Legend Marie Lu Adaptation

[Yogprasad Moneta]

Theaccumulation of adaptive mutations is essential for survival in novel environments. However, in clonal populations with a high mutational supply, the power of natural selection is expected to be limited. This is due to clonal interference - the competition of clones carrying different beneficial mutations - which leads to the loss of many small effect mutations and fixation of large effect ones. If interference is abundant, then mechanisms for horizontal transfer of genes, which allow the immediate combination of beneficial alleles in a single background, are expected to evolve. However, the relevance of interference in natural complex environments, such as the gut, is poorly known. To address this issue, we have developed an experimental system which allows to uncover the nature of the adaptive process as Escherichia coli adapts to the mouse gut. This system shows the invasion of beneficial mutations in the bacterial populations and demonstrates the pervasiveness of clonal interference. The observed dynamics of change in frequency of beneficial mutations are consistent with soft sweeps, where different adaptive mutations with similar phenotypes, arise repeatedly on different haplotypes without reaching fixation. Despite the complexity of this ecosystem, the genetic basis of the adaptive mutations revealed a striking parallelism in independently evolving populations. This was mainly characterized by the insertion of transposable elements in both coding and regulatory regions of a few genes. Interestingly, in most populations we observed a complete phenotypic sweep without loss of genetic variation. The intense clonal interference during adaptation to the gut environment, here demonstrated, may be important for our understanding of the levels of strain diversity of E. coli inhabiting the human gut microbiota and of its recombination rate.

Adaptation to novel environments involves the accumulation of beneficial mutations. If these are rare the process will proceed slowly with each one sweeping to fixation on its own. On the contrary if they are common in clonal populations, individuals carrying different beneficial alleles will experience intense competition and only those clones carrying the stronger effect mutations will leave a future line of descent. This phenomenon is known as clonal interference and the extent to which it occurs in natural environments is unknown. One of the most complex natural environments for E. coli is the mammalian intestine, where it evolves in the presence of many species comprising the gut microbiota. We have studied the dynamics of adaptation of E. coli populations evolving in this relevant ecosystem. We show that clonal interference is pervasive in the mouse gut and that the targets of natural selection are similar in independently E. coli evolving populations. These results illustrate how experimental evolution in natural environments allows us to dissect the mechanisms underlying adaptation and its complex dynamics and further reveal the importance of mobile genetic elements in contributing to the adaptive diversification of bacterial populations in the gut.

Copyright: 2014 Barroso-Batista et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Mutation is the fuel of evolution and beneficial mutations the driver of organismal adaptation. When a small group of organisms founds a new niche it will rely on de novo mutations to adjust to such novel environment. If the rate of emergence of new beneficial mutations is low, adaptation will proceed through the asynchronous accumulation of such mutations, one at a time. This will result in short-term polymorphism, during which the frequency of the beneficial mutation will rapidly change. Such strong selective sweeps will purge linked neutral variation, a phenomenon long recognized as the signature of selective sweeps in bacterial populations [1]. Thus, for reasonably small populations and for low mutation rates, population mean fitness will increase in steps, where at each step neutral variation becomes completely depleted. The adaptive walk will therefore proceed by discrete movements along the fitness landscape.

But how strong is CI and what consequences does it entail? While it has been shown to occur in bacteria [5], [12] and eukaryotes [3], [13] in laboratory settings, its relevance in natural environments is poorly known. Interestingly, CI has recently been inferred to be an important determinant of the evolution of the influenza virus [14]. Several examples from the study of rapid adaptation in natural populations have also shown the violation of the classical hard selective sweep model as well as the assumption of the mutation limited regime of adaptation. In contrast multiple adaptive alleles at the same locus can sweep through the populations at the same time, a phenomenon known as soft sweeps. These alleles can emerge from de novo mutation or from standing genetic variation (see [15] for a revision). The phenomenon of CI is theoretically expected to impact the dynamics of adaptation if the effective population size (Ne) and/or the rate of occurrence of beneficial mutations (Ub) is large. More specifically, when the number of competing mutations is bigger than one, that is if 2Ne Ub Ln(Ne sb/2) >1 (where sb is the mean effect of a beneficial mutation [8]). Desai and Fisher [16] made the case that in extremely large populations with very high mutational inputs, haplotypes with multiple beneficial mutations are expected to arise and increase in frequency. Furthermore, important advances of the theory of CI have also recently been made [11], [17], [18]. Since the parameter values important to determine the importance and level of interference are expected to be dependent on the environment, the relevance of CI for bacterial evolution in natural conditions remains to be demonstrated.

We have studied the process of accumulation of beneficial mutations and the strength of their effects in a natural environment of E. coli, the mouse gut. We found that CI is pervasive in vivo and described the genetic basis of the initial steps of adaptation, which were observed to exhibit a striking parallelism. Remarkably we have found that in the same population, distinct mutations with equivalent functional effects (i.e., targeting the same gene or operon) reach detectable frequencies simultaneously. This leads to the occurrence of a phenotypic hard sweep without loss of variation at the genetic level. However, most of these mutations get extinct after a few generations, a signature of soft sweeps [23].

A genetically homogeneous population of E. coli, except for a chromosomally encoded fluorescence marker (see Material and Methods), was used to trace the occurrence of different adaptive mutations [2] and determine the strength of their fitness effects. This population, composed of equal amounts of two subpopulations expressing either a yellow (YFP) or cyan (CFP) fluorescent protein, was used to inoculate inbred mice orally. Subsequently, we followed fluorescent-markers frequency from daily collected fecal samples, for 24 days. The experiment was repeated three times to a total of 15 mice housed individually, where E. coli adaptation was followed.

We also have used a recently developed method [26] to estimate the fitness of the haplotypes that segregate at sufficiently high frequency to lead to changes in marker dynamics. This method takes the frequencies of the neutral markers across all the time points of the experiment and allows for the occurrence of CI. We started by estimating the distribution of fitness effects of the minimum number of haplotypes, as proposed by Illingworth and Mustonen [26], to fit the marker frequency data. Assuming the simplest possible model of Darwinian selection, with constant selection across space and time (admittedly an oversimplified view of the gut), we fitted a series of models, which differ in the number of beneficial mutations. Starting from the simplest minimal model where only one beneficial mutation occurs, we sequentially increase the number of mutations until a maximum of five. For each model this approach fits, by maximum likelihood, the observed frequency changes at a marker locus with two alleles (our fluorescent alleles) and then chooses the simplest possible model. The predictions described faithfully the empirical data in terms of marker frequencies (lines in Figure 1A). With this method the distribution of haplotype fitnesses across all populations, can be determined (Figure 2). The inferred fitness effects of segregating haplotypes are quite large with a mean of (15%) and some haplotypes leading to increases in fitness of more than 30%. We note that given the intense CI observed, this approach misses some of the mutations contributing to the dynamics (see below).

Identified mutations in clones isolated from populations 1.1 to 1.14 (evolved in vivo for 24 days), represented along the E. coli chromosome. For simplicity, the genomes are represented linearly and vertically drawn. The type and position of mutations are shown by triangles for insertions and deletions, small vertical bars denote single nucleotide polymorphisms (SNPs), and one duplication in clone number 1.12 is depicted as a horizontal bar. See the symbol legend for other events. The genes dcuB, srlR and focA and one operon (gat) are highlighted. These represent regions of parallel mutation in at least two genomes. The genomic context of these mutations is represented on the right. (reg) after the gene name, means that the regulatory region, rather than the coding region, was affected. Numbers above marked mutations represent the number of times a particular mutation was detected at the same position.

The genetic analysis showed that similar and parallel adaptive paths were taken during the initial adaptation to the gut (Figure 3, Table S2). The most striking recurrent event was detected at the level of mutations in the gat operon, which occurred in all the sequenced clones (79% IS insertions and 21% small indels). The gat operon consists of six genes that collectively allow for galactitol metabolism [28]. We found that galactitol had an inhibitory effect on the ancestral strain when grown in minimal medium with glycerol (Figure S2). However in all the evolved clones (carrying mutations either in the coding region of gatA, gatC, gatZ or in the regulatory region of gatY (see Figure 3)) this inhibition was surpassed (Figure S2). All these clones exhibited a gat-negative phenotype, inability to metabolize galactitol. Since galactitol is part of the host' metabolism of galactose, E. coli might be frequently exposed to this compound in the gut. This may have selected for the gat-negative phenotype.

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