Tag Archives: frequency-dependent selection

On the Evolution of Citrate Use

Those who follow the long-term evolution experiment (LTEE) with E. coli know that the most dramatic change we have observed to date is the origin of the new ability to grow on citrate. It’s dramatic for several reasons including the fact (external to the LTEE) that E. coli has been historically defined as a species based in part on its inability to grow on citrate in oxic environments and the fact (internal to the LTEE) that it was so difficult for the bacteria to evolve this ability that only one of the populations did so, and that it took over 30,000 generations even though an abundance of citrate has been present in the medium throughout the LTEE. Even after 64,000 generations, only the Ara–3 population has evolved that new ability.

Zachary Blount, formerly a graduate student and now a postdoc in my lab, has spent the last decade studying the evolution of this population and its new ability. His two first-authored papers in PNAS (2008) and Nature (2012) demonstrated, respectively, that (i) the origin of the ability to grow on citrate in the LTEE was contingent on one or more “potentiating” mutations that happened before the “actualizing” mutation that conferred the new function first appeared, and (ii) the actualizing mutation was a physical rearrangement of the DNA that brought together a structural gene, citT, that encodes a transporter and a previously unconnected regulatory region to generate a new module that caused the phenotypic transition to Cit+. These papers presented and discussed much more than these two points, of course, but they are the key findings. More recently, Zack was a coauthor on a paper in eLife (2015) by Erik Quandt, Jeff Barrick, and others that identified two mutations in the gene for citrate synthase—one that potentiated the evolution of citrate utilization, and another that subsequently refined that new function.

So we were keenly interested when we saw a new paper titled “Rapid evolution of citrate utilization by Escherichia coli by direct selection requires citT and dctA” by Dustin Van Hofwegen, Carolyn Hovde, and Scott Minnich. The paper is posted online as an accepted manuscript by the Journal of Bacteriology. What follows here are some overall impressions of their paper that Zack and I put together. We may follow these impressions later with some further analysis and comments.

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Let’s begin by saying that it’s great to see other groups working on interesting systems and problems like the evolution of citrate utilization in E. coli.

Moreover, the actual science that was done and reported looks fine and interesting, though we have a few quibbles with some details that we will overlook for now. By and large, the work confirms many of the findings that were reported in our papers cited above:

(i) the ability to grow on citrate in the presence of oxygen can and does evolve in E. coli (Blount et al., 2008);

(ii) when aerobic growth on citrate evolves, it does not do so quickly and easily (Blount et al., 2008) but instead takes weeks or longer—more on that below;

(iii) all strains that have evolved this new ability have physical rearrangements that involve the citT gene and appear also to involve a so-called “promoter capture” whereby a copy of this transporter-encoding gene acquires a new upstream regulatory region (Blount et al., 2012); and

(iv) genetic context matters—the strain one uses affects the likelihood of evolving the Cit+ function (Blount et al., 2008) and the resulting ability to grow on citrate (Blount et al., 2012; Quandt et al., 2015).

The problem, then, is not with the experiments and data. Rather, the problem is that the results are wrapped in interpretations that are, in our view, flawed and fallacious.

“No new genetic information”

The authors assert repeatedly (last sentence of their Importance statement, and first and last paragraphs of their Discussion) that “no new genetic information evolved.” However, that statement flatly contradicts the fact that in their experiments, and ours, E. coli gained the new ability to grow on citrate in the presence of oxygen. We would further add (which we have not emphasized before) that these Cit+ strains can grow on citrate as a sole carbon source—when E. coli grows anaerobically on citrate, it requires a second substrate for growth in order to use the citrate (a phenomenon called “co-metabolism”).

The claim that “no new genetic information evolved” is based on the fact that the bacteria gained this new ability by rearranging existing structural and regulatory genetic elements. But that’s like saying a new book—say, Darwin’s Origin of Species when it first appeared in 1859—contains no new information, because the text has the same old letters and words that are found in other books.

In an evolutionary context, a genome encodes not just proteins and patterns of expression, but information about the environments where an organism’s ancestors have lived and how to survive and reproduce in those environments by having useful proteins, expressing them under appropriate conditions (but not others), and so on. So when natural selection—that is, differential survival and reproduction—favors bacteria whose genomes have mutations that enable them to grow on citrate, those mutations most certainly provide new and useful information to the bacteria.

That’s how evolution works—it’s not as though new genes and functions somehow appear out of thin air. As the bacterial geneticist and Nobel laureate François Jacob wrote (Science, 1977): “[N]atural selection does not work as an engineer works. It works like a tinkerer—a tinkerer who does not know exactly what he is going to produce but uses whatever he finds around him, whether it be pieces of string, fragments of wood, or old cardboards; in short, it works like a tinkerer who uses everything at his disposal to produce some kind of workable object.”

To say there’s no new genetic information when a new function has evolved (or even when an existing function has improved) is a red herring that is promulgated by the opponents of evolutionary science. In this regard, it seems relevant to point out that the corresponding author, Scott Minnich, is a fellow of the Discovery Institute and was an expert witness for the losing side that wanted to allow the teaching of “intelligent design” as an alternative to evolution in public schools in the landmark Kitzmiller v. Dover case.

“Rapid evolution of citrate utilization”

In the title of their paper and throughout, Van Hofwegen et al. emphasize that, in their experiments, E. coli evolved the ability to grow aerobically on citrate much faster than the 30,000 generations and ~15 years that it took in the LTEE. That’s true, but it also obscures three points. First, we already demonstrated in replay experiments that, in the right genetic background and by plating on minimal-citrate agar, Cit+ mutants sometimes arose in a matter of weeks (Blount et al. 2008). Second, rapid evolution of citrate utilization—or any evolution of that function—was not a goal of the LTEE. So while it is interesting that Van Hofwegen et al. have identified genetic contexts and ecological conditions that accelerate the emergence of citrate utilization (as did Blount et al., 2008), that in no way undermines the slowness and rarity of the evolution of this function in the context of the LTEE (or, for that matter, the rarity of Cit+ E. coli in nature and in the lab prior to our work). Third, the fastest time that Van Hofwegen et al. saw for the Cit+ function to emerge was 19 days (from their Table 1), and in most cases it took a month or two. While that’s a lot faster than 15 years, it’s still much longer than typical “direct selections” used by microbiologists where a readily accessible mutation might confer, for example, resistance to an antibiotic after a day or two.

So while we commend the authors’ patience, we do not think the fact that their experiments produced Cit+ bacteria faster than did the LTEE is particularly important, especially since that was not a goal of the LTEE (and since we also produced them much faster in replay experiments). However, in a manner that again suggests an ulterior nonscientific motive, they try to undermine the LTEE as an exemplar of evolution. The final sentence of their paper reads: “A more accurate, albeit controversial, interpretation of the LTEE is that E. coli’s capacity to evolve is more limited than currently assumed.” Alas, their conclusion makes no logical sense. If under the right circumstances the evolution of citrate utilization is more rapid than it is in the LTEE, then that means that E. coli’s capacity to evolve is more powerful—not more limited—than assumed.

“Speciation Event”

To us, one of the most interesting facets of the evolution of the citrate-using E. coli in the LTEE is its implications for our understanding of the evolutionary processes by which new species arise. Part of the reason for this interest—and the one that’s most easily stated in a popular context—is that the inability to grow on citrate is part of the historical definition for E. coli as a species, going back almost a century. But the deeper interest to us lies not in labeling a new species or debating where to draw the line between species—various criteria are used by different scientists, and inevitably there are many cases that lie in grey areas. Rather, as evolutionary biologists, we are most interested in the process of speciation—the ecological and genetic dynamics that lead to changing biological forms that, over time, are more and more like a new species until, eventually, perhaps far in the future, there is no doubt that a new species has evolved.

In short, speciation is not an event. As Ptacek and Hankison (2009, in Evolution: The First Four Billion Years) put it, “[S]peciation is a series of processes, with a beginning stage of initial divergence, a middle stage wherein species-specific characteristics are refined by various forces of evolution, and an end point at which a new species becomes a completely separate evolutionary lineage on its own trajectory of evolutionary change with the potential for extinction or further diversification into new lineages.” We realize that scientists (ourselves included) often use shorthand and jargon instead of writing more carefully and precisely. We have no doubt that one can find solid scientific papers that talk about speciation events; but except for cases that involve hybridization leading to polyploids that are reproductively isolated in a single generation (as sometimes occurs in plants), this is simply an imprecise shorthand.

In our first paper on the citrate-using E. coli that arose in the LTEE, we clearly emphasized that becoming Cit+ was only a first step on the road to possible speciation (Blount et al., 2008). One criterion that many biologists would apply to investigate speciation is whether a later form merely replaced an earlier form (evolution without speciation) or, alternatively, one lineage split into two lineages that then coexisted (incipient speciation). In fact, we showed that, after the new function evolved, the Cit+ and Cit lineages coexisted (and their coexistence was confirmed using genomic data in Blount et al., 2012). We concluded the 2008 paper by asking explicitly: “Will the Cit+ and Cit– lineages eventually become distinct species?” (emphasis added) and discussing how we might assess their ongoing divergence.

By contrast, Van Hofwegen et al. dismiss the idea of speciation out of hand, not only by calling it an event but by treating the issue as though it hinges, literally, on the individual mutations that produced a Cit+ cell. For example, they write: “[B]ecause this adaptation did not generate any new genetic information … generation of E. coli Cit+ phenotypes in our estimation do not warrant consideration as a speciation event.” And in the penultimate sentence of their paper, they say: “[W]e argue that this is not speciation any more than any other regulatory mutant of E. coli.” (We also note that this is a rather bizarre generalization, as though the gain of function that gave access to a new resource is equal in regards to its speciation potential to, say, the loss of regulation of a function that is no longer used by a lineage in its current environment. Both might well be adaptations, but one seems much more likely to begin the process of speciation.)

In conclusion, Van Hofwegen, Hovde, and Minnich have done some interesting experiments that shed further light on the nature of the mutations and ecological conditions that allow E. coli cells to evolve the ability to grow aerobically on citrate, a function that this species cannot ordinarily perform. However, they misunderstand and/or misrepresent the relevance of this system for evolutionary biology in several important respects. 

And the meaning of historical contingency

The paper by Hofwegen et al. is accompanied by a commentary by John Roth and Sophie Maisnier-Patin. Their abstract begins: “Van Hofwegen et al. demonstrate that E. coli rapidly evolves ability to use citrate when long selective periods are provided. This contrasts with the extreme delay (15 years of daily transfers) seen in the long-term evolution experiments of Lenski and coworkers. Their idea of ‘historical contingency’ may require reinterpretation.”

Historical contingency is a complicated notion, but it essentially means that history matters. In Blount et al. (2008), we made it clear what we mean by historical contingency in the context of the evolution of the Cit+ lineage in one of the LTEE populations. Was this an extremely rare event that could have happened at any time? Or did it instead depend on the occurrence of a sequence of events, a particular history, whereby an altered genetic context evolved—a potentiated background—in which this new function could now evolve?

Roth and Maisnier-Patin’s suggestion that our idea of “historical contingency” may require reinterpretation reflects a false dichotomy between historical contingency, on the one hand, and the effects of different selection schemes, on the other. The fact that evolution might be fast and not contingent on genetic background (though the evidence of Van Hofwegen et al. is, at best, ambiguous in this regard) in one set of circumstances has no bearing on whether it is contingent in another set of circumstances. The historical contingency of Cit+ evolution is not mere conjecture. We showed that the evolution of this new function in the LTEE was contingent. In replay experiments, Blount et al. (2008) showed that that the Cit+ trait arises more often in later-generation genetic backgrounds than in the ancestor or early-generation backgrounds. Moreover, Blount et al. (2012) performed genetic manipulations and showed that a high-copy-number plasmid carrying the evolved module that confers the Cit+ function had very different phenotypic effects when put in a Cit clone from the lineage within which Cit+ evolved than when placed in the ancestor or even other late-generation lineages not on the line of descent leading to the emergence of the Cit+ bacteria. In the clone on the line of descent, this module conferred strong, immediate, and consistent growth on citrate. In the other genetic backgrounds, growth on citrate was weak, delayed, and/or inconsistent.

The hypothesis of historical contingency is not mutually exclusive with respect to causal factors of an ecological or genetic nature—it simply says that factors that changed over time were important for the eventual emergence of Cit+. Moreover, historical contingency was invoked and demonstrated in a specific context, namely that of the emergence of Cit+ in the LTEE—it does not mean that the emergence of Cit+ is historically contingent in other experimental contexts, nor for that matter that other changes in the LTEE are historically contingent—in fact, some other evolved changes in the LTEE have been highly predictable and not (or at least not obviously) contingent on prior mutations in the populations (e.g., Woods et al., PNAS, 2006). [For more on historical contingency and the LTEE, you can download a preprint of Zack’s latest paper from his website: Blount, Z. D. A Case Study in Evolutionary Contingency. Studies in the History and Philosophy of Biology and Biomedical Sciences.]

Erik Quandt offers this analogy to illustrate our point that contingency depends on context: “It’s kind of like the difference between being an average person attempting to dunk a basketball when all by yourself, with unlimited time, and maybe even with a trampoline versus having to get to the rim in a game with LeBron James and the Cavs playing defense. Just because you can do it by yourself under optimal conditions, does this negate the difficulty of doing it in an NBA game or say anything about the kind of history (training and/or genetics) that you would need for that situation?”

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LTEE lines centered on citrate #11

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Questions from Jeremy Fox about the LTEE, part 1

EDIT (23 June 2015): PLOS Biology has published a condensed version of this blog-conversation.

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Over at the Dynamic Ecology blog, Jeremy Fox asked me some interesting questions about the history, philosophy, and science of the E. coli long-term evolution experiment. Perhaps mistakenly—in terms of time management, not my interest!—I agreed to try to answer them … though over what time frame, I’m not sure. Anyhow, here is Jeremy’s first question followed by my (very) short and (too) long answers.

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  • When you first started the LTEE, did you consider it to be a low risk or high risk experiment? Because I could see arguing both ways. In some ways, it’s low risk, because one can imagine lots of different possible outcomes, all of which would be interesting if they occurred. But in other ways, it’s high risk–I imagine that many of the interesting outcomes (including those that actually occurred!) would’ve seemed unlikely, if indeed they’d even occurred to you at all. Or did you not worry much about the range of possible outcomes because the experiment was basically a lottery ticket? “This’ll be cheap and not much work, let’s just do it and see what happens. Something really cool might happen, but if it turns out boring that’s ok because it wasn’t a big investment.”

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The short answer: Life was good, and I wasn’t thinking about risk. Or as they say about investing: it’s better to be lucky than smart!

The long, non-linear* answer: I’d already had success with some shorter duration, more traditionally designed experiments (e.g., Lenski, 1988), and so it wasn’t a total shot in the dark—that is, I knew the LTEE would yield data. I also knew, though, that it was an unusually abstract, open-ended, and non-traditional experiment, and that it might not appeal to some people for those reasons. But I loved (and still do) the seemingly simple (but in reality complex) questions, issues, and hypotheses that motivated the LTEE.

I never thought of the LTEE project as a “lottery ticket”, but some follow-up work that grew out of it had that feel.** And, oddly enough, there was one lottery-ticket aspect of the research early on, although that reflected a lack of preparation rather than a well-conceived feature.***

Maybe I was overly confident, but I’d also say that I was pretty sure the outcomes—whatever they might be—would be “cool.” The questions were intriguing, and there hadn’t been many, if any, previous attempts to answer them quite so directly. Data would be forthcoming, and even if the results weren’t definitive, I felt there would be some interest in trying to interpret whatever data emerged.**** Plus, I knew enough about what would happen—based on the experiments I had already done—that I was confident that the data and analyses would be informative with respect to at least some of my questions. Also, the use of microbes to study evolution in action was still uncommon, so the novelty of the approach would ensure some interest among my colleagues—although let me emphasize that Lin Chao, Dan Dykhuizen, Barry Hall, and Bruce Levin, among others, had already demonstrated the power of using microbes for experimental studies of evolutionary questions.*****

I should also say, in case it’s not obvious, that I had no idea or intention that the experiment would continue for anywhere near as long as it has lasted—nor that it might, I now hope, be running long after I’m gone. I had previously performed some experiments that lasted several hundred generations, and as I saw the dynamics and thought about the math behind the dynamics, I realized that over those time scales I might be seeing the effects of only one or two beneficial mutations as they swept to fixation. That hardly seemed satisfactory for experiments to explore the structure of the fitness landscape. So I decided the experiment should run for 2,000 generations, over which time I expected there would be at least several fixations of beneficial mutations in each population (and I was right), and that would deserve calling it long-term. That would take a little less than a year, given the 100-fold dilution and 6.6 generations of re-growth each day.

Of course, propagating the lines for 2,000 generations was one thing—running the competitions to measure fitness, analyzing the data, writing the paper, responding to reviews, all that took longer. So while the experiment began in February 1988, the first paper (Lenski et al., 1991) was not submitted until August 1989, resubmitted September 1990, accepted that November, and finally published in December 1991. Meanwhile, the LTEE itself continued and the generations ticked by. The baseline work of keeping the populations going is not that onerous—yes, somebody has to attend to the transfers every day, but once a lab team reaches a moderate size, it’s not too hard to arrange. And I lived next to the campus in Irvine, so it wasn’t hard for me to come in on the weekends and holidays … and my wife still loves me, and my kids recognized my face ;>)

You also wondered whether some of the interesting possible and actual outcomes had occurred to me when I started. Definitely not! I had made a strategic decision to make the environment of the LTEE very simple in order to eliminate, or at least reduce, certain complications (especially frequency-dependent interactions and clonal interference). And while I think my planning kept these complications from getting out of hand, the tension between the simplicity of the experimental design and all the complications has definitely been part of its interest. That tension, along with time, the evolutionary potential of the bacteria, and the smart, talented, creative** and hard-working students and colleagues have made the LTEE what I call “the experiment that keeps on giving.”

Footnotes

*Hey, that’s what footnotes are for, right?

**I’ve thought that way about some follow-on work that uses the LTEE lines, but not about the project as a whole. Here are a couple of examples of “lottery tickets” that people suggested to me, and that won big. A former postdoc Paul Sniegowski, now on the faculty at Penn, wanted to know whether the actual mutation rate itself might be evolving in the LTEE populations. Bingo! Several lines evolved hypermutability and so, curiously enough, the first mutations we ever mapped affected the mutation rate itself (Sniegowski et al., 1997). Another example: Dominique Schneider is a molecular microbiologist in Grenoble, and we’ve collaborated for over 15 years. He thought we should look at whether DNA topology—the physical supercoiling inside the cell—might have changed in the LTEE lines. Well, I thought to myself, why would it change? But Dom’s lab will do all the work, so sure, why not look? And it turns out, sure enough, that DNA supercoiling changed repeatedly in the LTEE lines (Crozat et al., 2005), and it even led us to discover a gene not previously known to affect supercoiling (Crozat et al., 2010). There’s a lesson here, by the way—work with people who are smarter, who have different interests, and who have different skills than oneself.

***I actually started two versions of the LTEE—not one experiment with two proper treatments, but two separate experiments that differed in terms of both the starting strain and the environment. Unlike the successful LTEE, I hadn’t done any previous evolution experiments with the other ancestral strain and environment. Anyhow, I soon stopped the other version when the populations evolved a phenotype that made it very difficult to work with them. In brief, the populations evolved to make pinprick-sized colonies that were next-to-impossible to count in the assays we use to measure fitness. Who needed that headache! So, in a way, I guess I had two lottery tickets: I hadn’t done the relevant prior work for one of them, whereas the one that paid off was actually a pretty strategic gamble.

****I was at UC Irvine when I started the LTEE, and Michael Rose was one of my colleagues there. His work on the evolution of aging—postponed senescence—in fruit flies (e.g., Rose 1984) was an inspiration in terms of the importance and power of long experiments. We also spent a lot of time discussing fitness landscapes, the alternative perspectives of Sewall Wight and R. A. Fisher about the dynamics on those landscapes, and what experiments might tell us. Michael didn’t design, direct, or do the lab work for the first LTEE paper, but he helped me clarify my thinking and write the first paper on the LTEE (Lenski et al., 1991). Perhaps more importantly, his interest in the questions and issues made me realize that other smart people would also be interested.

*****I used to complain, mostly in jest, that “Evolutionary biologists say I’m asking the right questions, but studying the wrong organism, and microbiologists tell me I’m studying the right organism but asking the wrong questions.” I got that sort of response occasionally, but many people from both fields were very interested and encouraging. For example, I remember David Wake telling me, after one of my first talks about the LTEE, how much he liked both the questions and the approach.

References

Lenski, R. E. 1988. Experimental studies of pleiotropy and epistasis in Escherichia coli. II. Compensation for maladaptive pleiotropic effects associated with resistance to virus T4. Evolution 42: 433-440.

Lenski, R. E., M. R. Rose, S. C. Simpson, and S. C. Tadler. 1991. Long-term experimental evolution in Escherichia coli. I. Adaptation and divergence during 2,000 generations. American Naturalist 138:  1315-1341.

Sniegowski, P. D., P. J. Gerrish, and R. E. Lenski. 1997. Evolution of high mutation rates in experimental populations of Escherichia coli. Nature 387: 703-705.

Crozat, E., N. Philippe, R. E. Lenski, J. Geiselmann, and D. Schneider. 2005. Long-term experimental evolution in Escherichia coli. XII. DNA topology as a key target of selection. Genetics 169: 523-532.

Crozat, E., C. Winkworth, J. Gaffé, P. F. Hallin, M. A. Riley, R. E. Lenski, and D. Schneider. 2010. Parallel genetic and phenotypic evolution of DNA superhelicity in experimental populations of Escherichia coli. Molecular Biology and Evolution 27:2113-2128.

Rose, M. R. 1984. Laboratory evolution of postponed senescence in Drosophila melanogaster. Evolution 38: 1004-1010.

 

LTEE flasks repeating

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An Absence of Posts, an Abundance of Talks, and More

Dear Reader:  No, I have not given up on this blog.  But I’ve been busy, busy, busy!

In the last four weeks alone, I have traveled to the University of Arizona, Harvard University, Duquesne University, and Princeton University.  Besides giving talks at each place (two public lectures and two academic seminars, with cumulative audiences of well over a thousand people), I have met with dozens and dozens of amazing scientists, from graduate students and postdocs to faculty both young and old.  It’s been a blast:  an exhausting blast, but a blast all the same!

And next week?  I’m hosting four terrific colleagues from two continents who will work with me to begin making sense of hundreds of newly sequenced genomes from the LTEE.

Oh, and we have some more job searches starting next week.

And did I mention?  We just had a fascinating (if I may so myself) and complex paper come out today in Science (on-line express for now) on the most deeply divergent (i.e., oldest sustained polymorphism) of the 12 LTEE populations.  And no, it’s not about the citrate eaters from population Ara–3.

Plucain, J., T. Hindré, M. Le Gac, O. Tenaillon, S. Cruveiller, C. Médigue, N. Leiby, W. R. Harcombe, C. J. Marx, R. E. Lenski, D. Schneider.  2014.  Epistasis and allele specificity in the emergence of a stable polymorphism in Escherichia coli.  Science.

It’s population Ara–2 instead, where two lineages—dubbed the Larges (L) and Smalls (S)—have coexisted for several tens of thousands of generations.  In superb research led by Dr. Jessica Plucain that she did in the lab of my long-time collaborator (and dear friend!) Prof. Dom Schneider (Grenoble, France), Jessica led the work to identify—out of hundreds of mutations—three that are sufficient to allow a “constructed” S ecotype (i.e., the ancestor plus three derived alleles) to invade and stably coexist with the evolved L ecotype.  Ecological context and specific genetic interactions are key to establishing this “half” of the polymorphism … and the other “half” of the story— what makes the L ecotype special—might well turn out to be just as complex, or perhaps even more so.

The S and L types are especially challenging (even painful!) to work with because this population became a mutator very early on—before the two lineages diverged—and so there are many, many mutations to contend with; moreover, they make colonies on agar plates that are quite challenging to score and count.  So congratulations to Jessica, Dom, and other members of Dom’s lab for their perseverance in studying this extremely interesting population.

Also on the list of authors are Prof. Chris Marx and two members of his lab.  They performed metabolic analyses showing how the carbon fluxes through the central metabolism of the S ecotype have diverged from both the ancestor and the L ecotype.  Chris was a postdoc in my lab almost a decade ago, but most of his work (then and since) has been on experimental evolution using Methylobacterium, and so this is the first paper we’ve co-authored.

There was a production error, though, in the on-line version of our paper; the final sentence of the abstract was dropped (except for one word).  The abstract, in total, should read as follows:

“Ecological opportunities promote population divergence into coexisting lineages. However, the genetic mechanisms that enable new lineages to exploit these opportunities are poorly understood except in cases of single mutations. We examined how two Escherichia coli lineages diverged from their common ancestor at the outset of a long-term coexistence. By sequencing genomes and reconstructing the genetic history of one lineage, we showed that three mutations together were sufficient to produce the frequency-dependent fitness effects that allowed this lineage to invade and stably coexist with the other. These mutations all affected regulatory genes and collectively caused substantial metabolic changes. Moreover, the particular derived alleles were critical for the initial divergence and invasion, indicating that the establishment of this polymorphism depended on specific epistatic interactions.”

[Edited on 07-Mar-2014:  The on-line PDF at Science Express now has the complete abstract.]

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The picture below shows Dom Schneider and Richard Lenski in Paris in 2013.  They are holding a petri dish that Jessica Plucain made to celebrate the 25th birthday of the LTEE.

Dom and Rich, Paris, 2013

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What We’ve Learned about Evolution from the LTEE: Number 4

This is the fourth in a series of posts where I summarize what I see as the most important findings and discoveries from the LTEE.  The previous entries are listed here:

Number 1.  The LTEE offers a simple, compelling demonstration of adaptation by natural selection.

Number 2.  Although the rate of improvement decelerates, it appears that fitness can increase indefinitely even in a constant environment.

Number 3.  The LTEE has produced many striking examples of both parallel and divergent evolution across the replicate populations.

Number 4.  The LTEE provides fascinating cases of the origin and subsequent evolution of both a novel function (citrate utilization) and complex ecologies (cross-feeding interactions).

These examples are particularly interesting—and surprising—because I chose the environment of the LTEE to be as simple as possible, thereby limiting the opportunity for novel functions and complex ecologies to emerge.  However, the evolving bacteria have proven me wrong by discovering new ways of making a living in the simple flask worlds where they live.

Novel function

Complex ecology

This photo shows the increased turbidity (cell density) of the population that evolved the ability to use citrate in the middle, along with two others from the LTEE.  Brian Baer and Neerja Hajela took this picture in my lab in 2008.

LTEE lines centered on citrate #11

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Chao and Levin, 1981, PNAS

This is the third in my series of must-read papers.  It’s an elegant paper that sits right at the interface of ecology, evolution, and behavior.  And like the last paper that I wrote about, this one is superb for teaching and capturing the interest of students.

Chao, L., and Levin, B. R.  1981. Structured habitats and the evolution of anticompetitor toxins in bacteria.  Proc. Natl. Acad. Sci. USA 78, 6324-6328.

Short summary:  Some bacterial strains produce and release toxins that kill members of their own species – except, that is, close kin that possess a linked immunity function.  The production of the toxins is also lethal to the small fraction of cells that actually do so in any given generation.  Lin Chao and Bruce Levin sought to understand when and how this trait would be beneficial.  When killer and sensitive strains competed in liquid, the killer strain prevailed, but only if it started out above a threshold frequency.  That raised the question of how the killer strain could reach that frequency, because it was at a disadvantage when it was below that threshold.  When the same strains competed in a structured environment (a gel-like matrix), this conundrum was resolved—the killer strain could invade a population of sensitive cells even if the killers started at an arbitrarily low frequency.  The difference arises because, in the structured environment, the resources made available by the killers accrue disproportionately to the killers’ kin.  This paper was ahead of its time, but it set the conceptual stage for the now-blossoming field that uses microbes to study the evolution of social traits and interactions.

Some additional background and explanation:  Many bacteria can produce and release toxins that kill other members of the same species.  These toxins are called bacteriocins in general; those studied by Chao and Levin are also called colicins because they are produced by, and used against, E. coli.  The toxin production and immunity functions are tightly linked in a genetic module, and such modules are often located on extra-chromosomal elements called plasmids.  Interestingly, the production of the toxin is lethal to the individual cell that does so, because the cell must lyse to release the toxin.  However, only a small proportion (maybe 1%) of the potential killers that carry the toxin/immunity module actually produce toxin in a given generation, while the others constitutively express the immunity function.

How can a function evolve that is lethal to the individual organism that expresses it?  Chao and Levin began by competing two otherwise identical E. coli strains—one that carries the toxin/immunity module, the other sensitive to the toxin—in a well-mixed liquid medium.  Let’s call the strains K and S for killer and sensitive, respectively.  If there were enough K cells (above ~2% in their experimental conditions), then K rose in frequency and drove the S type extinct.  Although the K population experienced some deaths from the production of the toxin, the resulting toxin concentration was so high that the death rate of S exceeded its growth rate.

But if the initial frequency of the K type was below that ~2% threshold, then the outcome was reversed—the S population rose in frequency, and the K population declined, although the exclusion played out more slowly than when K started out above the threshold.  What’s happening here?  The K cells still had the extra cell deaths caused by the release of toxin, but the concentration of toxin was not sufficient to wipe out the S population.  Some S cells were killed, and their resources—those released upon their death plus those they could no longer consume—became available to other cells.  Because the competition environment was well mixed, any cell—whether K or S—had equal access to the freed-up resources.  If the death rate of the K type (the proportion that produces toxin and then lyses) were greater than the kill rate of the S type, then K would decline in frequency because the resulting benefit—the extra resource that became available—was equally available to all survivors, regardless of whether they had the K or S genotype.

From an ecological standpoint, it’s a nice example of a dynamically unstable equilibrium between two competitors.  However, it raises a problem from an evolutionary perspective.  If possession of the toxin/immunity module is beneficial when it is common in a population, but disadvantageous when it is rare, then how can it go from being rare to common?

Chao and Levin recognized that a physically structured environment might be important, because it would change the distribution of the freed-up resources to the two cell types.  So they repeated the competitions between K and S strains, again varying the initial frequency of the K type, except now in a semi-solid medium called “soft agar.”   (The procedures get more complicated here; to propagate the competing cell types, each day they had to free the cells from the soft-agar matrix and transfer them into a new matrix.)  When the two types competed in this structured environment, the unstable equilibrium disappeared, and the K strain could invade and take over from an arbitrarily low initial frequency.  That is, the K genotype could now go from being rare to common.

Why this difference between the liquid and semi-solid environments?  In the structured environment, the bacteria grew as colonies, not as individuals floating about at random.  As a consequence, the extra resources made available by the killers flowed disproportionately to their own kin.  Here a picture is worth a thousand words; I show a figure from Chao and Levin below that makes this point graphically.  In a sea of crowded S colonies, there’s one K colony.  The K colony is larger than most of the S colonies.  Each colony began from a single cell; the fact that the K colony is larger than most means that it got more than its share of resources.  Even more strikingly, the K colony is surrounded by a large zone that is entirely devoid of colonies—the toxins released by the small proportion of K cells that lysed have diffused into this zone and prevented growth of S cells.  The resources diffused randomly, but the K colony sat alone in the middle of this zone of inhibition that it generated, and so indeed it got more than its share of resources.

Chao and Levin Fig 3

The figure above is from Chao and Levin, 1981, Proc. Natl. Acad. Sci. USA; it is shown here under the doctrine of fair use.  The image is centered on a single colony of toxin-producing bacteria surrounded by an inhibition zone and, further out, by colonies of sensitive bacteria.  The scale bar is 0.5 mm.

A Later, Related Paper:  There’s another nice paper by Ben Kerr, Peg Riley, Marc Feldman and Brendan Bohannan (2002, Nature) that builds on the work by Chao and Levin.  Kerr et al. added a third “player”—a third strain—into these experiments, one that was resistant to the toxin but did not produce it.  In a physically structured environment, the toxin-producing killer strain could invade and displace the sensitive strain, just as Levin and Chao saw.  However, the resistant strain could invade and displace the toxin-producer, because the physiological cost of resistance was less than the combined costs of toxin-production and immunity.  And the sensitive strain could invade and displace the resistant strain, because the sensitive strain did not pay the cost of resistance.  In other words, the pairwise interactions were non-transitive, just like the game of rock-paper-scissors.  But although each pairwise interaction had a winner and a loser, the three types could coexist indefinitely in a spatially structured environment provided different spatial regions were out of phase—in effect, the three populations chased one another around in space and time.

Why I like this paper so much:  First, the paper by Chao and Levin beautifully illustrates how population biologists frame, dissect and analyze a complex problem—one that involves frequency-dependent effects, tradeoffs, spatial structure, and genetic relatedness along with both scramble and interference competition.  Out of all these complications, there comes that “Aha!” moment when it all makes sense—just like the feeling one gets from the Luria and Delbrück experiment.

Second, there’s been a boom in the study of the evolution of social behaviors using microbes over the last 15 years or so.  The current phase began with papers by Paul Tuner and Lin Chao on interactions among viruses infecting the same cell leading to a Prisoner’s Dilemma (Nature, 1999); by Greg Velicer, Lee Kroos, and myself on cheating during multicellular fruiting-body development in the bacterium Myxococcus xanthus (Nature, 2000); and by Joan Strassmann, Yong Zhu, and David Queller on cooperation and cheating in aggregations of the social amoeba Dictyostelium discoideum (Nature, 2000).  Today, there are many groups around the world who study quorum sensing, fruiting-body formation, biofilms, toxin degradation, and other microbial behaviors from an evolutionary perspective.  The 1981 paper by Chao and Levin showed that microbial systems could serve as model systems for studying social evolution while being fascinating in their own right.  (It’s also fitting to note that John Bonner, who pioneered the study of D. discoideum, served as the editor for Chao and Levin’s paper.)

Third, Bruce Levin was my postdoctoral mentor, and Lin Chao did his graduate work with Bruce.  Lin had moved on to a postdoc position before I joined the lab, but this paper was one of my formative exposures to the conceptual elegance and experimental power of using microbes to study population dynamics.  Lin and Bruce had also written two papers on the dynamics of interactions between bacteria and phage (Levin et al., 1977, Am. Nat.; Chao et al., 1977, Ecology), and those papers were the ones that first led me to write Bruce about the possibility of joining his group as a postdoc.

Finally, this paper provides a sobering reminder that we humans are not as special as we often imagine, even in warfare.  Mindless bacteria were killing each other billions of years before we came on the scene.  Perhaps we can use our minds to suppress the worst of our primal urges.

[ADDED 13 Sept. 2013] Lin Chao emailed me that “The inspiration of that work was a lecture that Bruce gave in his Pop Biology class at UMass where he discussed the limitations of Lotka Volterra equations for interference competition.  That sat in my mind for a couple of years until it became a real project.” So this must-read paper also provides a nice example of the productive interplay between teaching and research.

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