13:05:41 Okay.
13:05:46 Oh, that was thanking Pankaj organizes great gathering, and for KTP was reflecting that it was 20 years ago my journey to biology started was protein for bio program, and well Sergei we will have lots of fun.
13:06:07 And, well, time flies.
13:06:10 Okay, so, boss asked me to give a primer bacterial physiology.
13:06:18 And that's a huge topic, and even.
13:06:24 Well, what we did in our group in the last 10 years so quite a bit of stuff, so I decided to kind of talk about several bits that I think will be interesting relevant to the overall topic here.
13:06:43 But really, I can skip some of the topics well but more interested in people kind of uh maybe raising question like the question you always wanted to ask, but no, there's a time.
13:06:54 Right, right. Let's have a more of a discussion than this kind of running over.
13:07:00 Right.
13:07:03 So, I have to start this study of a growth physiology with this striking result of from Holy Moly snap.
13:07:12 And so they they took at a time.
13:07:15 Some monopoly repeated for equal Ryan other organisms to grow cells in exponential growth field and it was various new chances to grow over the range of the growth rate.
13:07:26 Imagine that you take culture. Measure out of the RNA measure all the protein divided to, and if I'm a straight line.
13:07:34 So what does this mean the amount of RNA.
13:07:40 Most of the Oregon the sales a rebel some army, and so good that's stuck symmetrically related to the number of the rival sons and related to the total amount of rebels are more proteins.
13:07:52 So, the ratio, and the total protein is a plasma dictates cell volume. So basically, this vertical axis is a measure of a number of ribosome per cell, right with some concentration, and the straight line, ignoring this offset, a bit, I won't get into
13:08:11 unless somebody asked to say, it says that the rebels on concentration.
13:08:18 Rebels on content is proportional to the growth rate.
13:08:22 So since rival sons are the machinery involved in making all the proteins in a cell and proteins a major massive component of the cell, then disproportionality suggests that the, the, the, the right hand side is a race, left hand side as the missing a
13:08:40 race but then the race will be engaged only the rivals, for all the rival sons working at a constant speed that you would.
13:08:47 That's one way to rationalize the circulation suggest that the translation of speed is a constant. And from the composition you catch the shuttle back out to a translational unification of speech but rivals.
13:09:02 Okay, so then mascot and I ran into this result and so that's very interesting. So, the, then you know but with biology, no just just because there is a appealing explanation doesn't mean that explanation right so if you want to be wait on it you want
13:09:19 to test it in different ways to see, but what is Lena. Right. And so we first look at the numbers, it seems about right order magnitude wise, right. So NASA Well, yes this result is true that if we look at the translational nutrients, then we should still
13:09:35 get straight line was a different slope and slope and said by location.
13:09:41 And so, so there were a number of translation on mute and little characterize so then we talked down moved into a self beaten mascot.
13:09:50 And they measured and they also realize that I was too high for me to get the data so I'm just going straight lines but the data is in original.
13:09:59 Right. Okay, so that's good but now, nowadays, when we learn to measure your engagement rate ourselves, and we've loved that. Nikolai but sinners video nature James had different temperatures.
13:10:12 Basically, this ratio if you plot the growth rate normalized by the maximum elongation right but you don't want to change a bit difficult to the maximum rich media maximum elongation rate.
13:10:22 All of them crabs optimistic for different organism different temperature, even as was someone.
13:10:26 net, we will nitrogen grows 50% faster Nikolai fast faster speed, and some Rizal being looked at as they're growing at one fifth of the speed of ecology, all follows.
13:10:43 Okay, so that's that's a.
13:10:47 We call this one of the microbial growth laws.
13:10:51 Right. and then you summarize this relation.
13:10:54 By that, so we qualify the fraction of a protein master throughout the summer proteins, and to offset this the grocery eating, relative to the maximal translations.
13:11:12 So, at a time. Suddenly, we were looking at this relation. And we're thinking it is missing a companion relief because this is a changing the nutrient levels.
13:11:25 And so, mascot of the experimental what he's fixing your chin and just very the translation right and he got another straight line going the opposite way.
13:11:33 And then we got bolder Wednesdays and then we started looking at other cellular proteins, and this is a this is a, actually the native labs D, which is the, which is, well, which, which is the color expresses the winner is going on laptops, but we will
13:11:51 look at the number of catabolic enzymes, were deleted a specific regulation, Nicholas roll up around meat requires glycerol to be turned on so if you remove group five and it's just responding to a general carbon sort of a status.
13:12:05 And you see that when under different carbon sources is going up in a straight line fashion.
13:12:13 And, and the and the by other treatments are by changing translation rate, with a fixed carbon source, it goes down in the special.
13:12:22 This is for, say, I think, less wrong, you can take a pork applesauce. You can take the richer carbon source and do the same experiment and you see a set of.
13:12:34 Again, the, the actual data was recorded in this paper.
13:12:37 Alright so then you can describe this by another just empirical relation, the fraction of a catabolic enzyme versus the growth rate as a linear dependence, with some with some coefficient, and you see here which plays a role of a translation speed as
13:12:57 to rivals from the interpretation it's some kind of a carbon uptake rate. Okay, but I'm going to hold that at the moment it's a physiological just for them logical parameter, that's related to the, to the nutrient nutrient quality, but later I'm going
13:13:13 to give a more specific interpretation that allows us go to the local consumer resource models and the different from this person.
13:13:24 So at the moment, it's just there's a linear relation between grocery and, and the fraction of the protein
13:13:35 capitalist.
13:13:50 Alright, so okay so then to summarize this relation we made a very simple for article theory. So we said that the protein to grow Sony to make the protein, and the more different kind of protein so so they are represents right well so more proteins translational
13:13:51 And this faction, just a file a direct way to think about on their proportional to concentration, because the total protein density is about the same across most college.
13:14:22 Right. And same with carbon uptake. Just by by this relations, and we have the same similar type of data for Biosciences. Okay. And then they all have them add up to about 40% of the type.
13:14:28 protein to grow fast you need to have more gradual some approach when your relation as justified by this in political law.
13:14:46 So that that's additional, but if you look at this additional data that showing here that gives us around 40%.
13:14:47 So, this, this.
13:14:52 In this model grocery and these protein fractions are the variables. And these are fun and logical parameters, but we know how they're related to the outside world, right so so this this new See, we know we're changing it in for training carbon substrate.
13:15:05 The scammer we know we're changing, we're changing.
13:15:20 And so this entire theory has only one parameter. By Mexico 40%, which is a number, right, and then, then this is able to Hatcher this pictures able to describe all of the data.
13:15:29 So for example, if you want to understand the sky.
13:15:33 Right. So now we can say, Well, now, even though this, this relation time is a linear relation between the catabolic enzymes and the growth rate, but here I am changing the coefficient you see right so then the way to get the relation between spicy and
13:15:49 the lambda is I use this constraint. Right, so then say if I see is five x minus five or minus five a, but that each of these two, I can just use this relation because I'm not touching this corporation right so I'm making orthogonal put the patient, these
13:16:04 are, these should be constant. And then I'll get this English. English.
13:16:09 Right. So if you think about this electrical system, or what this is calculator in biology, you give some perturbation and you measure what is responding.
13:16:19 Okay, but it's, but then, if you think about this as electrical circuit, then you have a.
13:16:25 You have a voltage, that's the five Max and some resistance, and this is the resistance of interest, and you can vary the resistance, right what the experiment is is a young measuring the voltage across this resistance and occurred on the class this resistance,
13:16:41 as you there is a resist eventually you get the English.
13:16:48 Right.
13:16:51 Now, notice that throughout this discussion. I never mentioned optimization.
13:16:58 Okay, so people often prescribed to us Oh we're talking about optimization no we're not doing optimization, this is just phenomenal logical just writing down what is it doing nothing more engine.
13:17:15 So, so the difference we can tell time The thing is this offset.
13:17:19 Okay and and in this picture I'm putting all of this offset into this. This is a conference not changing.
13:17:28 So basically for each of this department, the sum of the ends of the domains let's look at amino acid synthesis, there's always some base or level in additional changes from only tracking the changes.
13:17:39 Got it. Okay, so it's the excess over some offset. Yeah, thank you for for the purpose of this picture just convenience and it doesn't matter what, what does the opposite of coming from co a just lumping to the left.
13:17:56 In, do I understand correctly that you get this relation, only if you very one at a time if we ever very both. It's right right so so that's what those is this these donations obtained by varying we're going to time.
13:18:08 Right. But then, what but when we put it together and implying that these are actually the state variables of the system and the state is determined by the set of this variable.
13:18:17 So the prediction is that if I make make multiple.
13:18:36 But do you understand it right they'd like you would have to measure the gamma in the new a if you change. So well we know Like for example, on glucose.
13:18:40 by, by putting this single, single piece.
13:18:43 Right. So the slope Give me the new seat for glucose, right, and then.
13:18:50 So, what we actually did was very in this new age so did you by changing nitrogen and things like that. Okay, so for them for for also from particular type of nitrogen let's say I have a valid.
13:19:01 Right now, now we change the carbon and the natural force. So, to a different new see for the carbon that measured and two different nitrogen and you can predict Once you're comfortable.
13:19:17 I want to understand your comments on optimization. I like is, I thought I understood this paper and now I you made this comment that when we were very careful to avoid using optimization, you know it because everybody wants to put optimization in our
13:19:31 mouth, we could not say that. Yeah, so that's what I'm trying, and there's a reason I will get to later why why this is not a result of optimization. Okay, that's what I wanted to ask about isn't there an assumption that like your relationships there
13:19:46 that they're linear to these fractions with this coefficient, right, it is somehow assuming that the cell knows how to reallocate thing yes for that to be true so not none like a filter sound knows how to reallocate but then if you give this constraint
13:20:04 that's all I can do.
13:20:05 Yeah yeah so it is it is no freedom so you don't need to use optimization.
13:20:12 But
13:20:15 it's more of a clarification. So in the way the carbon source differences exist here is the assumption here the carbon sources are meant to be the source of energy like they are the carbon source in the context of a tower get the energy in a minute at
13:20:27 the moment, energies that I see So suppose, I guess my question. Energy is an afterthought. I suppose you do the same experiment for CSI know bacteria, and you provide carbon just in the context of co2.
13:20:41 You got to realize somewhere on that list. yes.
13:20:43 From that, from that perspective side opportunities very attractive because it allow us to separate the two. Right. And, but then the problem is, then it's got all these intrinsic, team building right so if there's another way to separate it to build,
13:20:57 it will be very coming.
13:21:03 the question.
13:21:05 Okay, so.
13:21:10 So in this particular study, we looked at a number of maybe half a dozen also reporters for various kind of a protein of interest. And then later. We followed up with a proteomics study.
13:21:21 And so this was for these different theories of limitations and these color codes for the, the abundance of the each protein. And the nice thing about proteomics is that, well, you need to get to the some estimate actual abundance, but then you can actually
13:21:40 add up the abundance of each protein. And that's exactly the course green sort of these sectors we're talking about. Alright, so, then you see that you do some trivial clustering and you see that response a bunch together.
13:21:53 And so for example, this group response to cover limitations, the increase. And the the you know in, in, in this way.
13:22:04 So, and the carbon limitation increase under natural England the translation on emission limitation decrease.
13:22:12 Now, the, if you look into the contents of what are these potent so at the moment which is grouped by so the response. Right. If you look at these.
13:22:21 The content of these guys, and the other many enzymes.
13:22:34 Many proteins that are present a very low level you wait by the abundance and the abundance, and then basically or what you will call it kind of things related to either energy or carbon.
13:22:40 Okay.
13:22:43 And similarly support translational protein ribosome then the helper biosynthesis and so forth. Okay.
13:22:51 And so that was kind of our say embarrassing agreement with this 2013 paper. Right. And, so much so that when this work was submitted to another journal, then we do come back to it.
13:23:07 You've already predicted it It's nothing new here.
13:23:11 Oh well we're so happy that way actually biology will get to this state, and people take our production seriously so anyways. But, but so that was the first effort that proteomics.
13:23:24 Okay, so what about energy. Right, so in here energy is missing.
13:23:29 Now, the problem was energy.
13:23:33 That's couple that's that's involved in energy production is also involved in other functions I biomass productions. So it's really a problem of how to entangled and so the same word same as doing multiple functions.
13:23:53 So it's really a problem of how to entangled and so the same word same ends and doing multiple functions. Right then how do you decouple these differences.
13:23:57 And so what's needed is a systematic way to make this a big competition, up, I should say, yeah, the actual say that we kind of update a
13:24:11 ad hoc job in the social work with Marcus person was studying over for metabolism. We took respiratory enzymes and and what is the enzyme and collected and Sam was separated by hand into these two groups.
13:24:26 Okay.
13:24:27 The. But then, but don't turn out this could work could be, this could be done systematically, and the hero of this work was the material Maury, He was actually the author of this Caspar work that Daniel mentioned in ignore his review, and I've met the
13:24:46 material, Alan was the visiting room. This is a question only just kind of over the summer, and develop this aspect, and he's been a postdoc in our lap and this is one of the many things he did.
13:24:59 And so, so okay so you what you can do is you can write v is just a set of flags for each other reaction. And you can, you can write us as some professional, thats related to okay so this is a part of contributing to the, in this case is the energy, but
13:25:32 Right, so then from the matrix and you can do patch them and get these corporations.
13:25:38 And then, so that you end up with this kind of I think basically short, the fluxes into the more basic components in terms of the functional components.
13:25:48 Right.
13:25:49 And so the input, that's needed is typical of what you would need to run FBA glucose uptake. So this is a. So we, we have a system so in this in this experiments to the what's grocery changed by varying the glucose uptake.
13:26:06 And so the measure. You need some inputs on the glucose in fact that the circles and acetate crucial in is something about biomass composition, which also changes was the gross condition, and you need the model, if we took the, the generic model from
13:26:26 Parsons lab or the FDA model. And that's the kind of a thing, able to produce so if you ask the Fluxus in the uptake of glucose into each of these functions production of energy, or on a DNA and so forth.
13:26:38 And the color codes, describe each of these function.
13:26:44 You can see that about 20% of the flux is goes into energy. OK, and then, and the fast growth.
13:26:52 It's doing respiration reflected by the acetate expression, and slow slower growth is.
13:27:04 Sorry, instrumentation and visible respiration.
13:27:04 Okay so that you can go into individual reactions, for example, to look into, and sound up, Carla says this is you know lays, and you see that after France.
13:27:13 So, this is a fraction of the fraction is conducting right about 40% is for energy and the rest of the bio automated way to do this.
13:27:26 So using the FDA I'm using using FBA model right, and together with the FDA using like optimizing.
13:27:38 Okay, so there's a very convenient, quick way to to generate once you have the model and the fluxes, it just tells you how much of a flux. Each reaction is carrying.
13:27:48 All right, and then.
13:27:52 Okay, so then, but then from the boxes we can get to now to the protein. I guess I imagine, each reaction, you have a protein, you have X amount of protein and but then this reaction half of this doing this happens doing that, well then we simply allocate
13:28:07 the protein to these two functions in proportional to the fluff.
13:28:10 Right. So, so then for this. Interlace, then we this is a measure the manufacturing from the podium. Right. And then we will then we will say okay this amount is devoted to energy and this is not about the policy.
13:28:26 Right.
13:28:27 So this will you know lace and then this is a as I met, he one of the highest expressed as a deep is Express and then a minimal.
13:28:49 This is the last step in the, in the biosynthesis of Messiah me. And it's a very, it's a slow enzyme, and all of it right is devoted to this one function.
13:28:51 Okay, so you generate the fan base. Now we can add up.
13:28:55 Right here we are those circles experimental like what are these circles circles on the data. So that's a balance of our actual protein, the protein as measured at this growth condition.
13:29:08 It's amazing I could this so it's the prediction and experiments matter no no no no no no no.
13:29:13 So, this is a prediction from this the FDA the competition of the process. Yes. Alright, so then you simply multiply this by the measured amount of the enzyme pressure so to prescribe how much of this enzyme is actually useful biosynthesis what energy
13:29:31 and various things.
13:29:33 Okay.
13:29:34 And.
13:29:36 All right, so then you can do this for every enzyme Terry yeah we're asking clarification questions can you explain what you said, then you just take partial derivatives and you get these fractions I didn't even understand the logic, I suspect What can
13:29:49 you go back one more slide.
13:29:51 One more to the before you start the back, just to the three it says, I thought I could ignore this slide because it was going to play a prominent role but can you explain more what was done here.
13:30:02 Okay, so this is the say that the. So this vector is a collection of or reactions.
13:30:12 And we attribute it okay so this is flux What is it doing it is feeding into biosynthesis is feeding to energy generation feeding to this and that. right so then we just writing it as.
13:30:13 Right, and each, Each has been fluff.
13:30:32 And so each will have a coefficient is how do you measure those or predict no this this is that, so then you, you take the derivative, and you get it right so this is from FDA and then and then you were the key is to get this coefficient.
13:30:40 Yeah.
13:30:42 Okay, so this this is a so okay so so so so when I mean how do you what do you take the derivative of with respect to what I guess take derivatives on FX.
13:30:55 Why don't you get from FB with respect to each, each fluff brightness, with respect to you change the. Imagine your change this, this, this part of the think a little bit right How much does that change.
13:31:11 Yeah you changed your bio my composition a little bit. Okay.
13:31:18 Yeah.
13:31:20 Sorry if you go forward to the one, the last slide you were showing please Terry.
13:31:27 But going back and going forward, forward, forward. So I just do you have any idea so as the growth rate goes up, you start to get fermentation and the mass fraction of the enzyme goes up, right.
13:31:40 Do you have any idea of what sort of genetic regulation is making that happen.
13:31:45 The.
13:31:48 No, I don't. So I have some guesses, but don't we yeah we did not talk about it.
13:31:54 Let's just have a conversation I mean, I'm just super interest yeah yeah yeah no yeah that that no they need it needs to. It needs to basically know about the energy expansion we have to grow.
13:32:04 Yes.
13:32:05 Okay.
13:32:20 can repeat the question Daniel. What on the for the met, he plot. Is it 7% of the total protein that it gets up to
13:32:28 Can I just ask about the absolute numbers here. So that Matty plot, it's 7% of the total protein wise I
13:32:30 the y axis.
13:32:33 Absolute abundance percent of the total protein in mass mass percent of total protein.
13:32:39 Well, so this is a crazy enzyme, you know, it says, six 7% of the, of the protein, just devoted to this enzyme. It's very interesting enzyme.
13:32:49 We can discuss
13:32:52 the two just quickly. I don't think I understand this decomposition. So let's say I have an enzyme, and it takes a substrate. It turns it into a product, it gets an ATP out, but the product is also going to biomass, right, like, how is that divided between
13:33:07 energy and.
13:33:10 So you can either talk about ATP floods versus that.
13:33:15 Yeah, so, so, so, so the.
13:33:22 Yeah, the ATP flux versus biomass.
13:33:22 Right.
13:33:22 Getting both from the same reaction, you're getting both from the same reaction so, so there's there's, there's there's a part of it. Yeah, so you're getting both but then, ultimately, you need let's say take that Colossus and a certain part of it, it
13:33:35 just needs to be, you're getting some energy for free. You're getting some energy from it. Right, but then you're putting your your your portion of your push into biomass okay but then there are other, but then there's other part of the guy caller says
13:33:56 you're not getting any biomass out of it, you're sending order way to absolutely right so that's the distinction will make. So then what you do in bio mass production there's energy production of course, anyway.
13:34:02 Okay. But, but that's for biomass production but then there's also the contribution to energy. Yeah, so then for one of those enzymes that's producing ATP in glycol genesis for example right you're somehow calculating the fraction of the flux through
13:34:14 that reaction that's going to ATP versus downstream, but it's ultimately it's falling to okay so you divide a flux, no lacking in this in this in this picture, though, so this part is going from the same reaction imagine a all of the carbons been pushing
13:34:32 out into athletic.
13:34:34 That's one component that we call the fermentation, that supplementation.
13:34:39 That part is going into biomass.
13:34:45 Can I ask some basic questions are the eaters or the NF the coefficients are the global, they're fixed for all fluxes it's decompose the same way or is it for each flux, those coefficients can vary it as a reaction, it depends on a model right so so so
13:35:05 so so you're you're taking derivative with respect to the girls condition, right so and abroad condition you have different competition and everything.
13:35:24 Yeah, I mean this is a really a sort of I saw a sore throat angle but it's sort of a no technical part but just kind of to get to a way to get to the competition, there may be other ways to do the competition but if we want to get into this.
13:35:36 The question becomes technical maybe we'll have a separate session just to talk about the technical. Right. But the idea is to separate up into different flux components there was prescribed function to answer.
13:35:47 All right.
13:35:51 So, um, I remember, I remember in in Daniels talk you criticize FBA for not concentrating energy, but you're using FBA was energy. It's a default parameters for setting for energy so there's assumption of harmony, how NADH turns into number of protons
13:36:09 and ATP, what what are the default.
13:36:15 All right, but anyway so so in this procedure that every enzyme, you can assign a certain portion of the enzyme is what this function is a biomass versus the energy.
13:36:25 And then, that you can add up all of the enzymes as. That's the doing energy, and then you get such okay now now it's again clustering but taking bits of pieces from every enzyme, and put them together.
13:36:50 And we want to show me that we can talk about the respiration versus fermentation, this is now against the protein against its function which is ATP flux generation, and he got this factor to a different that we already saw in the buttons.
13:37:04 But this is getting a more. This is not a good way to just comment on the oxygen availability. So, Oxygen.
13:37:12 oxygen is limiting enough to get some fermentation, in this case absolutely not limiting but we can of course change it to one offering is limit.
13:37:23 Show it right and they can do this for each pathway of the licensing that says, look at the cost of basic making each of the floods.
13:37:33 Okay. And we're finding is by far the largest.
13:37:46 Yeah.
13:37:51 I'm just it's a bit of a selfish question but you did you have any vitamins and you're a minimum media buys me know Yeah, so you're synthesizing me signing without be 12.
13:37:52 Okay so anyway so so then from this we can go back to our pie chart, but now actually composed by function.
13:37:59 Right, right, right, so now he is the one that's been talking the panel, okay but that might not be necessarily like generalizable if you were able to use them at age, yeah well yeah if you provide.
13:38:10 Yeah, yeah, my page will be
13:38:14 alright. So, so now you get this one quick question broken down. Okay.
13:38:21 How are you, converting from boxes to enzyme abundance without putting in some information on like kinetics are kicking up because I explained to you the flux competition right and then we'll just say for each enzyme, you just take the proportional.
13:38:36 Right. The 30% is for this and 30% of enzyme is, despite the dysfunction.
13:38:44 Okay.
13:38:46 So all of this, like, okay, there's the FDA model, which was stuck in metric model right wisdom parameter from the uptake flux and exclamation points.
13:38:55 That's it. Right. And so you get this decomposition. You see that about 40% of the enzymes.
13:39:02 40% of the proteins, you can, the enzyme show can prescribe metabolic functions for. But then there are many other proteins that do not have a enzymatic functions for example, ribosome is not part of the, the FDA, but we obviously know the assumption
13:39:17 in this agenda. Right. And so these. So these are the these are mostly mostly this part part of rivals on the Magellan stuff.
13:39:29 Then, then it's actually interestingly, a big part of this is, basically, they are enzyme became principal associate flex to them, but they carry no flex, according to history.
13:39:40 Okay so examples are transported. So, in carbon limiting conditions equal I actually put out lots of transporters, but only a few of which is actually what what the word was out that like it doesn't know what it is it's just a generic response.
13:39:55 All right.
13:39:56 Okay, so then who is this, we can, we can repeat what the just plotted against evolution of the growth rate of the, each of these factions of course went into biomass energy and so forth.
13:40:07 And then, is then, these, these are in political relation very much, kind of, we can write down similar relations are we good now actually thought it'd be a more rigorous way of describing the enzyme and ended the assumptions.
13:40:21 And we basically get back to the same model and the new part is that we now have a section for energy, which is really distributed among are these enzymes that are attributed to carbon.
13:40:50 be crashing.
13:40:52 Right. And then the thing is that the grocery dependence of this EC centers are basically the same up to a coefficient, therefore, be based basis, this justifies why we were able to throw away the energy and get away with it physically, they could just
13:41:01 Alright so that's a roundabout way of filling in some details, but I just want to make sure I'm understanding this correct so suppose I drive the expression of a useless protein, like GFP or sniffing.
13:41:18 And do you expect like taking away from particular parts of this pie chart, or do you expect a more global collateral. We did that experiment in NASCAR's experiment we only looked at globally at the rivals on so forth and we also follow up with proteomics,
13:41:18 I'm not sure where we whether we published it, but basically it's pretty boring. It basically squeezes out everything else, everything.
13:41:35 Yeah.
13:41:35 Sorry, I'm trying to understand.
13:41:38 Maybe this question doesn't make sense but I try to respond to what extent this is just data or data with models somehow, this is just data, analyzing the data by the petitioner with some assumptions.
13:41:49 Yeah, so what data then then sort of leads to this can be described by a few parameters, because you have some FBA model and I didn't understand all the details so maybe that's just the flux constraint Right, exactly.
13:42:04 So yeah, then you have something that like for growing faster. You need more of flux into the energy, what do you label there's energy. Right, let's say that's kind of some harsh like something that's in those equations.
13:42:21 Right, right.
13:42:23 But then also the way you allocated the enzymes to the energy was derived by taking these partial derivatives.
13:42:34 So, how do you make sure. So those are all experimental input into these are the glucose intake and the acetate.
13:42:44 So right so it knows it's generating more energy because it's going more glucose going in and it's not going to only a part of is going to biomass.
13:42:54 Okay, so then, and we do not see any questions coming out or anything else coming out so normally it is what else do you make it. I mean it's starting to energy.
13:43:04 Okay, that's, that's the that's the, just the expand of the concentration but the because of the constraint that the only other ways to put it into energy.
13:43:16 Thanks, I'm sort of fall by trees question I guess I'm about these useless proteins. How does the cell know sort of which pie slice they fall into like if you put in a transport that is useless does that behave the same way as GFP and if not, how does
13:43:31 it.
13:43:34 If you Yeah, if you saw sense so the, the, So the.
13:43:38 If you putting a transporter.
13:43:41 That is possible if you putting a transporter you're doing more perturbation for we also try to do this kind of experiment, but actually was the intention.
13:43:48 Try to try to crowd the surface.
13:43:51 Okay, so then, but actually that we've got our international problems such as the messing up the circulatory pathway the things like that, right. So, you do not always get away with putting a neutral perturbation, but to the extent you can then.
13:44:18 So neutral here is like only taking a podium fraction. The only, only taking up proteome fraction and not not taking up rivals on basically who make this, and yet somehow the rest of it knows is to, yeah.
13:44:18 I'm still trying to put on my way around it that this is not optimization it's not based on that.
13:44:23 So it's a growth rate is changed by some other factor like temperature would have this, what would happen okay temperature is very interesting.
13:44:32 Okay, so first of all, yeah DD know if you do optimization, you later, you'll you'll get similar picture. Okay, except what numbers.
13:44:40 Okay. The, the, I'll get your numbers in a minute.
13:44:43 Right. The so there's so there's a debate kind of within this field is, is, is, is this a result of the morality, or what, right, am I have a different view and we can talk about at the end.
13:44:57 The.
13:44:57 But then if you change temperature.
13:45:00 Nothing changes, grocery chain changes the elongation rate changes.
13:45:08 Okay, but if you put compare the podium, don't I'm talking about lowering the temperature.
13:45:13 Okay, so my student Brian compared to the podium at quarter 37 degree and 25 degree grocery different by a factor of three.
13:45:23 Okay, the podium look like digital copy.
13:45:27 There are a few, you know, Hong Kong shops, proteins that turn on off but it's the same.
13:45:40 And this is one of the most amazing phenomena that that I know. We gave up we didn't know what to do. We know what to do with and it turned out and I saw this 2030 years ago and he gave up.
13:45:46 Sorry, can I just ask a follow up on what I asked earlier. So, instead of a useless protein, suppose I take a copy of something in fermentation say that you know lives, and I drive expression, not through the regulated pathway that the cell has, but independently
13:45:59 in a separate way does it does it reduce the amount we know less that it can express. So you have a separate, you have a separate system if you have a negative impact and.
13:46:14 Now, I mean, particular which protein you look at it will look like it's a regulatory scheme right so some, I would imagine for some enzyme was regulated by it by its function and it will accommodate but others will not.
13:46:27 We can talk about later if you want the temperature, why. I mean, why do you think it's so shocking. I mean, you know, translation transcription. Everything depends fairly similarly on temperature and so this is a big conspiracy
13:46:47 generically you know you do something. Okay, the style changes. Right.
13:46:52 My way when it doesn't change my obviously we can say oh this compensation so basically any static property looked at.
13:46:59 Right, so it's scientifically that it's not just spiraling down the clock, right, nothing changes, okay but then the problem is that there are thousands of reaction out there, how do you how do you coordinate all of their rates.
13:47:16 or different but they have all temperature dependence but why should they all behave the same way. I guess maybe a more global question is, you know, do you really need every right to change the same way.
13:47:28 I mean, if you have your transcription and translation scaling in the same way.
13:47:43 Okay so okay fine so translation slow down. Okay, then there are these enzyme that's feeding amino acid to it right now if if these rates are not the same, then that amino acid will pile up, then, then we should see a signal in repressing of the pathway
13:47:47 of these answers, there's no, there's no such thing.
13:47:53 Right, so if, right, because eventually regulatory signals are picked up by intermediate metabolites if the, if the rates are not match, you're going to see signal.
13:48:03 Gonna make a tiny comment about temperature. Yeah. You know, we looked at temperature compensation and chemo taxes with Victor surge IQ. And the answer is all the rage change they change it different, different extents, and it's all in the wiring of the
13:48:16 system that keeps it still functioning. It's not like it all just slows up. Yeah, so, so I don't know but then the the okay well it's a wiling, what is the value that will do this right, without putting that will change example where it's clearly not
13:48:33 the proteins change or not. Yeah, some of them. Absolutely. You know key foreign key be get expressed at different levels but there's a compensation. I mean, so we're looking at right if we make a correlation part of the different protein, basically just
13:48:47 just, I don't know, maybe key PPP is that a very low level that escaped our discussion but the major metabolic enzymes.
13:49:00 Alright, so let me leave you with a puzzle.
13:49:04 Okay, so this is a puzzle I refer to the when Daniel was talking, the price of energy.
13:49:12 So this so so this doesn't even involved, protein, right so if you look at your site is competition. And so, So, so the this is the energy production.
13:49:22 Okay so respiratory reaction will produce this much ATP flux and biomass from glucose making the biomass and make another quite a bit of a energy. Okay.
13:49:34 And the. This is how much you're tasting protein synthesis those just stitching together for 80 people put up a boundary peptide bond.
13:49:43 You see that actually the energy that's produced just from turning glucose into the amino acids already again it pays for the, for the making of this phone.
13:49:54 Okay, and that it's generating all of this energy, we do not know how to account for.
13:50:01 You do not need a fancy decomposition if I just take my house numbers. Okay, Adam up, you get the same picture.
13:50:10 Okay.
13:50:28 Well, you know, the rate of making biomass, maybe faster reaction with the cost more energy because the less efficient. Is it possible to make cost more energy.
13:50:34 Maybe faster reaction with the cost more energy because the less efficient. Is it possible to make cost more energy. I don't know, just so like if I recall back in thermodynamics right so if you want something to be highly efficient, you have to go really
13:50:42 really slowly right to to. This is much more trivial just the ATP that's involved in reaction to make amino acid, you need to have, you follow this, if you have to follow this the pathways are right you need to have so many ATP.
13:50:53 And we know the rate of how many amino acids needed in a cell debris. So you can account for the right account for the number of ATP that spirit to make this stuff.
13:51:02 Yeah, but what about also like the proof reading Ray so to ensure. Okay.
13:51:07 But I'm saying that normally you know in a taxable event, the universe will say that you're here that the most expensive energy consumption reaction is the making of the peptide bond.
13:51:21 For ATP.
13:51:31 Okay, and you need to make 10 to the nine such reactions. The tantrum the night, the 10 to the six amino acid each couple hundred 10 to the night. Okay.
13:51:35 And that's the amount of ATP that's needed. Okay, and we empirically will try to make many perturbation that will add few cycles to equal right, we have this effect.
13:51:45 Okay, but then when you when you put in this comparison and it's kind of a mind boggling right that it's generating all of the energy.
13:51:54 Well if if proofreading is very expensive we should be in a textbook should be no. All right, but but no these are just kind of a process of hand waving process.
13:52:07 So I guess observational II that seems weird to me because so if you do a simple biochemistry experiment where you take an ATP as you create a dead mutant and you take the wild type, and you express both at high levels.
13:52:16 That's right. So, yeah.
13:52:19 We observed like toxic effects of expressing the wild type. So, You know, if you knock it out yet.
13:52:29 No, no, I'm saying an exogenous a DPS, I'm not saying, knock out anything from equality color be as happy as it wants. Yeah, just add any ATP is taking a human HTTPS.
13:52:45 At least observational II the growth rate slows down. If you have a wild type copy of HTTPS.
13:52:52 Let drive it in as a wild a protein versus an ATP is dead protein.
13:52:53 So unaccounted for doesn't mean it's not being used, it's just we don't know where it's going. I don't know where it's going to make the same calculation for yeast, you know just using numbers in the literature and it's much worse that it's very hard
13:53:05 to get protein synthesis to account for 10% and everything else like an alien cell wall and DNA synthesis is much smaller so I agree there's a major mismatch between what we can explain.
13:53:20 And what cells make an experiment that's three suggested cell says that cells are using that extra ATP for something that matters to them. We just don't have the faintest idea what it is, is a physician, I don't know about as well.
13:53:34 I don't know about ATP as we, I think we played a little bit with ATP as, but then we putting other Utah cycles, like leaky protons and various things that we thought would be putting perturbation comparable to the protein synthesis budget, no budget.
13:53:53 And it doesn't slow down cell growth Not much, not much.
13:54:02 Yeah, what what I guess I'm saying that I did not yeah I do not know it's uncomfortable, right but, and I, I didn't even I didn't even know it.
13:54:18 But until until I see what it is okay, assess it and I don't know.
13:54:27 So, I just I'm just curious what kind of quantitative measurements, do you think could give you some insight into this like what are we quantitative all the ATP in the cells are we doing any energetic measurements like what what would give us some of
13:54:40 the following ATP is very tough right and the, the know it couldn't even be that just the model, the FBA model is just way around, it's assuming certain of each entity we actually generate imaginary how many ATP.
13:54:53 Okay. But let's say that the efficient is one, one fifth of what what this really is. But that but that doesn't answer your question is is like in principle I could do that much but I just it chooses to do a lot less.
13:55:09 Okay but but I do not know how to I do not know what to measure it. So, if I knew I would have been trying. This is obviously very important question.
13:55:18 Do you have any estimate of the protein turnover, whether that could, you know protein is being turnover was already measured in classical work, and we have done some major difference in this kind of a gross condition, minus, 3%, whatever you
13:55:39 want to recall a that's a winter, we had a winter course on so some microbiologist talked about heat generation.
13:55:46 So I thought like the 40s or whatever the 60% of marriage have just gone to as a heat.
13:55:51 Because you mentioned right, very high volume of fermentation it's very hard so that's why you have the quarter down. Yeah, and he explained that sort of like the way I know it could be that salad some purposely running for maybe four reason we don't
13:56:04 appreciate, it's running through the cycle degenerating.
13:56:13 This is only an aerobic conditions. Is that right, okay so this is a robot condition. We do the same thing for anaerobic condition than its actual numbers are much closer.
13:56:23 So the anaerobic condition, the biomass sentences actually requires input.
13:56:31 Okay, so in other can spy on messenger so you're getting Sep alpha three already. Okay, so in this case it goes the other way around. And you see so the brain is accounted for.
13:56:44 Once right so at least in fast growth, it's reasonably accounting for most of us who knows maintenance and and all kinds of things but we just to make sure the energy production here is part data but part FBA modeling it's not a direct measurement of
13:57:02 ATP total ADP just based on the flux, based on a flux. The how much assets is excluded.
13:57:04 And right so you have total glucose coming in, you know how much of that is to go to biomass.
13:57:09 The remainder is come out right it's a commercial to ascertain that well then you know what what the doctor metrical so there's no guessing, just be here in terms of how many radiation.
13:57:26 What about if you force them through anaerobic respiration. Ah, what about a particular experiment there's not much yeah I mean there's a little better because the other stuff that's excluded but not much.
13:57:40 The amount of guesswork is very minor compared to. Arabic.
13:57:52 Know what about anaerobic respiration. What about what we haven't looked at, we haven't done exponents needed experimental parameters, how much experience. Yet we just did it for was the acid excretion.
13:57:57 A okay and Oh another another sign that you see that I know the energy may not be that important is the grocery of equal on glucose, a robot groceries point nine to our flower string and I'll condition anaerobic is point eight.
13:58:18 Okay, you're, you're depriving and a lot of energy right i mean the only two ATP January for glucose.
13:58:25 Okay, excellent difference.
13:58:34 So, I'm just, why are you have you counted per carbon where all the carbons go Why are you so confident that if I just know acetate it's not secretly.
13:58:46 Not just acetate we measure formats and all this stuff.
13:58:52 Okay.
13:58:55 What time is it, two o'clock so I'm going to okay so this next module is basically sort of Andrew asked a question about how does it know right to to to coordinate.
13:59:26 So, can I ask you the energy problem but we could, we could look at the ribosome, and the growth coordination, but I'm going to skip that it's, it's kind of a. The work is published in this paper, but I'm going to skip down, go to the carbon utilization.
13:59:34 Okay, so.
13:59:41 Okay, so the, maybe just mentioned is one, one piece that's important. Thank be so the key here is that the so how. So how does the cell know how much to ribosome to make it a demon gross condition it doesn't have a counter to counter to counter growth
13:59:57 rate. Right, so it's measuring something internal.
14:00:01 Okay. And, in principle, it's measuring the state of amino acid you're on a charging and all that stuff. Okay, but that that system is plenty amino acid 20, you know, the only species and it was just had so many different things.
14:00:16 So then we had a guess, and by the time we wrote this paper on what what what is listening to and I will guess is that it's listening to the translation rate, the translation rate is an integral integral point where if any of the amino acids missing anyone's
14:00:22 Okay. And the show.
14:00:34 youngest my stuff translation rate will be affected.
14:00:37 Okay.
14:00:40 And so I'm just going to show you a piece of data to show this is actually the case right so molecular one knows that eventually, how much rebels will sell make is the ultimate control by PGP.
14:00:52 Okay. But, but then what the P question is what is the level of PGP listening to what is the reporting. Right, so I will guess is that it is reporting translation.
14:01:04 Right.
14:01:04 And so here's the experiment that we did to test this and this was a work of a postdoctoral humble question.
14:01:12 So we look at a transition of glucose to cluster on a typical dioxide, traditional.
14:01:18 And then during this transition the glossary obviously changed a lot, and we've already in in this Erickson work we look at the whole platoon level change and assuming that the signal is the translation rate we could account from logical account for the
14:01:30 dynamics. Right. And so then, rock on measured during this transition process. The level of GDP, which spikes up quickly and and goes down, and also the translational rate as measured but instantaneous transformation with that that's another book.
14:01:52 And so now you can make a scatter plot of it.
14:01:58 For this in political proof, if you will, right, that PP GDP is listening to translation. Right.
14:02:07 And so now we have a simple model of how this comes about.
14:02:12 So if you think about what translation right so right now, English translation right which is the kind of a stepping time for ribosome to go from one ready to it to one coat on to another.
14:02:22 Right. So that compose a two part is a prime, as a wait for the right to NATO come along. That's a challenging time. And then after two young and come round is a translocation move forward.
14:02:33 If the charging time is infinite, of a zero, you don't have to wait at all, then that will just be the translocation time that will be the sigma max the maximum translation.
14:02:45 And so then, our model so to attain this resolve, you just have to have a process, which is a synthesizing PDP, according to the charging time.
14:02:58 And with some just a default like this then you have a PB GDP level will be proportional to the, to the charging time, which will be exactly given by what exactly what this especially.
14:03:13 Now, how could. How could a sub monitor the charging time.
14:03:17 Well, the structure of a railway which is the enzyme that synthesize BGP actually gives you gives you a picture. The little tantalizing picture. So here's a crowd em picture of three young a inside the rabble So, these two are charged.
14:03:35 And the last ones I'm charged by the experiment they arranged for the last year and we cannot be charged.
14:03:43 And you see that a rail a, so the in the background is the rail a protein that kind of stuck in there.
14:03:50 So basically when you have and trust you on a going to the side.
14:03:54 That's where basically well it can fit in, and only when rain is split. In this way, could the business and the PvP sentences and actually be free to make it.
14:04:06 So, we think this is an elaborate device. So actually using to counter the charging, but the more you have an interest Young Money, the more you have to really get caught in the situation and make up
14:04:22 the way.
14:04:24 Yeah.
14:04:28 So so so transactional they will have to play the arrival, and then the transit location.
14:04:35 So if the arrival so then our model is that it's listening to the arrival time modularized the synthesis.
14:04:42 And then we'll be, yeah. Be comfortable bisexual mechanism.
14:04:48 Okay, So, so basically the point of this is that the you so it is it is this this whole scheme here is a is a process that listening to to be to the minimum a parameter problem not knowing which one, which which molecule to listen in to.
14:05:05 If you listen to the activity listening to the process.
14:05:09 Right, then it has a chance to Chicago the parameter.
14:05:16 Alright, so let me go back to the last topic I want to talk about.
14:05:22 So back to this simple picture I said in the beginning.
14:05:26 And I want to talk about carbon utilization biggest focusing on despite.
14:05:30 Yeah.
14:05:35 I mean, would you argue then that mutants that affect your name modifications, like to allow for Wallabies pairing are going to have the largest impact on that right so you think you could you could see in this picture was say that the New York Times
14:05:53 that appears upstream or downstream of it on a charge and will have fundamentally different effects, and indeed make a new look at it. So if you affect young charging, then this will say, Okay, then it's interpreted as a nutrient neutron shortage.
14:06:07 Because Try not charging too young and upcoming. If you track the say the, the, the pilot, that's for the translocation, then, then you have basically the trust young is stuck there right for for for a long time, then that will suppress the people in
14:06:34 is Daniel interpreted as a nutrient Is it is it is too high, right if you're not making enough ribosome, and then upgraded Right, right. You can interpret or.
14:06:46 Alright, so a couple updates.
14:06:46 So let's first. We have a single carbon fourth. All right. And then with the carbon uptake FX, which is measured in the mass of a mass of. So I measure everything your mask off putting to convert it to number.
14:07:02 The mass of this, say catabolic enzyme, multiply by is raised with a materialist dependence on the substrate. As a substrate concentration.
14:07:09 And usually, in our experiment was in batch culture, the new trying as much love as much higher than can. I'm going to forget about the subsidy panels.
14:07:18 So that's just basically Casey.
14:07:22 The V max space.
14:07:24 Okay, so, sex, violence, right so if the cell is not stupid is throwing away carbon, and the uptake is alternate into growth biomass growth.
14:07:34 Right, so then uptake multiplied by you factor turns to biomass growth, and you have growth rate should be proportional to the proper the catabolic and them fraction multiplied by Casey Yna to compare to this equation here for this catabolic and imagining
14:07:46 the offset is very low. And this is basically.
14:07:55 Okay, so that when we say carbon quality, basically what we're saying is that the. Well, okay, interpret this way, Mr. Casey.
14:08:05 So, so, so if the uptake rates for the glucose is high, for Mandelson's lot and it was sad. They are changing and Casey, by carbon types.
14:08:13 But this interpretation doesn't quite work.
14:08:15 Okay, if you're talking a number, because it was, you know, ballpark number of these. The Casey, it's much much larger than the observed. You see, when you see I remember in particular, which is talking to the take the slope.
14:08:29 Ok.
14:08:34 our hypothesis.
14:08:36 Yes, what underlies This is a conundrum. Is that the actual flux killing part of the catabolic enzymes, is a much smaller fraction of the the the the actual catabolic Yes.
14:08:37 And then, so
14:08:49 Okay. And this is blown out by more later proteomics study. And you see that, so, so, so, so the over here the total catabolic sector.
14:09:03 Okay, you add up all of the catabolic enzymes that the increased the carbon limitation.
14:09:09 But if you look at those that actually flux carrying and they'll be different ones in different conditions.
14:09:14 It's a small fraction.
14:09:19 Okay. And just to give you some examples. So if you're growing on glycerol, then you have as much as 1.5% of the podium thats related to actually grow up, pick a few downsides.
14:09:31 But then there are these all these other enzyme soldiers.
14:09:36 Just put down to here, RBS which the involving chance for the rivals, and gels, involving transportable galactose, you know, there are the same level express the same level as the generic mix.
14:09:51 Okay, so it is doesn't appear to be caring about me, it just generically putting on this stuff.
14:10:00 So now let's think about was this in mind, let's think about coal utilization.
14:10:11 So we'll see what I have to substrate in in a medium. Okay. And each individual carbon, I have a grocery lambda one of them that.
14:10:17 Right, so the question is what is if I put them together.
14:10:21 And so okay so let's say it both carbons are utilized, then, then each we're bringing this amount of a flux, and the grocery will be the sum of the two.
14:10:31 And then we have this other constraint, but I include her also the spicy zero which is a generic background color pelicans and that's expressed.
14:10:39 Okay.
14:10:51 Now the, the canonical way of think about this is that well, if I have option of putting in see one will see two. And let's say see one is better. Okay, I'll take carbon better than that I should replace Okay, I should not be expressing should not be
14:11:05 up CPU should be taking up Stephen right and that's usually how we justify carbon higher. But that's not how it works.
14:11:06 Right. And the world's II know because we know that each one of these, these factions, they are proportional to the way when you turn this on, if you put in this carbon than this.
14:11:22 This particular individual repression gets removed if you turn on that carbon, Lucas removed.
14:11:29 And so, if you don't use them, then you're just sacrificing that part.
14:11:33 Okay, is there any one small part of the total.
14:11:38 Okay.
14:11:43 So then, and these coefficients are set genetically basically what they mean is, this is based on common regulation or regulated by Corp. Right. Right.
14:11:57 And this conversation that just that, if you are at the maximum. When you have inducer. We are at the maximum.
14:11:59 What's your basically your basic promoter level so what's the maximum amount of this protein you put that's genetic parameter. It has nothing to do with the update to sell can adjust that to actually basis fix the car don't have typically.
14:12:11 Right. And then you do some analytics and you get you get to a grocery composition formula that's a bit more strange so it's likely. It's kind of a relative relativistic additional formula so that small grocery that they act, but at the eventually they
14:12:40 have the common speed limit, which is this lambda see that is the ankle of the ceiling can never go above.
14:12:40 Okay. And we have in this work we have done experiment to button.
14:12:41 Alright so basically, so then was this way of thinking. We can rationalize co utilization, but we cannot rationalize hierarchical utilization, higher to be obviously occur.
14:12:54 Right, but I don't think it's for the reason that people think about what we want, which we also originally was the reason we thought we thought that it's for optimal optimizing.
14:13:09 Yes, you have to experiment to take the glucose cholesterol system which hierarchical of glucose person right if you do experiment do an experiment to to remove that higher theater itself and grow fast.
14:13:31 In fact, my question was going to be exactly that because I guess I was thinking in my head presumably this may be true like broad pairs of carbon sources but are there any privileged ones that sort of fall outside the bounds because the point of regulation
14:13:34 least I know more than East I don't understand it as my older Nikolai but glucose is a privilege carbon source and the way I cut tablet repression works.
14:13:41 So, when glucose is present presumably the repression is so strong and everyone else, you don't produce these excess proteins, or is that not true for Nikolai.
14:13:51 So there's a high correlation between glucose and other calculated substrates.
14:13:56 Okay, but not putting glucose and glucose Neo Genesis substrate.
14:14:04 So there's some reason it's doing this. Okay. and it's doing this at the price of sacrificing grocery.
14:14:28 Alright, so now let's go to multiple species and the multiple nutrients.
14:14:28 So we have now say substrate as I go to one to whatever number of resources, and each has been taken up in this way, as I was describing yesterday.
14:14:42 And let's do this function keep on a period was given name. All right.
14:14:47 And then the soul so again we we take self, so no expression, in this case, whatever is taking the sum of all the carbon has taken in weighted by the fighter, give rise to the growth of biomass
14:15:05 and.
14:15:07 Okay, so then we can, you can we can express in terms of the protein fraction right of each of the carbon devoted to each of the carbon okay, Right, and.
14:15:21 Okay, so if we want to simplify this, in language what a package right yesterday, if we take you to a level to be small grocery is very low, and your mutual level has to be though also, and then which then we just have this different product of a substrate
14:15:36 and or the bottom
14:15:43 Alright so, then we have the see sector regulation. It's a some, some number multiplied this overall carbon regulation.
14:15:53 And we have these other constraints. right so then you put it together. Then you have the some of these catabolic enzymes.
14:16:01 Right, is given by some fraction of these, these, these eight us a multiplier, despite max climax is one, I mean just the overall allocation to the adjustable fraction of the product.
14:16:18 Right, and not impossible, there's a grocery dependence because there's a minus lambda, all the gamma lambda over new April the first point of growth rate will be just forget about that.
14:16:30 Okay, so then when we put into the, the species.
14:16:35 The the the concentrations then we end up this activity with this relations that Pankaj wrote down yesterday but now was actually more now molecular parameter values at his firm logical level for itself.
14:16:49 So what was the connection to this parameter.
14:16:51 Okay.
14:16:54 So, this point I have to bring up a network.
14:17:01 Oh, does it then there's a constraint.
14:17:03 Right, the sum of. Okay. So, sigma is the species number.
14:17:08 Right.
14:17:22 So there's so. So this is for one species right so then if the for each of these species that in principle does the, it has its own signal max of five Max and has its own location. Okay, so
14:17:27 when were to say, though, is is that this coefficient in the front.
14:17:33 So net had a very interesting paper couple years ago. I'm
14:17:41 basically a just writing down these relations right without sort of a bottle into going into the state of this generation that. So these are the parameters used in his papers so and again Andy is the cell density as in this case is the concentration of
14:18:00 the substance.
14:18:02 So now we can do a comparison of us to try to figure out sort of the molecular terms what they are.
14:18:12 Right.
14:18:22 Under this important construct the sum of these got what he called is an occasional thing is a constant.
14:18:24 I'm so parameters, first of all, if I look at this one alpha is, it's just this coefficient sitting in front of this term. So if compared here, and this alpha is this just this stuff, like it's a ratio of the mechanics constant multiplied by the podium
14:18:41 fresh.
14:18:44 And then the yield is just the additional stuff in front, and that's this VI.
14:18:51 So the first assumption in the model.
14:18:55 In this model is that the he assumes that the the eyes are not the yields are not species dependent.
14:19:05 And unless I'm willing to accept that. Right. The.
14:19:09 Basically, it may not be completely true but if you're saying okay Group Co Co co co co co co like glucose young Pseudomonas about the same now.
14:19:22 Okay, so then the
14:19:26 next thing is that the so so so so now the. So given this definition of is defined in this way, then, then the constraint here is all about this wi right so so compare those two spicy my is wi times Alpha Sigma, right.
14:19:45 So then you go back to work out with Wi Fi is just the ratio of office office in my device.
14:19:51 Is that
14:19:54 Okay so that is a assumption that the different species, share the same enzyme.
14:20:04 So that one, and more.
14:20:10 Hasn't hesitant to SF okay but I also see that know if you want to do a theory, comparing, you have to compare apples Apple right and and the show if you have August you have species was a better enzyme it's just going to take off.
14:20:26 Okay. But on the other hand, I'm not sure how realistic that is the you know the the.
14:20:33 Yeah, so the, the, the uptake as that property of the uptake of glucose in different ends of different species
14:20:45 are they are they all the same.
14:20:47 Yeah.
14:20:52 So so so I'm just comparing some of the line, line by line so alpha is this combination, and a constrain right is the alpha times a sigma independent number is he
14:21:13 Yeah, I'm just comparing this to him I'm not even company yet, that's okay so so if so I'm just comparing comparing.
14:21:19 Ow comes in here right so okay but anyway so so yeah so so you, you, you could well.
14:21:27 Yeah, I don't know how I'm just just just just plugging this thing in here, right, and then it compared to that. And this is the assumption on the answers.
14:21:40 And then there's a third one. I actually.
14:21:44 The second point is capital keys mono constant right the West, this is a concentration mano a mano the K is that Kevin catalytic right okay right and I
14:21:59 have a call I can have this capital keys VRM by
14:22:06 the same substrate, different speed.
14:22:16 I totally sympathize with, you're gonna write down a model is that different is simply nothing can do let me know how do i do compare right by other hand, I'm not sure of the experiment with trying to explain whether these, these subjects actually are
14:22:29 taking up with the same kinda little confidence, but again, those capital keys only would matter for low concentration on them yes and we're showing some very low considerations as.
14:22:47 Then you'll you'll have other stuff and you basically need to have rivals from being the same know and the bathroom at the ends up being the same.
14:22:55 Right.
14:22:56 Okay, so then a fight. The third condition is that the, you know this this constraint this global constraint for on a single species level is species independent.
14:23:08 Again, um and and I guess if we put in a correction to have a higher gross rating rebels promotional company.
14:23:14 So that could be the case that could be not, I simply don't know but then we're but then what, what, what, I understand from this comparison is. This is a, so this model, and it's very interesting to pull the pull out of this point out of this all of
14:23:29 the parameters, a very interesting point, but least okay the way I'm doing the parameter adaptation.
14:23:36 It is rather restrictive in the amount of the answer. So basically saying autumn species have the same enzyme, and the same constraint same rivals on the same same of all sort of a fight consultant, which we don't.
14:23:51 Well, we have we have to see.
14:23:54 Yeah, and if it was a case right then, in a sense.
14:23:59 So, so it will say what is this is a trivial degeneracy because it because now we're talking about same self, almost but not not not that trivial right because it's still can use different application that's, that's an extreme if the enzyme or the same
14:24:11 everything the same on Amazon, different species in this case will have different educational needs. Okay, that's still a very concrete statement.
14:24:26 is a that so well applications that ADA is application to see proteins to to to particular flux caring ends up but we can even call this a that one right so so maybe the color strategies for mothers still the overall sort of five laps needs to be the
14:24:43 same.
14:24:44 Now, I actually we measured. Some.
14:24:50 A few species, okay and actually find it similar.
14:24:55 Okay, but so maybe there's a guess, if what that is saying is true that needs to be like really a lot of content it's not something that can easily update the needs a lot of a conspiracy to to get it but, but, but the hope is still out that may be fine
14:25:09 as we look at it like no two.
14:25:16 Okay, but that ends up being the same, I'm really nice.
14:25:17 So I guess connected Aspen, if it's sort of dead extreme models not true what what is still saved in your opinion if we start to relax right if the five Max's are different and the wy wants to go away from that condition then then that fixed point disappears.
14:25:32 It's gone. I'm trying to understand sort of the structure of the growth rates I still get sort of substitute double resources for free in this kind of model, even if the Wi Fi or not.
14:25:45 I know I have a different mechanism. Now we'll talk about crossbreeding all that that's all I have another talk next week we'll talk about eye view of what might happen.
14:25:56 Okay, so that's, that's all. And this really work is talking about collection will work that done over the past decade by various rap members, members, and your particular motel in a row has been instrumental in some of the recent work.
14:26:20 Can I ask a relatively maybe simple question so based on what I remember, or maybe Miss remember from bunker just.
14:26:28 Do you then think the way the CRM reduced. There is a limit way way, the way the CRM that you've assigned now where it is pseudo degenerate species were species that allocate potentially differently or their constraints on the total number of subpopulations
14:26:42 that are allowed of a degenerate species. Well I'm also to still be basically I mean this kind of a model, I mean if you plug in, like this is a standard consumer research model, which was particular choice of identification of.
14:26:56 No, shoulder parameters. And so it's still subjected to MacArthur's exclusion, nothing, nothing, nothing special about Jerry one quick question.
14:27:07 Yeah. The fact that you have such a qualitative mismatch in the energy budgets for aerobic respiration but a relatively good match and fermentation would seem to me to exclude all mechanisms associated with maintenance.
14:27:21 You know, proofreading and editing and fixing DNA and so on because those have to be happening in both of those conditions, right. So, given that that's why I was hesitant to take up the more kind of a Yeah, the more positive.
14:27:37 What's left, I mean what's left is the difference between these two metabolic strategies right electron transport something, what's being Miss accounted for in the in the respiration case i mean can you speculate for us so there are so I can speculate
14:27:54 so actually say for Jolla, swimming, okay. It's actually we not realizing it's a much bigger part of the energy budget and then what what we used to think, okay, the and and for jealous, turn off anaerobic growth.
14:28:09 It's, but I cannot account for half of the budget okay but know that there are things like that that that's turned off. Let me just come into your question, wimping who's staying quiet but showed that in the generic consumer resource model, you don't
14:28:21 get MacArthur's principle you generically get half as many species as resources so that's a check, random matrices would say, at most, if you have any resources you can have em over to species, but it was random matrix there, so it's a way to check how
14:28:38 much the structure here matters compared to randomness. So in principle, if you could measure all the metabolites, you can measure the diversity in, in at least a diverse enough proper thing you would say there's half is the bound even though now usually
14:28:52 it seems like you should be able to pack the whole thing. And if you do better than that. That means there's much more structure in the thing, I don't know, it's just a thought,
14:29:03 maybe as an experimental it's maybe I can post a question so if if what bunker just said is a lower bound on what you can measure, and you have an actual fairly elaborate protein allocations for a measure of different pathways and how they behave under
14:29:19 different resources if you know provide say three different carbon sources or two or four or whatever. And you have known proteins that are symbols of particular resources being allocated accordingly.
14:29:29 You should be able to check how many subpopulations actually arise in target experimentally measurable way No, or I'm, I guess I'm trying to understand Yes, yes so for a few species, this can be measured my one problem is a package is going to tell me
14:29:43 that Oh, a few years is too little, and it's not going to matter to him
14:29:53 Ty is a lot more than a few means two or three, right, but but as the other thing is a you know a really to check these theories.
14:30:04 You really are to do in a chemo star. Right. And I am not ready to send my students to do this so chemistry experiments.
14:30:10 You guys are welcome to do it.
14:30:14 And also, the guest Monday I will, I will explain as fundamentally I don't believe in the steady state the results.
14:30:23 Sure, I guess.
14:30:37 Mine is a much more simple clarification rather than the provocative experiment that it seems to be. It's much more that if I understand the pseudo degeneracy argument you don't need multiple species, if the if I understand the way you construct this
14:30:40 but a pseudo degenerate you don't need multiple species, suppose it just equal lie. Yeah, there should be a prediction for how it partitions in different bins, different sorts of equally partition the resources Yes, and that in some ways would women yes
14:30:53 yes there's there's that quite experimental will satisfy all these conditions that experiments been done.
14:31:01 Thank you.
14:31:03 You mentioned that you felt that the same enzymes in different species tend to have different catalytic efficiency, and like Ned's assumption brought me this line way of doing adaptations that may be may not be the only way right so if I follow those
14:31:17 and doing. Take this model seriously, and this is what it's saying, I was wondering if you have a sense of whether through usually trade offs that relate these the performance of these different enzymes because in a, in a throwaway comment you mentioned
14:31:30 oh there could be a bug which has all the enzymes performing better.
14:31:35 Is that the case or is it usually if some of the enzymes are more efficient I don't I don't see why did you have executive enzymes that do very and, if so,
14:31:48 I mean, to me the way I'm doing the errands I'm answering the Enter properties not dying but it's all self, wherever the ends I'm in the cell can vary the growth rate, the carbon quality by just changing this.
14:32:04 That is a, you know, whether it's 5% or 7% of the sea sector, you put us at this point okay already can write, increasing grocery by 50%. So this is a very simple, easy way to change the application.
14:32:25 Task the same thing I was saying earlier, maybe in a different way, if you deleted one of the specific carbon utilization pathways, would your model predict that the cell then reallocates the flux through all the other ones, trying to sell no you cannot
14:32:46 measure it, wrecks the cell wouldn't know. Yeah, so the overall growth rate does not change decrease decrease uh but yeah so that's slow growth in matters.
14:32:50 Okay, so like, so, you know, if you delete a useless sort of a explain, oh yeah those definitely if you delete them. Yeah, slow growth, you can see a big difference right so if you delete the useless one so what if you delete the useful ones right so
14:33:01 you have the data useful Yeah.
14:33:14 In that media and you delete the glucose transport down there you will not grow, but will it reallocate the other, you know bro download the the measure sorry let's say you've multiple carbon sources in the media and yeah you just delete one of them,
14:33:19 and they're sort of globally regulated. Does it reallocate the podium partitioning to the experimental but we have done experiment with a glucose cholesterol, which is naturally it has a hierarchical control.
14:33:31 Right. And then we we delete, we remove the regulation that that subject let's roll to hire people control.
14:33:41 Okay. And we see grocery actually increasing.
14:33:47 And it sounds like maybe the it's more a bit more comfortable we haven't done experiment you you asked. Chelsea that's sort of the stronger version of next model that, you know, it will reallocate to stay in that energy budget if you delete any individual
14:33:58 resource pathway.
14:34:02 I might so if you say if you delete it. Okay, you have to substrate and you delete one of them forcing you to go on one. Yeah, it will, it will grow yeah okay we actually, we have that Yep, so it will grow a bit faster but not as fast as you can use both.
14:34:22 both. Because, as I said, it's, it's not determined by catalyst set by the it's not, it Yeah, it's not advocating.
14:34:31 So it seems like one interpretation of stuff you've been saying is that microbes live in unpredictable environments, and therefore, you never know what you're going to need.
14:34:43 And so you should make a little bit of everything.
14:34:46 Right. That's why you make all these enzymes yeah yeah yes or yes, you put out a street.
14:34:51 It's hard to predict the future.
14:34:53 And so then what it would suggest is that if you do the sort of experiment that people like Johan Polson are now trying to do which is to evolve eco light to grow fast enough to better stats, they are in a high glucose environment.
14:35:23 Then, in principle, if you're paying to have those other things to metabolize cholesterol and then like, you ought to get genetic changes that eliminate that production and it will support the idea that this is
14:35:24 actually being done already. And if you look at the landscape evolution lies. You see, you see these guys getting out there. Yo yo Lynskey experiment Yeah, other stuff is easily available you see you see these guys getting knocked up.
14:35:59 How do you do the calculations for the energy. It's not FBA right in FBA every ATP is accounted for. So I don't understand I realized understand maybe this is a coffee discussion but earnest and how do you see this gap right in FBA, there is no no you
14:36:16 have this maintenance thing. Right, right.
14:36:32 for account function for assigning function. But isn't that independently measured on the ATP the non growth associated ATP maintenance right isn't that independently measure that's a value that is independent measure maybe extrapolate into the zero growth
14:36:53 but we're talking about each growth rate, there's a part that's an unconquerable slow growth of horsemen the non work related thing.