This approach to studying evolution takes advantage of the establishment of replicate microcosms maintained under defined environmental conditions that select for strains with increased fitness. Given the rapidity of microbial growth, these microcosms can be maintained for thousands of generations. Because microbes can be cryopreserved, entire communities can be saved as a living “fossil record”. These can be resuscitated later to investigate a posteriori key parameters such as fitness or diversity through time and across replicates. In the past two decades, experimental evolution using microbial systems has led to tremendous insight regarding numerous topics such as the rate and tempo of evolution, the repeatability of evolution, factors influencing ecological diversification, and the effect of productivity and disturbance on diversity, etc. (For an excellent review, see Lenski & Elena, 2003.) In short, experimental evolution of microbial populations allows “big questions” to be addressed in an experimentally tractable system amenable to hypothesis testing.
Let’s address a seemingly very different question. Biological systems are composed of modules of interacting components that perform various particular functions, each module being knitted together into larger and larger networks. (For a fantastic perspective on modularity, see Hartwell et al., 1999.) Given this ‘everything-is-connected’/6-degrees-of-Kevin-Bacon view, how can the output of biological systems be improved through modifications to individual components – either by researchers or by natural selection? Metabolic engineering has labored to generate super-bugs out of bacterial strains, but only rarely have the end results been as glorious as imagined. Why not? What are the limiting factors in a system in order to achieve increased performance in an industrial or evolutionary setting? The usual approaches to understanding intact biological systems fall into two categories: compare an organism’s response to a perturbation of its environment, or perturb the genome (often with knockout mutations) and compare mutant to wild-type. Obviously, much has been learned using these two broad approaches, but neither address how to make a ‘better’ cell…
From an evolutionary perspective, fitness – the relative competitive ability of one cell type versus others in the population – is the fundamental parameter that determines which organisms increase their numbers in a population. From a physiological perspective, fitness is critical because it integrates all cellular processes relevant to the environment in question. Fitness is the key link to the two perspectives…
Experimental evolution results in strains naturally selected for increased fitness in the environment defined by the experimenter. Thus, comparison of the evolved lines that result from experimental evolution to their ancestor (or other evolved lines) offers a window into what it takes to become better in that very environment. Therefore, the genetic basis of improved fitness links evolutionary dynamics to the underlying physiological changes.
Evolutionary systems biology
Powerful new functional genomics approaches can now be applied to address the physiology of adaptation in a system-wide manner. These allow one to address in a broad, top-down fashion what physiological changes have occurred in strains with increased fitness, and whether different populations have happened across the same phenotypic solutions to adaptation – and use these as clues as to the underlying beneficial mutations. Alternatively, methods for detecting mutations or genomic rearrangements are beginning to become available to allow a bottom-up approach – find the mutations first, and then determine if they affect fitness, and then why. It is an exciting time to be involved in microbial evolution!
In summary, this approach sees experimental evolution as a window into larger questions of bacterial evolution and physiology. On one level, microbial experimental systems provide the means to test general evolutionary theory. On another level, fitness necessarily integrates myriad aspects of cell physiology. Beneficial mutations are naturally-selected perturbations of the ancestral state of the system that result in improved performance under the defined environment. Thus, experimental evolution opens the door to connecting the biochemical complexity inside of individual cells with the ecological complexity within populations.