13:03:43 Thank you. Thank you. Well, thank you, Thank you for having me.
13:03:46 I already regretting that I was only able to come far.
13:03:50 Oh week already kinda, kinda ton.
13:03:55 As you'll see, I'm.
13:03:59 I'm an electron and pretty much everything that I do in science these days so I'm a telecom plant scientist and I have become a dilettante microbiology microbiologist and the first 35 or 40 minutes or so I'll tell you about plans.
13:04:15 And so those of you who really only love microbes.
13:04:20 Take a nap. Go to sleep. And then I'll shout, when we're done with the plans. And I'll talk about microbes and the plan serve to give you an idea why I have become obsessed with with microbes so
13:04:36 yeah that's that's true, that's true. So, I'll tell you about how plant genetics taught me to love microbes and just disclaimers in addition to my day jobs I get money for doing things for these other organizations.
13:04:53 Yeah.
13:04:53 Alright, so I'll have pictures of the various people involved in the research as we go along, but I want to, in case I forget to mention anybody currently still in the lab and method and direct and then a number of people who have moved on to better and
13:05:16 greater places and then my main partners in crime and much of what I do.
13:05:22 Definitely dangle at UNC Eric lemon at University of tubing and Jonas and Jones that Sainsbury lab.
13:05:29 So, I'm a geneticist by training, and this story started like many good stories in science, where by serendipity.
13:05:41 And so, work by a graduate student, then the lambda and Chris boundless who is now professor at age, almost 20 years ago.
13:05:52 They made crosses between plans. And so that quite often, when you cross different strains of discipline I would also say yeah, yeah, you would get these f1 hybrids that looked.
13:06:08 Not so good.
13:06:09 And there were quite a few cases of this, where development biologist at the time and we're staring at the plants and thought there was something wrong was development couldn't quite figure it out.
13:06:20 So we thought well the next best thing would be to interview the plants now plants don't talk, you can ask them stuff but you can look at their gene expression programs that's sort of an interview.
13:06:32 And back then that was still with for metrics arrays.
13:06:36 We looked at a couple of these hybrid weakness cases.
13:06:41 And even though, when you look at the plans so here in the center is always the f1, they look quite different. Some are really really poor very very tiny others not so bad, even though they didn't look all that stuff, like the gene expression programs
13:06:55 were really quite similar.
13:06:57 really quite similar. And the only Gene Ontology go categories that were overrepresented related to immune response.
13:07:05 I call it my friend Jeff dangle and ingested wild a couple of other things you might want to look at if this has anything to do with immune jeans and immunity.
13:07:14 For example, you know, they should be spelled su stain the least for themselves and look at whether you see dead cells and yes they were, that sounds so
13:07:24 simple conclusion. These are plans that stuff from other immunity.
13:07:30 So the way we think about this plan says smart plans know that they are dangerous microbes everywhere. And they have to be prepared for these dangerous microbes.
13:07:45 But sometimes they seem to be getting carried away, and they think they are dangerous microbes, when really they are not so they are sort of paranoid plans.
13:07:57 And they mountain immune response, even when they are no pathogens.
13:08:02 It wasn't too difficult to come up with a hypothesis of what was going on.
13:08:07 We're putting two genomes together, and obvious hypothesis is a detector contributed by one genome, and the assumption else contributed by the other genome that is being detected as foreign specifically passage then arrived.
13:08:27 So we went on.
13:08:30 We looked at the genetics of this and it turned out that genetics was often really simple. This is quantitative trade locals map. The five different chromosomes, of our adopters, Diana and very nice geeks, to jeans.
13:08:50 All these jeans dangerous mix or em jeans.
13:08:55 You know, one from one parent to from one parent than one from the other parent. And this is a two dimensional genome scan the five different chromosomes and shown on one triangle.
13:09:11 Evidence for empathetic interaction and then on the other triangle. The joint logarithm of odds
13:09:29 to interacting low side are responsible for the phenotype you see nicely they as low as one Robinson's three and the other one on chromosome five consistent with this.
13:09:32 Okay.
13:09:36 That was good news.
13:09:38 Simple genetics, large effect genes so we should be able to own these genes.
13:09:44 And indeed, that's what we were able to do.
13:09:46 And the first gene that we've got to it was the screen on chromosome five yeah one dangerous makes fun. Oh, it's one of these, no immune receptors and R stands for nucleotide binding site loose and rich repeat receptor, but they also called an eyes because
13:10:04 they're very similar proteins in animals which are involved in detection of pathogens and they are all beer and R stands for something slightly different but abbreviation is the same to highlight a of immune receptors in plants and animals that serve
13:10:23 to detect invaders. And so this is a small region of the been on some some like 15 kilo basis or so.
13:10:36 And I'm so till you microbiologists this is you know, not very surprising you're saying and my and microbes that we see all the time but but people who work with you carry at this is rather unusual.
13:11:02 We're looking at three different strains of the same species and you can easily see that this region of the genome looks very very different in these three strains, so a lot of structure variation and many points that you can even sign up and be under
13:11:08 Center, the system the reference genome, Columbia because it was originally isolated in Columbia, Missouri.
13:11:18 You have these duplicated and our genes, and this is the strain from the village of on K, two k one.
13:11:27 As the good Leo is the several fragments of our genes that are related to this highly rearrange, none of them functional.
13:11:36 And then this is the region of the genome from the Spain that has the battlefield. UK three and see here, fully functional fully intact and Arjun and 20% amino acid difference so you can actually debate whether these are really illegals or are they just
13:11:55 different genes that happen to sit in the same place of the gene went so we showed that these genes were both necessary and sufficient so knocking it down or transferring it from one thing to the other.
13:12:08 But they were causally involved in this hybrid.
13:12:16 So, this was very nice. Christine has an immune receptor because our hypothesis had been on genome contributes Thompson that detects Thompson from the other genome as being Brian or Pasadena, Dr.
13:12:33 Before I tell you what the other team does short primer on how community works and plans.
13:12:38 It's conceptually, not too different from immunity and animals.
13:12:43 The first arm of the immune system in plans detects brawling conserved patterns so called pathogen associated molecular patterns or microbe associated molecular parents Pam's moms.
13:13:07 They also damage associated molecular patterns and dams, but today we'll just talk about these maps and downs.
13:13:09 So, he has a microbe and microbe produces certain molecules that find many different micro so for example flagella and and have detector for piece of flagella and they don't have to have five like vertebrates have but they also use use and rich repeat
13:13:32 to detect a piece of the gel and or
13:13:38 FTU is another one. If your fingers you make heightened plan doesn't make heighten the receptor for item for example, and so on and so forth.
13:13:47 So, these conserved molecules are being recognized by these eyes which stands for plump recognition receptors. and that gives you a mild immunity response so yes effective immunity.
13:14:05 But one of the hallmarks of Platinum plan community that I just mentioned cell death is not yet triggered but this leads to PGI of time triggered immunity.
13:14:15 What does the pathogen do. So the pathogen typically injects proteins into the plant style bacteria do that but also Oh my seeds, fungi. Also animals efforts will do that nematodes will do that, they inject their own proteins into the plant style to manipulate
13:14:34 the plant immune response so they target. He proteins in unity and they will degrade them they will first relate them they will assimilate them do all kinds of things to them, but they can't do their job.
13:14:52 And so then that allows the microbe again to proliferate because now we have a factor triggered susceptibility of the plan is the immune response is repressed again.
13:15:04 So this is where the second arm of the plant immune system comes in.
13:15:10 And the second arm is constantly constitute primarily is these analyze these nucleotide binding site use original receptors.
13:15:20 And they are specifically evolved to detect the presence of factors.
13:15:25 Some of them do that directly, they bind directly to factors, many of them do that, indirectly, they actually don't monitor a foreign protein directly, but they monitor the plants own protein, whether they have been modified by a passive then so whether
13:15:42 those plant proteins look different, or maybe gone completely. And then they as another way and they do it so with this decoys and talk about later. But so they have these ways of detecting these, and factors.
13:15:57 They signal.
13:16:02 And again, that's not really germane to the talk here but if anybody's interested in wanting to know how they how they signal. They have been recently some really important breakthroughs in our understanding of how these are receptive signal.
13:16:16 The signal to get an enhanced immune response. It's qualitatively similar to what you get with these passive voice recognition receptors. And it's qualitatively stronger, and often associated with South as.
13:16:32 And now that is you affect the trigger immunity and again you suppress the pathogens.
13:16:37 What does the passage and do by the pathogen changes it factors, so it typically Well, that's a factor that is being recognized, and then deploy other factors so typically pathogens inject actually a whole suite of factors into the plan.
13:16:56 They don't normally rely on any one of them alone but on this entire suite and they can afford to get rid of some of them through inactivation or moving away, so that then again you know you have can affect the triggered susceptibility, you can proliferate
13:17:15 as a pathogen.
13:17:20 And then the cycle starts over the plant evolves another and I detect now the effective that is presently in you get again, effect a triggered immunity so and originally This was known as the, the exact model of immunity and this is from a review by Jonathan
13:17:39 Jones and Jeff dangle and the proposal really initially was from Jonathan Jones that at the end of the 90s but this has been really very effective explaining plan.
13:17:51 So, our expectation was in our hybrid, that this other genome would contribute, either a protein that looked like a plant factor or a pathogenic factor, or protein that somehow looked like a pathogen modified plant protein so we were quite surprised the
13:18:09 DM to this partner also encoded in an immune receptor, and this region of the genome is even crazier. This is reference strain. These are three different strains that all give hybrid compatibility with different illegals at the slow case this is the sister
13:18:27 species are upset Robin can see crazy structural diversity. These are all in large means colored and different accolades are shown with different colors and just eyeballing.
13:18:42 How did this evolve so no idea what the history was so lots of rearrangements and and whatnot.
13:18:51 involved. So, who receptors that was a bit of a surprise. We were able to show and specific music was able to show that receptor is our large complexes, and that complex formation is necessary but not sufficient.
13:19:09 So DMTG is a those hammerlock that doesn't trigger unity in this large, complex as dm to the, the big because all across all protein. also in a similar sized complex so when we took away from this.
13:19:29 This is from a review by France that I can from a few years ago. These are proteins, they bind ATP ATP so they are essentially enzymes. It turned over ADP and ATP and the idea is that they are vendor ATP bounty and an Upstate.
13:19:49 And they are in a confirmation, where the business end of the molecule, either disperse the sea domain on to its job.
13:19:57 And then when the passage in effect that comes in at PS exchange for ATP.
13:20:11 Asked here. HTTPS being exchanged for ATP. And now the business and becomes available for doing its job. And so as an enzyme basically you go back and forth between on Upstate and ideas.
13:20:23 We can form complexes, of these receptors. If you have the wrong constituents that they are just too far on this on state side so any enzyme Of course will go no spontaneously through this cycle.
13:20:38 In the past when that factor is just the catalyst of of this. So that was one example. And then, when, when young came to the lab many years ago, she's now on the faculty at the National University of Singapore.
13:20:52 She said okay, we want to be a little bit more systematic about this. The first ad paradoxes Diana strains that we had sequence
13:21:02 in 2009. She took those and cross them all to each other so we became effectively I would officer breeders looking at over 6000 process here and you can see there is a white bread hybrid necrosis of different severity the magenta here are the words the
13:21:22 the blue are relatively mild, these are different geographic regions, you can also see there's no geographic pattern so it's not like when you combine combine a plants that are from far away that they are more likely to cause I have hiring process that
13:21:36 plants from nearby and in case. In fact, this first case that I showed you was from a single Village. Okay.
13:21:44 Yeah.
13:21:47 So there are quite a few of these little cases here is we cases.
13:21:53 So we really think this is sort of tip of the iceberg situation where there are many more hybrids where they as immunity. That's something that we've been trying to show for for a while.
13:22:07 Now, since we had all these pains genome sequence that became quite simple.
13:22:27 You have all kinds of interesting genetic architectures. So for example you have different leaders at the same locus that can interact with this phenotype.
13:22:43 ERDM to our record holder five different illegals, each of which interacts with another region and the genome.
13:22:45 And then, Lily, as a geneticist. My favorite case, young six and seven three of the leaders at this lockers and three year olds at this lockers, that genetically interact with each other.
13:22:58 That's something that Christina who is now at the saints very loud was looked into more detail so this specific interaction you first met Sarah was crazy 10, that this hybrid phenotype but not when you cross max the Euro was phase zero or dot zero.
13:23:16 And so for me, as a geneticist was very clear, earlier specific interaction that means Protein Protein interaction.
13:23:24 Unfortunately, the molecular plant micro field is really full of bullies. And so my friends they all bullied me into doing the work with the proteins to show that it really was at the project level so we looked at this locals in more detail on the one
13:23:43 side was rpp seven which encodes and our protein. On the other side is is a different class of proteins that had been linked to immunity wasn't very clear at the time but they actually do.
13:23:56 And what you see here is again, crazy, diversity in this region of the genome.
13:24:03 Christina went on to show indeed that coding sequences because all they are is repeats here and the number of repeat.
13:24:11 Basically determines whether or not you have this interaction with specific variant of the app up seven and Yun receptor.
13:24:22 And then the icing off the cake. Lay who is now on the faculty at the Institute for genetics development college.
13:24:30 Tennis Academy and Beijing show that indeed bH for protein acted as a ligand had caused the formation of a large molecule more of this RP seven protein and it's in a specific fashion so only when you have the cause of variance on both sides but you see
13:24:50 this or not when you have a cause a variant on one side but not really hearing on the other side and I had shown these cartoons of the structures, these are actually real structures that was the really large breakthrough for the field, gd children when
13:25:07 you saw the structure of several of these complexes so they are this process the songs they call it resists the songs behind it to emphasize similarity to inform our songs, made up of inner eyes and animals.
13:25:23 These proteins is up for debate nature for proteins probably have a potentially direct role in defense.
13:25:30 and kill cells and need these proteins alone when you over express them and plants we can kill plant cells, you can for example, put them into eco lion.
13:26:02 We can also quite effectively kill equalize cells and, also, East so what we think is going on here that these proteins is HR for RPWH proteins that part of the plant defense mechanism.
13:26:10 Upon activation of defense they are made and helps the plant cells with suicide, basically.
13:26:17 So how do we then think about this.
13:26:22 We think this really fits this original paradigm that we had in mind.
13:26:28 So these Asia for proteins, they likely make these Olive. Yes, thank you.
13:26:39 Of course you can say. So, just for our own education so how many of those analog hours are in our offices genome and how specific they are so the way, what I understood from your previous introduction is that they are specific to just a small class of
13:26:57 targets. So in other words, in, in our immune system because we wove new ones, what what those NLRB do how do they specifically to unknown by this instance it's a very good question a second and that's actually one of the big questions, you know that
13:27:12 I would have mentioned this morning if we had talked about you know non microbes a little bit more.
13:27:18 So in a single genome you can enumerate, how many of these analyze they make two things that we don't don't know and this is really, you know, this is what this talk and my research program is largely about.
13:27:33 You can enumerate these things, but how many of these have actually a positive function. And how many of them are just a reservoir of something, waiting to become useful.
13:27:45 And then how many genes are they an avid officers or any other plant species. That's not so easy to answer. I can count in a single genome, how many genes they are how many low say but you saw how crazily diverse they are.
13:28:00 So, when you then look at the entire population. There are many many more genes in the entire population and and I'll say something about this what the diversity there is but that's really, sort of, you know, taking this preempting this sort of my major
13:28:16 obsession.
13:28:19 How many are they, how many of those have actually function. And how many of them are just reservoirs to be there and as an evolutionary biologist, I'm very much concerned about these trade offs and basically, the more you have the better, but apparently
13:28:34 the more you have also, the more likely that stuff happens that you don't want to happen.
13:28:41 And this age of HR for, I kind of maybe have a shower for to NLP or is it something which binds it and triggers apoptosis or right so so so so we think these proteins, on their own, they can kill the plan cell.
13:28:58 This is the cartoon, what we think is going on with this immune receptor. And so this is hypothetical. So we know they can insert into the plant membrane and they can build a plan self.
13:29:11 So, it would very likely be targets of effective proteins from pathogens. We don't know which effect of protein, that would be that would somehow modify these, so that they can go to the membrane anymore and do their job.
13:29:25 And this is where then the rpp seven an immune receptor comes in. So the immune receptor would bind to these modified proteins, recognize them. And then there's this alternative pathway of immunity that happens.
13:29:43 And what we think is going on with the Asia for phase zero. So, this form that is being recognized the hybrid, that this illegal here basically looks like an effect on modified protein, and then it has been recognized by the FTP server receptor in an
13:30:09 of a pathogen. That's our working model of what's going on. So just to summarize this.
13:30:14 So we think there's a wide range of direct and interactions.
13:30:21 And the important part here is that we think that explains why there's a limit to how many resistance is to pathogens, you can accumulate in a single genome so if you go into population.
13:30:35 You almost always will find an individual that is resistant to a specific pathogen. So this, what that means, then they all have a different collection of analyze this individual is resistant to this spectrum of pathogens.
13:30:49 This individual on overlapping set of pathogens. This individual to again overlapping set of pastors.
13:30:57 Now you ask yourself if I always find somebody who can be resistant to any one pathogen. Why hasn't anybody, you know, been optimized and recognize everybody, every passenger.
13:31:11 And so we think the explanation is, the more you put together, because these proteins do interact just the way that they function, it just becomes too dangerous.
13:31:21 And the more you put together, run the risk, they start to signal in the absence of a pastor, not necessarily that they kill the plan, but obviously just a small, you know, increase in fitness would be enough to prevent that.
13:31:35 And that has actually been shown the a single enter our genes. Dr Bergersen has done a really nice work with, with this already 15 years ago. single nr jeans, you take them away.
13:31:47 In the absence of the pathogen, they will increase the fitness of the plan by something like 5%.
13:31:54 When the absence of a pathogen really huge fitness auto are their studies in other studies in natural populations where you can see the individuals are.
13:32:11 They're resistant as a population or as an individual or not that's exactly my research program for the next 10 years. So, exactly look look at that so maybe also take a step back there.
13:32:23 The field in a way has been held back by the successes in crops.
13:32:36 And in crops, you're looking at large fields which are genetically uniform huge selection pressure on the pathogen. And so it's all this one on one, Whereas natural population it's many on many.
13:32:42 And so we basically have very little very limited information out works in national association. There is an appreciation by more and more people and this was really pioneered by Bruce McDonald at an ETH Zurich and then Elisa liner.
13:33:01 Those of you haven't heard of Anna Lisa. She is one of my favorite scientists in the world. She does absolutely spectacular work on the ecology and evolution of plants and they're microbes.
13:33:16 So it's quite clear that this principle of diversity that you could deploy this in agricultural fields, if you had a population where you have many different disease resistant genes that that will be much more durable than what we currently do so that
13:33:30 just as an.
13:33:31 As an aside, so we.
13:33:40 Yes.
13:33:51 Can you exactly typically so so Tony given pathogen Will you normally have individuals that are resistant to it yes you typically will have, but we have so limited information on how many would be resistant to a specific pathogen.
13:33:56 What is the diversity of pathogens, all that stuff is is unknown, and that's what our research program is actually about to generate this very basic information so you would think that plant biologists would have figured this out.
13:34:10 Many years ago, actually not so is beautiful was beautiful work in the 80s pre molecular. We are colleagues like Ian crude would go to the field, they would take a leaf of individual plans, they would isolate pathogens, and then they would, you know,
13:34:28 test different pathogens strains on different leaves from the same plan. So to do genetics, before you could do anything molecular Lee, but there hasn't been the equivalent.
13:34:42 Today, in my past life they worked on product, product direction that works and I know that the urban ops is is one of the model arguments for which we figured it out.
13:34:51 Did you or anybody else try to see for interaction partners of ours, I realized that they have to be badly for aided by those factors, just to get an idea of how those interacting peers can trigger can trigger this desirable.
13:35:16 So absolutely so so we have limited structural information on some peers and is quite beastly to work with from biochemical side but these large PPI networks actually the first thing was worth by led by McAfee doll together with tracker and then just
13:35:27 angle and then there was a philosophy, study, to which we also contributed.
13:35:31 Then when you take a factors from many different pathogens. Throw them onto the plant protein, you will see that they indeed converge on a few hubs. So you have factors that look totally different from totally different presidents, and they will go to
13:35:47 the same August, that also makes it for the plan, much more easy to monitor, many different factors, because they are these conserved hub so it makes sense for the plant, if you will, to look after its own proteins, rather than to be on the lookout for
13:36:08 acid and proteins. So and so this idea that many of these proteins can promiscuously interact, this has in the meantime also been confirmed by the work of others including Frank talkin and and also my friend, Sophia moon.
13:36:25 So all of this sort of first half of my plant presentation.
13:36:32 We discovered this, by chance you can say you know what is it good for we don't know what it good for but you know it has taught us that in to diverse that intelligence can be dangerous.
13:36:42 As led to this question, how philosophic are these genes, really.
13:36:46 And this was not easy to answer because they are so different I showed you this one example 20% amino acid differences. Obviously short route sequencing isn't gone into a whole lot for you.
13:36:57 So, a graduate student Daya Kareena G.
13:37:02 Nevertheless, use short reads and just took our genes, the ones that you find the reference. And then from different expressions.
13:37:09 Just map them onto these and our genes. And you can see are there are you know whatever maybe 20% or so, which can easily find, but then they are many of them, where you don't find any heads so which are missing from all these other expressions so this
13:37:24 just gives you this 30,000, foot view impression of the diversity. And then in a follow up study, much more recently, together with Jeff and Jonathan isolated thousands and thousands of our genes from 64, different expressions and assemble them with a
13:37:46 and here you can see what is the presence, out of the 64 strains of individual Anya as you can see that there's a very relatively limited number that you find in many strains in men of many, most of these analyze.
13:38:14 are ignoring here, small scale snaps. So this is just really high blood types, you see that most popular types are found in very few strength. So, why are they so diverse obvious answer that everybody here I'm sure it's going to give me about this is
13:38:22 negative frequency dependent selection, you know, Why do you even ask this.
13:38:27 frequency dependent selection, you know, why do you even ask this. I agree with you, but actually negative frequency dependent lecturer balancing selection. Although, I think we all believe in it has been really difficult to demonstrate directly, everybody knows of MHC.
13:38:40 And then how many more examples, do you know.
13:38:43 And so using primary genome information Malinowski know pretty good populations and SS has looked very hard for signs of balancing selection in primary genomes.
13:38:56 He has come up with seven examples in primary. So, so we know this must exist, but they are difficult to find. And the reason why they are difficult to find has to do with if aliens are really old.
13:39:07 It's actually difficult to spot, that, that, because they are they are they are known polymorphous is different, difficult to spot the data.
13:39:17 So we totally locked out recent study with a relative of our offices Diana relative Tina Scott seller.
13:39:26 Many of you will know shepherds purse Abella personal stories, that's the same genus species Casella rubella granny flora and Orientalism this work by then clinic was now on the faculty of UC Riverside.
13:39:42 So, he looked at a modest number of individuals from these three species. And so what we already knew that upsell and rubella had evolved from brand new flora, a couple of hundred thousand years ago and this this is what you see what's this distance pretty
13:39:55 from old genomes, where all these genomes nest within granted Flora expansions are much shorter indicative of their being much less variation in rubella than in Grand the flora, which makes sense.
13:40:07 You'll recognize the flora has these large flowers and it has these large flowers.
13:40:20 And somebody has to attract this pollinator so.
13:40:24 Exactly, exactly.
13:40:27 And then the other species here and we'll come back to this other species. So since rubella evolved relatively recently from Grindr Flora Of course there are many leaders that are being shared by the two species, that's not surprising, but we're surprising
13:40:41 that the earliest sharing along the genome was very uneven.
13:40:45 So, they are parts of the genome where there's basically no diversity within rubella and high differentiation as measured with the fixation index FST between rubella and, and granted Flora basically what's happened is single individual became cell thing.
13:41:01 I wanted the species, and then almost all the diversity got lost.
13:41:06 Okay. But this is not true, everywhere. We've had these other regions of the genome, where we actually have substantial diversity and rubella. And there's very little differentiation between rubella and brandy flora that is whatever else you find and
13:41:22 rubella you also find them.
13:41:24 rubella you also find in Brenda flora. And so then went on and looked at you know how much of the genome is involved in these unusual pattern where diversity that was present in the original species was maintained.
13:41:41 Even though diversity was wiped out and most of you know, and so you find that this is strictly true for about 2% of the genome 21 regions.
13:41:50 Nine over these nine of these overlap was immune receptor gene and our immune receptor genes, and five more with other immune in such as pattern recognition receptors and several of them have known functions Ayana.
13:42:02 So what that looks and smells like, yes, you can get rid of much of your genetic diversity, but not at immune gene so they are somehow special.
13:42:13 Now, I think a lot of quantitative people here and they'll say, yeah, that's another anecdotal story and equals one.
13:42:19 Is that really true. So, as I said, we really lucked out because we had this other species, your orientalist.
13:42:27 And it very very recently went through an extreme bottleneck. See there's almost no diversity, the tunnel branches here very very short, we don't know what that bottleneck was, but I did go through such a bottleneck.
13:42:41 16, different strains we only find something like 70,000 snaps which is basically nothing to take two grand Flora individuals you have a million snips that they can watch them.
13:42:52 And the 16 orientalist individuals only 70,000 steps, but 10,000 of these shared with rubella, and granted flora, even though they split 2 million years ago, an oriental is live somewhere completely different from grander flora and rubella me even more
13:43:09 crazy when we look at where diversity is retained its retained at the same low side, we're also rubella and brandy flora, continue to share, diversity.
13:43:21 So, this really looks like.
13:43:24 Balancing selection and yes one particular example, the mo to locus will walk along the locus here. These are trees, and you can see that, you know, he and the flank, you have blue goes was blue so basically rebellious pastor was rebellious and red goes
13:43:41 was red so Orientalism alias cluster was orientalist alias, but then here over mo to a all of a sudden we have this distinct pattern where one of the readily of both was one of the blue aliens, and he another readily of those was other blue aliens.
13:43:57 And so when we look at diversity along this region of the genome, they see that this is between the same Leland the two species, and then both between different Leo's in orientalist and rubella, the background, you have some some like 3% difference that's
13:44:11 what you expect after a couple of million years of evolution. But then, here we're looking at the same earlier in the two species, they show the background diversity.
13:44:22 But when we have the same when we have the different illegals in.
13:44:28 In the same species, you see that they are differences much much higher. So 15% difference between different aliens in the same species, indicating that, on average, peacefully assumption like five times older and the split between the species and this
13:44:53 shows the sin other in. In another format, if you will. So, these are they out crossing know rubella, and orientalist suffers.
13:45:02 And granted Flora is an outcast so we strictly, we don't know whether they maintained diversity since the split, or whether it was continued gene flow.
13:45:14 In the end for the interpretation, you know, of course, geneticists would say these are different mechanisms, whether it's ancient balancing selection or continued progression or gene flow, but at the end, it doesn't matter and so far.
13:45:28 The immune genes, is where you need to have diversity. I guess the question I was going to ask is if you cross the cell thing species and create because now you if their cell phone your homozygous.
13:45:40 And now if you make them heterozygous Do you see fitness defects, and have those vanished and now crossings.
13:45:47 So, um, Yes, they are also is is also having the closest in top seller is not something that we have worked on with Michael Anna has worked on.
13:45:55 But that actually gets the Andrew that gets actually to another question that I'm keenly interested in I'm not gonna say anything further about it.
13:46:02 But diversity of energies and selfish and out process. So we know that out process have a ton more diversity.
13:46:09 So expectation is that and our genes are much more diverse and our process.
13:46:15 But when you think about these negative hybrid interactions in the south first.
13:46:21 They are very rare. So I adopted this out process about every 10th generation. And just as an aside, link is physical delivery on is similar to humans.
13:46:45 have with humans don't self but there's a lot of no marriage of relatively close related individuals.
13:46:45 So, I would also say yeah and I'd probably doesn't matter a whole lot, because these hybrids are rare, you know, and if one out of 50 doesn't do well who cares.
13:46:53 But the old crossers, of course, it shouldn't matter. And so this is something that we'd like to have the answer to, but again it's, it's one of these obvious things that we can answer.
13:47:04 Yeah, so, so, so I told you the story, you need to have diversity at certain low side, but it's sort of crazy that it's the same low side in these very different species so here's capsule oriental as you can see, even though it's highly bottleneck.
13:47:20 This is a pretty large room regionally and Central Asia where we have our collection from, and then Rebecca and granted Flora around the Mediterranean.
13:47:36 the Mediterranean coast.
13:47:39 So,
13:47:39 but that has really led to this research program and now we finally get to the micro so those of you who took a nap and you want to hear about microbes associated with plants, time to slowly, wake up.
13:47:52 What drives the diversity vacation of the immune system in the wild.
13:47:58 And as I said so. Now, was really through this roundabout story was plant genetics that we came to love the microbes interested in the microbes.
13:48:07 And so I'm only going to talk about the Hello sphere plans as you all know they have leaves above ground and then we have roots down here.
13:48:16 This lovely review by my friend Julia for hold.
13:48:22 Totally ignores the route, as we can see here and focuses on on on the leaf. Yeah.
13:48:27 And so, they are, I had only talked about defense by proteins. That is not the entire story because obviously first defense of plants is physical defense so there is an epidermis so that presidents can easily get in, they also have these errors which
13:48:44 are often fall with accent.
13:48:48 So, if, if a microbe wants to get something from the planet has to get inside the plan and filament is pathogens, fungi Oh my seeds, they can actually penetrate the planet's surface so they can develop substantial pressure to poke holes into the plant
13:49:08 surface bacteria can do this. They typically first colonize the outside of the leaf. The so called atmosphere. And then they have to get in through the stomata, which are the openings that the plan needs for gas change.
13:49:25 and many of them can actually manipulate these openings so can make them open up so that they can get inside. Once inside the job is not done yet, because different from what you might think inside of the leaf per se, is not a very hospitable place so
13:49:40 there's nothing much around this actually, there are no nutrients. So they also have to somehow manipulate the plant cells to get nutrients.
13:49:50 activate trigger transporters and places where the sugar transporters are not supposed to be active, so that they pump out sugar into this, this digital space if whether by the past.
13:50:06 Okay so, so we concern ourselves, only with Philadelphia for really operational reasons that we ignore the road and we are interested in. interesting Allah pathogens.
13:50:21 Both bacteria and oh my seat but I'm not going to tell you anything about our own my seed work to bed, today so today is all going to be about bacteria.
13:50:32 So, I'm coming back to the problem at hand.
13:50:36 So illustrate why it is so difficult to make a connection between pathogens, and the plant.
13:50:46 Very nice, study from a keras of when she was a graduate student with Troy Bergersen published a number of years ago, where they looked at a resistant gene, but up yes five.
13:51:00 And then, imagining effective gene and Pseudomonas called a VIP PHP, which is being recognized by RPS five.
13:51:08 And so they looked at the prevalence of a VIP PHP and local Pseudomonas populations. They look at the presence of the Assistant Dean and local out of this Diana population so this is obviously a map of Europe.
13:51:26 Here is the north west of France. And this is actually around Lake Michigan So, but important is what you see here IPS five.
13:51:34 You have functional Leo, it varies quite a bit and different expressions, but you know an average, whatever, a third or half or so of the plans have a functional, Leo.
13:51:46 Very rarely that all of them have them very rarely that none of them.
13:51:50 But then when you look at here a VIP PHP, both in the United States, where our absence was introduced, only in the year 1600 as we found out from sequencing, barium specimens.
13:52:02 And here in the northwest of France, a VIP PHP is actually quite an array on Pseudomonas so when you look at this, this doesn't make a whole lot sense that the resistant gene is much more common than what it supposedly recognizes so so it's very clear
13:52:22 that we're missing large pieces of the puzzle. And again, that's really what we've been trying to start to fill in, in my lab in the past couple of years.
13:52:32 So first question is to just ask who is the what microbes are they actually on this planet so Tanya was an a postdoc in my lab is now on the faculty of the University of Utah and together with Manuela no man.
13:52:47 Unfortunate was hired by Bosh global because they realized if they know how to protect plant pathogens that's also pretty useful if you want to build devices to detect human viruses and much more profitable than plan past, so I started to look at natural
13:53:06 plants. This is the city of giving an E and so I would ask this Diana is a real plan was real ecology, it's really quite common once you know where, where to look for it.
13:53:16 You see it everywhere. And so, various populations that they have that they have looked at.
13:53:37 So, a short excursion here just want to remind everybody here that typically one looks at this with 16 as our DNA or IDs, our DNA applicants, you all realize that they are compositional that's not so much the issue but the issue is, it doesn't give you
13:53:42 a necessarily an indication of the absolute load of by crops and we think that's important. We want to understand how plants, deal with the microbes, and we think it's important that we measure.
13:53:54 Really the absolute number of of micro so this is just a simple cartoon just to remind you, you can have two samples, for example two different time points, we look at this naively and you think it's pretty clear that you know this light green pathogen
13:54:09 expanded at the expense of the red Caspian but when you look at the real world scenarios that are possible. Under this observation, it can be anything so it can be that population overall stay the same and green instead, in the blue at the expense of
13:54:26 red. It could be that there are a lot more microbes on time point to that red, maybe shrink a little bit and green, blue, a lot, or that there are many many more microbes on the second time point both of the populations growth are actually the both of
13:54:42 them, shrunk so that's something that has been quite important to us and that's why we've been wearing quite a bit about measuring not only relative abundance of microbes but also an absolute abundance and.
13:54:55 Initially, we tried many different ways to get rid of the plant DNA that didn't really work so we restored it ourselves as Diana has a relatively small genome we restarted so so to speak to the very dramatic approach of brute force, and just taking the
13:55:12 whole plan and sticking it into the sequence and just asking how many leads do we get from the plan because that's a measure of the landmass, and how many leads do we get from microbes, that's a measure of microbial biomass and again and again so that's
13:55:26 you know sort of boring for most of you but just to remind you.
13:55:31 So, total reads equal it will look something like this. You can keep the microbial reads equal. That's what what happened was applicant sequencing, or if you sequence also part of the plan.
13:55:44 You can eat the plant nuclear reads equal and then you really see what is the variation in prevalence of other microbes. So,
13:55:59 this is all on a linear on a linear scale.
13:56:06 Yeah, so it depends a little bit if you have real disease microbreweries can be 50%. So normally it's a few percent. but these are these are actually real data.
13:56:17 So you can see that so most of them is plant organ now.
13:56:21 But nucleus. And then so so this, as I said, this is from real data and these are the microbial read so it can be here. Probably the best one had 20 or 30%, most of them had relatively little.
13:56:31 And then this is just rescaling these data here for, for illustration purposes.
13:56:36 So we have used this quite a bit we think it's important. So, one of the first observations that we made that really made this point.
13:56:45 I'll tell you more about your homeowners in a second but as a plant biologist you think about student loans a lot because it causes many diseases.
13:56:53 And so, again, these are real data, you look at them here. And you see that you know huge variation in the blue fraction. And then it looks like eyeballing, that there is actually variation in the other direction in the red fraction the red fraction is
13:57:08 Springer moaners, and indeed when you plot that against each other then it looks like there's negative regular regulation, negative correlation with an R value of minus point sex.
13:57:21 But when you use the shotgun data so and again these are real data, you see that they're both positively regular positively correlated so all of a sudden instead of minus point six is no best point six and both of these are highly significant I didn't
13:57:37 buy that P value, sir. So, can get really very different ideas and this is why direct Lundberg developed this method of MPC so the shotgun sequencing is very simple but it's not very cost effective because he mostly sequence the plan.
13:57:53 You can use that approach to do applicant sequencing, combined with whole genome shotgun sequencing and then normalize, if you will, the applicant data that that that works we have shown that.
13:58:06 But again, when you work with plants that have very large enormous it's, it's not really the way to go. so direct develop this method is really quite nice.
13:58:14 So you amplify some gene from the host. That is conserved to amplify the microbial microbial target genes to normalize the DNA that you have that you have amplified.
13:58:30 And then there's a really neat trick. So, each sample has a barcode.
13:58:36 We combine these and then you attach a new barcode and then you get this one reference sample, but you know, that is the unmanipulated original, and click on the data.
13:58:49 The data were actually the plant data will will be much higher abundance. And you also still have the backwoods of the individual samples so you know for every sample what is the absolute amount of planned reads and that's what really matters.
13:59:03 And then if you run these applicants separately here, just on a gel.
13:59:09 You make the applicants in such a way that they are separated separately separable by size on the gel, and then you cut out this entire slice of plant and click on and then this entire slice of microbiome click on either six or IDs.
13:59:37 And then you just re recombine them but we use that all of this, and he used a lot of this year to reduce her presentation of the host DNA. And of course for the green guys here.
13:59:43 Once you put out this single slice here. The illusion factor is the same across all samples. So you reconstitute this and then you also have your reference sample, you put that on a sequence or you count the antler cons, And then in Silicon Valley, you
13:59:57 what the original abundances were without having to sequence, all of these plan sequences, but only a small portion of them. And we just. This was just published came out online, couple of days ago.
14:00:16 So again this is real data the next slide here, these were.
14:00:23 These were initially just our communities, direct, together with Prucha to either more communities of have different microbes and plant DNA, or synthetic communities that we've got from our colleagues are here, simple communities and this is just to show
14:00:42 that the reconstruction, really is very faithful to be original library. Okay so end of excursion. Coming back to what we are really interested in what if what are the microbes on national outdoors, on our plans.
14:00:59 And again, so you might say, you know, isn't this known for 20 years but no it's not now, so it's sometimes really quite remarkable. What it's not not so Tanya and I know Ella, they looked at, together with Giuliana and Maria from a chemist lab followed
14:01:17 over several years and season, the philosophy of natural order of, Diana populations and what they found was that the most common or to use this little bit all the time that the most common use typically Pseudomonas and if you type in Pseudomonas and
14:01:39 plant into Google, and now first things that come up is Wikipedia fantasy so these are obviously much more interesting clients and our officers Diana but just make the point is that is that important plant pathogens.
14:01:51 They do also in boot some mentors, but really known for being planned.
14:01:58 And, Indeed. When we look at the 16 s data at the end of verdict, or episodic data, or we look at isolates that we sequence so we we cultivated. Many of the strains and then sequence over 1500 of these and see that indeed there is a single audio, which
14:02:22 we call Oq five. If you're interested in species name it will be Pseudomonas very be flower. That is really highly highly prominent so this is the Pseudomonas collage.
14:02:39 These are other Pseudomonas strains that we see in our cultivation or in the 16 s survey. So this is one group, which is dominant so the single audio file.
14:02:46 It actually largely corresponds to a single ASP there's no variation, 16 s.
14:02:51 But even though there's no variation in the 16 s sequence. There's plenty of variation in the genome so these are these 1500 genomes all of these are you five, and see that they have
14:03:05 something like 1000 genes, as a genome and then 10s of thousands of genes, where they vary.
14:03:15 And we can come back to this later, but what's going on in the individual plans, and this was really nice that we were able to do this because we had culture it and then sequence the entire genomes, we could look at what had happened in the individual
14:03:34 plans, you can see that the individual plans are correct the rise by these blooms.
14:03:48 Were, especially in spring, not quite so much in the fall cohort but especially in spring, when you look at the largeness of the genomes that we get from single plans that they are typically blown expansions.
14:03:52 Yeah, and the second fall it looks a little bit different, we see more of the non otu fives and then also among the audio files we see a little bit more diversity.
14:04:04 Now, what's perhaps more important and this is why I made this point about load, because we had the opposite is absolute data we could actually ask who drives bacterial load in these plants and bacteria those yes just defined as the ratio of microbial
14:04:22 reads per plant read so in other ways.
14:04:25 It's essentially the number of bacteria chromosomes divided by the number of chromosomes.
14:04:31 And so, this is a correlation of all the different odd us with bacterial load in our office Diana you can see you five is really the top guy here so you five is what drives total load.
14:04:46 And so, this is bacterial load compared to the fraction of audio files over all the other microbes and again you see a nice positive correlation. If there's high bacterial load, it means that otu five is dominating the bacterial population.
14:05:07 Now, how does that actually correlate with what we know from the lab. So, Pseudomonas is highly loved by an apologist is being used as a model of pathogen should point out.
14:05:24 Normally what people work with is actually not in darkness out of the Santa pass it in but is a president comes from tomatoes so this stands for a Pseudomonas to rank a possible tomato.
14:05:35 This the isolate it is because.
14:05:38 So tire looked at what kind of loads. One achieves in the lab. So she infected in the lab, either with a strain that is being recognized person has an effect that AVRB that's recognized by the particular strain we use, or as strange as not being recognized
14:05:57 Avi our mind minus. And that can proliferate unchecked, and again so compared meta genome analysis with what you see with colony counts, this would be the usual measure that.
14:06:09 I would also say Ghana plant pathologist would would use.
14:06:12 And so 10% of Pseudomonas wreath. is equal to about 500 bacteria scrambling of leaves. So, with these data then you can go back to the data from the wild and ask the total amount of microbes that we see in these plants, how does that compare to, when
14:06:30 we in fact plans in the lab.
14:06:34 So this is the lab infection with the strain that is not being recognized that can proliferate unchecked, and out of society Ghana. And these are the loads of the day, one day two day four day six it goes down because I often chromosomes integrate integrate.
14:06:53 integrate. And these are the wild samples, and you can see the water samples. Most of them have actually relatively low load. So, insurance is the densities that mimic uncontrolled lab infections actually really rare nature.
14:07:08 And that really fits was when you look at these plans nature they look quite good, so obvious symptoms of disease is is really real in nature.
14:07:16 And so, the same data, just rescheduled a little bit.
14:07:21 And here compared to what happens when you interact with a microbe that's recognized.
14:07:27 Day one anyone day to day for you see that most of them have loads, most of the wild plants have loads that are below what you see, after day for. In, after an infection was a strain that's being recognized and about quarter have ever been.
14:07:42 So again the point here is that extra microbial load in the wild isn't all that high compared to what you know people do who torture, our doctors on purpose in the plant by injecting Pseudomonas into the leaves.
14:07:57 So that's what it just says microbial loads and wild plants, typically in the medium between compatible and incompatible interaction that's a pathology term.
14:08:06 So, the call incompatible. When the pathogen has been detected and compatible with the past and it's not being detected it's a little bit weird but that comes from this region genetics.
14:08:19 Now, coming back to this view here with your five I had already indicated that there was actually a nice quote genome of something like 1000 genes, but then 10 thousands of genes, which they deliver and indeed you see phenotypic differentiation.
14:08:33 This is in a normal biotic system. So, we isolate this passage in from the wild from plants and look healthy. But when we infect plants and the lab, in the absence of any other microbes they actually really efficient killers of plants.
14:08:50 So this is this model pathogen that everybody uses makes plants quite a bit smaller, is you five, many of them can completely wipe out plans after two days and this just the fresh weight of plans, but not so important here is that it can some of them
14:09:07 can kill us right out right but they asked quite a bit of phenotypic differentiation among these five members so there are some of them that don't really seem to do a whole lot.
14:09:16 And so here in this other color here is green turquoise color, non audio five, you see that that they tend to be non.
14:09:27 ls.
14:09:27 So this observation then that most of the non audio five isolated from my parents were non colors and most of these audio files were killers inspired a student in the lab Mashallah, who is now postdoc with Christopher ROTC at the University of tubing
14:09:45 in, where he is working on real microbial ecology, it's a little bit of a difficult life so yeah fine come in here.
14:09:54 Okay, so it inspired, or to look at groups that went too fast. Okay, go back here.
14:10:04 And it inspired, or.
14:10:06 Okay so inspired for a look at the interaction between these two to five pathogens, the pathogen in the lab so opportunistic pathogens probably the more correct word interaction with other Pseudomonas also taken from the wild.
14:10:24 So what he did was, in fact plants but now on soil, and instead of what people normally do, when they go to the plant and they inject the bacteria directly into the leaf he just raised them so it mimics natural and the natural situation was Pseudomonas
14:10:39 probably much of them is with rain sprays and then he looks after a couple of weeks, what happens to the plan. And you can see that when you interact with a moderator complex community of seven of these five members, which he calls pasa con for Pacific
14:11:03 community. You can see that they tend to reduce weight and depends a little bit on on.
14:11:04 It depends a little bit on the exact, I would obviously on a strain that you use. Okay.
14:11:12 And so, again, these are soil grown plants and the plants are not killed but you see that there is a reduction in size.
14:11:20 And then, the
14:11:23 two more communities.
14:11:25 Use non otu five Pseudomonas so what he called commensals because on their own and another biotic system they didn't build the plan. Also, community of staff members, and then mixed community.
14:11:37 And you can see that this common calm, either doesn't do anything to the plant or slightly increases growth of the plant. But more importantly, you have the mixed community pathogens and commensals together that almost always, you have protection protection
14:11:53 from the reduction and plan size asked by the pathogenic unity.
14:12:01 And so this is not used to reducing total load. So this shows over, you know all the all the over many samples. The total load. This is the load that you get with the pathogenic community loan, get substantially less was the comments or community.
14:12:18 And here the mixed community actually see that the load is very similar to what you have with the pathogenic community. So here you have the pathogens and the commensals together.
14:12:27 Yeah, I'm wondering how you did the inoculations where the commercials put on first or where they mixed together, know if they weren't they were mixed together and they were mixed, so that the Audi was added.
14:12:39 So, you can argue what what's the what's the right way should one you know have half of match to that the total audience to say, but he has actually started with double DOD basically.
14:12:49 So exactly the same chemical.
14:12:53 No, nothing. So just so so so so it's really annoying experiments to do because you you know use an airbrush to spray the plan. So you need a lot of, lot of replicates.
14:13:04 We figured that this is much more, you know, a much better facsimile of what happens in the wireless carriers, whether it's you know, maybe we'll get into this whether it's like the actual microbes or just you know because there's well known, like in
14:13:17 do Civil Defense responses in plants, whether you think that might be something extra. Yes, I mean we also looked at, we can talk about this later we did actually look at transcript Tomich changes, I'm not going to show this here that transcript toxic
14:13:28 changes are, it's, It's quite different from what you might think, basically.
14:13:34 So, but so again the important thing is, it's not just by reducing load.
14:13:39 Although the. When you then decompose it. So these fans, they were all barcoded that that was the major aspect of the study that all the students were barcoded and we could follow the abundance of each individual strain.
14:13:54 When you see that the pathogens actually proliferate less than they would normally, whereas the commensals proliferate as much or more than when they are alone, so you don't reduce the total load, but you reduce the load of the passage and so these commenters
14:14:12 are quite competitive bags of course the question when we go to the wild is otu five are the ones that we isolate much more commonly in these non audio files so what's going on there so that's another piece of the puzzle that we have to somehow figure
14:14:26 out. So, like I told you this audio five of course you want to know who drives you five evolution, the sad story here is 45 is relatively promiscuous, so even though it's by far the most abundant micro on ourselves as Diana, you also find it on many other
14:14:44 species so this again direct sample the number of wild plants is one of our favorite sites here.
14:14:51 It's an abandoned train track so we're not at risk of being run over there. So, but when you do this so collected many different number of different species.
14:15:04 Again applicant sequencing, and then focused on the Pseudomonas ot us, and looked at the YASV is actually but this indicates the equivalent, or do you see that oh five is most common on these classic case here so also on grammar and not a dominant.
14:15:22 And then other groups tend to have their own favorite. I'm Pseudomonas but they are not, they are by far they are not exclusive and we also know that from strange altering and by the way just as a digression here not going to show data here but Derek
14:15:35 was another really nice trick to the madness, you can select for with natural front and center is really quite need to what he does is he attracts expects micros basically from wild plants, and then grows then on selective media, and then scrapes off
14:15:51 the entire plate and shotgun sequences that. So that's sort of in between cultural mix where you do individual isolates and a total shock can sequence and you do shotgun sequencing but you focus on what really matters.
14:16:08 So, the strange thing if you will is when you look at your five how old it is and we were quite confident that this is for real we got advice from Russia now on that so Chris has told us what to look for and we excluded regions of the genome that looked
14:16:23 like they had been recombined. So, we are fairly certain that this is a relatively conservative estimate.
14:16:28 So just in this really small region of Germany as maybe 30 by 30 kilometers 20 by 20 miles, this population, we estimate about 300,000 years old.
14:16:45 So as I said, so they are regions where looks like that recombination could have could have happened but we haven't we haven't formally mentioned that, how much they recombined.
14:16:57 But mostly, they are clone.
14:16:59 But the crazy thing is that this population is 300,000 years ago so if you think of living and 300,000 years ago, while there was no have a DOCSIS 300,000 years ago.
14:17:09 So, we had multiple times or at least the resources that are there now. Wasn't there 300,000 years ago so you had multiple times of glaciation in the last Glacial Maximum is much much more recent.
14:17:21 So this population of microbes is really super frequent on this plant has been around for much much longer.
14:17:30 So, another,
14:17:33 another fact that, you know, we are really, we're really at a loss to,
14:17:40 to explain. Can I ask a question on this point. How did you time calibrate that biologically.
14:17:57 What kind of anchors did you use to fill out to do this. Yeah, yeah, so I got a few fossils and how did you do today i know i mean this is we did some approximation of how many you know what generated how many generations I do not remember the exact numbers
14:18:03 how many generations we'd expect per year.
14:18:05 And we took measured mutation rates. Okay.
14:18:09 So, but as I said, we try to be pretty conservative in in these assumptions, I guess, in other words, what are the, what is the uncertainty around the DMCA could be comparable to the pattern that you're so prepared by yeah so I mean, I would ask this
14:18:25 would be the, you know, some some more on the order of 10,000 years, so even an order of magnitude. And as I said, we think we were conservative so if you would take more average numbers, you would get considerably older.
14:18:40 So,
14:18:43 so I'm afraid what I'm have left you with now is basically a whole palette of questions observations that maybe ties in nicely to this morning or this phenomenology which we really have very little clue what is behind there was very clear is that we do
14:18:59 need more data and so now comes the sales pitch. So again, anybody who doesn't like sales pitches. Go back to sleep so.
14:19:09 So, and the sales pitches that together with a breeze and joy who would have loved to be here we recently got funded in a six year ERC synergy grant on which I'm the corresponding pi on a project to try to understand the passive in communities and the,
14:19:30 if you will, our pitch our stickers that pathogens normally don't act in isolation is that what you know, typically plant pathologist Do they have the plan was a single pathogens but that's probably not what, What, you know, is going on out there and
14:19:45 I think this gives you a little bit of tidbit from from artwork with the different Pseudomonas how they can keep each other in check so that the way we like to think about questions and not so much the past and taking over the plan, but the pathogens,
14:20:00 taking over the microbial communities, and then they often do that more effectively, when they are not alone.
14:20:06 And again, as many of you know that many diseases also as humans that we have is not just a single pathogen but many participants, you know, in the last year we've seen this with covered, people have compromised lines they often do something else then,
14:20:24 and just the virus.
14:20:27 So, the idea is really to look at this and two different levels to look at it in a genetic level where we look at meta genomes genetic elements and genetic drivers and then at the ecological level community memberships microbial interactions and ecological
14:20:44 drivers and the way we are going about this is one aim is to generate a large set of real world data. We're working in North America, around the lake michigan southwest of France house west of Germany so to sample over several seasons, what are the microbes,
14:21:04 microbes, these plans to measure bacterial load. Look at interest specific diversity by enrichment sequencing on both the plant and the host side, not shown here is we also have gone to have a significant transcriptome program where we basically want
14:21:19 correlate what microbes you see and it's actually the immune system activated, because almost certainly they're going to be many cryptic infection, and then have a data on companion species, the weather the soil, and so on and so forth.
14:21:37 So, so that we focus on four different species, he has three species of pathogens animals Pseudomonas and Pantoja and this mental, which is one of the most common bacteria on.
14:21:51 I would also say is we've recently discovered. So that's the real world part. Then the last part is, and the credit there really goes to joy she came up with this really super cool idea.
14:22:04 So, not only barcode, the bacteria which we already do but also tobacco the plants and.
14:22:13 Ideally, we'd like to look at all, 600 by 600 pairs of
14:22:22 of isolates that we have so hundred 50 each for these for these four species.
14:22:29 In fact, the plans was replicates so there's hundreds of thousands of samples image the plans and counter barcodes, and then use this also for genetic mapping because we have them all genome sequence.
14:22:42 And the cool thing is, this is going to be across the three labs and about a year or so it's going to be almost a million separate infections of whole plans, because we barcode and we only have to do 4000 DNA extractions and PCs to get these million data
14:23:00 points, which is really pretty awesome. And then we have complemented this by not looking at all the players but a subset of the most formative pairs, where we looked in different conditions and also do this outside, so it has a nice has access to a few
14:23:14 sites in the US, to see how you know changing a biotic environment or going out in nature, how that changes competition and cooperation between the different bags that we are looking at and so we also were looking at avionic factors we're looking at the
14:23:32 presence of single moaners, and then also looking at the effect of host genetics, how it changes, we are ps4 on this bail from competition, cooperation, and then we're working with Stefan Palestina to model these interactions and allow us to explore and
14:23:50 not just these pairwise interactions, but higher order, communities, put this all together with these other data here, and then asked if we now look at the natural data.
14:24:02 Is there anything that we have learned from the lab.
14:24:06 That allows us to say something about the natural data. So for example, can we explain success of passive biota as a function of possible without richness, or, and we explain us by all the richness as a function of the number of cooperative jeans the
14:24:23 cooperative genes we get from having look, identify them in, in the lab.
14:24:29 So, again, it's this virtuous cycle here. And so, hopefully we'll be able to figure it out at the end of six years, a hierarchy of the different factors such as a biotic first biotic what's the importance of ecology versus genetics taxonomy of pathogens
14:24:46 versus actual functions coded in the genomes.
14:24:50 Well I've produced hopefully this really cool resource that you know many people can can use this.
14:24:56 Hopefully amazing data set to produce these economic landscape of species interactions to allow us to understand evolutionary patterns of cooperation.
14:25:19 work with us into News, New York, and living in. And finally, I would ask this Diana is a real species. So if you work with it in the real world. Sometimes you have to login under the snow but you also get to go to abandon churches and Ireland, or here
14:25:33 I would also say Ghana, on the bank of the Baltic Sea are here, bottom crawling under some practice in South of France, and
14:25:46 And I'll finish by acknowledging the Max Planck society to let me work on all these things, even though I never studied ecology, or microbial biology and this was
14:25:59 shot from a recent.
14:26:01 Farewell, one of the students in the lab, but in from the Institute for the hills off center.
14:26:14 again, thank you all for indulging me, and I really hope to get feedback, and you can be as critical as you wish, though.
14:26:21 That's all I had to say. And,
14:26:27 Whoever has the guts to get up there and tell me, boy, this is really a complete waste what you're doing you should do it completely different. I would love to hear it.
14:26:37 If you think some of the stuff we're doing is on the right track. Please tell me as well.
14:26:43 Anybody who wants to tell him why this is a waste of time.
14:26:47 All right.
14:26:49 Put your gloves on.
14:26:51 My question about the first part to make sure I understood this immune system like thing. The meant to be a bit of the collaborators engine launch is going to give a talk here on Monday.
14:27:00 We think about Bradley neutralizing allegories, and a dramatic a bit of.
14:27:05 I just want to have a question about this. So in that context, you know, you have some virus that's changing and you want to have anybody that can protect the usual strategies do you hope to vaccinate in a way where each person develops and anybody covers
14:27:18 all of the relevant energetic space, but an alternative strategies you could imagine, giving them five different vaccines, two subsets of your population, so that each person gets anybody that covers part of the damage in space.
14:27:33 I should have mentioned sometimes it's that a biophysical reasons why broadly neutralizing anybody's don't evolve, very easily, so it's easier to get anybody that cover a subset of energy and space.
14:27:43 And then you could hope that by tiling and having different subsets of your population cover different parts. You have to collective you could spread.
14:28:00 But what this closely requires is that people near you have the opposite right instinct it needs to be this anti correlation between the spatial distribution of these styles in the, what anybody's Yeah, I guess my question is in the first part when you
14:28:10 said, when you said you like you said, each plant covers one part of energetic space. How is that variation created and is there a way where it can be anti correlated in space.
14:28:20 Yeah so so so so so thank you for asking that question there there are several levels. So, maybe, first one I started at very high level so what I forgot to mention why this is in a way amazing to see that some of these immune genes have been around and
14:28:36 effective for millions of years is so radically different in an agricultural field.
14:28:45 So the same genes these no our genes which, you know, I hope I convince you and our doctors can sell and so on they can be effective for 10 or 20 million years.
14:28:53 When they're deployed in breeding, the last four, maybe five years.
14:28:59 Literally, They good for five years after five years the pastures have figured out how to circumvent then the genes become useless for the farmer, they are broken, you know obviously the gene is not broken but system is broken so agricultural field, five
14:29:15 years field 5 million years. So, which I think is really super remarkable So, coming back to the question at hand.
14:29:24 Is this is typically not in a monoculture, but it's one plant of many, it's not even you know really dominant in in bio mass. So, I exaggerated a little bit because I emphasized the interest specific diversity I think that's also important and, and we
14:29:40 have looked at diversity within the field of our offices Diane and they are diverse, obviously because their self, the seats, tend to fall, near each other.
14:29:55 That is stated that the diversity is clumpy that you know the neighbors are more related to each other, but you have all these other species in between.
14:30:00 and. and that that makes it super interesting to work with. But it also means that it's really one of these promise where it's really unclear whether it can ever be solved.
14:30:03 and.
14:30:11 And so, and Alyssa mentioned before, has written a lovely book about, you know, evolution of plant pathogens interactions.
14:30:18 And when you look at the example such the enumerate.
14:30:22 There's basically, they are no studies that have ever been published that have any power. So, detect this whole evolution, because as soon as you have, you know, certain number of factors in play.
14:30:38 You cannot have enough, if not data to show this. So this makes it so super pesky that you know in a real situation you have so many different species species is composed of genetically different individuals, and then the most plant pathogens so estimates
14:30:55 are about half a dozen species of hosts, that each of them is, is on. And it's really difficult to know when we work with our daughters passage and it might be really important for our daughters, but the passage and might not really care about our process
14:31:08 at all, because they are other plants that are much more important. And it's really, you only see what you're looking for right you're always looking under the lamppost, so it's next to impossible to know who is actually important for for the passage
14:31:21 and so today we had this question, what will be your dream data set my dream data set, would be if I had.
14:31:42 I could drive across the field, and then the sequencing would be done in the back, and would tell me in real time. What is all the genetic diversity along that path that I driven and then I come back next year and drive there again to record this.
14:31:52 what we'll try anyway. To see now so so really what what is it what is the distribution of diversity. So, one of my, you know, the question that I I put down this morning is.
14:32:08 There's all this diversity around us, how much of this diversity is beautiful selection and evolution and how much of the diversity is just extra if you will, is, you know, without any without any function.
14:32:24 So, maybe, on that note, I can ask a follow up question.
14:32:28 You had.
14:32:39 I'm not mistaken, you had the data slide on this day to five you tested the effect on the planet right. I think it was basically the size was there.
14:32:44 phenotypic variability.
14:32:46 Among the so to use sorry members of the OT five.
14:32:55 Yeah, so, so that we didn't, we didn't do no whole plan we only did that in the bionic Si, but we do this again I didn't show those data. We have done actually then also asked in terms of when we see the fitness defects are all the staff members the same
14:33:11 and we found that No, they are not all the same. And not only are they not all the same of this small seven member community, they all they have is also differences how they react the presence of the command centers.
14:33:18 And so that's maybe also in in another interesting story here. So, this super small community seven commensals and seven pathogens. We tested in vitro pairwise interactions.
14:33:30 And we see plenty of pairwise interactions.
14:33:34 Do not correlate with anything that we see in the plant.
14:33:36 So all the negative interactions that we see on played mean nothing inside the plant, which is, you know, pretty demoralizing but that's the observation.
14:33:52 So, sort of, along the same lines.
14:33:55 How did you pick the members of this community in your story which you pitched in the end, and is there any division of labor within this community, what do they do together, so we actually did it so so what we try to pick the most abundant or to us and