Principal Investigator @Instituto Gulbenkian Ciência Instituto Gulbenkian de Ciência Instituto Gulbenkian de Ciência Evolutionary Biology Group Rua da Quinta Grande, 6 Oeiras, 2780-156 Portugal Website
Progression through an adaptive fitness landscape requires the appearance and fixation of beneficial mutations. But fixation of a beneficial variant is not a necessary outcome, as deduced by J.B.S. Haldane in 1927, instead its probability can be given by twice the fitness effect: Pfix= 2s. This is based in the reasoning that even beneficial variants are lost with high probability by genetic drift. In this work, we performed invasion experiments with inbred lines of Caenorhabditis elegans in well-defined demographic conditions to experimentally demonstrate the determinant role of drift in the initial dynamics of new beneficial alleles. We provide the evidence that extinction rates (Pext) decrease with the initial numbers of beneficial variants, as expected. We also show that the extinction of a deleterious variant, when at low frequency, is higher than that of a beneficial variant thus establishing that classical population genetics theory can accurately predict the fate of low frequency variants. Remarkably though we also find that, when at high frequency the fate of these variants is distinct from their low frequency dynamics, which results not in their ultimate fixation or loss, but on their maintenance. Our data confirm one of the key results of population genetics theory and highlights the complex nature of adaptation, where polymorphism can be maintained or lost depending on population structure.
The role of mutations in evolution depends upon the distribution of their effects on fitness. This distribution is likely to depend
on the environment. Indeed genotype-by-environment interactions are key for the process of local adaptation and ecological
specialization. An important trait in bacterial evolution is antibiotic resistance, which presents a clear case of change in the
direction of selection between environments with and without antibiotics. Here, we study the distribution of fitness effects of
mutations, conferring antibiotic resistance to Escherichia coli, in benign and stressful environments without drugs.We interpret the
distributions in the light of a fitness landscape model that assumes a single fitness peak. We find that mutation effects (s) arewell
described by a shifted gamma distribution, with a shift parameter that reflects the distance to the fitness peak and varies across
environments. Consistent with the theoretical predictions of Fisher’s geometrical model, with a Gaussian relationship between
phenotype and fitness, we find that the main effect of stress is to increase the variance in s. Our findings are in agreement with
the results of a recent meta-analysis, which suggest that a simple fitness landscape model may capture the variation of mutation
effects across species and environments.
The process of adaptation in bacterial populations is often studied in simple and well-defined laboratory environments, mainly involving abiotic interactions. On the other hand, adaptation to complex environments, within ecological communities, involving biotic interactions, is only rarely studied. A medically important and extremely diverse community is the gut microbiome. Here, we study the process of adaptation of Escherichia coli to the mouse gut. We combine methodologies from evolutionary genetics and molecular biology to understand the rate of adaptation and the number and selective strength of newly arising mutations. Previous work from our lab has shown that, in contrary to what is theoretically predicted and normally observed in-vitro, the rate of adaptation does not decrease through time, during two consecutive colonizations of the mouse gut (~900 generations). We now isolated three genetically distinct clones (from the second colonization), which represent three independent evolutionary paths and test whether the evolutionary process proceeds at the same pace (both in terms of rate of adaptation and selective strength of new mutations). To better understand the adaptive process, we use genome re-sequencing of the evolved clones and measure their fitness across a variety of environments that mimic different components of the gut environment. Our results, will allow us to further test the relevance of the following theoretical predictions: 1) as populations adapt to a given environment, the rate of adaptation decreases; 2) in the absence of recombination, clonal interference dominates the adaptive process. Moreover, we will be able to infer what are the main forces shaping the adaptation of an important commensal to the mouse gut.