Deployment of a Vibrio cholerae ordered transposon mutant library in a quorum-competent genetic background.

Vibrio cholerae, the causative agent of cholera, has sparked seven pandemics in recent centuries, with the current one being the most prolonged. V. cholerae's pathogenesis hinges on its ability to switch between low and high cell density gene regulatory states, enabling transmission between host and the environment. Previously, a transposon mutant library for V. cholerae was created to support investigations aimed toward uncovering the genetic determinants of its pathogenesis. However, subsequent sequencing uncovered a mutation in the gene luxO of the parent strain, rendering mutants unable to exhibit high cell density behaviors. In this study, we used chitin-independent natural transformation to move transposon insertions from these low cell density mutants into a wildtype genomic background. Library transfer was aided by a novel gDNA extraction we developed using thymol, which also showed high lysis-specificity for Vibrio. The resulting Grant Library comprises 3,102 unique transposon mutants, covering 79.8% of V. cholerae's open reading frames. Whole genome sequencing of randomly selected mutants demonstrates 100% precision in transposon transfer to cognate genomic positions of the recipient strain. Notably, in no instance did the luxO mutation transfer into the wildtype background. Our research uncovered density-dependent epistasis in growth on inosine, an immunomodulatory metabolite secreted by gut bacteria that is implicated in enhancing gut barrier functions. Additionally, Grant Library mutants retain the plasmid that enables rapid, scarless genomic editing. In summary, the Grant Library reintroduces organismal relevant genetic contexts absent in the low cell density locked library equivalent.

Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations.

A general method to infer both positive and purifying selection during the real-time evolution of hypermutator pathogens would be broadly useful. To this end, we introduce a Simple Test to Infer Mode of Selection (STIMS) from metagenomic time series of evolving microbial populations. We test STIMS on metagenomic data generated by simulations of bacterial evolution, and on metagenomic data spanning 62,750 generations of Lenski's long-term evolution experiment with Escherichia coli (LTEE). This benchmarking shows that STIMS detects positive selection in both nonmutator and hypermutator populations, and purifying selection in hypermutator populations. Using STIMS, we find strong evidence of ongoing positive selection on key regulators of the E. coli gene regulatory network, even in some hypermutator populations. STIMS also detects positive selection on regulatory genes in hypermutator populations of Pseudomonas aeruginosa that adapted to subinhibitory concentrations of colistin-an antibiotic of last resort-for just twenty-six days of laboratory evolution. Our results show that the fine-tuning of gene regulatory networks is a general mechanism for rapid and ongoing adaptation. The simplicity of STIMS, together with its intuitive visual interpretation, make it a useful test for positive and purifying selection in metagenomic data sets that track microbial evolution in real-time.

Model Systems in Ecology, Evolution, and Behavior: A Call for Diversity in Our Model Systems and Discipline.

AbstractEcologists and evolutionary biologists are fascinated by life's variation but also seek to understand phenomena and mechanisms that apply broadly across taxa. Model systems can help us extract generalities from amid all the wondrous diversity, but only if we choose and develop them carefully, use them wisely, and have a range of model systems from which to choose. In this introduction to the Special Feature on Model Systems in Ecology, Evolution, and Behavior (EEB), we begin by grappling with the question, What is a model system? We then explore where our model systems come from, in terms of the skills and other attributes required to develop them and the historical biases that influence traditional model systems in EEB. We emphasize the importance of communities of scientists in the success of model systems-narrow scientific communities can restrict the model organisms themselves. We also consider how our discipline was built around one type of "model scientist"-a history still reflected in the field. This lack of diversity in EEB is unjust and also narrows the field's perspective, including by restricting the questions asked and talents used to answer them. Increasing diversity, equity, and inclusion will require acting at many levels, including structural changes. Diversity in EEB, in both model systems and the scientists who use them, strengthens our discipline.

Maintenance of Metabolic Plasticity despite Relaxed Selection in a Long-Term Evolution Experiment with Escherichia coli.

AbstractTraits that are unused in a given environment are subject to processes that tend to erode them, leading to reduced fitness in other environments. Although this general tendency is clear, we know much less about why some traits are lost while others are retained and about the roles of mutation and selection in generating different responses. We addressed these issues by examining populations of a facultative anaerobe, Escherichia coli, that have evolved for >30 years in the presence of oxygen, with relaxed selection for anaerobic growth and the associated metabolic plasticity. We asked whether evolution led to the loss, improvement, or maintenance of anaerobic growth, and we analyzed gene expression and mutational data sets to understand the outcomes. We identified genomic signatures of both positive and purifying selection on aerobic-specific genes, while anaerobic-specific genes showed clear evidence of relaxed selection. We also found parallel evolution at two interacting loci that regulate anaerobic growth. We competed the ancestor and evolved clones from each population in an anoxic environment, and we found that anaerobic fitness had not decayed, despite relaxed selection. In summary, relaxed selection does not necessarily reduce an organism's fitness in other environments. Instead, the genetic architecture of the traits under relaxed selection and their correlations with traits under positive and purifying selection may sometimes determine evolutionary outcomes.

Changes in Cell Size and Shape during 50,000 Generations of Experimental Evolution with Escherichia coli.

Bacteria adopt a wide variety of sizes and shapes, with many species exhibiting stereotypical morphologies. How morphology changes, and over what timescales, is less clear. Previous work examining cell morphology in an experiment with Escherichia coli showed that populations evolved larger cells and, in some cases, cells that were less rod-like. That experiment has now run for over two more decades. Meanwhile, genome sequence data are available for these populations, and new computational methods enable high-throughput microscopic analyses. In this study, we measured stationary-phase cell volumes for the ancestor and 12 populations at 2,000, 10,000, and 50,000 generations, including measurements during exponential growth at the last time point. We measured the distribution of cell volumes for each sample using a Coulter counter and microscopy, the latter of which also provided data on cell shape. Our data confirm the trend toward larger cells while also revealing substantial variation in size and shape across replicate populations. Most populations first evolved wider cells but later reverted to the ancestral length-to-width ratio. All but one population evolved mutations in rod shape maintenance genes. We also observed many ghost-like cells in the only population that evolved the novel ability to grow on citrate, supporting the hypothesis that this lineage struggles with maintaining balanced growth. Lastly, we show that cell size and fitness remain correlated across 50,000 generations. Our results suggest that larger cells are beneficial in the experimental environment, while the reversion toward ancestral length-to-width ratios suggests partial compensation for the less favorable surface area-to-volume ratios of the evolved cells.IMPORTANCE Bacteria exhibit great morphological diversity, yet we have only a limited understanding of how their cell sizes and shapes evolve and of how these features affect organismal fitness. This knowledge gap reflects, in part, the paucity of the fossil record for bacteria. In this study, we revived and analyzed samples extending over 50,000 generations from 12 populations of experimentally evolving Escherichia coli to investigate the relation between cell size, shape, and fitness. Using this "frozen fossil record," we show that all 12 populations evolved larger cells concomitant with increased fitness, with substantial heterogeneity in cell size and shape across the replicate lines. Our work demonstrates that cell morphology can readily evolve and diversify, even among populations living in identical environments.

Divergent Evolution of Mutation Rates and Biases in the Long-Term Evolution Experiment with Escherichia coli.

All organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good BH, McDonald MJ, Barrick JE, Lenski RE, Desai MM. 2017. The dynamics of molecular evolution over 60,000 generations. Nature 551(7678):45-50.), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB-loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.

Genomic and phenotypic evolution of Escherichia coli in a novel citrate-only resource environment.

Evolutionary innovations allow populations to colonize new ecological niches. We previously reported that aerobic growth on citrate (Cit+) evolved in an Escherichia coli population during adaptation to a minimal glucose medium containing citrate (DM25). Cit+ variants can also grow in citrate-only medium (DM0), a novel environment for E. coli. To study adaptation to this niche, we founded two sets of Cit+ populations and evolved them for 2500 generations in DM0 or DM25. The evolved lineages acquired numerous parallel mutations, many mediated by transposable elements. Several also evolved amplifications of regions containing the maeA gene. Unexpectedly, some evolved populations and clones show apparent declines in fitness. We also found evidence of substantial cell death in Cit+ clones. Our results thus demonstrate rapid trait refinement and adaptation to the new citrate niche, while also suggesting a recalcitrant mismatch between E. coli physiology and growth on citrate.

Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli.

Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely--or at least for a long time--even in a constant environment.