that

4998
03:10:40,070 --> 03:10:37,120
we're not seeing a lot of

4999
03:10:43,030 --> 03:10:40,080
positive changes in shannon entropy

5000
03:10:44,389 --> 03:10:43,040
outside of the p3 region we're seeing a

5001
03:10:45,990 --> 03:10:44,399
lot of the host range mutations are

5002
03:10:47,670 --> 03:10:46,000
really happening there

5003
03:10:50,710 --> 03:10:47,680
also you should be able to tell that

5004
03:10:52,550 --> 03:10:50,720
there's more diverse sites associated

5005
03:10:54,469 --> 03:10:52,560
with enrichment for the wild type

5006
03:10:57,990 --> 03:10:54,479
population on the top rather than the

5007
03:10:59,830 --> 03:10:58,000
ehg or the g515s populations below the

5008
03:11:02,229 --> 03:10:59,840
wild type had more different ways to

5009
03:11:04,070 --> 03:11:02,239
infect atrophasians than the two strains

5010
03:11:06,790 --> 03:11:04,080
that already had a host range mutation

5011
03:11:08,070 --> 03:11:06,800
in their p3 gene

5012
03:11:09,990 --> 03:11:08,080
i'm showing you just the results from

5013
03:11:11,750 --> 03:11:10,000
illumina we also did this with

5014
03:11:13,830 --> 03:11:11,760
painstaking cloning

5015
03:11:15,830 --> 03:11:13,840
and sanger sequencing and when we did

5016
03:11:18,150 --> 03:11:15,840
that approach with groups of 50

5017
03:11:21,030 --> 03:11:18,160
individual mutants we found that

5018
03:11:23,030 --> 03:11:21,040
about 20 of the clones we pulled up from

5019
03:11:25,670 --> 03:11:23,040
phi 6 wild-type didn't have any

5020
03:11:27,590 --> 03:11:25,680
mutations in their p3 gene

5021
03:11:29,269 --> 03:11:27,600
we were surprised by this that was a

5022
03:11:31,030 --> 03:11:29,279
really high result occasionally that's

5023
03:11:33,030 --> 03:11:31,040
happened in five six studies in the past

5024
03:11:35,590 --> 03:11:33,040
but it's been one out of forty two out

5025
03:11:37,670 --> 03:11:35,600
of a hundred but it was closer to one

5026
03:11:39,429 --> 03:11:37,680
out of five in this study

5027
03:11:40,950 --> 03:11:39,439
and the illumina sequencing results gave

5028
03:11:42,070 --> 03:11:40,960
us some perspective of what was

5029
03:11:43,429 --> 03:11:42,080
happening there

5030
03:11:45,429 --> 03:11:43,439
because we got to see that there was

5031
03:11:48,070 --> 03:11:45,439
similar enrichment uh in the small

5032
03:11:52,469 --> 03:11:48,080
segment in uh for five six wild type but

5033
03:11:54,790 --> 03:11:52,479
not for five six ehg or 5 6 g515s

5034
03:11:56,229 --> 03:11:54,800
no part none of the genes on the small

5035
03:11:58,950 --> 03:11:56,239
segment have ever been associated with

5036
03:12:00,710 --> 03:11:58,960
host range and very intriguingly the

5037
03:12:03,349 --> 03:12:00,720
gene that has the most

5038
03:12:04,870 --> 03:12:03,359
over-represented sites both in

5039
03:12:06,309 --> 03:12:04,880
our luminous sequencing and once we got

5040
03:12:08,070 --> 03:12:06,319
these results we went back and we did

5041
03:12:10,389 --> 03:12:08,080
sanger sequencing on our clones we

5042
03:12:12,229 --> 03:12:10,399
confirmed that they had

5043
03:12:15,590 --> 03:12:12,239
single mutations or in some cases double

5044
03:12:16,550 --> 03:12:15,600
mutations in the p12 gene on the small

5045
03:12:19,670 --> 03:12:16,560
segment

5046
03:12:23,030 --> 03:12:19,680
p12 is a protein that's not even in the

5047
03:12:25,190 --> 03:12:23,040
fully assembled and articulated uh five

5048
03:12:27,269 --> 03:12:25,200
six variant it's not part of the

5049
03:12:28,710 --> 03:12:27,279
structure of the of the variant so this

5050
03:12:31,349 --> 03:12:28,720
is a really interesting

5051
03:12:33,110 --> 03:12:31,359
result that there is this way that so

5052
03:12:35,990 --> 03:12:33,120
the 5 6 wild type can enhance its host

5053
03:12:37,910 --> 03:12:36,000
range possibly in helping it get out of

5054
03:12:39,990 --> 03:12:37,920
that first p uh first infected

5055
03:12:41,910 --> 03:12:40,000
atrophoscene cell we don't have any

5056
03:12:44,309 --> 03:12:41,920
we're just speculating at this point but

5057
03:12:45,510 --> 03:12:44,319
those pathways appear to be closed off

5058
03:12:47,349 --> 03:12:45,520
to

5059
03:12:52,469 --> 03:12:47,359
the five six strings that already have a

5060
03:12:56,550 --> 03:12:54,870
all in all wild type just has a lot of

5061
03:12:58,710 --> 03:12:56,560
different ways to get into atrophasians

5062
03:13:01,429 --> 03:12:58,720
having a host range mutation is limiting

5063
03:13:03,030 --> 03:13:01,439
you already and this is clearly due to

5064
03:13:04,630 --> 03:13:03,040
epistasis and interaction amongst

5065
03:13:06,389 --> 03:13:04,640
mutations the mutations that are

5066
03:13:08,630 --> 03:13:06,399
conferring um the ability to infect

5067
03:13:10,309 --> 03:13:08,640
atrophasians for the wild type aren't

5068
03:13:13,510 --> 03:13:10,319
necessarily working for those that

5069
03:13:15,830 --> 03:13:13,520
already have a mutation in their p3 gene

5070
03:13:18,070 --> 03:13:15,840
we assume that this is a problem of p3

5071
03:13:19,269 --> 03:13:18,080
structural stability that if you have a

5072
03:13:21,269 --> 03:13:19,279
tweak that

5073
03:13:24,150 --> 03:13:21,279
allows you to expand your host range and

5074
03:13:26,150 --> 03:13:24,160
get into host tomato another tweak not

5075
03:13:27,910 --> 03:13:26,160
as many of those secondary tweaks can

5076
03:13:29,510 --> 03:13:27,920
are tolerated even though they would

5077
03:13:31,349 --> 03:13:29,520
allow you to maybe get into another host

5078
03:13:33,349 --> 03:13:31,359
it may be reducing very instability in

5079
03:13:35,590 --> 03:13:33,359
some way shape or form

5080
03:13:38,630 --> 03:13:35,600
this is potentially a more generalizable

5081
03:13:40,550 --> 03:13:38,640
thing beyond phi 6 while we see zoonotic

5082
03:13:43,110 --> 03:13:40,560
uh spillover from

5083
03:13:45,429 --> 03:13:43,120
a common source population into

5084
03:13:48,229 --> 03:13:45,439
other hosts a lot serial host shifting

5085
03:13:50,630 --> 03:13:48,239
of a bird flu going into

5086
03:13:52,389 --> 03:13:50,640
a horse and then going into a dog from

5087
03:13:54,550 --> 03:13:52,399
the horse which has happened for

5088
03:13:56,950 --> 03:13:54,560
influenza those kinds of sequential host

5089
03:13:58,229 --> 03:13:56,960
shiftings are rarer so

5090
03:13:59,510 --> 03:13:58,239
epistatic interactions amongst

5091
03:14:02,870 --> 03:13:59,520
two-string mutations might be a

5092
03:14:03,750 --> 03:14:02,880
generalizable problem for viruses

5093
03:14:05,830 --> 03:14:03,760
again

5094
03:14:07,830 --> 03:14:05,840
this is a fairly short-term scale that

5095
03:14:10,870 --> 03:14:07,840
we're examining the costs and benefits

5096
03:14:14,070 --> 03:14:10,880
of host change mutations on i this is

5097
03:14:16,309 --> 03:14:14,080
only a few generations 10 15 generations

5098
03:14:19,190 --> 03:14:16,319
from the spontaneous host range mutation

5099
03:14:21,110 --> 03:14:19,200
itself we also have been giving our

5100
03:14:22,950 --> 03:14:21,120
viral strain some time to evolve in

5101
03:14:24,950 --> 03:14:22,960
their uh in different environments to

5102
03:14:26,870 --> 03:14:24,960
see what the effects are on the

5103
03:14:28,630 --> 03:14:26,880
evolutionary trajectory if you carry

5104
03:14:31,269 --> 03:14:28,640
host range mutations

5105
03:14:33,750 --> 03:14:31,279
so this is a study that went for 30

5106
03:14:35,910 --> 03:14:33,760
overnight passages so roughly 150 viral

5107
03:14:38,469 --> 03:14:35,920
generations with four treatments the

5108
03:14:40,309 --> 03:14:38,479
wild type 56 virus shown in teal

5109
03:14:43,030 --> 03:14:40,319
and the eag virus

5110
03:14:44,790 --> 03:14:43,040
shown in a pale beige color if it

5111
03:14:46,870 --> 03:14:44,800
evolved just on the original host

5112
03:14:48,870 --> 03:14:46,880
phaseolicolla wildtype of course can

5113
03:14:50,790 --> 03:14:48,880
only infect phaseoliculus so we have

5114
03:14:53,190 --> 03:14:50,800
wild-type infecting physiolicula for 30

5115
03:14:56,229 --> 03:14:53,200
passages ehg infecting phaseolicola for

5116
03:14:58,309 --> 03:14:56,239
30 passages or ehg alternating daily

5117
03:15:01,590 --> 03:14:58,319
passage on the original host and a novel

5118
03:15:03,670 --> 03:15:01,600
host either tomato and red or era in

5119
03:15:06,229 --> 03:15:03,680
black so four different treatments that

5120
03:15:08,790 --> 03:15:06,239
would allow us to to compare the effects

5121
03:15:10,550 --> 03:15:08,800
of genetic generalism by looking at the

5122
03:15:12,150 --> 03:15:10,560
wild type evolving on phasing likelihood

5123
03:15:14,389 --> 03:15:12,160
compared to eag evolving on facing

5124
03:15:17,110 --> 03:15:14,399
alicula or the effect of ecological

5125
03:15:18,550 --> 03:15:17,120
generalism eag it has a host strange

5126
03:15:20,150 --> 03:15:18,560
mutation but it's still seeing that

5127
03:15:22,790 --> 03:15:20,160
original host a constant host

5128
03:15:25,349 --> 03:15:22,800
environment compared to uh forcing it to

5129
03:15:28,389 --> 03:15:25,359
see multiple hosts either two in the

5130
03:15:31,349 --> 03:15:28,399
pisaringi species or a pisaringi and a

5131
03:15:32,630 --> 03:15:31,359
pietra uh pcoral colligence alternating

5132
03:15:35,190 --> 03:15:32,640
days

5133
03:15:36,229 --> 03:15:35,200
the fitness results are shown on this

5134
03:15:38,150 --> 03:15:36,239
slide

5135
03:15:40,389 --> 03:15:38,160
on the y-axis we have relative fitness

5136
03:15:42,469 --> 03:15:40,399
on the original host phaseolicula in

5137
03:15:43,670 --> 03:15:42,479
this case one does not mean the fitness

5138
03:15:45,429 --> 03:15:43,680
of the

5139
03:15:47,910 --> 03:15:45,439
wild-type virus it means the fitness of

5140
03:15:48,950 --> 03:15:47,920
the common competitor we used to compare

5141
03:15:51,429 --> 03:15:48,960
all these

5142
03:15:53,269 --> 03:15:51,439
strains to the black box is the wild

5143
03:15:54,229 --> 03:15:53,279
type

5144
03:15:56,070 --> 03:15:54,239
fitness

5145
03:15:58,309 --> 03:15:56,080
those teal are the four descended

5146
03:16:00,550 --> 03:15:58,319
populations uh wild type evolved on the

5147
03:16:03,590 --> 03:16:00,560
original host for 30 days it's about the

5148
03:16:06,070 --> 03:16:03,600
same fitness as it had when it started

5149
03:16:09,750 --> 03:16:06,080
the gray box is the original fitness of

5150
03:16:11,510 --> 03:16:09,760
the ehe ancestor the pale dots are

5151
03:16:13,910 --> 03:16:11,520
after 30 days of evolution on phase

5152
03:16:16,070 --> 03:16:13,920
aligala again it was pretty decent

5153
03:16:16,950 --> 03:16:16,080
infecting vasolicola we don't see a big

5154
03:16:19,590 --> 03:16:16,960
change

5155
03:16:22,309 --> 03:16:19,600
in orange we see the eag populations

5156
03:16:24,389 --> 03:16:22,319
that alternated with host tomato in

5157
03:16:25,910 --> 03:16:24,399
burgundy the population is alternated

5158
03:16:27,910 --> 03:16:25,920
with host era

5159
03:16:29,190 --> 03:16:27,920
there are more data points for these

5160
03:16:30,870 --> 03:16:29,200
latter two groups because we measure

5161
03:16:33,429 --> 03:16:30,880
their fitness coming off of phase

5162
03:16:35,670 --> 03:16:33,439
allicola and coming off of tomato or era

5163
03:16:39,110 --> 03:16:35,680
so day 29 and day 30 to make sure there

5164
03:16:41,030 --> 03:16:39,120
wasn't a maternal host effect

5165
03:16:43,030 --> 03:16:41,040
when you compare between wild type and

5166
03:16:44,710 --> 03:16:43,040
eag grown on the same host you don't see

5167
03:16:48,469 --> 03:16:44,720
a lot of difference there's not a big

5168
03:16:50,389 --> 03:16:48,479
cost of carrying ehe longer term on the

5169
03:16:53,190 --> 03:16:50,399
host physiolicola they're both doing

5170
03:16:54,950 --> 03:16:53,200
just fine when you compare the different

5171
03:16:57,269 --> 03:16:54,960
kinds of generalist environments that

5172
03:16:59,990 --> 03:16:57,279
eag could be in we saw something pretty

5173
03:17:01,670 --> 03:17:00,000
surprising which is even though the ehe

5174
03:17:04,229 --> 03:17:01,680
that was exposed to both phaseolic and

5175
03:17:06,309 --> 03:17:04,239
tomato was seeing phaseolicola every

5176
03:17:08,550 --> 03:17:06,319
other day some of the populations were

5177
03:17:10,870 --> 03:17:08,560
losing fitness on the original host

5178
03:17:12,710 --> 03:17:10,880
there was so much selection on the novel

5179
03:17:15,349 --> 03:17:12,720
host that this was

5180
03:17:17,110 --> 03:17:15,359
apparently more important to the uh the

5181
03:17:18,710 --> 03:17:17,120
fitness of the overall

5182
03:17:20,710 --> 03:17:18,720
uh multiple day fitness of these

5183
03:17:22,309 --> 03:17:20,720
organisms that we still are seeing

5184
03:17:25,750 --> 03:17:22,319
fitness declining on the original host

5185
03:17:27,190 --> 03:17:25,760
despite exposure to the original host

5186
03:17:28,550 --> 03:17:27,200
and i can show you some molecular

5187
03:17:29,670 --> 03:17:28,560
evidence for that strong selection in

5188
03:17:32,550 --> 03:17:29,680
this figure

5189
03:17:34,710 --> 03:17:32,560
now i'm showing you the top ten snips

5190
03:17:36,550 --> 03:17:34,720
from each of four replicate populations

5191
03:17:39,349 --> 03:17:36,560
that were evolved from the wild type on

5192
03:17:40,790 --> 03:17:39,359
phaseolicola ehe and phaseolicula ehg

5193
03:17:42,630 --> 03:17:40,800
alternating between phase glycol and

5194
03:17:45,030 --> 03:17:42,640
tomato ehg alternating between

5195
03:17:47,830 --> 03:17:45,040
phaseolicola and era

5196
03:17:50,150 --> 03:17:47,840
light color pink indicates a low

5197
03:17:52,469 --> 03:17:50,160
frequency closer to zero dark purple

5198
03:17:54,550 --> 03:17:52,479
indicates a high frequency

5199
03:17:56,389 --> 03:17:54,560
and darkest purple would be one and what

5200
03:17:58,950 --> 03:17:56,399
you can see here is that

5201
03:18:00,630 --> 03:17:58,960
the of the top ten snips we don't see a

5202
03:18:02,790 --> 03:18:00,640
lot of snips going to particularly high

5203
03:18:04,070 --> 03:18:02,800
frequency in the populations evolving on

5204
03:18:07,269 --> 03:18:04,080
phaseolic

5205
03:18:09,830 --> 03:18:07,279
wild type and its isagenic uh

5206
03:18:11,990 --> 03:18:09,840
eag immediate offspring host range

5207
03:18:13,670 --> 03:18:12,000
mutant we're already pretty good at

5208
03:18:15,910 --> 03:18:13,680
infecting phase gallicola we don't see a

5209
03:18:17,349 --> 03:18:15,920
lot of change happening in 30 days but

5210
03:18:18,710 --> 03:18:17,359
the ehe populations that we're

5211
03:18:21,190 --> 03:18:18,720
experiencing a more generalist

5212
03:18:23,349 --> 03:18:21,200
environment we see some significant

5213
03:18:24,870 --> 03:18:23,359
selection uh some mutations are even

5214
03:18:27,910 --> 03:18:24,880
being fixed because

5215
03:18:29,349 --> 03:18:27,920
in the novel host genetic diversity uh

5216
03:18:30,710 --> 03:18:29,359
apparently

5217
03:18:33,030 --> 03:18:30,720
uh is

5218
03:18:34,870 --> 03:18:33,040
helping out these uh these viruses get

5219
03:18:36,469 --> 03:18:34,880
to a better fitness level and so we see

5220
03:18:38,550 --> 03:18:36,479
that there's a very different

5221
03:18:39,990 --> 03:18:38,560
evolutionary scenario for the generalist

5222
03:18:41,910 --> 03:18:40,000
viruses when they're in the different

5223
03:18:43,269 --> 03:18:41,920
hosts they are experiencing a selection

5224
03:18:44,309 --> 03:18:43,279
that they weren't experiencing when they

5225
03:18:48,630 --> 03:18:44,319
were just

5226
03:18:49,429 --> 03:18:48,640
cruising along in their usual uh host

5227
03:18:52,070 --> 03:18:49,439
so

5228
03:18:55,269 --> 03:18:52,080
perhaps unsatisfyingly the answer to

5229
03:18:57,110 --> 03:18:55,279
what are the benefits and uh

5230
03:18:59,429 --> 03:18:57,120
detractions of having an expanded host

5231
03:19:01,990 --> 03:18:59,439
range is well it there's pluses and

5232
03:19:03,830 --> 03:19:02,000
minuses there absolutely are fitness

5233
03:19:05,030 --> 03:19:03,840
costs and episodic costs of hosting

5234
03:19:07,910 --> 03:19:05,040
mutations that can influence

5235
03:19:10,070 --> 03:19:07,920
evolutionary trajectories but

5236
03:19:11,830 --> 03:19:10,080
whether or not these things are good or

5237
03:19:14,070 --> 03:19:11,840
bad are going to depend on what kind of

5238
03:19:16,790 --> 03:19:14,080
environment the virus lives in if you're

5239
03:19:19,190 --> 03:19:16,800
in an extremely homogenous environment

5240
03:19:21,830 --> 03:19:19,200
let's imagine an industrial fermenter

5241
03:19:23,110 --> 03:19:21,840
there's no reason to have a lot of host

5242
03:19:25,429 --> 03:19:23,120
refutations

5243
03:19:27,110 --> 03:19:25,439
you want to kill the dominant bacteria

5244
03:19:29,110 --> 03:19:27,120
the only bacteria that they put in there

5245
03:19:30,870 --> 03:19:29,120
to ferment the

5246
03:19:32,389 --> 03:19:30,880
food substance they're interested in if

5247
03:19:34,710 --> 03:19:32,399
you're out in a more natural community

5248
03:19:37,030 --> 03:19:34,720
with many many different hosts around

5249
03:19:39,349 --> 03:19:37,040
you that may make it would make a lot

5250
03:19:42,070 --> 03:19:39,359
more sense to have some expanded hosting

5251
03:19:43,510 --> 03:19:42,080
mutations in your standing population

5252
03:19:47,590 --> 03:19:43,520
genetic variation

5253
03:19:50,150 --> 03:19:47,600
even if they confer small

5254
03:19:52,630 --> 03:19:50,160
levels of fitness effects on your the

5255
03:19:54,309 --> 03:19:52,640
host you more typically encounter

5256
03:19:56,070 --> 03:19:54,319
most of the work i presented today was

5257
03:19:58,309 --> 03:19:56,080
the thesis work of lola jiao who's now a

5258
03:20:00,389 --> 03:19:58,319
post-doc at oxford big data institute

5259
03:20:02,070 --> 03:20:00,399
she was helped by uh two undergrads

5260
03:20:03,750 --> 03:20:02,080
drago stomate and alvin crespo and

5261
03:20:05,269 --> 03:20:03,760
manchester pastricia a postdoc in my

5262
03:20:07,429 --> 03:20:05,279
group was also contributed to the

5263
03:20:08,550 --> 03:20:07,439
mutational spectrum project thank you so

5264
03:20:10,469 --> 03:20:08,560
much for listening thank you for the

5265
03:20:21,110 --> 03:20:10,479
invitation organizers and i'm happy to

5266
03:20:25,510 --> 03:20:23,429
i actually have a question to start off

5267
03:20:26,389 --> 03:20:25,520
sure so

5268
03:20:29,110 --> 03:20:26,399
if we're

5269
03:20:32,309 --> 03:20:29,120
thinking about culturing viruses for the

5270
03:20:34,309 --> 03:20:32,319
future this idea that

5271
03:20:37,190 --> 03:20:34,319
maybe to increase our ability to culture

5272
03:20:38,630 --> 03:20:37,200
viruses we want viruses that can infect

5273
03:20:40,790 --> 03:20:38,640
many different types of hosts with a

5274
03:20:43,030 --> 03:20:40,800
broad host range right so you're saying

5275
03:20:45,190 --> 03:20:43,040
if we go along this line that if we have

5276
03:20:47,190 --> 03:20:45,200
a more simple environment which selects

5277
03:20:50,150 --> 03:20:47,200
for a certain type of

5278
03:20:51,830 --> 03:20:50,160
metabolism maybe that it will be harder

5279
03:20:54,150 --> 03:20:51,840
to culture viruses from those type of

5280
03:20:55,670 --> 03:20:54,160
environments

5281
03:20:58,630 --> 03:20:55,680
i don't know if we know enough to answer

5282
03:21:00,389 --> 03:20:58,640
one way or the other at this point um

5283
03:21:02,309 --> 03:21:00,399
even though we didn't see

5284
03:21:04,950 --> 03:21:02,319
many high frequency snips in our

5285
03:21:07,190 --> 03:21:04,960
population survived on just the original

5286
03:21:09,670 --> 03:21:07,200
host physiolicula they did have a higher

5287
03:21:11,190 --> 03:21:09,680
diversity overall than our populations

5288
03:21:13,990 --> 03:21:11,200
that we're seeing a wider number of

5289
03:21:16,150 --> 03:21:14,000
hosts because selection purges diversity

5290
03:21:17,830 --> 03:21:16,160
at linked sites you know we always

5291
03:21:20,070 --> 03:21:17,840
forget this you know evolution's great

5292
03:21:21,750 --> 03:21:20,080
it natural election is great except it's

5293
03:21:23,750 --> 03:21:21,760
getting rid of that lovely diversity

5294
03:21:26,389 --> 03:21:23,760
that helps the next step that

5295
03:21:30,790 --> 03:21:28,070
i'm not sure we have a science-based

5296
03:21:37,590 --> 03:21:30,800
answer to that question yet

5297
03:21:41,429 --> 03:21:39,429
i had you question sort of a more

5298
03:21:44,630 --> 03:21:41,439
general one

5299
03:21:47,030 --> 03:21:44,640
have you or anyone else looked at some

5300
03:21:48,469 --> 03:21:47,040
of the more you know broad host range

5301
03:21:49,990 --> 03:21:48,479
viruses

5302
03:21:52,070 --> 03:21:50,000
um because in this case you're looking

5303
03:21:54,070 --> 03:21:52,080
at these individual mutations in a nice

5304
03:21:56,070 --> 03:21:54,080
well-defined system but if you think

5305
03:21:57,910 --> 03:21:56,080
about it from some of the the cucumber

5306
03:22:00,870 --> 03:21:57,920
mosaic viruses or those that have you

5307
03:22:02,870 --> 03:22:00,880
know much broader host ranges do you see

5308
03:22:04,469 --> 03:22:02,880
the same kinds of trade-offs you know

5309
03:22:06,469 --> 03:22:04,479
fitness or otherwise or has anybody

5310
03:22:09,110 --> 03:22:06,479
really done good experiments that i

5311
03:22:11,670 --> 03:22:09,120
imagine that's hard to do

5312
03:22:14,389 --> 03:22:11,680
we know that broad host range plant

5313
03:22:16,309 --> 03:22:14,399
viruses see different uh plant hosts

5314
03:22:18,630 --> 03:22:16,319
differently and a lot of that's the work

5315
03:22:20,790 --> 03:22:18,640
of marilyn bruce nick's group santiago

5316
03:22:22,389 --> 03:22:20,800
lane has some work too but marilyn uh

5317
03:22:23,910 --> 03:22:22,399
really characterized that the kinds of

5318
03:22:26,229 --> 03:22:23,920
mutations that are favored in the

5319
03:22:28,309 --> 03:22:26,239
different environments uh are it's

5320
03:22:31,030 --> 03:22:28,319
clearly different in uh different plant

5321
03:22:32,229 --> 03:22:31,040
hosts but we don't in plant viruses we

5322
03:22:34,229 --> 03:22:32,239
don't see a lot of host specific

5323
03:22:36,229 --> 03:22:34,239
adaptation so you see this when you're

5324
03:22:38,710 --> 03:22:36,239
infecting a plant but it doesn't seem to

5325
03:22:40,950 --> 03:22:38,720
persist when you're looking at the

5326
03:22:42,630 --> 03:22:40,960
between host

5327
03:22:44,630 --> 03:22:42,640
evolution even if you're keeping them in

5328
03:22:45,990 --> 03:22:44,640
the same host for long periods of time

5329
03:22:47,269 --> 03:22:46,000
it's been

5330
03:22:48,469 --> 03:22:47,279
a frustrating difference between the

5331
03:22:49,750 --> 03:22:48,479
phage literature and the plant

5332
03:22:51,830 --> 03:22:49,760
literature is that there's much more

5333
03:22:54,229 --> 03:22:51,840
host specific adaptation that you can

5334
03:22:55,590 --> 03:22:54,239
measure in the phage literature

5335
03:22:59,990 --> 03:22:55,600
is that possibly because of how they're

5336
03:23:04,469 --> 03:23:01,670
and my postdoc also was whispering the

5337
03:23:06,550 --> 03:23:04,479
exact same thing i vectors

5338
03:23:09,590 --> 03:23:06,560
plant viruses are often uh vector

5339
03:23:11,269 --> 03:23:09,600
specific and host generalist but this is

5340
03:23:13,910 --> 03:23:11,279
these sorts of patterns occur even in

5341
03:23:15,510 --> 03:23:13,920
wind transmitted plants viruses so this

5342
03:23:16,950 --> 03:23:15,520
isn't something that's restricted

5343
03:23:18,710 --> 03:23:16,960
because you have to be you don't have to

5344
03:23:20,710 --> 03:23:18,720
look a certain way to go

5345
03:23:22,710 --> 03:23:20,720
with a vector between hosts

5346
03:23:25,110 --> 03:23:22,720
on a population level even with the same

5347
03:23:26,790 --> 03:23:25,120
host we don't see as much host specific

5348
03:23:28,150 --> 03:23:26,800
adaptation

5349
03:23:30,870 --> 03:23:28,160
when people look at this question of

5350
03:23:34,070 --> 03:23:30,880
broader host range in animals the they

5351
03:23:35,590 --> 03:23:34,080
do shorthand it to arbor viruses versus

5352
03:23:37,349 --> 03:23:35,600
something that's mammal specific and

5353
03:23:39,670 --> 03:23:37,359
that's not a great comparison either

5354
03:23:52,309 --> 03:23:39,680
because yeah

5355
03:23:52,319 --> 03:23:58,389
any other questions

5356
03:24:01,030 --> 03:23:59,670
i'm curious if you've done similar

5357
03:24:02,870 --> 03:24:01,040
experiments with single-stranded dna

5358
03:24:05,670 --> 03:24:02,880
viruses

5359
03:24:09,750 --> 03:24:05,680
we so singles uh our single-stranded dna

5360
03:24:12,389 --> 03:24:09,760
um phage in the lab is 5x174 and it is

5361
03:24:14,710 --> 03:24:12,399
pretty difficult to get onto alternative

5362
03:24:16,870 --> 03:24:14,720
hosts there's a very short list of

5363
03:24:18,790 --> 03:24:16,880
alternative hosts for that particular

5364
03:24:20,469 --> 03:24:18,800
virus it doesn't have

5365
03:24:21,910 --> 03:24:20,479
a massive host range

5366
03:24:26,950 --> 03:24:21,920
mutation generation ability it's

5367
03:24:30,550 --> 03:24:28,950
and i i work with many uh people who

5368
03:24:31,830 --> 03:24:30,560
work on the gemini viruses the the

5369
03:24:33,510 --> 03:24:31,840
biggest group of plant-infecting

5370
03:24:35,750 --> 03:24:33,520
single-stranded dna viruses and the lack

5371
03:24:40,389 --> 03:24:35,760
of host-specific adaptation is just

5372
03:24:43,910 --> 03:24:42,150
thanks yeah we're of course we're

5373
03:24:46,309 --> 03:24:43,920
looking at some of these strange

5374
03:24:50,309 --> 03:24:46,319
single-stranded dna viruses as well and

5375
03:24:52,070 --> 03:24:50,319
you know love to have some handles on it

5376
03:24:54,070 --> 03:24:52,080
they're everywhere and someone should

5377
03:24:56,790 --> 03:24:54,080
develop one of the ones that infects

5378
03:24:59,590 --> 03:24:56,800
fungi or you know some protists into a

5379
03:25:01,830 --> 03:24:59,600
good working experimental system

5380
03:25:03,349 --> 03:25:01,840
i agree

5381
03:25:04,550 --> 03:25:03,359
i'll take an archaeal system if you can

5382
03:25:08,550 --> 03:25:04,560
get that thing

5383
03:25:13,670 --> 03:25:08,560
the 25 kb one to grow well

5384
03:25:17,750 --> 03:25:15,590
arvin had a nice notice in the chat

5385
03:25:20,150 --> 03:25:17,760
group about um that plan virus evolution

5386
03:25:21,590 --> 03:25:20,160
and ecology that was their recent arvind

5387
03:25:23,830 --> 03:25:21,600
are you still around

5388
03:25:24,870 --> 03:25:23,840
um online here that was a recent review

5389
03:25:29,429 --> 03:25:24,880
correct

5390
03:25:30,790 --> 03:25:29,439
covers a lot of work from ecology to

5391
03:25:33,030 --> 03:25:30,800
evolution

5392
03:25:35,269 --> 03:25:33,040
also looks at tradeoff hypothesis in

5393
03:25:37,750 --> 03:25:35,279
there talks about insects playing a

5394
03:25:40,710 --> 03:25:37,760
major role and how insects and plant

5395
03:25:44,710 --> 03:25:40,720
viruses have potentially co-evolved

5396
03:25:48,229 --> 03:25:46,950
yeah thanks it's um i can say this

5397
03:25:57,190 --> 03:25:48,239
because i'm not one of the authors it's

5398
03:26:00,870 --> 03:25:58,550
we're still at the point where they have

5399
03:26:02,790 --> 03:26:00,880
to have special mixer sessions at asv

5400
03:26:04,389 --> 03:26:02,800
for the animal and plant virus people to

5401
03:26:06,550 --> 03:26:04,399
talk to each other and try to figure out

5402
03:26:08,550 --> 03:26:06,560
what's similar across our disciplines

5403
03:26:13,429 --> 03:26:08,560
and those rooms don't include the phage

5404
03:26:18,389 --> 03:26:16,469
the vast numbers of us

5405
03:26:20,790 --> 03:26:18,399
i i think if we have take hands on this

5406
03:26:23,510 --> 03:26:20,800
call we'll be fine

5407
03:26:26,469 --> 03:26:23,520
no um which i think is a great

5408
03:26:29,590 --> 03:26:26,479
transition so in theory in the schedule

5409
03:26:31,910 --> 03:26:29,600
um i'm supposed to say something about

5410
03:26:34,710 --> 03:26:31,920
closing remarks um i'd actually much

5411
03:26:36,710 --> 03:26:34,720
prefer to open this up to

5412
03:26:38,389 --> 03:26:36,720
really everyone

5413
03:26:40,790 --> 03:26:38,399
uh to

5414
03:26:42,070 --> 03:26:40,800
make comments and unfortunately i snuck

5415
03:26:44,309 --> 03:26:42,080
out at the break but it seems that there

5416
03:26:46,389 --> 03:26:44,319
were some issues with seeing yourself

5417
03:26:48,469 --> 03:26:46,399
and not seeing yourself

5418
03:26:49,910 --> 03:26:48,479
as far as being bizarre for presentation

5419
03:26:51,269 --> 03:26:49,920
wise

5420
03:26:52,950 --> 03:26:51,279
do we have any

5421
03:26:56,070 --> 03:26:52,960
more feedback on that or any other

5422
03:26:58,229 --> 03:26:56,080
questions for other people um before we

5423
03:27:06,309 --> 03:26:58,239
sort of wrap up for today and then pick

5424
03:27:11,830 --> 03:27:09,269
anybody at ni central have some uh

5425
03:27:13,349 --> 03:27:11,840
comments thoughts um i completely agree

5426
03:27:15,510 --> 03:27:13,359
with the the chats we need to try and

5427
03:27:16,950 --> 03:27:15,520
get a transcript for that um i think

5428
03:27:18,150 --> 03:27:16,960
there's a lot of really cool stuff going

5429
03:27:19,670 --> 03:27:18,160
on there i just haven't been able to

5430
03:27:22,309 --> 03:27:19,680
split my

5431
03:27:24,630 --> 03:27:22,319
attention i'm really bad at multitasking

5432
03:27:27,349 --> 03:27:25,990
uh well

5433
03:27:29,349 --> 03:27:27,359
you know i've been paying attention to

5434
03:27:31,269 --> 03:27:29,359
the chats and answering a few things and

5435
03:27:34,469 --> 03:27:31,279
asking a few things so we will have

5436
03:27:37,269 --> 03:27:34,479
those captured um we also

5437
03:27:40,309 --> 03:27:37,279
uh would like to make sure that everyone

5438
03:27:43,269 --> 03:27:40,319
from whom we have slides uh is willing

5439
03:27:46,150 --> 03:27:43,279
to have us post them on the nai website

5440
03:27:48,150 --> 03:27:46,160
under this workshop

5441
03:27:50,870 --> 03:27:48,160
so i guess we'll

5442
03:27:52,630 --> 03:27:50,880
you know ask anyone who presented who

5443
03:27:54,309 --> 03:27:52,640
doesn't want that to happen to certainly

5444
03:27:57,269 --> 03:27:54,319
email us right away

5445
03:27:58,790 --> 03:27:57,279
if not we'll certainly confirm with you

5446
03:28:01,190 --> 03:27:58,800
before we post them

5447
03:28:01,910 --> 03:28:01,200
uh if you need to take any proprietary

5448
03:28:06,790 --> 03:28:01,920
or

5449
03:28:09,030 --> 03:28:06,800
what uh if you need to do a clean up on

5450
03:28:11,190 --> 03:28:09,040
them and after that uh within a couple

5451
03:28:13,110 --> 03:28:11,200
of days we'll have those posted also

5452
03:28:16,309 --> 03:28:13,120
we've recorded this so for any of you

5453
03:28:17,830 --> 03:28:16,319
who joined us uh late or intermittently

5454
03:28:19,910 --> 03:28:17,840
uh you'll be able to catch the parts

5455
03:28:22,229 --> 03:28:19,920
that you didn't

5456
03:28:24,389 --> 03:28:22,239
you weren't able to join us for

5457
03:28:26,710 --> 03:28:24,399
and then for anybody who wasn't

5458
03:28:29,030 --> 03:28:26,720
present right at the beginning

5459
03:28:32,309 --> 03:28:29,040
one of the aspirations of this effort is

5460
03:28:33,830 --> 03:28:32,319
to produce tangible product and one is a

5461
03:28:35,830 --> 03:28:33,840
journal article

5462
03:28:38,550 --> 03:28:35,840
produced by you folks

5463
03:28:41,750 --> 03:28:38,560
i'll facilitate it as much as i can

5464
03:28:44,070 --> 03:28:41,760
for the journal astrobiology and then a

5465
03:28:46,790 --> 03:28:44,080
distillation of that for the upcoming

5466
03:28:48,550 --> 03:28:46,800
planetary decadal white paper so that's

5467
03:28:49,830 --> 03:28:48,560
just to recap what i said in the

5468
03:28:50,870 --> 03:28:49,840
beginning for those of you who weren't

5469
03:28:52,710 --> 03:28:50,880
on

5470
03:28:54,469 --> 03:28:52,720
and with that i think uh that's all i

5471
03:28:56,870 --> 03:28:54,479
need to say

5472
03:29:00,229 --> 03:28:56,880
except i had a great time and a lot of

5473
03:29:03,590 --> 03:29:01,830
yeah thanks and any comments if you

5474
03:29:06,550 --> 03:29:03,600
don't feel like um sharing them in a

5475
03:29:09,190 --> 03:29:06,560
general chat feel free to do a direct

5476
03:29:10,630 --> 03:29:09,200
chat to any of us um as far as that's

5477
03:29:13,110 --> 03:29:10,640
concerned you can also find our email

5478
03:29:14,790 --> 03:29:13,120
addresses etc i haven't been watching on

5479
03:29:18,790 --> 03:29:14,800
twitter i'm sure we've completely blown

5480
03:29:23,110 --> 03:29:21,590
and uh yeah let's see and thanks again

5481
03:29:24,790 --> 03:29:23,120
penny for pointing out the the article

5482
03:29:27,190 --> 03:29:24,800
and white papers we will be reaching out

5483
03:29:29,910 --> 03:29:27,200
to you i guarantee that um that will

5484
03:29:32,229 --> 03:29:29,920
happen keep an eye on your your inboxes

5485
03:29:35,830 --> 03:29:32,239
and we will we'll let you know about

5486
03:29:37,750 --> 03:29:35,840
that um i will try and synthesize a

5487
03:29:41,030 --> 03:29:37,760
little bit more of what i've heard today

5488
03:29:42,229 --> 03:29:41,040
um as i was uh personally chatting with

5489
03:29:43,990 --> 03:29:42,239
someone

5490
03:29:45,910 --> 03:29:44,000
even i'm a little overwhelmed at this

5491
03:29:47,990 --> 03:29:45,920
point so i need to sit back and

5492
03:29:49,349 --> 03:29:48,000
synthesize some of these things maybe

5493
03:29:51,990 --> 03:29:49,359
re-listen to a couple of the

5494
03:29:55,349 --> 03:29:52,000
presentations and i'll try and fit some

5495
03:29:57,269 --> 03:29:55,359
of that into my closing talk tomorrow as

5496
03:29:59,190 --> 03:29:57,279
well

5497
03:30:01,269 --> 03:29:59,200
one other point that i want to make

5498
03:30:03,750 --> 03:30:01,279
we've had a great turnout for this the

5499
03:30:05,990 --> 03:30:03,760
highest number of participants on at any

5500
03:30:08,070 --> 03:30:06,000
one time was 87

5501
03:30:10,150 --> 03:30:08,080
and we probably have a few more of that

5502
03:30:11,910 --> 03:30:10,160
in terms of you know total coming and

5503
03:30:13,910 --> 03:30:11,920
going so

5504
03:30:15,110 --> 03:30:13,920
that exceeds my expectations for how

5505
03:30:17,190 --> 03:30:15,120
many people we could pull out of the

5506
03:30:19,030 --> 03:30:17,200
woodwork who are interested in this

5507
03:30:20,550 --> 03:30:19,040
whether or not they happen to be experts

5508
03:30:22,630 --> 03:30:20,560
so i think that there's a lot of

5509
03:30:24,950 --> 03:30:22,640
interest in the community and

5510
03:30:27,190 --> 03:30:24,960
that makes it worth having gone to the

5511
03:30:29,670 --> 03:30:27,200
trouble of doing this to try to get

5512
03:30:31,990 --> 03:30:29,680
everybody to be talking to each other

5513
03:30:34,150 --> 03:30:32,000
including folks that may not consider

5514
03:30:35,750 --> 03:30:34,160
themselves virologists we discussed this

5515
03:30:37,510 --> 03:30:35,760
at the beginning uh there are many

5516
03:30:39,190 --> 03:30:37,520
people who are not virologists but who

5517
03:30:42,150 --> 03:30:39,200
have uh

5518
03:30:43,910 --> 03:30:42,160
uh probably things to contribute and uh

5519
03:30:47,349 --> 03:30:43,920
getting them also thinking along the

5520
03:30:48,710 --> 03:30:47,359
lines of the role of viruses and other

5521
03:30:50,950 --> 03:30:48,720
mobile

5522
03:30:53,670 --> 03:30:50,960
genetic entities that are moving things

5523
03:30:55,590 --> 03:30:53,680
around i think is really worthwhile

5524
03:30:57,750 --> 03:30:55,600
for the effort and so i look forward to

5525
03:30:59,349 --> 03:30:57,760
seeing everybody tomorrow afternoon and

5526
03:31:00,309 --> 03:30:59,359
maybe a few additional people that we

5527
03:31:01,990 --> 03:31:00,319
didn't have

5528
03:31:03,990 --> 03:31:02,000
who couldn't make it today so thanks

5529
03:31:06,070 --> 03:31:04,000
everybody for attending i wanted to

5530
03:31:07,590 --> 03:31:06,080
throw one last bit in there if you're

5531
03:31:09,110 --> 03:31:07,600
not a virus specialist or even if you

5532
03:31:11,190 --> 03:31:09,120
are you may have not understood some of

5533
03:31:12,950 --> 03:31:11,200
the jargon that was discussed today on

5534
03:31:15,510 --> 03:31:12,960
our website we have some helpful

5535
03:31:17,110 --> 03:31:15,520
resources but also feel free to email us

5536
03:31:19,349 --> 03:31:17,120
with any questions there's no bad

5537
03:31:21,510 --> 03:31:19,359
question if you want to know what is a

5538
03:31:23,510 --> 03:31:21,520
lytic virus or something please email us

5539
03:31:24,630 --> 03:31:23,520
so we can help you out that way if you

5540
03:31:26,389 --> 03:31:24,640
feel like it might help you be more

5541
03:31:30,389 --> 03:31:26,399
engaging tomorrow and might be useful

5542
03:31:36,150 --> 03:31:33,670
yeah all i can say is is thank you um to

5543
03:31:39,429 --> 03:31:36,160
everybody has participated this has been

5544
03:31:42,710 --> 03:31:39,439
um really really wonderful at least from

5545
03:31:45,750 --> 03:31:42,720
from my highly biased point of view

5546
03:31:47,830 --> 03:31:45,760
so um thanks to everybody and hopefully

5547
03:31:49,750 --> 03:31:47,840
we'll see all of you or at least hear

5548
03:31:50,550 --> 03:31:49,760
from some of you tomorrow

5549
03:31:52,830 --> 03:31:50,560
great