OK. I've done a little homework on what I'm calling your 3rd example of out of
equilibrium (OOE) patterns not well-classed as "evolution through selection"
(EtS). I watched and transcribed the Lennon talk, which was very cool, particularly the
sheer number of nearly inert spores in terms of biomass and the energy required to
produce an endospore in atp units. I can use ffmpeg to extract the slides ... maybe
later. Anyway, good stuff. Thanks.
But in trying to hammer out what you're gesturing at, I went a couple of rounds
with Claude and Asta and landed on a 5 point ball of leads, hoping that listing
those 5 will trigger your memory or cajole you into winnowing it down to 1
thing I can do more homework on. Here's the ball. Obviously, it's not the
Lennon-Shoemaker cite, since you gave that one to me. But it's included for
completeness.
• Steven Finkel (USC): GASP/long-term stationary phase
Finkel SE. "Long-term survival during stationary phase: evolution and the GASP
phenotype." *Nature Reviews Microbiology* 4(2):113–120, 2006.
doi:10.1038/nrmicro1340. PMID 16415927.
• Zambrano & Kolter (Harvard): the GASP founding observation
Zambrano MM, Siegele DA, Almirón M, Tormo A, Kolter R. "Microbial competition:
*Escherichia coli* mutants that take over stationary phase cultures." *Science*
259(5102):1757–1760, 1993. doi:10.1126/science.7681219. PMID 7681219.
• Richard Lenski (Michigan State): LTEE
Lenski RE. "Experimental evolution and the dynamics of adaptation and genome
evolution in microbial populations." *ISME Journal* 11(10):2181–2194, 2017.
doi:10.1038/ismej.2017.69.
• Jay Lennon/William Shoemaker (Indiana → UCLA): extreme energy limitation
Shoemaker WR, Jones SE, Muscarella ME, Behringer MG, Lehmkuhl BK, Lennon JT.
"Microbial population dynamics and evolutionary outcomes under extreme energy
limitation." *PNAS* 118(33):e2101691118, 2021. doi:10.1073/pnas.2101691118.
• Cho / Palsson collaboration (KAIST + UCSD): adaptive laboratory evolution of
genome-reduced E. coli
Choe D, Lee JH, Yoo M, Hwang S, Sung BH, Cho S, Palsson B, Kim SC, Cho B-K.
"Adaptive laboratory evolution of a genome-reduced Escherichia coli."
Nature Communications 10:935, 2019. doi:10.1038/s41467-019-08888-6. PMID 30804335.
As always, I don't intend to abuse your generosity. Feel free to ignore me. The
LTEE experiment is popular in the culture wars ... so I'm already interested in
that. >8^D
On 4/12/26 6:29 PM, Santafe wrote:
Sorry to drop; I also wanted to do a little looking for materials.
On Apr 11, 2026, at 0:43, glen <[email protected]> wrote:
Very cool. Thanks for continuing this. I have 2 requests if you can answer off
the top of your head:
1. One or two good citations for the 2 classes of the out of equilibrium
patterns. I'm at a loss for an example pattern Lachman might include, but you
exclude.
I can give you an idea how widely Michael wants to scope. But for the example I will mention, I can’t find any publication where he built this out, or even a podcast where he discusses it. Probably because it would be hard to find buyers. So these are just things he used as examples in working conversations (maybe even 6 or 7 years ago now? I’m not sure). Michael wanted to treat rocks rolling down hills at different rates as an equally good exemplar of selection. Take lifecycles and everything biological out of the picture entirely. This isn’t a terrible math-analogy for how mortality selection works, if we think of death as regression toward the equilibrium of a Gibbs chemical ensemble. (In other ways, that’s a terrible mangling of categories, but for the tiny bit of math that is left in this case, it works out the same way.) Michael’s limiting case, though, lacks any amplification step or anything like a lifecycle. So there can’t really be anything like fecundity
selection, and there isn’t persistent non-equilibrium patterning. (One could go into the direction of erosion, and look for some kind of amplification, to produce a limited analogue to fecundity selection. But that is still only surfing the shoulder of a transient, so it isn’t a good model for true patterned persistent states in other ways.)
As the other side, where there is differential amplification and attenuation,
but in highly structured systems, a standard layout would be the one I always
trot out by Michael Lynch, as a summary of the population-geneticsts’
abstraction:
The frailty of adaptive hypotheses for the origins of organismal complexity
<https://www.pnas.org/doi/10.1073/pnas.0702207104>
pnas.org <https://www.pnas.org/doi/10.1073/pnas.0702207104>
pnas.2007.104.issue-suppl_1.cover.gif
<https://www.pnas.org/doi/10.1073/pnas.0702207104>
<https://www.pnas.org/doi/10.1073/pnas.0702207104>
Now, I generally put Lynch up as a foil, because he lays out a set of systems, arguing that they are all-and-everything you need, to belittle and attack those who try to put up further “evolutionary syntheses” or their equivalent. However, the formalisms that Lynch is actually offering only apply properly to the abstractions of the replicating genes of Williams and Dawkins. Then, without happening to comment on the fact that he is changing the subject, he goes on to shout “of course selection takes place at the level of genotypes” etc. Yet, where there is relational information that _makes_ genotypes genotypes, he has said nothing about the system of accounting that characterizes how such information is retained and propagated, in his earlier “all-and-everything”. And of course, it was the wish to deal with all that relational information (and other kinds, like symbiotic dependencies in communities) that motivated a lot of the extended syntheses that he mocks and
criticizes. I do often find that his technical criticisms of the extended syntheses are appropriate, because many of them don’t seem anchored in really well-formed principles. But to criticize the argument that something is needed seems misguided to me. I can imagine things that go along the lines of conceptual clarity of the way Fisher worked, but that pick up the many interesting questions that were not in play in Fisher’s day.
I don’t know the literature on pan-genomes well, so much of what I have of them
is from meetings. I did want to mention Jay Lennon, from this meeting here:
Microbial communities: Energetics and dynamics across space and time
<https://www.nitmb.org/microbial-communities-workshop>
nitmb.org <https://www.nitmb.org/microbial-communities-workshop>
95c3c6_6fcd4e52c85c426b8bc99314e9f0a8c4~mv2.png
<https://www.nitmb.org/microbial-communities-workshop>
<https://www.nitmb.org/microbial-communities-workshop>
as someone interesting, whom I heard recently enough that I can remember the
source. I don’t have a paper that seems to exactly cover the scope of his
talk, which had lots of inter-related things and off-hand comments that reflect
the breadth of intuitive appreciation that a worker often has of an area,
beyond what ever makes it into papers. But, from the angle of sporulation, he
does give some discussion of how dormant phases can be reservoirs of genetic
capabilities, which can be actively and selectively re-activated, here:
pmc-card-share.jpg
Evolution with a seed bank: The population genetic consequences of microbial dormancy
<https://pmc.ncbi.nlm.nih.gov/articles/PMC5748526/>
nlm.nih.gov <https://pmc.ncbi.nlm.nih.gov/articles/PMC5748526/>
<https://pmc.ncbi.nlm.nih.gov/articles/PMC5748526/>
Somebody else, who does very-long-term starvation phenotypes on E. coli, and
shows that the whole genome and cell form undergo radical metamorphoses, was
the first person who really got my attention on the dynamic and intentional
characteristics of pan-genomes. But I don’t remember who it was. (Oddly, I
have some synesthetic image of the room I was sitting in watching, but I
couldn’t tell you what meeting or what year it was in.) He is somebody
well-known for this.
2. I'm assuming you and Lachman's ability to grok and play along with each
others' preferences is *because* you work in the same physical location and can
talk informally back and forth. Is that true? Or do you think you could come to
the same facile donning-doffing of each perspective if you *only* communicated
by electronic means ... or through publication letters and such?
It’s a good question. Probably equal amounts of both.
My impulse — being someone given to abstraction — is to suggest that the main
driver is temperament. Neither Michael nor I is out to capture or defend
territory. We also share taking no enjoyment in “conversations” that go in
circles forever because the interlocutors talk past each other and
misunderstand each other’s claims. Michael is, in general, a much more
easy-going and tolerant person than I am, so he doesn’t tend to the immediate
impatience and annoyance with such conversations that I have. But he never
drifts into that direction, so there is never needless upstream swimming to do.
He is also very clear with his categories. Since we both enjoy and are
looking for questions that are actually about something, then, it is
almost-always pretty systematic to see where a misunderstanding has happened,
and figure out how to unravel it to get to a meaningful question we can try to
puzzle out.
But equally much, being in a room has mattered. For a long time now, it has been several years at a time between my path-crossings with Michael. However, it does turn out to be invaluable that I can trudge a half-hour across town in the snow, to sit for an afternoon in a room with him, to try to hash through something. The counterexample that shows this is probably essential is that he makes certain statements to the effect that Hector Zenil’s information-theoretic criticisms of Walker and Cronin’s Assembly Theory are “wrong”. While there is a lot of Zenil’s screed in his blog posts that is unhelpul — but which reviewers and editors were largely able to get him to cut out when he got a few papers on this published — there is a core of his assertion, that the Assembly Index is a certain version of a compression index, that seems correct to me. I am sure that Michael speaks in good faith, and also that he knows what he is talking about. And I am a semi-tourist in these
algorithmic information things, not an essential worker. But for all that, I don’t understand just what Michael is claiming in detail, and probably won’t until I have a couple hours with him for which that is the main topic to sort out. I have felt the lack of that as a kind of exposure, because I worry where I am missing something.
It’s all interesting,
Eric
--
¡sıɹƎ ןıɐH ⊥ ɐןןǝdoɹ ǝ uǝןƃ
ὅτε oi μὲν ἄλλοι κύνες τοὺς ἐχϑροὺς δάκνουσιν, ἐγὰ δὲ τοὺς φίλους, ἵνα σώσω.
WEBVTT
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Good afternoon, everyone. I can start off by challenging some assumptions, I guess,
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about the physiology of microbial systems and start with the proposition that most organisms,
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microbes included, but also plants and animals, live in environments that are typically not
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suitable for growth and reproduction, at least not maximal growth and reproduction. And as
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a result of that, those populations are at risk for extinction. But a lot of different
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strategies have evolved among diverse organisms, including their ability to alter their behaviors.
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Some organisms will disperse into new environments and take on the risk of encountering some
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new set of environmental conditions that might be better. Or some organisms may choose to
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just stay put and evolve locally through a process of natural selection and local adaptations
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to those model conditions. Another option, however, that I'm going to talk about today
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is that organisms can disperse in time. So many organisms have all the capacity to engage
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in dormancy, which we're going to define as the ability for an individual to enter a reversible
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state of reduced metabolic activity. And that's a pretty loose definition, but when we do
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that, there are many different types of plants and animals, bacteria, fungi, insects, rotifers,
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protists, amphibians, birds, all different types of organisms have this ability to engage
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in this process of dormancy. And so that's an example of convergent evolution, because
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the way in which those processes have evolved has arisen independently. There's no shared
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origin in their ability to achieve this process. So it kind of suggests that there's a solution
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to some kind of common problem that isn't encountered. And I guess I want to say by
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showing these different examples, also highlight the mechanisms by which organisms can. For
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some, it's a very passive process where an individual can just kind of passively fall
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into a state of inactivity. But in many instances, there's really complex underlying mechanisms
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that control the ability of an organism to engage in this life history process. Different
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pathways, different developmental pathways, different genetic regulatory mechanisms, often
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leading to vastly different changes in organismal morphology as it goes from a state of being
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an actively growing organism to one that's metabolically connected.
02:38.000 --> 02:43.000
So despite all those fascinating details, I'd like to argue that there maybe are just
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some three essential criteria that need to be met in order for an individual, regardless
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of what taxonomic group you're thinking about, to engage in this process. The first thing
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is that an individual needs to be able to occupy at least one of two different states.
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In the most simplest version of dormancy, you could have an on versus off metabolic
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state. Criterion two is that individual then needs to be able to move or transition between
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those two states. And that can happen in different ways. So we heard a little bit about this
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idea of stochastic switching so that environments may be so unpredictable that individuals would
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randomly move between an active and inactive state. But in many cases, they're tracking
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environmental cues and that's what's regulating the transitions between those two metabolic
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states. So it could be temperature, it could be a depletion of resources, the accumulation
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of waste products in the environment, all those occurring perhaps at the local patch
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scale, or individuals can be queuing in on broader geographic cues like changes in photo
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periods from here. The third criteria that must be met is that there's no benefit to
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be dormant because you're not reproducing. And that's ultimately what's important and
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selected for by natural selection. But you can enjoy protection against the environmental
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conditions that would otherwise increase your mortality. So there has to be some protection
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that's afforded to individuals that are not engaging in metabolism and replication. So
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those are the central criteria for being a dormant order and engaging in this process.
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So we've been thinking about these processes and how they influence microbial communities
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for quite a while now. I think we've been able to demonstrate that it's important for
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the maintenance of the diversity of complex microbial communities, and in some case helps
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us understand and predict the functioning of an ecosystem. And the figure I'm showing
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here right now is just looking at the accumulation of metabolically inactive individuals into
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all microorganisms. And so what you can see is that they're accumulating collectively
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the abundance and biomass of these different individuals in different ecosystems in a variable
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way. In some cases, in soil, which we care about in terms of thinking about the sequestration
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of carbon from the atmosphere, nutrient cycling for crop and food production, upwards of 90%
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or more of those microbial cells are in a state of metabolic inactivity. And so these
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observations that we made a long time ago, just by combing information from the literature,
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motivated us to be thinking about developing experimental systems that we can bring into
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the lab to generate and test theory regarding the evolutionary properties of microbial life.
05:25.000 --> 05:36.000
Yeah, so in this case, this is all based on single cell data where you could look at,
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for example, the recovery of ribosomes from cells or the ability of certain metabolic
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dyes that will fluoresce in a certain way if there's an active electron transport chain.
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And we're looking at, we're classifying those either after or in the next.
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Yeah, that's a good question. So the residence time of the ecosystem is really important.
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If you're not replicating, if you think about a chemostat and you put a bunch of cells in
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there and they go dormant, then they're just essentially inert particles that we would
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So it must mean that the human gut or the animal gut is kind of deviating in some way
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from first order expectations of something like a chemostat. There are lots of folds
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and villi and things and pockets and ducts that can trap microbiota from the gut and
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probably reduce residence time.
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Yeah, those are all surface water samples.
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So I'm just curious that the idea of this kind of binary decision between either being
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growing or not growing, I guess in principle some forms of, that's a wooden performance
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you could just be up on an end of a continuous gradient. Like, so I invest more in RPOS,
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but that slows my growth. I'm just wondering, like, how many of these cells that are active
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are at a lower activity level than they could in principle accidentally achieve in those conditions?
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Yeah, I think the idea that there could be some kind of binomial distribution of metabolic
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activity in a microbial community is something that we've recently kind of dismissed and
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or ruled out. It seems like there is more of a continuous distribution such that there
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is a small proportion of cells that are carrying out most of the activity and there's these
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long term distributions of metabolic and kinetics. But it's not two distinct distributions.
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So yeah, so we wanted to develop an experimental system that we could work with in the laboratory
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and address some questions. And for a long time I avoided the temptation and suggestions
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that we should be working with SCORE coming back to this. Mostly because I think there
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are organisms that don't do sporulation. I was initially a little bit reluctant to accept
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that this was the model. But then I realized that there were a lot of features to study
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SCORE forming bacteria regarding their genetics, their ability to be visualized, experimental
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trafficability in general. And so this is a really ancient form of a dormancy. It's
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only found within one phylum of bacteria. For those of you who are not microbial biologists
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or not familiar with the tecton and phylogeny, there's hundreds of different phylum. We
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are one phylum, a chordata, a little chord, basically every other organism that walks
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on the lens or tube. So there's only one phylum of bacteria in the tree of life, called the
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bacillota from accutes. And even within that lineage, not all organisms do that. But the
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ancestor that is at the root of that tree was a SCORE forming, had the SCORE forming
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capacity. And that dates back to about 3 billion years. So this is a really ancient trait.
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It's also very complex. There are upwards of 500 genes that are required and they're
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upregulated when a cell goes from growing under good condition, where an individual
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can divide once every 20 minutes, to entering into this pathway where you upregulate tons
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of genes to make SCORE. It's also very timely, time consuming. So again, 20 minutes. To carry
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out the whole process to create a mature SCORE takes about 8 hours. But when you're done,
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you have a structure that is extremely hardy. It's almost energetically inert. You can expose
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it to any kind of environmental condition you can think of and the cells usually survive.
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People put them on the outside of the International Space Station in the vacuum of space and they
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seem to survive those conditions just now. And as a result of that, they have a pretty
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wide geographic distribution. You can find endoscores virtually everywhere. They're littered
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across soils, they're found in our guts, they're found in the oceans, where it's been conservatively
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estimated that there are somewhere on the order of 10 to the power of 28 endoscores.
10:11.000 --> 10:17.000
And so if we use numbers that people have, thinking about global patterns of diversity
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and abundance, there's about 10 to the 30 cells, 10 to the 29 to 30 microbial cells
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from the planet. So just with this one group of organisms, we can conservatively conclude
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that about 10% of the global microbial biosphere is in a seed bank or is in some state of the
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environment. So I think this all kind of sets up a bit of an energetic paradox or a
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conundrum, at least for me, because these spores and the production of this pathway,
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which is time consuming and energy consuming, only happens when there's vanishingly small
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quantities of energy in the surrounding environment. So why would you go through this whole process
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of going through this elaborate process of up-regulating all these genes and making proteins
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to create this protein-rich complex structure when there's no energy around in the environment?
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And so this kind of just sort of begs the question in an unknown, which is what is the
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energetic cost of making an endoscore? And the approach to do this is what we thought
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about for a while. You could imagine that there are microcell limits in me and other
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types of approaches where you can carefully measure the amount of energy flux in a cell,
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and people have tried that without much success. We adopted another strategy that was developed
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by a colleague of mine, Mike Lynch, about 10 years ago, where he took a bottom-up approach.
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And initially it was used to quantify the cost of making a gene in units of ATP, which
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is a universal currency of life. Since then, that process has been extended to quantify
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the energy involved in making new membranes. It's been used to quantify the energetic
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cost of making entire viruses. And it's been recently used to estimate the cost of producing
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and making an entire multicellular metadome, all by based on the assumptions of the cost
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of making a nucleotide or a ribonucleotide, and then translating that information into
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protein. Those are the three dominant costs. There's other things that are going on that
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we can account for, but those are the three major sources of energy consumption in ATP
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for biosynthesis. So this work is all being conducted by a former postdoc of mine, John
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Impelli, a former Ph.D. student at Washington University.
12:49.000 --> 12:56.000
So we use this approach. Basically, it's just a detailed countdown. It's not really all
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that exciting. You know which genes in a genome are associated with the process of making
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a score, and you count those up. You know which ones are being transcribed by mining
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and existing transcriptome datasets that are being done at precise time resolutions. And
13:11.000 --> 13:15.000
there are databases where people have measured protein expression under those same conditions
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under these characteristic stages of development. And so the first thing that's interesting
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that the cell needs to do when it engages in the process of correlation is it makes
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a copy of its genome. So there's now two copies. And shortly thereafter, you get the formation
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of a septum. To the left of that, you have a larger mother cell, and to the right of
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that, you have the developing core cell. There's going to be one copy of the genome on the
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left side, and there's going to be another copy of the genome on the right side. After
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that, it's been set up. Now you have differential gene expression occurring on both sides of
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that barrier, and there is some exchange that's going on between the two of them. Eventually,
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there's a score that starts to develop. It engulfs the mother, and you result in the
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end with a free-standing mature endosport. This whole investment is extremely front-loaded
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based on the data that we've estimated. So in the first two hours of this eight-hour
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process, 85% of the ATP investment occurs. And it's sort of coincidental or not that
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this happens right before this dashed vertical line, which is the point of commitment or
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no return. Once you get beyond that point, the cell can no longer change its mind and
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go back to being a vegetative cell. So there's a decision that needs to be made with consequences
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for the recuperation of allocated energy, whether it's opportunity costs where energy
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and ATP can be used for other processes that might be generating energy and involved in
14:50.000 --> 14:54.000
other processes beyond dormancy.
14:54.000 --> 14:55.000
Yeah.
14:55.000 --> 15:02.000
How big is the exchange rate investment compared with the COVID-19 sales for experiential
15:02.000 --> 15:03.000
environment sales?
15:03.000 --> 15:07.000
So that's a great question. And if I can just pause for one second, I'll get to that because
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I have the same exact... What's the exchange rate or currency? I don't know how to interpret
15:12.000 --> 15:17.000
the nine ATPs compared to other cellular processes. So I'm going to have a figure where I go through
15:17.000 --> 15:22.000
and show that.
15:22.000 --> 15:31.000
Should we think of this as having accepted the ordinary life cycle reproductive system
15:31.000 --> 15:37.000
or is it something completely independent that is going to parallel in place?
15:37.000 --> 15:46.000
They're distinct. Yeah. There's a decision that's made and once they undergo that process,
15:46.000 --> 15:51.000
cells are no longer going under any kind of vegetative growth. So there's two distinct
15:51.000 --> 15:55.000
choices and bifurcations in there.
15:55.000 --> 16:02.000
Even the chromosome copy, is that using standard machinery and then stream some other choices
16:02.000 --> 16:03.000
maybe?
16:03.000 --> 16:06.000
Yeah. And it happens very early on. And so even if the cell were to proceed with vegetative
16:06.000 --> 16:11.000
growth, we'd still need to make a copy of its genome. But early on in the stages of
16:11.000 --> 16:16.000
spore relation, we need to have a second copy made and then there's chromosomal segregation
16:16.000 --> 16:26.000
into the development of the score.
16:26.000 --> 16:30.000
So translation costs dominate this. So genome replication that we're talking about right
16:30.000 --> 16:37.000
now is important, but it's not the predominant cost. Making proteins is the biggest thing.
16:38.000 --> 16:43.000
Thinking about this subcellular allocation strategy, there's analogies to thinking about
16:43.000 --> 16:47.000
embryogenesis and the way in which maternal investments in their offspring and we see
16:47.000 --> 16:51.000
parallels to that here. The mother cell is accounting for a disproportionate cost of
16:51.000 --> 16:58.000
the spore development. She's paying 90% of the total process of making a spore is occurring
16:58.000 --> 17:09.000
in that left-hand side of the middle cell.
17:09.000 --> 17:13.000
So what I showed you in the last process, early on there was a diagram showing the transition
17:13.000 --> 17:19.000
into dormancy and out of dormancy. So this is the cost of initiating dormancy. What I
17:19.000 --> 17:27.000
want to say is that if you stay as a dormant spore for 100,000 years, which one of my undergraduates
17:27.000 --> 17:33.000
now is resurrecting cells from ancient Vietnamese settlements and it seems to be pretty easy
17:33.000 --> 17:39.000
to do, if they stay in that state eternally, then there's no distinction between that being
17:39.000 --> 17:45.000
a potentially viable cell and a dead cell. In order for this to be an evolutionarily
17:45.000 --> 17:50.000
advantageous strategy, the spore needs to germinate, it needs to wake up, it needs to
17:50.000 --> 17:55.000
outgrow, and it needs to divide. And if that doesn't happen, then all of the investments
17:55.000 --> 18:00.000
of ATP up to that point are for naught. So what we wanted to do was come up with a full
18:00.000 --> 18:05.000
cost accounting of this entire life cycle, so we're also quantifying the costs associated
18:05.000 --> 18:11.000
with revival. And this happens over a much shorter time scale, so our intuition, naively,
18:11.000 --> 18:15.000
was that this should be a less costly process. In fact, what we found is that revival is
18:15.000 --> 18:23.000
more expensive than the initiation of formation. And that's probably due, again in retrospect,
18:23.000 --> 18:30.000
again to proteins, right? So transcripts of proteins are about 100 to 1,000 fold more
18:30.000 --> 18:37.000
abundant inside a cell than they are in transcripts. And this spore needs to, as it's outgrowing,
18:37.000 --> 18:43.000
needs to produce a vast repertoire of proteins that are needed for vegetative growth. And
18:43.000 --> 18:48.000
so there's a complete proteome turnover, and that seems to be why we're seeing a large
18:48.000 --> 18:54.000
decline associated with spore revival in general. And so how do they do this? It's
18:54.000 --> 18:59.000
not relying on the storage of internal ATP reserves, but these ATP surveys are certain
18:59.000 --> 19:05.000
of that. In the literature, we've done some careful investigation, and there's at most
19:05.000 --> 19:12.000
a couple hundred ATP molecules inside of an under-spore. So that must be enough to reboot
19:12.000 --> 19:17.000
a spore, but it's definitely not enough to meet a great shortfall by at least six orders
19:17.000 --> 19:24.000
of magnitude, and what's required for that under-spore to rebar. Which means, I think,
19:24.000 --> 19:29.000
that germinating an under-spore has to make the timing really important, because as soon
19:29.000 --> 19:34.000
as it germinates, it needs to get its hands on a sufficient supply of exogenous resources
19:34.000 --> 19:39.000
from outside the cell to meet a solid germination. Again, otherwise, the spore, the whole spore
19:39.000 --> 19:42.000
cycle will come to a close.
19:42.000 --> 19:48.000
So do you have any direct understanding of the degradation of proteins, the degradation
19:48.000 --> 19:54.000
flux of these things? There's this proposal of that. Sometimes it costs four ATP per amino
19:54.000 --> 19:57.000
acid to do preparation, but sometimes you can actually get energy from that process.
19:57.000 --> 20:03.000
Yeah, and I think there is some internal recycling. So we have kind of worked through this, and
20:03.000 --> 20:07.000
there's a manuscript that we can develop, and there are some calculations that might
20:07.000 --> 20:11.000
diminish some of that cost, and there's some internal recycling during the hydrolysis process
20:11.000 --> 20:19.000
associated with germination. But I don't have those numbers.
20:19.000 --> 20:27.000
Okay, so getting back to this question of how do we compare a process or a relative
20:27.000 --> 20:35.000
option, these costs, to other things that a bacillus cell might do. And so we carried
20:35.000 --> 20:39.000
out the same process, not just with sporulation and germination, but a whole bunch of other
20:39.000 --> 20:44.000
things that this cell does using data that we can get our hands on. And from that, we
20:44.000 --> 20:48.000
found that sporulation is probably one of the more expensive things that a cell can
20:48.000 --> 20:54.000
do. It makes up about 10 percent of the total budget of the cell. And there are a bunch
20:54.000 --> 20:59.000
of alternate strategies that these cells would prefer to engage in when confronted with stress
20:59.000 --> 21:05.000
that they do before they will produce an endosporin. So some of them, when stressed, will start
21:05.000 --> 21:12.000
to collectively engage in biofilm formation. They engage in things like cannibalism. They
21:12.000 --> 21:19.000
start expressing competence. They allow them to acquire genes from their environment, which
21:19.000 --> 21:23.000
perhaps could influence their fitness. There are a bunch of alternate strategies. All of
21:23.000 --> 21:28.000
those are much less expensive than making an endosporin.
21:28.000 --> 21:34.000
So at the end, there's a question about the break-even point here. And so let's imagine
21:34.000 --> 21:41.000
that you can reduce maintenance energy requirements by 100,000. So that's a cost that you have
21:41.000 --> 21:45.000
to pay continuously, but that might still be advantageous compared to the one-time big
21:45.000 --> 21:52.000
investment of making a score. And so the characteristic time or frequency at which fluctuations must
21:52.000 --> 21:57.000
occur between good and bad environments in order for sporulation to be optimal for this
21:57.000 --> 22:03.000
to be the favored, persistent strategy is about 30 days. So once the environment goes
22:03.000 --> 22:09.000
beyond being inhospitable for growth and reproduction, once you get to that 30-day
22:09.000 --> 22:14.000
point, now sporulation starts being a beneficial process.
22:14.000 --> 22:18.000
I see that we're standing here, so I'm going to just wrap up. We thought a little bit about
22:18.000 --> 22:22.000
how this could limit something called sporulation efficiency. If you put cells in a given environment
22:22.000 --> 22:27.000
that's not suitable for growth and reproduction, which fraction of those cells will be able
22:27.000 --> 22:33.000
to be producing endospores, we see in the literature it ranges from 0 to 100 percent
22:33.000 --> 22:38.000
and with a mean of about 30. This has commonly been in bulk as a form of bet hedging that
22:38.000 --> 22:43.000
not all individuals need to do this process to ensure the persistence of this sporulation.
22:43.000 --> 22:48.000
We don't acknowledge to us that actually it seems that there's constraints and energy
22:48.000 --> 22:53.000
limitation at the population scale that prevents cells from being able to form endospores.
22:53.000 --> 22:57.000
And the last thing I wanted to talk about, and I won't go into a ton of detail here,
22:57.000 --> 23:01.000
is the evolutionary implications for cost and the maintenance of this trait over long
23:01.000 --> 23:05.000
periods of time. I mentioned it was first evolved three billion years ago. This trait
23:05.000 --> 23:12.000
has been lost repeatedly over geologic time scales. And in addition, if you passage these
23:12.000 --> 23:16.000
cells in the laboratory, if I put them in a cleanest cell, if I put them in batch culture
23:16.000 --> 23:20.000
and I passage them under good conditions, in a matter of weeks, months, we see a three
23:20.000 --> 23:25.000
billion year old trait. You go, why is that? Because five to ten percent of the entire
23:25.000 --> 23:30.000
genome is devoted to sporulation. And when that's under relaxed selection, it's a large
23:30.000 --> 23:35.000
target for mutation to accumulate. Essential genes that once perturbed, you've lost that
23:35.000 --> 23:42.000
trait in perpetuity. So this is the use it or lose it idea that under relaxed selection,
23:42.000 --> 23:48.000
not knowing anything about energetics, we see the loss of this trait over geologic time
23:48.000 --> 23:53.000
scales. We did some work with mutation accumulation experiments, which allowed us to look at deletions,
23:53.000 --> 23:59.000
so large traits of DNA that can be lost. And this would be an energy-saving mechanism that
23:59.000 --> 24:04.000
is consistent with adaptive streamlining, so why genomes get small. So if evolution
24:04.000 --> 24:09.000
can see those nucleotides that are being paved through the process of genome duplication,
24:09.000 --> 24:13.000
selection can actually move them in a way that saves energy for the cell, becomes the
24:13.000 --> 24:20.000
consequence of losing this trait. And so I think some of these things could be important
24:20.000 --> 24:24.000
for thinking about community dynamics, which has been a theme of what we've been talking
24:24.000 --> 24:29.000
about. Some of the work that we're doing is trying to think about how spores can provide
24:29.000 --> 24:32.000
defense against phages, and that seems to be something that we're going to hear about
24:32.000 --> 24:38.000
tomorrow. They can't attach to the receptors, because there aren't any receptors on these
24:38.000 --> 24:44.000
spores. And so there is a physical defense that is important for phage attack, and subsequent
24:44.000 --> 24:51.000
rates of coevolution and diversification. So thinking about this as a mechanism of abiotic
24:51.000 --> 24:55.000
tolerance, there's implications for thinking about the diversity of biological systems.
24:55.000 --> 24:57.000
Okay, thank you.
24:57.000 --> 25:05.000
I have time for a few questions.
25:05.000 --> 25:30.000
Great talk. I was wondering about the 180Ps that you mentioned. Do you think they are
25:30.000 --> 25:34.000
not getting hydrolyzed, or are they getting constantly generated? In other words, is it
25:34.000 --> 25:40.000
a non-occurring, stationary-stating thing, or is it a turnover of ATP in the spore?
25:40.000 --> 25:45.000
From people I talk to, and people who study ribosomes and other cellular processes, it's
25:45.000 --> 25:51.000
a very hard thing to study and to measure. My expectation is that of any form of dormancy
25:51.000 --> 25:57.000
that I'm aware of, spore is the least amount of biological activity in a turnover. So perhaps
25:57.000 --> 26:01.000
there's actually consumption of ATP over time, but I don't think there's any generation of
26:01.000 --> 26:05.000
new ATP in the endosporus.
26:05.000 --> 26:27.000
Could you contrast the state of being dormant versus being an endosporus and develop the
26:27.000 --> 26:31.000
frequency at which one finds these two states in nature?
26:31.000 --> 26:36.000
I'm very careful in how I define dormancy, and I keep it super generic, because there's
26:36.000 --> 26:41.000
a lot of language to describe different ways in which organisms achieve the same thing.
26:41.000 --> 26:45.000
I think those differences are interesting and important. I would definitely say that
26:45.000 --> 26:50.000
endosporus is a classic example of dormancy. I'm not sure there being any other organism
26:50.000 --> 26:58.000
that would be more metabolically inactive than an endosporus. I'm not sure if that's
26:58.000 --> 27:02.000
your question, but...
27:02.000 --> 27:07.000
My question is, I just think that you refer to all the time that this is dormant. It's
27:07.000 --> 27:09.000
a wider classification.
27:09.000 --> 27:10.000
Wider?
27:10.000 --> 27:14.000
That's my guess. I don't know yet. Endosporus is dormant.
27:14.000 --> 27:15.000
For sure.
27:15.000 --> 27:22.000
Okay. I just don't know.
27:22.000 --> 27:24.000
It only occurs in one phylum.
27:25.000 --> 27:31.000
This particular flavor of dormancy only occurs in a subset of bacteria that fall within one
27:31.000 --> 27:32.000
phylum?
27:32.000 --> 27:36.000
Yes, it must be. Other phylum must have it.
27:36.000 --> 27:42.000
They do a different one, right? Maybe not to the same degree. Again, this is an example
27:42.000 --> 27:47.000
of a really complex form of dormancy. They're exceptionally long-lived compared to other
27:48.000 --> 27:55.000
One last question from Alfred.
27:55.000 --> 28:04.000
Yeah, very nice analysis. I really like this. Ten percent of the total energy budget for
28:04.000 --> 28:12.000
stolomation is not that bad. From your curve, it looks like the biggest energy expense is
28:12.000 --> 28:22.000
for the checkpoint. How much energy, in terms of metabolizing per unit time, or how much
28:22.000 --> 28:30.000
metabolism would need to go on to cover the last hum? And also, obviously, the cells cannot
28:30.000 --> 28:39.000
predict the environment and whether the snacks will be. Are there any ideas of what the selection
28:39.000 --> 28:44.000
is behind that, or is it simply those that can't make it, you don't have a file in this
28:44.000 --> 28:45.000
environment?
28:45.000 --> 28:51.000
I mean, some element of this is work hypotheses necessarily going in about the checkpoints,
28:51.000 --> 28:55.000
but we knew that those checkpoints existed, and it just so happens that a lot of the energy
28:55.000 --> 29:01.000
was expanded prior to that. If conditions change in that two-hour window before commitment,
29:01.000 --> 29:05.000
then the cell has an opportunity to reuse the energy that's been collected for other
29:05.000 --> 29:09.000
purposes. Once you get past that, that's the point of no return, and there's no way
29:09.000 --> 29:15.000
to recoup that energy unless you go all the way through the process of making a mature
29:15.000 --> 29:22.000
stool and then successfully germinate and outgrow. So, I'm not sure what happened after
29:22.000 --> 29:26.000
the checkpoint, but it looks like there's not as much in terms of energy as premature.
29:26.000 --> 29:31.000
It's just really 85 percent of it is in that first two hours leading up to the formation
29:31.000 --> 29:33.000
of the cell.
29:33.000 --> 29:40.000
And how much longer could the cell live with this 85 percent in terms of maintenance energy?
29:40.000 --> 29:42.000
I mean, how much mileage does it require?
29:42.000 --> 29:44.000
What could you do with that 85 percent?
29:44.000 --> 29:45.000
Right.
29:45.000 --> 29:50.000
Yeah, yeah. Let's probably go back to that table where I showed a comparative cost, and
29:50.000 --> 29:56.000
maybe you could make a bioform, or maybe you could express some compositions, or make
29:56.000 --> 30:02.000
up 75 percent in maintenance metabolism for that period of time. You could put in those
30:03.000 --> 30:04.000
Thank you.
30:04.000 --> 30:05.000
Somebody's over making bricks.
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