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thank you well welcome everyone to the

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next in our series of webinars this one

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is about substituting space for time

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just a couple of quick announcements the

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slides to this if you happen to be only

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connecting an audio are linked directly

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from the event notice on the front of

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the screen there will be a video up on

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this recording this probably women the

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next day and just reiterating what like

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it said this event is being recorded and

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will be publicly available such as John

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Denver like to say if you're going to

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sing along seem good with that Eric well

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okay um so this is a topic that was I

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think originally proposed by Everett

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shock and then put together by Everett

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and Eric Boyd and me um but ever it was

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the one to originate the title I think

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how can we substitute space for time to

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better understand geochemical & Co

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evolutionary dynamics on the space for

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time refers to something that's

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essentially of well known a lot of what

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happens in geochemistry and evolutionary

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dynamics and the coupling between the

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two occurs on time scales that are not

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accessible to us experimentally usually

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you would want the control of

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experiments to do things like infer

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out-of-sample which is relevant for

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detecting preferred places to look for

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life outside the earth and also

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understanding cause because without a

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model you can't simply infer from a

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sample what happens outside the sample

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condition the problem when you have no

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direct access to deep time is that you

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may have variation in the present but

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simple sample comparison of diversity

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does not directly get you at causation

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or at out-of-sample inference so then

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the question is what can we do to make

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how can we in a principled way use

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variation in the present to provide

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access to the things about the past that

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are needed

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for inference and for the deduction of

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cause three obvious ways this can be

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done which are not limited to biology

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they occur also in geology and many

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other areas if you have processes that

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are continuously reinitiated you can

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catch them at different stages and so

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you can substitute of synchronic

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comparisons for diachronic comparison in

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that way when there are accidental

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components or historically contingent

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components in the production of

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diversity you can use those to

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reconstruct history with phylogenetic

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methods and by then filling in the

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events of the past you can try to use

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those events to correct the things like

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Galton's problem to understand

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likelihood or context for the changes

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rather than simply looking at the

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diversity as it occurs now and this

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particularly for us this will be of

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interest for the relation between

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metabolic phenotypes and ways of living

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and the geological context where they

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occur and then of course the other thing

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that goes together with reconstructing

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accidental parts of the past is

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inferring a process model for what the

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laws are that have been active in

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evolution over that time so why is this

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a a thing that clearly there's a lot we

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can do with the biosphere is enormously

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diverse its diverse in its gene

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inventory it's diverse and the way genes

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are gathered in two genomes it's diverse

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in the way organisms anto genetically or

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developmentally produce phenotype from a

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combination of genes and environment and

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its diverse an ecological assembly and a

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lot of the diversity in ontogeny or

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development in ecology is coupled to the

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types of geochemical environments and

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thermodynamic environments that

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different organisms and their

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communities can inhabit so working from

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that what are the guiding questions in

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making use of the rich data record that

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while of genomic diversity makes

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available to us okay most basic question

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of life how did it originate and then

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how how and why was the diversity of

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life on earth produced as it was

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particularly with application to

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herbalism what are the metabolic

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features that we can reconstruct for

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early life and how do they give us a

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principled way to choose places to

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investigate and also modes of

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Investigation for astrobiology with

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regard to the question of whether or not

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there are time independent processes

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that can be inferred the sorts of things

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for which we already have some evidence

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but we would like a more systematic

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understanding are some environments more

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conservative both geologically and in

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the mode and tempo of evolution that

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they induce than others are can we say

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something about which types of

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environments are which when organisms

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diversify some of that may come from the

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bottlenecks of evolutionary discovery

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but some of it may also come from strict

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limits that are imposed geologically

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either on the organism or on the

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community structure of the organism um

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sometimes the limitations on community

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structure may come from limitations in

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one individual species can do other

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times the limits on community structure

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may be more fundamental to the community

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than they are to the individual and it's

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worth noting in all of these that all

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evolution essentially is coevolution

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it's a very rare geological environment

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that can be inhabited by only one

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species that's not affected by the

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dynamics of other species that share it

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and in everything from phylogenetic

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reconstruction understanding evidence

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about species interactions in genomic

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records what you would like is to be

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able to calibrate mode and tempo of

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evolution to figure out what's happening

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in the same places at the same time so

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why is this not an easy thing to do a

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lot of time has expired the geological

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intervals that are given names are to

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some extent historical but in many

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respects they have to do with actually

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of different chemistry different Rock

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dynamics and different behavior of the

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atmosphere and oceans and also different

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phases of life and feedbacks of life on

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the geochemical environment and we have

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to look back through all of that in

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order to correctly interpret the

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diversity that we find

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the record today as just one example you

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know so life or life's origins are

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somewhere in the murky area between the

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Hadean the hidden era and the early

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Archaean where we have some ability to

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start talking about the chemistry of

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rockland oceans between then and now we

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have a whole sequence of major

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transitions and as an example you know

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many of the major transitions in life

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were actually major transitions of the

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biogeochemical environment all jointly

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this is a slide from ariel on bar

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science paper in 2008 which just tracks

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elemental abundances in the ocean

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jointly with the rise of oxygen as its

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approximately afford to invert today and

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both through direct interactions with

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molecular oxygen and particularly

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through things like the oxidation states

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of sulfur and what that makes soluble or

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insoluble you see that you have many

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orders of magnitude change especially in

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transition metals that are fundamental

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to biochemical functions and these

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determine both what it was

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thermodynamically affordable to do and

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to some extent they may have affected

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the partitioning of the way elements

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occur in different organisms so for

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instance you see the zinc and copper are

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extremely low concentration in anoxic

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oceans and then with the rise of oxygen

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at the same time as iron molybdenum

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cobalt nickel or driven out of solution

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zinc and copper come into solution so

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there can be different eras in

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evolutionary innovation that are coupled

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to just what's available and of course

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life is feeding back it was organism

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dynamics that created this so the

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sequence of the next several slides have

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to do with particular areas where we can

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say something about what's in the genome

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inventory how it couples within the

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ecosystem and also to the geochemistry

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there are sort of examples of how

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problems of this kind can be solved so

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I'll switch off at this point and

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transfer Eric void to do them okay so

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Eric did a nice job of outlining some of

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the barriers to these kind of studies

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and really outlined

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why we think that these kind of studies

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are necessary to understand why we have

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the diversification of life that that

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that we have today and really trying to

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understand how we got there and so

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there's a critical feature of microbial

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life that that we believe makes these

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kind of studies tractable and that is

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that they that life tends to inherit

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their genotypes or their genomes and

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thus their phenotypes from their

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ancestors okay and so the extent that in

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ecology of an organism so the

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environment that an organism tends to

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inhabit is related to what they can do

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or their their phenotype there should be

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a positive relationship there and so

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really guiding this word from here for

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it is is the tenant that genomes are a

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data rich historical record of the

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interactions between life and its

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environment and it's a data-rich record

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that we believe far exceeds the

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geological records so much as half

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there's many gas in the geological

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record there's there's really large

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barriers to understanding what what the

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environment might have been like say two

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billion years ago or whatnot and we

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think that we can actually mine this

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information out of existing genomes and

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so as we start down this path I just put

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this plot in here to illustrate this

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this basic tenet of microbiology and

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that is as a species diversifies as it

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increases its phylogenetic distance from

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its ancestor what you tend to see is a

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corresponding increase in the metabolic

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dissimilarity of those organisms and so

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this is taking 1800 genomes comprising

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both bacteria and archaea defining what

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their metabolic capacity is using a

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series of statistical and bioinformatic

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tools that I won't go into here and just

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simply creating a matrix to describe how

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similar those organisms are

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at a metabolic level and then relating

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that to a matrix describing how

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evolutionarily related those organisms

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are and so what you can see from that is

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that there is a correspondence so as you

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evolve new metabolic traits or new

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combinations of metabolic trades there's

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a corresponding diversification at an

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evolutionary level and so the question

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is is what drove the development of this

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phenotypic diversity so to the extent

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that environment or inter species

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interactions are driving or providing

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new ecological niches how did that

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select for new metabolic properties of

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these organisms and so just to simplify

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a little bit and take us a step back two

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things that I think most of us

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understand we can go back to Darwin's

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work back in the 1800s and you know

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Darwin without the benefit of genomics

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and without the benefit of phylogenetics

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started to notice is pattered in beat

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morphology of these finches and found a

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00:12:01,199 --> 00:11:58,089
tight correlation between the morphology

281
00:12:03,900 --> 00:12:01,209
of these Finch beaks and the lifestyle

282
00:12:06,600 --> 00:12:03,910
strategies that these finches lived and

283
00:12:09,750 --> 00:12:06,610
that is what kind of foraging habit

284
00:12:12,290 --> 00:12:09,760
habits do they have what kind of food

285
00:12:16,290 --> 00:12:12,300
resources did they use and noticed a

286
00:12:18,120 --> 00:12:16,300
correspondence in the beat morphology of

287
00:12:19,949 --> 00:12:18,130
these organisms and their local

288
00:12:21,600 --> 00:12:19,959
environment okay and so here we're not

289
00:12:23,579 --> 00:12:21,610
necessarily talking about a chemical

290
00:12:25,680 --> 00:12:23,589
environment we're talking about a food

291
00:12:28,079 --> 00:12:25,690
resource but you know let's think back

292
00:12:30,690 --> 00:12:28,089
to microbes and their food resource at

293
00:12:34,350 --> 00:12:30,700
least in most systems are our chemicals

294
00:12:36,810 --> 00:12:34,360
and so just using this as an analogy and

295
00:12:40,860 --> 00:12:36,820
and and what was particularly striking

296
00:12:43,769 --> 00:12:40,870
to me is this work by sato back in 1999

297
00:12:46,829 --> 00:12:43,779
I took these finches and actually

298
00:12:49,980 --> 00:12:46,839
subjected those these Finch populations

299
00:12:52,890 --> 00:12:49,990
to phylogenetic reconstruction and show

300
00:12:55,019 --> 00:12:52,900
that lifestyle strategy or their

301
00:12:57,060 --> 00:12:55,029
phenotypes tracked very nicely with

302
00:12:58,500 --> 00:12:57,070
their evolutionary history which is

303
00:13:00,930 --> 00:12:58,510
exactly what you would expect if

304
00:13:03,240 --> 00:13:00,940
metabolic innovation is driving

305
00:13:06,210 --> 00:13:03,250
taxonomic diversification

306
00:13:08,190 --> 00:13:06,220
and so the essence of these slides is

307
00:13:09,600 --> 00:13:08,200
that we believe that you can begin to

308
00:13:12,660 --> 00:13:09,610
understand the role of environment

309
00:13:14,340 --> 00:13:12,670
shaping biodiversity by examining

310
00:13:19,860 --> 00:13:14,350
patterns in the distribution of species

311
00:13:23,880 --> 00:13:19,870
and their functions okay and so a

312
00:13:26,550 --> 00:13:23,890
framework that we've used in moving this

313
00:13:28,980 --> 00:13:26,560
research forward is really could be

314
00:13:33,420 --> 00:13:28,990
summed up by this Venn diagram here

315
00:13:37,410 --> 00:13:33,430
where we have ecological interactions by

316
00:13:38,820 --> 00:13:37,420
this I mean in organisms ability to

317
00:13:41,760 --> 00:13:38,830
interact with its environment its

318
00:13:43,230 --> 00:13:41,770
environmental tolerances biological

319
00:13:46,980 --> 00:13:43,240
interactions these get a little bit more

320
00:13:50,610 --> 00:13:46,990
difficult to decipher when we're looking

321
00:13:54,050 --> 00:13:50,620
back in time and then we have evolution

322
00:13:56,340 --> 00:13:54,060
so these two interactions are together

323
00:13:58,260 --> 00:13:56,350
converging to drive an evolutionary

324
00:14:00,330 --> 00:13:58,270
phenomena and the way to really think

325
00:14:03,210 --> 00:14:00,340
about this is at the level of the

326
00:14:06,350 --> 00:14:03,220
ecological niche which is simply the

327
00:14:08,579 --> 00:14:06,360
multiplicity of a chemical physical and

328
00:14:10,950 --> 00:14:08,589
importantly biological parameters that

329
00:14:13,920 --> 00:14:10,960
characterize a local habitat and so that

330
00:14:16,829 --> 00:14:13,930
biology through mutagenesis every time a

331
00:14:18,870 --> 00:14:16,839
cell replicates mutations are introduced

332
00:14:22,320 --> 00:14:18,880
into the genome creating new

333
00:14:25,110 --> 00:14:22,330
opportunities to evolve new phenotypic

334
00:14:27,180 --> 00:14:25,120
traits or trait variants that enable

335
00:14:29,670 --> 00:14:27,190
that population to successfully compete

336
00:14:33,300 --> 00:14:29,680
and proliferate potentially in a new

337
00:14:38,000 --> 00:14:33,310
ecological niche ok and so interactions

338
00:14:40,530 --> 00:14:38,010
then in that newly expanded upon niche

339
00:14:42,480 --> 00:14:40,540
ultimately dictate the success of these

340
00:14:44,160 --> 00:14:42,490
diversification of entities you do and

341
00:14:45,750 --> 00:14:44,170
so it's a fairly simple framework and

342
00:14:50,670 --> 00:14:45,760
obviously you can get more complicated

343
00:14:53,340 --> 00:14:50,680
with it but I think it leads you to ask

344
00:14:56,700 --> 00:14:53,350
a couple of fairly simple questions of

345
00:14:58,800 --> 00:14:56,710
biological data so evolutionary history

346
00:15:02,220 --> 00:14:58,810
is informative okay so what was the role

347
00:15:04,680 --> 00:15:02,230
of analyte X so this can be whatever

348
00:15:06,750 --> 00:15:04,690
your favorite compound is in driving the

349
00:15:07,920 --> 00:15:06,760
diversification of lineage wide again

350
00:15:10,110 --> 00:15:07,930
that can be whatever your favorite

351
00:15:12,930 --> 00:15:10,120
lineage is and so you can ask these

352
00:15:15,630 --> 00:15:12,940
questions and any number of combinations

353
00:15:16,090 --> 00:15:15,640
and ask about how the evolutionary

354
00:15:19,360 --> 00:15:16,100
history

355
00:15:24,280 --> 00:15:19,370
of these populations or communities even

356
00:15:26,050 --> 00:15:24,290
was shaped by environmental variation we

357
00:15:29,350 --> 00:15:26,060
also believe that the distribution of

358
00:15:30,910 --> 00:15:29,360
lineages is import informative so what

359
00:15:32,910 --> 00:15:30,920
environment types harbor the earliest

360
00:15:35,280 --> 00:15:32,920
branching lineage is for example

361
00:15:40,600 --> 00:15:35,290
focusing in on some of the major

362
00:15:42,220 --> 00:15:40,610
transitions and in life on earth such as

363
00:15:45,639 --> 00:15:42,230
photosynthesis what kind of environment

364
00:15:51,370 --> 00:15:45,649
types dictate the distribution of that

365
00:15:54,009 --> 00:15:51,380
those kind of processes okay so how do

366
00:15:57,160 --> 00:15:54,019
we go about answering these questions so

367
00:15:59,889 --> 00:15:57,170
going back to Eric slide number two you

368
00:16:02,410 --> 00:15:59,899
know how can we actually use space to

369
00:16:05,829 --> 00:16:02,420
substitute that for or for time and so

370
00:16:08,680 --> 00:16:05,839
we believe again that the genomes of

371
00:16:11,710 --> 00:16:08,690
extant organisms are a data-rich record

372
00:16:14,530 --> 00:16:11,720
by which we can mine that we can mine at

373
00:16:16,749 --> 00:16:14,540
a phylogenetic level to understand how

374
00:16:19,300 --> 00:16:16,759
environmental gradients that have played

375
00:16:21,400 --> 00:16:19,310
out over over geological time have

376
00:16:23,800 --> 00:16:21,410
dictated the expat distribution of life

377
00:16:27,610 --> 00:16:23,810
and so what kind of a system would would

378
00:16:31,600 --> 00:16:27,620
serve us well for such studies and of

379
00:16:33,370 --> 00:16:31,610
course my work with Everett takes us to

380
00:16:36,309 --> 00:16:33,380
Yellowstone often to ask these kind of

381
00:16:39,040 --> 00:16:36,319
questions and the reason why is here's

382
00:16:41,499 --> 00:16:39,050
just a plot of I think 14 hundred

383
00:16:43,150 --> 00:16:41,509
springs in Yellowstone as a function of

384
00:16:46,569 --> 00:16:43,160
their pH and temperature space and you

385
00:16:48,420 --> 00:16:46,579
can see that you can sample any gradient

386
00:16:51,639 --> 00:16:48,430
of pH and temperature combinations

387
00:16:55,030 --> 00:16:51,649
combinations you can expand on this to

388
00:16:57,280 --> 00:16:55,040
virtually any analyte of interest aside

389
00:17:00,550 --> 00:16:57,290
from pressure and maybe salinity and you

390
00:17:03,220 --> 00:17:00,560
can sample orders of magnitude gradient

391
00:17:05,380 --> 00:17:03,230
spatial gradients in these and these

392
00:17:07,179 --> 00:17:05,390
analytes and so then you can take and

393
00:17:10,090 --> 00:17:07,189
you can sample microbial communities

394
00:17:12,069 --> 00:17:10,100
across these gradients eject them to

395
00:17:14,860 --> 00:17:12,079
phylogenetic analysis or a series of

396
00:17:20,439 --> 00:17:14,870
analyses and ask you know what the

397
00:17:22,149 --> 00:17:20,449
historical pattern is there so when we

398
00:17:25,149 --> 00:17:22,159
do this with something like

399
00:17:27,159 --> 00:17:25,159
photosynthesis so we call this the

400
00:17:28,060 --> 00:17:27,169
transition to photosynthesis I don't

401
00:17:29,860 --> 00:17:28,070
know if you can see Mike

402
00:17:32,650 --> 00:17:29,870
here on the screen but so starting in

403
00:17:37,360 --> 00:17:32,660
the center of this panel on the Left we

404
00:17:39,670 --> 00:17:37,370
have an acidic hot spring in Yellowstone

405
00:17:41,350 --> 00:17:39,680
the source is up near the top there

406
00:17:44,020 --> 00:17:41,360
where you see that yellow that's

407
00:17:46,450 --> 00:17:44,030
elemental sulfur and as that spring

408
00:17:48,910 --> 00:17:46,460
emanates outward from the source it

409
00:17:52,360 --> 00:17:48,920
cools forms a gradient and ultimately

410
00:17:54,160 --> 00:17:52,370
you can see green and purple life forms

411
00:17:56,620 --> 00:17:54,170
of fear up here well those are those are

412
00:17:59,710 --> 00:17:56,630
photo tropes and so there's something

413
00:18:00,820 --> 00:17:59,720
about the the source fluid of this

414
00:18:03,100 --> 00:18:00,830
system that's constraining

415
00:18:05,800 --> 00:18:03,110
photosynthesis not allowing it to

416
00:18:08,410 --> 00:18:05,810
compete in that environment and here's

417
00:18:12,690 --> 00:18:08,420
an environment here on the right this is

418
00:18:15,280 --> 00:18:12,700
roadside spring another spring close to

419
00:18:16,990 --> 00:18:15,290
norris geyser basin has a different p

420
00:18:19,810 --> 00:18:17,000
agent temperature regime and we can see

421
00:18:23,230 --> 00:18:19,820
that that that transition from a largely

422
00:18:25,360 --> 00:18:23,240
chemosynthetic community to one that

423
00:18:29,740 --> 00:18:25,370
photosynthetic occurs at a different ph

424
00:18:32,920 --> 00:18:29,750
and temperature issue okay so we took

425
00:18:37,720 --> 00:18:32,930
and we mapped the distribution of

426
00:18:39,790 --> 00:18:37,730
photosynthesis and I think roughly 450

427
00:18:42,010 --> 00:18:39,800
different hotspur 440 hot springs in

428
00:18:43,480 --> 00:18:42,020
Yellowstone and and this is just three

429
00:18:45,880 --> 00:18:43,490
analytes that we've measured we measured

430
00:18:48,250 --> 00:18:45,890
temperature pH and sulfide we just

431
00:18:51,120 --> 00:18:48,260
simply ask the question where do we find

432
00:18:53,260 --> 00:18:51,130
photosynthesis evidence for genetic or

433
00:18:55,480 --> 00:18:53,270
biochemical evidence for photosynthesis

434
00:18:57,820 --> 00:18:55,490
and where do we not and the first thing

435
00:18:59,500 --> 00:18:57,830
I'd like to point your attention to is

436
00:19:01,270 --> 00:18:59,510
this panel on the left now this is the

437
00:19:04,300 --> 00:19:01,280
distribution of photosynthesis as a

438
00:19:08,160 --> 00:19:04,310
function of temperature and pH and what

439
00:19:12,520 --> 00:19:08,170
we see well we see kind of a stepwise

440
00:19:15,220 --> 00:19:12,530
function there we're at ph 5 you see

441
00:19:17,560 --> 00:19:15,230
photosynthesis and the systems with ph

442
00:19:18,970 --> 00:19:17,570
greater than 5 we see photosynthesis all

443
00:19:24,400 --> 00:19:18,980
the way up is about 73 degrees

444
00:19:26,860 --> 00:19:24,410
centigrade and below this ph realm more

445
00:19:29,470 --> 00:19:26,870
acidic systems we see photosynthesis

446
00:19:30,790 --> 00:19:29,480
more constrained to lower lower

447
00:19:34,090 --> 00:19:30,800
temperature environments and so what is

448
00:19:35,860 --> 00:19:34,100
this telling us well we think that this

449
00:19:38,410 --> 00:19:35,870
is telling us that photosynthesis it's

450
00:19:39,549 --> 00:19:38,420
very unlikely photosynthesis originated

451
00:19:42,489 --> 00:19:39,559
in the hot spring with the 10

452
00:19:43,779 --> 00:19:42,499
greater than 72 degrees centigrade we

453
00:19:46,539 --> 00:19:43,789
think that there's something very unique

454
00:19:49,539 --> 00:19:46,549
about this 73 degrees centigrade upper

455
00:19:51,369 --> 00:19:49,549
temperature limit that is keeping

456
00:19:53,230 --> 00:19:51,379
photosynthesis from diversifying into

457
00:19:54,220 --> 00:19:53,240
those into those environmental realms

458
00:19:56,639 --> 00:19:54,230
and I actually had a very nice

459
00:19:59,230 --> 00:19:56,649
discussion with with Eric my

460
00:20:01,180 --> 00:19:59,240
co-presenter hear about what this what

461
00:20:04,869 --> 00:20:01,190
might be defining the supper temperature

462
00:20:06,159 --> 00:20:04,879
limit we started really well we spent

463
00:20:07,539 --> 00:20:06,169
about 30 minutes that we should been

464
00:20:09,310 --> 00:20:07,549
using to prepare for this presentation

465
00:20:11,590 --> 00:20:09,320
talking about what what this might

466
00:20:13,230 --> 00:20:11,600
reflect and it got very interesting

467
00:20:16,149 --> 00:20:13,240
talking about inorganic carbon

468
00:20:19,659 --> 00:20:16,159
availability potentially the constraints

469
00:20:22,299 --> 00:20:19,669
at that place is on the ability for

470
00:20:24,940 --> 00:20:22,309
these organisms to get rid of reducing

471
00:20:26,529 --> 00:20:24,950
equivalents or electrons that their

472
00:20:27,879 --> 00:20:26,539
chatter that they generate through

473
00:20:30,850 --> 00:20:27,889
photosynthesis they can't really

474
00:20:32,470 --> 00:20:30,860
regulate photosynthesis and their

475
00:20:34,840 --> 00:20:32,480
inability to get rid of those electrons

476
00:20:36,940 --> 00:20:34,850
so at this 73 degree temperature limit

477
00:20:39,430 --> 00:20:36,950
perhaps they're there they're just

478
00:20:42,039 --> 00:20:39,440
burning up with energy what about this

479
00:20:44,859 --> 00:20:42,049
this this step function that occurs here

480
00:20:46,950 --> 00:20:44,869
at about ph 5 well that turns out to be

481
00:20:49,029 --> 00:20:46,960
a strip demarcation between

482
00:20:51,989 --> 00:20:49,039
cyanobacterial dominated systems at

483
00:20:56,169 --> 00:20:51,999
about between ph 4 and 5 and above

484
00:20:59,799 --> 00:20:56,179
versus algal dominated systems below

485
00:21:03,789 --> 00:20:59,809
below this ph realm so if we now

486
00:21:05,769 --> 00:21:03,799
transition over to panel B we have math

487
00:21:08,259 --> 00:21:05,779
to the distribution of photosynthesis as

488
00:21:09,519 --> 00:21:08,269
a function of temperature and sulfide we

489
00:21:11,200 --> 00:21:09,529
can see that there appears to be an

490
00:21:14,080 --> 00:21:11,210
upper temperature or an upper sulphide

491
00:21:15,940 --> 00:21:14,090
limit for for most of these photo tropes

492
00:21:18,690 --> 00:21:15,950
and I should mention that this is

493
00:21:21,159 --> 00:21:18,700
probably Yellowstone specific as there's

494
00:21:22,960 --> 00:21:21,169
known to be some cyanobacteria that

495
00:21:24,879 --> 00:21:22,970
tolerate much higher concentrations of

496
00:21:26,440 --> 00:21:24,889
sulfides of this and so for whatever

497
00:21:29,980 --> 00:21:26,450
reason is those organisms aren't

498
00:21:32,739 --> 00:21:29,990
successful in Yellowstone but anyway so

499
00:21:34,359 --> 00:21:32,749
we saw this data and we decided well

500
00:21:36,159 --> 00:21:34,369
this is interesting let's see if we

501
00:21:38,950 --> 00:21:36,169
can't understand what the effect of

502
00:21:41,259 --> 00:21:38,960
sulfide is on photosynthetic activities

503
00:21:42,999 --> 00:21:41,269
we picked a couple algal dominated

504
00:21:44,379 --> 00:21:43,009
systems and a couple of cyanobacterial

505
00:21:46,389 --> 00:21:44,389
dominated systems and we showed that

506
00:21:49,509 --> 00:21:46,399
cyanobacteria don't seem to be sensitive

507
00:21:53,940 --> 00:21:49,519
to sulfide okay but the algal

508
00:21:57,460 --> 00:21:53,950
populations co2 fixation systematically

509
00:22:00,550 --> 00:21:57,470
goes down with increasing sulfide

510
00:22:03,120 --> 00:22:00,560
concentration suggesting that something

511
00:22:07,990 --> 00:22:03,130
may perhaps sulfide gradients might have

512
00:22:11,170 --> 00:22:08,000
impacted the evolution of algae and how

513
00:22:15,550 --> 00:22:11,180
the ability for eukaryotes to perform

514
00:22:19,030 --> 00:22:15,560
photosynthesis and this final slide I'm

515
00:22:21,970 --> 00:22:19,040
just going to cut to the chase here this

516
00:22:23,620 --> 00:22:21,980
is about thirty thirty communities in

517
00:22:25,530 --> 00:22:23,630
the Yellowstone that we generated meta

518
00:22:30,010 --> 00:22:25,540
genomic sequence data so that is

519
00:22:32,710 --> 00:22:30,020
randomly sequence total genomic DNA from

520
00:22:36,610 --> 00:22:32,720
these communities through a series of

521
00:22:38,830 --> 00:22:36,620
bioinformatics tools that get a little

522
00:22:41,680 --> 00:22:38,840
complex we generate a comparative

523
00:22:42,850 --> 00:22:41,690
analysis of the metabolic composition of

524
00:22:44,860 --> 00:22:42,860
these communities or the genetic

525
00:22:46,960 --> 00:22:44,870
composition of these communities so

526
00:22:49,210 --> 00:22:46,970
those communities that are separated by

527
00:22:51,550 --> 00:22:49,220
a short branch links here are more

528
00:22:53,830 --> 00:22:51,560
similar metabolically than those that

529
00:22:58,120 --> 00:22:53,840
are separated by longer branch links and

530
00:23:00,790 --> 00:22:58,130
what you can see here very simply is

531
00:23:03,340 --> 00:23:00,800
this B mark ation between photosynthetic

532
00:23:06,310 --> 00:23:03,350
and chemosynthetic ecosystems and if we

533
00:23:09,850 --> 00:23:06,320
think back to this transition that we

534
00:23:11,980 --> 00:23:09,860
noted in our distribution analysis you

535
00:23:15,250 --> 00:23:11,990
can pretty much overlay that right here

536
00:23:17,650 --> 00:23:15,260
so as we transition from kemah trophic

537
00:23:19,690 --> 00:23:17,660
communities to phototrophic communities

538
00:23:23,010 --> 00:23:19,700
you know whatever that was 2.8 million

539
00:23:25,440 --> 00:23:23,020
years ago all hell broke loose

540
00:23:29,020 --> 00:23:25,450
metabolically all kinds of news

541
00:23:30,460 --> 00:23:29,030
metabolic innovations the second thing I

542
00:23:32,500 --> 00:23:30,470
want to point out on this flight I don't

543
00:23:35,770 --> 00:23:32,510
have it clearly delineated here but

544
00:23:38,260 --> 00:23:35,780
within that kima trophic cluster there's

545
00:23:41,430 --> 00:23:38,270
two there's two primary clusters sub

546
00:23:43,930 --> 00:23:41,440
clusters one of these is comprises

547
00:23:45,990 --> 00:23:43,940
communities that inhabit circum neutral

548
00:23:48,700 --> 00:23:46,000
to alkaline systems and the other

549
00:23:51,310 --> 00:23:48,710
comprises communities that have it

550
00:23:54,010 --> 00:23:51,320
acidic systems and that demarcation is

551
00:23:57,150 --> 00:23:54,020
right there at about ph 5 and so there's

552
00:23:59,290 --> 00:23:57,160
something about systems that are

553
00:24:01,450 --> 00:23:59,300
alkaline or circum neutral that select

554
00:24:05,670 --> 00:24:01,460
for different metabolic functions than

555
00:24:08,550 --> 00:24:05,680
those that are acidic now this analysis

556
00:24:10,710 --> 00:24:08,560
is interesting as it might be is not

557
00:24:12,900 --> 00:24:10,720
where Eric and I would like to see that

558
00:24:15,180 --> 00:24:12,910
and what we would really like to do and

559
00:24:18,690 --> 00:24:15,190
what we're really proposing here in this

560
00:24:21,120 --> 00:24:18,700
light paper is to take this data to take

561
00:24:23,580 --> 00:24:21,130
this data that we already have and turn

562
00:24:26,160 --> 00:24:23,590
it and really analyze it within a

563
00:24:28,020 --> 00:24:26,170
phylogenetic framework so the problem

564
00:24:30,510 --> 00:24:28,030
with this data set as it exists we can't

565
00:24:32,250 --> 00:24:30,520
establish trajectory okay we can map

566
00:24:36,480 --> 00:24:32,260
geochemical gradients on this very

567
00:24:39,600 --> 00:24:36,490
easily but we can't map trajectory so to

568
00:24:42,180 --> 00:24:39,610
really link this this space for time

569
00:24:44,700 --> 00:24:42,190
argument and make use of it right we

570
00:24:47,310 --> 00:24:44,710
want to feed this into a phylogenetic

571
00:24:49,620 --> 00:24:47,320
context or a phylogenetic context and

572
00:24:53,430 --> 00:24:49,630
then at that point really start looking

573
00:24:55,860 --> 00:24:53,440
at specific metabolic pathways how they

574
00:24:57,360 --> 00:24:55,870
evolved when they evolved in what kind

575
00:25:00,390 --> 00:24:57,370
of environment types seem to have

576
00:25:06,960 --> 00:25:00,400
selected for or the innovation of those

577
00:25:09,000 --> 00:25:06,970
of those metabolisms and then finally if

578
00:25:11,970 --> 00:25:09,010
we're able to get that far in our

579
00:25:13,590 --> 00:25:11,980
analyses what we really think should be

580
00:25:15,360 --> 00:25:13,600
done is we think that we should

581
00:25:17,760 --> 00:25:15,370
integrate reaction kinetics into these

582
00:25:21,030 --> 00:25:17,770
models and so you can make the argument

583
00:25:24,120 --> 00:25:21,040
that that geochemistry is extremely

584
00:25:26,340 --> 00:25:24,130
important in the diversification of life

585
00:25:27,900 --> 00:25:26,350
without a doubt that was the case but

586
00:25:29,130 --> 00:25:27,910
something that's very difficult to

587
00:25:32,550 --> 00:25:29,140
incorporate into those kind of

588
00:25:36,440 --> 00:25:32,560
considerations is the fact that some

589
00:25:39,240 --> 00:25:36,450
reactions have huge kinetic barriers to

590
00:25:41,750 --> 00:25:39,250
biology and maybe they don't have such

591
00:25:45,870 --> 00:25:41,760
high kinetic barriers to abiotic

592
00:25:49,470 --> 00:25:45,880
reactions and so the example that that I

593
00:25:51,480 --> 00:25:49,480
like to use is so we've we've all heard

594
00:25:55,230 --> 00:25:51,490
of these these really interesting Oh

595
00:25:56,790 --> 00:25:55,240
flight systems such as lost city where

596
00:26:00,060 --> 00:25:56,800
they're generating massive quantities of

597
00:26:02,010 --> 00:26:00,070
hydrogen abiotic Lee well if you're a

598
00:26:04,020 --> 00:26:02,020
fervent eighth of organism you're an

599
00:26:05,340 --> 00:26:04,030
organism that's fermenting for made or

600
00:26:08,400 --> 00:26:05,350
you're fermenting whatever your favorite

601
00:26:11,100 --> 00:26:08,410
organic molecule is and you critically

602
00:26:15,360 --> 00:26:11,110
depend on low partial pressures of

603
00:26:17,190 --> 00:26:15,370
hydrogen to run that reaction forward to

604
00:26:18,770 --> 00:26:17,200
take that reaction forward now that's

605
00:26:21,350 --> 00:26:18,780
not going to be a great place for you to

606
00:26:23,740 --> 00:26:21,360
to be catalyzing these processes you can

607
00:26:26,000 --> 00:26:23,750
also think about this as you have these

608
00:26:27,910 --> 00:26:26,010
ophiolite sequences that are cat

609
00:26:30,530 --> 00:26:27,920
catalyzing the reduction of co2

610
00:26:34,520 --> 00:26:30,540
producing formate as an intermediate on

611
00:26:36,950 --> 00:26:34,530
its way to methane if you are an

612
00:26:40,550 --> 00:26:36,960
organism that wants to squeak out a

613
00:26:43,490 --> 00:26:40,560
living i'm using a form 8 as an electron

614
00:26:46,040 --> 00:26:43,500
or carbon source and that abiotic

615
00:26:48,140 --> 00:26:46,050
reaction that abiotic reduction of

616
00:26:51,350 --> 00:26:48,150
formate to methane is too fast for you

617
00:26:55,460 --> 00:26:51,360
to keep up you're at a lot right there's

618
00:26:57,530 --> 00:26:55,470
no energy we have for you and so ideally

619
00:26:59,060 --> 00:26:57,540
you know focusing on a couple of

620
00:27:01,220 --> 00:26:59,070
reactions that we think are important

621
00:27:03,590 --> 00:27:01,230
for early life now we might be able to

622
00:27:05,090 --> 00:27:03,600
get at this these kind of questions and

623
00:27:08,240 --> 00:27:05,100
integrate this greater consideration

624
00:27:13,460 --> 00:27:08,250
into these models that we would hope

625
00:27:16,220 --> 00:27:13,470
would be developed and I guess just to

626
00:27:18,590 --> 00:27:16,230
summarize the point here is is how can

627
00:27:21,110 --> 00:27:18,600
we take advantage of expanders

628
00:27:23,720 --> 00:27:21,120
distributions of life and their

629
00:27:25,330 --> 00:27:23,730
metabolic strategies the guide our

630
00:27:27,950 --> 00:27:25,340
understanding of what early life

631
00:27:30,800 --> 00:27:27,960
metabolic strategies were and how they

632
00:27:32,660 --> 00:27:30,810
diversified okay and so really trying to

633
00:27:35,480 --> 00:27:32,670
understand what the role of environment

634
00:27:38,450 --> 00:27:35,490
an environmental variation is in those

635
00:27:40,880 --> 00:27:38,460
events how can we integrate a biotic

636
00:27:42,860 --> 00:27:40,890
reaction kinetics into these models this

637
00:27:44,330 --> 00:27:42,870
is something that that has been avoided

638
00:27:45,950 --> 00:27:44,340
and probably with good reason because

639
00:27:49,730 --> 00:27:45,960
it's not easy to do these kind of

640
00:27:53,690 --> 00:27:49,740
experiments or integrate those into your

641
00:27:57,620 --> 00:27:53,700
models but how can we use abiotic

642
00:28:00,710 --> 00:27:57,630
reaction reaction kinetic kinetics to

643
00:28:03,440 --> 00:28:00,720
further our understanding of what early

644
00:28:04,820 --> 00:28:03,450
life might have been up against we

645
00:28:07,310 --> 00:28:04,830
didn't talk much about the role of inter

646
00:28:09,260 --> 00:28:07,320
species interactions but certainly as

647
00:28:12,410 --> 00:28:09,270
Eric mentioned there's very few

648
00:28:15,020 --> 00:28:12,420
environments that are mono species

649
00:28:16,670 --> 00:28:15,030
environments typically you have a very

650
00:28:19,910 --> 00:28:16,680
complex community and so you can't

651
00:28:21,950 --> 00:28:19,920
neglect the role of interspecies

652
00:28:25,870 --> 00:28:21,960
interactions in dictating

653
00:28:27,800 --> 00:28:25,880
co-evolutionary dynamics and I guess

654
00:28:30,380 --> 00:28:27,810
finally you know why would any

655
00:28:32,100 --> 00:28:30,390
astrobiologist care you know how can we

656
00:28:34,799 --> 00:28:32,110
use the information that we would gain

657
00:28:38,730 --> 00:28:34,809
came from such a these analyses to guide

658
00:28:42,090 --> 00:28:38,740
or improve guiding a site selection for

659
00:28:44,460 --> 00:28:42,100
four missions and Eric and I both think

660
00:28:48,299 --> 00:28:44,470
that by focusing on these early early

661
00:28:51,660 --> 00:28:48,309
life sustaining metabolisms exploitation

662
00:28:53,549 --> 00:28:51,670
of small energetic gradients that those

663
00:28:57,330 --> 00:28:53,559
are the kind of metabolisms that we most

664
00:29:00,330 --> 00:28:57,340
likely see on another planet and that

665
00:29:02,610 --> 00:29:00,340
could provide some new insight in that

666
00:29:04,770 --> 00:29:02,620
regard and so with that that's the end

667
00:29:07,500 --> 00:29:04,780
of our presentation I'd be great to open

668
00:29:11,400 --> 00:29:07,510
this up for any discussion that people

669
00:29:14,669 --> 00:29:11,410
might have Thanks great thank you very

670
00:29:17,430 --> 00:29:14,679
much um just while you're doing the

671
00:29:21,930 --> 00:29:17,440
presentation we switched the document so

672
00:29:23,520 --> 00:29:21,940
it's now open for adding comments I can

673
00:29:26,880 --> 00:29:23,530
see there are several people in here

674
00:29:29,490 --> 00:29:26,890
it's helpful if you can actually log in

675
00:29:32,460 --> 00:29:29,500
with your google ID just so the authors

676
00:29:34,590 --> 00:29:32,470
can see who's writing what so if you're

677
00:29:38,340 --> 00:29:34,600
logged in and you know you are anonymous

678
00:29:40,110 --> 00:29:38,350
narwhal or anonymous wombat as Google

679
00:29:41,760 --> 00:29:40,120
likes to give you these names it's great

680
00:29:44,310 --> 00:29:41,770
if before you add your comments you

681
00:29:45,960 --> 00:29:44,320
could just authenticate if for some

682
00:29:48,659 --> 00:29:45,970
reason that doesn't work then it's worth

683
00:29:52,110 --> 00:29:48,669
sticking your name in when you add your

684
00:29:54,960 --> 00:29:52,120
virtual post-it notes so um at this

685
00:29:58,260 --> 00:29:54,970
point where i can see dave is is typing

686
00:30:00,990 --> 00:29:58,270
comments already but the audio lines are

687
00:30:03,180 --> 00:30:01,000
now open Jennifer I've noticed that

688
00:30:04,860 --> 00:30:03,190
you're sort of coming in and out of the

689
00:30:06,690 --> 00:30:04,870
space oh and presumably a slight

690
00:30:10,039 --> 00:30:06,700
technical problems there but hopefully

691
00:30:12,990 --> 00:30:10,049
you're still with us on audio so

692
00:30:14,850 --> 00:30:13,000
questions observations what should the

693
00:30:38,320 --> 00:30:14,860
authors be thinking about and how can we

694
00:30:42,889 --> 00:30:41,180
actually won't dave is type in cleansing

695
00:30:45,490 --> 00:30:42,899
I know that just recently you've always

696
00:30:49,639 --> 00:30:45,500
wanted to ask questions with regards to

697
00:30:51,289 --> 00:30:49,649
where this would shape activities but I

698
00:30:55,430 --> 00:30:51,299
don't want to put words into your mouth

699
00:30:58,940 --> 00:30:55,440
so what is even normally asking hey the

700
00:31:00,680 --> 00:30:58,950
presenters to put cool yeah so I mean

701
00:31:02,600 --> 00:31:00,690
that this is this is sort of a question

702
00:31:05,060 --> 00:31:02,610
that we've been trying to move forward

703
00:31:08,389 --> 00:31:05,070
with and that sort of you know this I

704
00:31:09,769 --> 00:31:08,399
know this topic is I find this one very

705
00:31:12,440 --> 00:31:09,779
interesting and you know i think that

706
00:31:14,869 --> 00:31:12,450
there's there's certainly a in some ways

707
00:31:16,999 --> 00:31:14,879
this feels like a very long term view of

708
00:31:20,570 --> 00:31:17,009
how to view this but what specifically

709
00:31:21,950 --> 00:31:20,580
do you guys think is more what kind of

710
00:31:23,330 --> 00:31:21,960
things do you think are more likely to

711
00:31:25,940 --> 00:31:23,340
be you know what we're going to look at

712
00:31:34,159 --> 00:31:25,950
in the next 10 years rather than sort of

713
00:31:35,960 --> 00:31:34,169
set the very long view ah I guess I'll

714
00:31:38,840 --> 00:31:35,970
take the first crack at that I don't

715
00:31:43,159 --> 00:31:38,850
think that this is a very real long-term

716
00:31:45,399 --> 00:31:43,169
view at all I think with the expanse of

717
00:31:47,810 --> 00:31:45,409
genome sequence technology i mean it's

718
00:31:49,460 --> 00:31:47,820
absolutely crazy what you can generate a

719
00:31:53,029 --> 00:31:49,470
meta-genome for one hundred two hundred

720
00:31:57,289 --> 00:31:53,039
dollars these days you have the samples

721
00:32:01,279 --> 00:31:57,299
that span that 1440 geochemical very hot

722
00:32:02,840 --> 00:32:01,289
spring gradient that i showed you and we

723
00:32:04,009 --> 00:32:02,850
have the bio and traumatic tools to make

724
00:32:07,159 --> 00:32:04,019
this happen i'm sorry i'm having trouble

725
00:32:10,730 --> 00:32:07,169
with my light son just keeps moving on

726
00:32:13,549 --> 00:32:10,740
me um anyway I so I don't think it

727
00:32:16,399 --> 00:32:13,559
necessarily is at least on that first

728
00:32:20,419 --> 00:32:16,409
part the sense this is a very long term

729
00:32:21,889 --> 00:32:20,429
goal I think we can do this now you

730
00:32:23,269 --> 00:32:21,899
think that kind of thing is the kind of

731
00:32:26,120 --> 00:32:23,279
thing you're looking at in the next 10

732
00:32:31,919 --> 00:32:30,630
meta-genome you can act in it I think

733
00:32:33,360 --> 00:32:31,929
you can do it with metagenomes I think

734
00:32:35,039 --> 00:32:33,370
he can do it with meta transcriptomes

735
00:32:39,630 --> 00:32:35,049
which would even get more interesting

736
00:32:40,830 --> 00:32:39,640
right so you can start looking at you

737
00:32:43,049 --> 00:32:40,840
could even look at temporal dynamics

738
00:32:47,760 --> 00:32:43,059
within a system and how that's causing

739
00:32:49,500 --> 00:32:47,770
metabolic complexity to evolve but I you

740
00:32:52,380 --> 00:32:49,510
know this is all stuff that I think the

741
00:32:55,260 --> 00:32:52,390
the integrating abiotic reaction

742
00:32:58,110 --> 00:32:55,270
kinetics for even biological reaction

743
00:33:02,100 --> 00:32:58,120
kinetics into these models is where the

744
00:33:04,860 --> 00:33:02,110
challenges that's that to me is where we

745
00:33:07,110 --> 00:33:04,870
need to go but Eric I don't give

746
00:33:11,399 --> 00:33:07,120
anything to add yeah I'd like to pick up

747
00:33:13,770 --> 00:33:11,409
on that and of agreeing with you too to

748
00:33:18,480 --> 00:33:13,780
say some some more things of a similar

749
00:33:23,430 --> 00:33:18,490
sort and hi Lindsay you know it seems

750
00:33:25,169 --> 00:33:23,440
Eric here there are basic things about

751
00:33:27,810 --> 00:33:25,179
the notion of cause and the notion of

752
00:33:29,880 --> 00:33:27,820
regulation where we spend a lot of time

753
00:33:31,799 --> 00:33:29,890
taking for granted when in fact we have

754
00:33:35,490 --> 00:33:31,809
the data to actually try to understand

755
00:33:37,260 --> 00:33:35,500
instead too many things organism focused

756
00:33:39,419 --> 00:33:37,270
we're at the level of basically trying

757
00:33:42,180 --> 00:33:39,429
to model constraints like full

758
00:33:44,250 --> 00:33:42,190
metabolism models for organisms it still

759
00:33:46,020 --> 00:33:44,260
is just the leading edge to try to

760
00:33:48,240 --> 00:33:46,030
understand the regulation of metabolism

761
00:33:52,020 --> 00:33:48,250
within organisms but there's a lot of

762
00:33:53,820 --> 00:33:52,030
reason I would argue to say that a lot

763
00:33:56,760 --> 00:33:53,830
of constraint or causation or even

764
00:33:59,220 --> 00:33:56,770
regulation of chemical reaction input

765
00:34:00,840 --> 00:33:59,230
output systems is not controlled at the

766
00:34:02,820 --> 00:34:00,850
organism level it's controlled at the

767
00:34:07,200 --> 00:34:02,830
ecosystem level and it's mediated by

768
00:34:08,909 --> 00:34:07,210
organism dynamics but the the point Eric

769
00:34:11,119 --> 00:34:08,919
was making where you can do dendrograms

770
00:34:16,230 --> 00:34:11,129
and you can do similarity relations at

771
00:34:19,169 --> 00:34:16,240
the sort of ecosystem level metabolic

772
00:34:21,270 --> 00:34:19,179
competence level you would really like

773
00:34:23,849 --> 00:34:21,280
to pair that with an organism

774
00:34:25,829 --> 00:34:23,859
phylogenetic reconstruction because what

775
00:34:28,260 --> 00:34:25,839
you get from organism histories are two

776
00:34:29,909 --> 00:34:28,270
things one is the dependency sequence

777
00:34:31,649 --> 00:34:29,919
and then the other is the degree of

778
00:34:33,450 --> 00:34:31,659
Trina sort of articulation which gives

779
00:34:36,550 --> 00:34:33,460
you some sense of where you need to know

780
00:34:38,700 --> 00:34:36,560
or don't need to know ecological context

781
00:34:41,710 --> 00:34:38,710
what the determinants were of

782
00:34:43,450 --> 00:34:41,720
opportunities for innovation and I feel

783
00:34:45,730 --> 00:34:43,460
like this is a place to actually get

784
00:34:47,710 --> 00:34:45,740
conceptually at where cause and

785
00:34:50,980 --> 00:34:47,720
regulation are going on in biology it's

786
00:34:52,990 --> 00:34:50,990
it's not us I was going to say something

787
00:34:56,800 --> 00:34:53,000
that would get me in trouble but I think

788
00:34:59,200 --> 00:34:56,810
better of it it's not a particularly

789
00:35:01,420 --> 00:34:59,210
scientifically well defended point of

790
00:35:04,530 --> 00:35:01,430
view to just suppose that everything

791
00:35:07,750 --> 00:35:04,540
happens at the level of the organism and

792
00:35:09,580 --> 00:35:07,760
you know the the tools we have both for

793
00:35:11,320 --> 00:35:09,590
modeling and just for data analysis

794
00:35:13,120 --> 00:35:11,330
allow us to frame a lot of those

795
00:35:15,040 --> 00:35:13,130
questions in a less prejudiced way and I

796
00:35:22,780 --> 00:35:15,050
think that stuff we can do in in real

797
00:35:26,830 --> 00:35:22,790
time with what we already have gentlemen

798
00:35:29,470 --> 00:35:26,840
DC the the question that dave has 20

799
00:35:32,110 --> 00:35:29,480
into your chat window so i do i'm

800
00:35:34,390 --> 00:35:32,120
reading now nothing said to give you a

801
00:35:43,720 --> 00:35:34,400
million or so typical it was typing for

802
00:35:45,720 --> 00:35:43,730
so long oh yeah the the connectivity of

803
00:35:47,800 --> 00:35:45,730
extreme environments you know i

804
00:35:51,510 --> 00:35:47,810
absolutely you know our hot springs the

805
00:35:55,120 --> 00:35:51,520
best environment study origin of life

806
00:35:58,150 --> 00:35:55,130
type to nibhana probably not right i

807
00:36:02,340 --> 00:35:58,160
mean for the reasons that you indicate

808
00:36:06,130 --> 00:36:02,350
here also because they jet they you know

809
00:36:08,770 --> 00:36:06,140
a little known fact is that they get a

810
00:36:11,620 --> 00:36:08,780
lot of support from their external

811
00:36:13,450 --> 00:36:11,630
environment which is you know adjacent

812
00:36:15,850 --> 00:36:13,460
soils and so on and so forth so they're

813
00:36:17,590 --> 00:36:15,860
connected you're making the claim that

814
00:36:21,070 --> 00:36:17,600
maybe some of these organisms don't have

815
00:36:23,410 --> 00:36:21,080
actually a heritage in these systems and

816
00:36:27,040 --> 00:36:23,420
actually recently invaded these systems

817
00:36:29,620 --> 00:36:27,050
and and I think that's partially true

818
00:36:31,300 --> 00:36:29,630
for sub dominant players but the

819
00:36:34,660 --> 00:36:31,310
dominant players and all of the systems

820
00:36:37,980 --> 00:36:34,670
at least that I've ever looked at have a

821
00:36:42,820 --> 00:36:37,990
strong hydrothermal early life

822
00:36:46,170 --> 00:36:42,830
hydrothermal heritage where I where I

823
00:36:48,450 --> 00:36:46,180
think you know we're going to improve

824
00:36:50,520 --> 00:36:48,460
site selection for

825
00:36:53,480 --> 00:36:50,530
you know some of these these missions

826
00:36:56,220 --> 00:36:53,490
well what do we need to do well I think

827
00:37:00,570 --> 00:36:56,230
moving from surface hot spring type

828
00:37:03,780 --> 00:37:00,580
systems for surface living into the deep

829
00:37:08,579 --> 00:37:03,790
subsurface rate so drilling in a

830
00:37:11,280 --> 00:37:08,589
hydrothermal system looking at some of

831
00:37:13,530 --> 00:37:11,290
these subsurface ophiolites and

832
00:37:16,890 --> 00:37:13,540
understanding how those organisms are

833
00:37:22,740 --> 00:37:16,900
exploiting small energetic gradients and

834
00:37:24,780 --> 00:37:22,750
I think that to me is the key parameter

835
00:37:28,589 --> 00:37:24,790
to focus in on it's not the heat it's

836
00:37:31,099 --> 00:37:28,599
not the low pH of a high pH it's its

837
00:37:36,079 --> 00:37:31,109
energetic gradients that are small and

838
00:37:39,240 --> 00:37:36,089
how does white develop a strategy to

839
00:37:41,730 --> 00:37:39,250
support itself based on those small

840
00:37:45,690 --> 00:37:41,740
energetic gradients and are there this

841
00:37:48,359 --> 00:37:45,700
is key are there some unique biomarkers

842
00:37:51,950 --> 00:37:48,369
whether it be a gaseous biomarker a

843
00:37:54,540 --> 00:37:51,960
metabolic biomarker a biochemical marker

844
00:37:58,130 --> 00:37:54,550
for those kind of organisms that we can

845
00:38:03,810 --> 00:37:58,140
exploit in our search for life elsewhere

846
00:38:08,099 --> 00:38:03,820
that would be my comments on your your

847
00:38:10,470 --> 00:38:08,109
comment David yeah I just put it out

848
00:38:12,650 --> 00:38:10,480
mostly as a cautionary note about how

849
00:38:14,970 --> 00:38:12,660
far you can push final genetics in this

850
00:38:17,400 --> 00:38:14,980
because as you guys know much better

851
00:38:19,140 --> 00:38:17,410
than I that when organisms associate in

852
00:38:21,060 --> 00:38:19,150
communities that gene transfers and

853
00:38:23,070 --> 00:38:21,070
stuffed end over time to organize them

854
00:38:25,470 --> 00:38:23,080
some of the earliest evidence for the

855
00:38:29,370 --> 00:38:25,480
antiquity of photosynthesis is really it

856
00:38:32,370 --> 00:38:29,380
sort of functional space more than then

857
00:38:34,500 --> 00:38:32,380
you know what is with us that we don't

858
00:38:36,930 --> 00:38:34,510
want to talk about them sequence

859
00:38:40,020 --> 00:38:36,940
similarity in on some of the molecules

860
00:38:41,609 --> 00:38:40,030
that code for it so you know it's just

861
00:38:42,960 --> 00:38:41,619
that I think this is sort of like when

862
00:38:44,700 --> 00:38:42,970
you go to Mars looking for life you have

863
00:38:45,960 --> 00:38:44,710
to worry about terrestrial contamination

864
00:38:48,900 --> 00:38:45,970
when you do this you have to worry about

865
00:38:51,599 --> 00:38:48,910
quote contamination from things that are

866
00:38:53,040 --> 00:38:51,609
really not intrinsically intrinsic

867
00:38:55,230 --> 00:38:53,050
principles of living in an extreme

868
00:38:58,920 --> 00:38:55,240
environment so just just sort of a

869
00:39:02,500 --> 00:38:58,930
cautionary known about phylogeny yeah

870
00:39:04,480 --> 00:39:02,510
well I think I think that I I definitely

871
00:39:09,040 --> 00:39:04,490
what you're saying but I think the point

872
00:39:10,630 --> 00:39:09,050
is is that unless you have a heritage an

873
00:39:12,730 --> 00:39:10,640
evolutionary history that allows

874
00:39:15,190 --> 00:39:12,740
whatever function that is that you got

875
00:39:16,840 --> 00:39:15,200
you know so its ecology really defines

876
00:39:18,250 --> 00:39:16,850
the success of horizontal gene transfer

877
00:39:22,330 --> 00:39:18,260
you're not going to see genes

878
00:39:24,460 --> 00:39:22,340
transferred from organisms one from an

879
00:39:26,860 --> 00:39:24,470
acidifying went from an alkyl ofile very

880
00:39:28,450 --> 00:39:26,870
often right you see it often within an

881
00:39:31,240 --> 00:39:28,460
asst it of silt in an acid environment

882
00:39:34,630 --> 00:39:31,250
or an alkyl environment so there are

883
00:39:37,630 --> 00:39:34,640
environmental barriers to do gene

884
00:39:39,070 --> 00:39:37,640
transfer and because of that when you

885
00:39:41,520 --> 00:39:39,080
think about these systems at the

886
00:39:44,560 --> 00:39:41,530
ecosystem level like Eric just mentioned

887
00:39:48,730 --> 00:39:44,570
those kind of considerations become less

888
00:39:51,790 --> 00:39:48,740
of a concern you know what you're

889
00:39:54,730 --> 00:39:51,800
talking we yeah that that's that's all

890
00:39:56,650 --> 00:39:54,740
I'd have to say about that yeah I always

891
00:39:59,260 --> 00:39:56,660
worried more about comparisons of genes

892
00:40:00,730 --> 00:39:59,270
within a given environment where

893
00:40:03,640 --> 00:40:00,740
organism might have come from a variety

894
00:40:05,380 --> 00:40:03,650
of sources but you're right on i think

895
00:40:07,810 --> 00:40:05,390
it's the process that's required to

896
00:40:13,660 --> 00:40:07,820
survive in that environment that is is

897
00:40:15,910 --> 00:40:13,670
the key thing to keep in the front and

898
00:40:17,650 --> 00:40:15,920
this good thing to to keep in mind here

899
00:40:23,080 --> 00:40:17,660
which is the phylogenetic siz not an

900
00:40:26,500 --> 00:40:23,090
oracle phylogenetics is one indication

901
00:40:28,240 --> 00:40:26,510
of relatedness or dependency which winds

902
00:40:31,120 --> 00:40:28,250
up being used in a very multi-factor

903
00:40:35,380 --> 00:40:31,130
argument and at this point that Eric

904
00:40:37,690 --> 00:40:35,390
just made about the sort of not only

905
00:40:39,970 --> 00:40:37,700
species separation environment but

906
00:40:42,790 --> 00:40:39,980
entire phenotype genotype class

907
00:40:44,380 --> 00:40:42,800
separations the amazing thing is that

908
00:40:46,270 --> 00:40:44,390
you can see that in phylogenetic

909
00:40:48,520 --> 00:40:46,280
signatures exactly where you would most

910
00:40:50,710 --> 00:40:48,530
not expect to see it from a standpoint

911
00:40:53,740 --> 00:40:50,720
of gene transfer so you look at

912
00:40:56,170 --> 00:40:53,750
innovations in carbon fixation and not

913
00:40:59,350 --> 00:40:56,180
taking any historical perspective you

914
00:41:01,540 --> 00:40:59,360
can say how can one lay out all known

915
00:41:03,300 --> 00:41:01,550
innovations in carbon fixation just to

916
00:41:05,680 --> 00:41:03,310
see how they depend on each other and

917
00:41:07,870 --> 00:41:05,690
the thing the staggering is that they

918
00:41:10,270 --> 00:41:07,880
reconstruct as a tree much better than

919
00:41:11,440 --> 00:41:10,280
most of the protein families for most

920
00:41:13,810 --> 00:41:11,450
genes in the organ

921
00:41:15,460 --> 00:41:13,820
that use them reconstruct as a tree and

922
00:41:18,490 --> 00:41:15,470
you think that's crazy why would there

923
00:41:22,540 --> 00:41:18,500
be trina's at the deep layers when gene

924
00:41:24,760 --> 00:41:22,550
transfer is easiest and one possible

925
00:41:26,950 --> 00:41:24,770
explanation for that is that the

926
00:41:30,520 --> 00:41:26,960
environments are so strongly in training

927
00:41:35,230 --> 00:41:30,530
organisms can do essentially you can't

928
00:41:37,030 --> 00:41:35,240
for a certain gene inventory far outside

929
00:41:38,530 --> 00:41:37,040
the environment where it's well selected

930
00:41:40,870 --> 00:41:38,540
without the organisms just becoming

931
00:41:42,880 --> 00:41:40,880
non-viable and so you get these tree

932
00:41:44,740 --> 00:41:42,890
like dependencies that are not accidents

933
00:41:46,540 --> 00:41:44,750
of inheritance but just the fact that

934
00:41:50,050 --> 00:41:46,550
environments don't mix without in the

935
00:41:52,150 --> 00:41:50,060
course changing so I think that's great

936
00:41:53,800 --> 00:41:52,160
you know absolutely your point is very

937
00:41:56,680 --> 00:41:53,810
well taken that one must always be

938
00:41:59,500 --> 00:41:56,690
thinking and not using these tools in a

939
00:42:01,120 --> 00:41:59,510
kind of a mindless way but in a

940
00:42:06,730 --> 00:42:01,130
multi-factor argument I think there's a

941
00:42:11,050 --> 00:42:06,740
lot that we can do with care agreed

942
00:42:30,460 --> 00:42:11,060
other other questions or observations

943
00:42:38,089 --> 00:42:35,680
no okay the monkeys gentlemen thank you

944
00:42:40,220 --> 00:42:38,099
Eric Boyd I'd also like to think

945
00:42:42,560 --> 00:42:40,230
probably the graduate student who did

946
00:42:44,000 --> 00:42:42,570
some great photo bombing behind you just

947
00:42:47,450 --> 00:42:44,010
poking her head through the little

948
00:42:49,940 --> 00:42:47,460
window in the club yes you can get a

949
00:42:52,430 --> 00:42:49,950
hold of me and tell about two minutes

950
00:42:56,660 --> 00:42:52,440
before we started this so I've been

951
00:42:58,700 --> 00:42:56,670
hearing her knocking how's that oh well

952
00:43:01,849 --> 00:42:58,710
you can you can say she's contributed to

953
00:43:03,530 --> 00:43:01,859
a webinar on astrobiology probably site

954
00:43:07,700 --> 00:43:03,540
of although i'm not sure what formats

955
00:43:08,990 --> 00:43:07,710
are cycling that is okay so particularly

956
00:43:11,510 --> 00:43:09,000
if you're watching this recording

957
00:43:13,690 --> 00:43:11,520
afterwards also encourage you to go to

958
00:43:17,780 --> 00:43:13,700
the document it's open for comments arm

959
00:43:19,849 --> 00:43:17,790
and that is about it for now so

960
00:43:22,280 --> 00:43:19,859
gentlemen thank you very much and thank