Fifty thousand generations, still improving

I take all my hats off to Richard Lenski and his team. If you’ve never heard of them, they are the group that has been running an evolution experiment with E. coli bacteria non-stop for the last 25 years. That’s over 50 000 generations of the little creatures; in human generations, that translates to ~1.5 million years. This experiment has to be one of the most amazing things that ever happened in evolutionary biology.

(Below: photograph of flasks containing the twelve experimental populations on 25 June 2008. The flask labelled A-3 is cloudier than the others: this is a very special population. Photo by Brian Baer and Neerja Hajela, via Wikimedia Commons.)

It doesn’t necessarily take many generations to see some mind-blowing things in evolution. An irreducibly complex new protein interaction (Meyer et al., 2012), the beginnings of new species and a simple form of multicellularity (Boraas et al., 1998) are only a few examples. However, a few generations only show tiny snapshots of the evolutionary process. Letting a population evolve for thousands of generations allows you to directly witness processes that you’d normally have to glean from the fossil record or from studies of their end products.

Fifty thousand generations, for example, can tell you that they aren’t nearly enough time to reach the limit of adaptation. The newest fruit of the Long-Term Evolution Experiment is a short paper examining the improvement in fitness the bacteria experienced over its 25 years (Wiser et al., 2013). “Fitness” is measured here as growth rate relative to the ancestral strain; the faster the bacteria are able to grow in the environment of the LTEE (which has a limited amount of glucose, E. coli‘s favourite food), the fitter they are. The LTEE follows twelve populations, all from the same ancestor, evolving in parallel, so it can also determine whether something that happens to one population is a chance occurrence or a general feature of evolution.

You can draw up a plot of fitness over time for one or more populations, and then fit mathematical models to this plot. Earlier in the experiment, the group found that a simple model in which adaptation slows down over time and eventually grinds to a halt fits the data well. However, that isn’t the only promising model. Another one predicts that adaptation only slows, never stops. Now, the experiment has been running long enough to distinguish between the two, and the second one wins hands down. Thus far, even though they’ve had plenty of time to adapt to their unchanging environment, the Lenski group’s E. coli just keep getting better at living there.

Although the simple mathematical function that describes the behaviour of these populations doesn’t really explain what’s happening behind the scenes, the team was also able to reproduce the same behaviour by building a model from known evolutionary phenomena. For example, they incorporated the idea that two bacteria with two different beneficial mutations in the same bottle are going to compete and slow down overall adaptation. (This is a problem of asexual organisms. If the creatures were, say, animals, they might have sex and spread both mutations at the same time.) So the original model doesn’t just describe the data well, it also follows from sensible theory. So did the observation that the populations which evolved higher mutation rates adapted faster.

Now, one of the first things you learn about interpreting models is that extrapolating beyond your data is dangerous. Trends can’t go on forever. In this case, you’d eventually end up with bacteria that reproduced infinitely fast, which is clearly ridiculous. However, Wiser et al. suggest that the point were their trend gets ridiculous is very, very far in the future. “The 50,000 generations studied here occurred in one scientist’s laboratory in ~21 years,” they remind us, then continue: “Now imagine that the experiment continues for 50,000 generations of scientists, each overseeing 50,000 bacterial generations, for 2.5 billion generations total.”

If the current trend continues unchanged, they estimate that the bugs at that faraway time point will be able to divide roughly every 23 minutes, compared to 55 minutes for the ancestral strain. That is still a totally realistic growth rate for a happy bacterium!

I know none of us will live to see it, but I really want to know what would happen to these little guys in 2.5 billion generations…

***

References:

Boraas ME et al. (1998) Phagotrophy by a flagellate selects for colonial prey: a possible origin of multicellularity. Evolutionary Ecology 12:153-164

Meyer JR et al. (2012) Repeatability and contingency in the evolution of a key innovation in phage lambda. Science 335:428-432

Wiser MJ et al. (2013) Long-term dynamics of adaptation in asexual populations. Science, published online 14/11/2013, doi: 10.1126/science.1243357

Slime moulds don’t play by the rules

I’m starting to think dictyostelids are seriously interesting. These are the guys whose eerily animal-like epithelial tissues prompted the idea of multicellularity being ancestral to the lineage containing animals, choanoflagellates, fungi and amoebae. (Incidentally, Parfrey and Lahr [2013] wrote a nice critical response to that hypothesis – it deserves a post of its own, but not this post.) They are used as model organisms in (evolutionary) developmental biology (Schaap, 2011), a field which is mostly dominated by animals and plants for obvious reasons.

Recently I wrote about the developmental hourglass pattern, which means that the most conserved developmental stages are not the earliest (as Karl von Baer thought at the dawn of comparative embryology), but some way into development. This pattern has been found in several animal phyla both at the morphological level and in various features of developmental gene expression, and it was recently also discovered in plants, which prompted my first post about it.

A group of researchers reckoned they should check how universal the hourglass is, and they thought the slime mould/social amoeba and honoured developmental model organism Dictyostelium is a good place to look (Tian et al., 2013). Unlike plants and animals, which develop from a single cell, the multicellular life stage of dictyostelids is a gathering of thousands of previously independent cells that may not be genetically identical. Therefore, these tiny creatures represent a very different approach to development from our favourite lab animals. Whether or not they still show an hourglass pattern could give clues about the deeper laws that govern all developmental processes.

Dictyostelids turn out to be complete deviants in this respect. Comparisons of the genes two species of Dictyostelium use in their multicellular development show neither von Baer’s “funnel” pattern of similarity nor an hourglass. If you include single-celled stages that aren’t, strictly speaking, “developmental”, similarities of gene expression give a “reverse hourglass” with lowest similarity in the middle. If you only consider the actual multicellular developmental stages, conservation increases towards the end – an “inverted funnel”. Other measures gave Tian et al. largely consistent results – genes expressed later in development were more likely to also be present in the other species, and their sequences were more similar on average.

Now that we have a pattern – what could explain it? The authors speculate that an idea that had been used to explain the hourglass in animals may apply just as well to the inverted funnel of slime moulds. This idea is that the evolvability of a developmental stage depends on the interactions that occur during it. The more interactions between genes/cells/tissues, the worse the effect of a tiny screw-up and the smaller the chance of a beneficial change, hence the most interconnected developmental stages will tend to be most conserved in evolution.

In animals, goes the reasoning, early development is relatively simple, and later development is relatively modular. Early on, there’s less to screw up, whereas later, every screw-up is limited to part of the embryo. In between is the sweet spot where everything talks to everything and a small modification can have large knock-on effects. The result is the hourglass. In slime moulds, however, that later stage when the developing organism is subdivided into semi-independent modules never comes. All tissues keep communicating and affecting each other right up to the point where the multicellular body is fully developed. Thus, if you like, only the first half of the hourglass happens in these creatures.

It’s an interesting idea. I like it.

***

References:

Parfrey LW & Lahr DJG (2013) Multicellularity arose several times in the evolution of eukaryotes. BioEssays advance online publication, 11/01/2013, doi: 10.1002/bies.201200143

Schaap P (2011) Evolutionary crossroads in developmental biology: Dictyostelium discoideum. Development 138:387-396

Tian X et al. (2013) Dictyostelium development shows a novel pattern of evolutionary conservation. Molecular Biology and Evolution advance online publication 16/01/2013, doi: 10.1093/molbev/mst007