One of the most recurrent observations after two decades of microbial evolution experiments regards the dynamics of fitness change. In a given environment, low-fitness genotypes are recurrently observed to adapt faster than their more fit counterparts. Since adaptation is the main macroscopic outcome of Darwinian evolution, studying its patterns of change could potentially provide insight into key issues of evolutionary theory, from fixation dynamics to the genetic architecture of organisms. Here, we re-analyze several published datasets from experimental evolution with microbes and show that, despite large differences in the origin of the data, a pattern of inverse dependence of adaptability with fitness clearly emerges. In quantitative terms, it is remarkable to observe little if any degree of idiosyncrasy across systems as diverse as virus, bacteria and yeast. The universality of this phenomenon suggests that its emergence might be understood from general principles, giving rise to the exciting prospect that evolution might be statistically predictable at the macroscopic level. We discuss this possibilities in the light of the various theories of adaptation that have been proposed and delineate future directions of research.

Low concentrations of some antibiotics have been reported to stimulate mutagenesis and recombination, which may facilitate bacterial adaptation to different types of stress, including antibiotic pressure. However, the mutagenic effect of most of the currently used antibiotics remains untested. Furthermore, it is known that in many bacteria, including Escherichia coli, stimulation of mutagenesis is mediated by the SOS response. Thus, blockage or attenuation of this response through the inhibition of RecA has been proposed as a possible therapeutic adjuvant in combined therapy to reduce the ability to generate antibiotic-resistant mutants. The aim of this work was to study the capacity of sublethal concentrations of antimicrobials of different families with different molecular targets to increase the mutant frequency of E. coli, and the effect that inactivation of recA would have on antibiotic-mediated mutagenesis. We tested the mutagenicity of the following antimicrobials: ampicillin; ceftazidime; imipenem; fosfomycin; ciprofloxacin; trimethoprim; sulfamethoxazole; trimethoprim/sulfamethoxazole; colistin; tetracycline; gentamicin; rifampicin; and chloramphenicol. Eight out of the 13 antimicrobials tested stimulate E. coli mutagenesis (slightly in most cases), with trimethoprim, alone or in combination with sulfamethoxazole, producing the highest effect. Inactivation of recA abolishes the mutagenic effect and also produces increased susceptibility to some of the tested antimicrobials. The fact that inactivation of recA reduces mutagenicity and/or increases the activity of a large number of antimicrobials supports the hypothesis that RecA inhibition might have favourable effects on antibiotic therapy.

Understanding the extreme variation among bacterial genomes remains an unsolved challenge in evolutionary biology, despite long-standing debate about the relative importance of natural selection, mutation, and random drift. A potentially important confounding factor is the variation in mutation rates between lineages and over evolutionary history, which has been documented in several species. Mutation accumulation experiments have shown that hypermutability can erode genomes over short timescales. These results, however, were obtained under conditions of extremely weak selection, casting doubt on their general relevance. Here, we circumvent this limitation by analyzing genomes from mutator populations that arose during a long-term experiment with Escherichia coli, in which populations have been adaptively evolving for >50,000 generations. We develop an analytical framework to quantify the relative contributions of mutation and selection in shaping genomic characteristics, and we validate it using genomes evolved under regimes of high mutation rates with weak selection (mutation accumulation experiments) and low mutation rates with strong selection (natural isolates). Our results show that, despite sustained adaptive evolution in the long-term experiment, the signature of selection is much weaker than that of mutational biases in mutator genomes. This finding suggests that relatively brief periods of hypermutability can play an outsized role in shaping extant bacterial genomes. Overall, these results highlight the importance of genomic draft, in which strong linkage limits the ability of selection to purge deleterious mutations. These insights are also relevant to other biological systems evolving under strong linkage and high mutation rates, including viruses and cancer cells.

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic—but statistically predictable—nature of mutational fitness effects.