The LTEE is Ending Today

April Fools!

Onward to 2,500,000,000 generations

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Favorite Examples of Evolution

When the cold bites, When the review stings, When the news is sad, I simply remember these evolving things, And then I don’t feel so bad! — with apologies to Rodgers and Hammerstein

Over on Twitter, the biology students from George Jenkins High School in Lakeland, Florida, asked me and many others: “What’s your favorite example of evolution?”  There are so many fascinating examples that it’s hard for me to pick just one. So, here are half a dozen examples that are among my favorites.

  • The discovery by Neil Shubin and colleagues of Tiktaalik, an extinct fish (pictured below) from the Devonian that was poised to give rise to terrestrial vertebrates. You can read about this work in Shubin’s award-winning book, Your Inner Fish, which was also made into a PBS show.
  • The discovery by Svante Pääbo and colleagues of the Denisovans, an extinct lineage of humans, based on sequencing a complete genome from the finger bone of a girl who lived tens of thousands of years ago.
  • The analysis by Tami Lieberman, Roy Kishony, and colleagues of the genetic adaptation of an opportunistic species of bacteria to the lungs of patients with cystic fibrosis. I’ve blogged about that paper here.
  • Here’s one from the long-term experiment in my own lab — the evolution of the ability to use citrate that arose in just one of the 12 populations and after more than 30,000 generations. There are nice summaries of this work in Carl Zimmer’s blog here and here.
  • A study by Hod Lipson and Jordan Pollack on the evolution of robots. I remember hearing about this paper and being shocked: “Wait a second. Robots are expensive, and most things go extinct during evolution. How could they even afford do this?” I had to read the paper to realize they were evolving virtual robots in a physical simulation of the real world. They then built and tested the winners in the physical world. And indeed, the robots worked as they had evolved to do.
  • Applying the mechanisms of evolution to artificial systems is a fascinating approach useful for both biology and engineering. One of my favorite basic-science uses of this approach was a paper where we used digital organisms – computer programs that self-replicate, mutate, and compete for resources – to show how very complex functions could evolve if simpler functions were favored along the way. These simpler functions provided building blocks for the more complex functions, illustrating how evolution works by tinkering and borrowing already existing structures and functions and using them in new ways. Incidentally, this work involved collaboration between a computer scientist (Charles Ofria), a philosopher (Rob Pennock), a physicist (Chris Adami), and a biologist (me).

Readers: Please feel free to add your own favorite examples of evolution in the comments section below.

[The picture below shows the Tiktaalik fossil discovered by Neil Shubin and colleagues.  It was posted on Wikipedia by Eduard Solà, and it is shown here under the indicated Creative Commons license.] Tiktaalik

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One of the Challenges—and Privileges—of Working at a Major Research University

Today is going to be difficult, but it should be interesting. There are not one, not two, but three seminars that I really want to—and will (or meant to*)—attend. They are scattered all across campus, with none in my building. I’ll also meet with one of the speakers–though I’d have liked to meet with all three if only I had unlimited time. The seminars are by:

  • Lee Spector, speaking on “The Future of Genetic Programming” for the College of Engineering;
  • Eugene Koonin, speaking on “Viruses and Transposons as Drivers of the Evolution of Life” for the Department of Biochemistry and Molecular Biology; and
  • J. J. Emerson, speaking on “Evolution and Novelty: Exploring Adaptation from the Perspectives of Experimental Evolution and Population Genomics” for the Ecology, Evolutionary Biology and Behavior Program.

So I won’t get much of my own work done today. That’s one of the challenges—and one of the privileges!—of being at a top university like MSU, which attracts visiting speakers in so many areas that interest me.

*End-of-day edit: Did I mention that having so many seminars to attend was a challenge? Ah yes, it’s in the title and at the end. Well, as it so happens, I screwed up reading my schedule today and so only made it to two of the three talks.

[This photo shows the Beaumont Tower on the MSU campus.  It was taken in May 2006 by Jeffness; it is from Wikipedia and shown here under the indicated Creative Commons license.] Beaumont Tower

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Funding the LTEE—past, present, and future: Questions from Jeremy Fox about the LTEE, part 4

This is the 4th installment in my responses to Jeremy Fox’s questions about the long-term evolution experiment (LTEE) with E. coli. This response addresses his 5th and 6th questions, which are copied below.

 ~~~~~

  • How have you maintained funding for the LTEE over the years, and how hard has it been? The difficulty of sustaining funding for long term work is a common complaint in ecology, and I’m guessing in evolution as well. And of course, if people think that they won’t be able to sustain funding for a long-term project, they’re less likely to start one in the first place. At best, they’ll try to do it by piggybacking short-term studies (or short-term rationales) on the long-term work, so that the long-term work can be sustained via a series of short-term grants. When you first proposed the LTEE to NSF or whoever, presumably you didn’t say “I propose to set up 12 replicate lines of bacteria, keep them going for decades, and see what happens”. And when you went back for your first (or second, or third…) renewal, presumably you still didn’t say “a bunch of cool stuff has happened already, so please give me more money to keep it going, just to see if anything else cool happens.”
  • Related to the previous question: Has it become easier to get funding to keep it going as you’ve gone along? Has it gotten to the point where the experiment (and you?) is widely seen as an “institution”? So that rather than needing to justify it anew every few years, people are basically eager to hand you money to keep it going, no questions asked?

 ~~~~~

Past.  All in all, I’ve been very fortunate with funding for my research. My first attempt to get the LTEE funded was rejected, but around that time I received a Presidential Young Investigator Award from the National Science Foundation (NSF) that gave me considerable freedom to pursue the research directions that most interested me. Various grants have supported the LTEE since then including, for the past 10 years, an NSF LTREB grant (LTREB stands for long-term research in environmental biology).  LTREB grants are very small, but mine provides core support to keep the lines going.  Other funds are required to do anything more than some basic quality control and assays. My professorship at MSU—named after John Hannah, who was president of MSU for 28 years, about the duration of the LTEE!—has provided discretionary funds that have been invaluable, allowing us to explore new scientific directions and techniques as they become interesting and available, without requiring us to first secure funding. And the graduate students and postdocs in my group have been very talented, and they’ve often been awarded fellowships that fund the essential brain-power and hard work that has made the LTEE so successful.

Present.  I take proposal writing very seriously, always emphasizing both the overarching questions that have been with the LTEE since it began and the specific aims that arise from new discoveries and technical advances. One always has to make the case for why a particular project, individual, or team merits support. So I wouldn’t say it has gotten easier to get funding, especially given the decline in funding rates. But I do sense that reviewers have, on balance, become increasingly excited by the LTEE project over the years, as it has borne a lot of fruit. In fact, the NSF program officer has told me that the LTREB grant will be funded again for the next 5 years. During the pre-proposal phase (yes, a pre-proposal was required for a project that has run for over a quarter century!), the panel summary called the LTEE “this community’s Hubble Telescope.” Now that was certainly gratifying!

Future.  The big challenge going forward will be to secure funds that will allow the LTEE to continue after I’m gone. Many colleagues have told me that the LTEE must continue, and I agree. (I’m not planning on retiring anytime soon, but I think it’s wise to hand off a project sooner rather than wait to the last hour.) I like to call the LTEE the experiment that keeps on giving, so the challenge is to find a way to make that happen.

I realize that not every scientist will have the same good fortune that I’ve had. Indeed, by continuing “someone else’s experiment” a young scientist might even be viewed by some as unoriginal and thus unworthy of the privileges of tenure and funding. To overcome that stigma, I’d like to secure funds to ensure that, not only can the LTEE continue, but that its continuation is rewarding rather than burdensome to future scientists. After all, it comes with its own inherent challenges—including the fact that the populations are tended every day as well as management of the ever-growing collection of frozen samples.

My thinking is that each successive scientist responsible for the LTEE would, ideally, be young enough that he or she could direct the project for 25 years or so, but senior enough to have been promoted and tenured based on his or her independent achievements in a relevant field (evolutionary biology, genomics, microbiology, etc.). Thus, the LTEE would likely continue in parallel with that person’s other research, rather than requiring his or her full effort, just like my team has conducted other research in addition to the LTEE. The goal, then, is provide the future project leaders with the benefits of continuing the LTEE while relieving them of the most onerous burdens.

So as I’ve said before, “If you know anyone who would like to endow a million-year experiment, have them get in touch with me.”

[This picture shows the Hubble Space Telescope. It was taken on a servicing mission in 1997, and it comes from the NASA website.]

Hubble Telescope

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Happy 27th birthday to the LTEE!

The title says it all:  today is the 27th birthday of the long-term evolution experiment (LTEE) with E. coli.

Well, the title doesn’t really say everything. I also want to give thanks to the many people—not to mention the trillions of bacteria—who have made it possible for the LTEE to keep on going and giving.

So thank you to all of the students, postdocs, and colleagues with whom I’ve collaborated on this project. There are too many to list here, but you will find their names on the papers that have come from the LTEE. I’ll call out just two, on this occasion, for special thanks. Dom Schneider has been an amazingly talented and generous collaborator for so many years—in fact, our first co-authored paper on the LTEE dates back to 1999. And Neerja Hajela has worked with me for 20 years now, and she is the most organized, dedicated, and all-around wonderful technician and lab manager that one could ever have.

Special thanks, too, to Madeleine Lenski, who has tolerated my long-term affair with the LTEE, and who wisely advised me to keep it going on one or two occasions when I was looking in other directions.

[The image below shows the abstract from the first paper on the LTEE, which appeared in The American Naturalist in 1991. It is reproduced here under the doctrine of fair use.  Some of the conclusions have changed a bit as the LTEE has had more time and we’ve gathered more data—that’s science!]

Abstract 1991 LTEE

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The LTEE as meta-experiment: Questions from Jeremy Fox about the LTEE, part 3

This is the 3rd installment in my responses to Jeremy Fox’s questions about the LTEE (my lab’s long-term evolution experiment with E. coli), which he asked at the Dynamic Ecology blog. This response addresses his 2nd and 7th questions, which I’ve copied below. I like all of Jeremy’s questions, but I especially like his 2nd one because it forced me—and many readers, I hope—to think carefully about what experiments are and why we do them.

~~~~~

  • Is the LTEE actually an experiment, and wouldn’t it have been even better if it was? It’s just one “treatment”–12 replicates of a single set of conditions. Wouldn’t it have been even more interesting to have, say, two treatments? Two different culture conditions, two different founding genotypes, two different founding species…?
  • Is the LTEE itself now a “model system”? Model systems in biology–systems in which it’s tractable to ask a given question–often are systems that we know a lot about. We can leverage that background knowledge to ask questions that otherwise wouldn’t be tractable. coli of course is a model organism for many purposes, because we know so much about it. But is the LTEE itself now a model system?

 ~~~~~

You’re certainly right, Jeremy, that experiments in the fields of ecology and evolutionary biology typically have two or more treatments. But it’s not an essential part of the definition of an experiment that it has that sort of structure. It would have been nice, perhaps, if the LTEE did have two or more environments and/or two or more ancestors, as you suggest—in fact, we’ve run several of those types of experiments over the years in my lab, and I’ll mention a few of them below.

The reason I didn’t do that with the LTEE, though, was because one of my core motivating questions (see part 2 of my response) concerned the repeatability of evolutionary dynamics across replicate populations. That’s a question about the trajectory of variances over time, which is challenging statistically because estimates of variances have large uncertainties. So if the LTEE had two treatments, I might have been able to say something meaningful about the differences between them, but I would have had less power to say anything about the among-replicate variances for either treatment. In other words, with respect to that motivating question, going from 12 replicate populations down to 6 replicates would have been risky.

It certainly would be nice to have more total populations, say, 24 or even more; and nowadays many labs use 96-well plates for evolution experiments, with each well a replicate population and liquid-handling robots to automate the transfers. When I started the LTEE, though, we worked with flasks (albeit small ones); 12 may not seem like too many, but when we run the competition assays to measure fitness, we then have replicate assays for each population and we analyze multiple generations simultaneously, so the students and postdocs running these assays are handling many dozens or even hundreds of flasks.

The LTEE as a meta-experiment

Stepping back a bit, I’d like to suggest that the LTEE is a sort of meta-experiment, to coin a term. (This idea echoes the question where you suggested that the LTEE has itself become a model system.) By “meta” I mean the LTEE transcends—goes above and beyond—what one usually considers an experiment because the LTEE enables experimentation at several levels.

Level 1: The LTEE as an experiment

First, it is an experiment in the sense that it set out to measure, under defined conditions and with replication, certain specific quantities, such as fitness trajectories. It may not be typical in having a single treatment, but the temporal dimension coupled with being able to analyze multiple time points simultaneously—that is, the “time travel” enabled by the frozen samples across the generations, including the use of the ancestral strain as an internal control in fitness assays—functions in much the same way from an analysis standpoint.

Level 2: The LTEE as a generator of new questions and experiments to answer them

Second, the LTEE has generated a number of new questions and hypotheses that are themselves amenable to structurally independent follow-on experiments. Let me give two examples. We observed fairly early on that several populations had evolved changes in their DNA metabolism and repair that caused their mutation rates to increase by roughly 100-fold (Sniegowski et al. 1997). Such “mutator” mutations can arise by hitchhiking, albeit only occasionally and stochastically, with beneficial mutations that they cause (Lenski 2004, see pp. 246-251). It wasn’t clear, though, whether they would necessarily increase the rate of fitness improvement, given the large populations and correspondingly large potential supply of beneficial mutations in the LTEE. So we designed a separate, shorter-duration experiment with some 48 populations where we varied the mutation rate, population size, and initial fitness of the founding ancestor, and assessed the resulting fitness gains over 1,000 generations (de Visser et al. 1999).

Another case is the “replay” experiments that Zachary Blount ran after one lineage evolved the ability to grow on citrate in the presence of oxygen, which E. coli generally cannot do (Blount et al. 2008). Zack ran thousands of populations that started from genotypes isolated at different times from the population that eventually evolved this new function, in order to test whether it could have arisen at any time by an appropriate mutation or, alternatively, whether it required first evolving a “potentiated” genetic background, or context, in which the “actualizing” mutation would then confer the citrate-using phenotype.

In both of these examples, the subsequent experiments, though separate and distinct from the LTEE, nonetheless emerged from the LTEE. That is, the questions and hypotheses tested in these later experiments were motivated by observations we had made in the LTEE itself.

Level 3: The LTEE-derived strains as useful ancestors for a variety of experiments meant to address existing questions

The third level of the meta-experiment involves questions that arise outside of the LTEE, but for which the LTEE generates a set of materials—specifically, strains—that are especially useful for experiments to address those questions. Again, I’ll give a couple of examples.

Many ecologists, physiologists, and others are interested in studying adaptation to specific environmental factors—such as resource availability, temperature, etc.—as well as examining possible tradeoffs associated with adaptation to those factors. One difficulty, though, is that by moving organisms from nature into the lab and allowing them to evolve under, say, different temperature regimes, adaptation to the shared features of the lab environments may well outweigh adaptation to the specific variable of interest. If so, that would interfere with one’s ability to identify the mutations and adaptations most relevant to the factor of interest, and it could also obscure tradeoffs that might be important if populations were already well adapted to the other aspects of the environment. With these considerations in mind, Albert Bennett and I took a strain from the LTEE that had evolved in and adapted to those conditions—the resources, pH, absence of predators, etc.—and we used it as the ancestor for a new evolution experiment where 6 replicate populations evolved under each of 4 different thermal regimes: 32C, 37C (the same as in the LTEE), 42C, and daily alternations between 32C and 42C (Bennett et al. 1992, Bennett and Lenski 1993). In that way, we could focus attention on temperature-specific adaptations, which were Al’s main interest, rather than having such changes overwhelmed by adaptation to the lab environment.

My second example where LTEE-derived strains were ancestors for an experiment meant to address an extrinsic question is one of an abstract nature. In this study, we quantitatively partitioned the effects of adaptation, history, and chance on phenotypic evolution by founding 3 replicate populations from 12 different ancestors—each one a genotype sampled from a different one of the LTEE populations—and we then let these 36 populations evolve in a new environment, where we changed the identity of the limiting nutrient (Travisano et al. 1995). By measuring the fitness of the 12 ancestors and 36 derived lines in the changed environment, we were able to disentangle and quantify the relative contributions of adaptation, history, and chance to the observed outcomes (see figure below). That is, adaptation measured the mean tendency for fitness to increase, history reflected the effect of the different starting genotypes on the fitness achieved, and chance the variation in the resulting fitness among the replicates that started from the same ancestor.

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.

Lenski, R. E. 2004. Phenotypic and genomic evolution during a 20,000-generation experiment with the bacterium Escherichia coli. Plant Breeding Reviews 24:225-265.

De Visser, J. A. G. M., C. W. Zeyl, P. J. Gerrish, J. L. Blanchard, and R. E. Lenski. 1999. Diminishing returns from mutation supply rate in asexual populations. Science 283:404-406.

Blount, Z. D., C. Z. Borland, and R. E. Lenski. 2008. Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli. Proc. Natl. Acad. Sci. USA 105:7899-7906.

Bennett, A. F., R. E. Lenski, and J. E. Mittler. 1992. Evolutionary adaptation to temperature. I. Fitness responses of Escherichia coli to changes in its thermal environment. Evolution 46:16-30.

Bennett, A. F., and R. E. Lenski. 1993. Evolutionary adaptation to temperature. II. Thermal niches of experimental lines of Escherichia coli. Evolution 47:1-12.

Travisano, M., J. A. Mongold, A. F. Bennett, and R. E. Lenski. 1995. Experimental tests of the roles of adaptation, chance, and history in evolution. Science 267:87-90.

[The figure below appeared in Science (Travisano et al. 1995), and it is reproduced here under the doctrine of fair use.]

Adaptation, chance, history image

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Science Communication: Where Does the Problem Lie?

When concerns arise about the public’s understanding of science—say, on the efficacy of vaccines vs. their risks—I see many articles, tweets, etc., bemoaning poor scientific communication. Communication involves multiple parties and several steps. The science must be published, discussed widely, explained openly, and eventually stated in terms that non-specialists can understand. It also must be heard—and not merely heard, but fairly considered, carefully weighed, and then accepted, rejected, or put on hold by the intended receiver. That’s not all, of course. There are generally intermediaries—including teachers, reporters, doctors, business interests, politicians, religious leaders, and others—who must also convey the scientific information, but who may block, change, confuse, or distort the message either accidently or deliberately. And none of this is a one-way flow of information. There are multiple voices, and there are feedbacks as questions are asked, answered in new words or with new evidence, and so on. So it’s a complex problem, too complicated for a poll to shed much light. And of course, a poll here will get a highly non-random sample—mostly scientists, students, and others with an interest in science. But perhaps some professional pollster or organization interested in the communication of science can develop a proper poll along these lines (with information about a respondents’ professions, ages, affiliations, etc.), and with proposals about how to improve the situation at the various roadblocks. (Or maybe similar polls already exist. Please feel free to suggest useful references in the comments.) It might also be interesting to run the same poll except with prompts about different issues such as vaccinations, global change, and evolution. So here’s the poll: If you had to say, which one of the following groups shoulders the greatest blame, and thus has the greatest room for improvement, when it comes to the problems of communicating science?

  • Scientists
  • Professional intermediaries such as teachers, reporters, and doctors
  • Other intermediaries such as businesses, politicians, and religious leaders
  • The public

[The image below is from the British Council / BBC World Service site on teaching English. It is shown here under the doctrine of fair use.] Communication

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