The role of recombination in evolutionary adaptation of Escherichia coli to a novel nutrient

Horizontal gene transfer and adaptive evolution in bacteria

Horizontal gene transfer (HGT) is arguably the most conspicuous feature of bacterial evolution. Evidence for HGT is found in most bacterial genomes. Although HGT can considerably alter bacterial genomes, not all transfer events may be biologically significant and may instead represent the outcome of an incessant evolutionary process that only occasionally has a beneficial purpose. When adaptive transfers occur, HGT and positive selection may result in specific, detectable signatures in genomes, such as gene-specific sweeps or increased transfer rates for genes that are ecologically relevant. In this Review, we first discuss the various mechanisms whereby HGT occurs, how the genetic signatures shape patterns of genomic variation and the distinct bioinformatic algorithms developed to detect these patterns. We then discuss the evolutionary theory behind HGT and positive selection in bacteria, and discuss the approaches developed over the past decade to detect transferred DNA that may be involved in adaptation to new environments.

The Ingenuity of Bacterial Genomes

The genomes of bacteria contain fewer genes and substantially less noncoding DNA than those of eukaryotes, and as a result, they have much less raw material to invent new traits. Yet, bacteria are vastly more taxonomically diverse, numerically abundant, and globally successful in colonizing new habitats compared to eukaryotes. Although bacterial genomes are generally considered to be optimized for efficient growth and rapid adaptation, nonadaptive processes have played a major role in shaping the size, contents, and compact organization of bacterial genomes and have allowed the establishment of deleterious traits that serve as the raw materials for genetic innovation.

Dynamics of genetic variation in transcription factors and its implications for the evolution of regulatory networks in Bacteria

The evolution of regulatory networks in Bacteria has largely been explained at macroevolutionary scales through lateral gene transfer and gene duplication. Transcription factors (TF) have been found to be less conserved across species than their target genes (TG). This would be expected if TFs accumulate mutations faster than TGs. This hypothesis is supported by several lab evolution studies which found TFs, especially global regulators, to be frequently mutated. Despite these studies, the contribution of point mutations in TFs to the evolution of regulatory network is poorly understood. We tested if TFs show greater genetic variation than their TGs using whole-genome sequencing data from a large collection of Escherichia coli isolates. TFs were less diverse than their TGs across natural isolates, with TFs of large regulons being more conserved. In contrast, TFs showed higher mutation frequency in adaptive laboratory evolution experiments. However, over long-term laboratory evolution spanning 60 000 generations, mutation frequency in TFs gradually declined after a rapid initial burst. Extrapolating the dynamics of genetic variation from long-term laboratory evolution to natural populations, we propose that point mutations, conferring large-scale gene expression changes, may drive the early stages of adaptation but gene regulation is subjected to stronger purifying selection post adaptation.

Evaluation of SNP calling methods for closely related bacterial isolates and a novel high-accuracy pipeline: BactSNP

Bacteria are highly diverse, even within a species; thus, there have been many studies which classify a single species into multiple types and analyze the genetic differences between them. Recently, the use of whole-genome sequencing (WGS) has been popular for these analyses, and the identification of single-nucleotide polymorphisms (SNPs) between isolates is the most basic analysis performed following WGS. The performance of SNP-calling methods therefore has a significant effect on the accuracy of downstream analyses, such as phylogenetic tree inference. In particular, when closely related isolates are analyzed, e.g. in outbreak investigations, some SNP callers tend to detect a high number of false-positive SNPs compared with the limited number of true SNPs among isolates. However, the performances of various SNP callers in such a situation have not been validated sufficiently. Here, we show the results of realistic benchmarks of commonly used SNP callers, revealing that some of them exhibit markedly low accuracy when target isolates are closely related. As an alternative, we developed a novel pipeline BactSNP, which utilizes both assembly and mapping information and is capable of highly accurate and sensitive SNP calling in a single step. BactSNP is also able to call SNPs among isolates when the reference genome is a draft one or even when the user does not input the reference genome. BactSNP is available at https://github.com/IEkAdN/BactSNP.

Sexual recombination and increased mutation rate expedite evolution of Escherichia coli in varied fitness landscapes

Sexual recombination and mutation rate are theorized to play different roles in adaptive evolution depending on the fitness landscape; however, direct experimental support is limited. Here we examine how these factors affect the rate of adaptation utilizing a “genderless” strain of Escherichia coli capable of continuous in situ sexual recombination. The results show that the populations with increased mutation rate, and capable of sexual recombination, outperform all the other populations. We further characterize two sexual and two asexual populations with increased mutation rate and observe maintenance of beneficial mutations in the sexual populations through mutational sweeps. Furthermore, we experimentally identify the molecular signature of a mating event within the sexual population that combines two beneficial mutations to generate a fitter progeny; this evidence suggests that the recombination event partially alleviates clonal interference. We present additional data suggesting that stochasticity plays an important role in the combinations of mutations observed.

Sexual recombination and mutation rate may play different roles in adaptive evolution depending on the fitness landscape. Here, Peabody et al. examine how the two factors affect the rate of adaptation of an E. coli strain capable of sexual recombination, under different conditions during experimental evolution.