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.

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.

Analysis of bacterial genomes from an evolution experiment with horizontal gene transfer shows that recombination can sometimes overwhelm selection.

Few experimental studies have examined the role that sexual recombination plays in bacterial evolution, including the effects of horizontal gene transfer on genome structure. To address this limitation, we analyzed genomes from an experiment in which Escherichia coli K-12 Hfr (high frequency recombination) donors were periodically introduced into 12 evolving populations of E. coli B and allowed to conjugate repeatedly over the course of 1000 generations. Previous analyses of the evolved strains from this experiment showed that recombination did not accelerate adaptation, despite increasing genetic variation relative to asexual controls. However, the resolution in that previous work was limited to only a few genetic markers. We sought to clarify and understand these puzzling results by sequencing complete genomes from each population. The effects of recombination were highly variable: one lineage was mostly derived from the donors, while another acquired almost no donor DNA. In most lineages, some regions showed repeated introgression and others almost none. Regions with high introgression tended to be near the donors' origin of transfer sites. To determine whether introgressed alleles imposed a genetic load, we extended the experiment for 200 generations without recombination and sequenced whole-population samples. Beneficial alleles in the recipient populations were occasionally driven extinct by maladaptive donor-derived alleles. On balance, our analyses indicate that the plasmid-mediated recombination was sufficiently frequent to drive donor alleles to fixation without providing much, if any, selective advantage.

Synonymous Genetic Variation in Natural Isolates of Escherichia coli Does Not Predict Where Synonymous Substitutions Occur in a Long-Term Experiment.

Synonymous genetic differences vary by more than 20-fold among genes in natural isolates of Escherichia coli. One hypothesis to explain this heterogeneity is that genes with high levels of synonymous variation mutate at higher rates than genes with low synonymous variation. If so, then one would expect to observe similar mutational patterns in evolution experiments. In fact, however, the pattern of synonymous substitutions in a long-term evolution experiment with E. coli does not support this hypothesis. In particular, the extent of synonymous variation across genes in that experiment does not reflect the variation observed in natural isolates of E. coli. Instead, gene length alone predicts with high accuracy the prevalence of synonymous changes in the experimental populations. We hypothesize that patterns of synonymous variation in natural E. coli populations are instead caused by differences across genomic regions in their effective population size that, in turn, reflect different histories of recombination, horizontal gene transfer, selection, and population structure.

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.

Programming Dynamic Division of Labor Using Horizontal Gene Transfer.

The metabolic engineering of microbes has broad applications, including biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multistep pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is the division of labor (DOL) in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted interstrain population dynamics. Through modeling, we show that dynamic division of labor (DDOL), which we define as the DOL between indiscrete populations capable of dynamic and reversible interchange, can overcome these limitations and enable the robust maintenance of burdensome, multistep pathways. We propose that DDOL can be mediated by horizontal gene transfer (HGT) and use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

Duplicated antibiotic resistance genes reveal ongoing selection and horizontal gene transfer in bacteria.

Horizontal gene transfer (HGT) and gene duplication are often considered as separate mechanisms driving the evolution of new functions. However, the mobile genetic elements (MGEs) implicated in HGT can copy themselves, so positive selection on MGEs could drive gene duplications. Here, we use a combination of modeling and experimental evolution to examine this hypothesis and use long-read genome sequences of tens of thousands of bacterial isolates to examine its generality in nature. Modeling and experiments show that antibiotic selection can drive the evolution of duplicated antibiotic resistance genes (ARGs) through MGE transposition. A key implication is that duplicated ARGs should be enriched in environments associated with antibiotic use. To test this, we examined the distribution of duplicated ARGs in 18,938 complete bacterial genomes with ecological metadata. Duplicated ARGs are highly enriched in bacteria isolated from humans and livestock. Duplicated ARGs are further enriched in an independent set of 321 antibiotic-resistant clinical isolates. Our findings indicate that duplicated genes often encode functions undergoing positive selection and horizontal gene transfer in microbial communities.

Programming dynamic division of labor using horizontal gene transfer.

The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

Phylogenomic analysis of the uracil-DNA glycosylase superfamily.

The spontaneous deamination of cytosine produces uracil mispaired with guanine in DNA, which will produce a mutation, unless repaired. In all domains of life, uracil-DNA glycosylases (UDGs) are responsible for the elimination of uracil from DNA. Thus, UDGs contribute to the integrity of the genetic information and their loss results in mutator phenotypes. We are interested in understanding the role of UDG genes in the evolutionary variation of the rate and the spectrum of spontaneous mutations. To this end, we determined the presence or absence of the five main UDG families in more than 1,000 completely sequenced genomes and analyzed their patterns of gene loss and gain in eubacterial lineages. We observe nonindependent patterns of gene loss and gain between UDG families in Eubacteria, suggesting extensive functional overlap in an evolutionary timescale. Given that UDGs prevent transitions at G:C sites, we expected the loss of UDG genes to bias the mutational spectrum toward a lower equilibrium G + C content. To test this hypothesis, we used phylogenetically independent contrasts to compare the G + C content at intergenic and 4-fold redundant sites between lineages where UDG genes have been lost and their sister clades. None of the main UDG families present in Eubacteria was associated with a higher G + C content at intergenic or 4-fold redundant sites. We discuss the reasons of this negative result and report several features of the evolution of the UDG superfamily with implications for their functional study. uracil-DNA glycosylase, mutation rate evolution, mutational bias, GC content, DNA repair, mutator gene.

Idiosyncratic Purifying Selection on Metabolic Enzymes in the Long-Term Evolution Experiment with Escherichia coli.

Bacteria, Archaea, and Eukarya all share a common set of metabolic reactions. This implies that the function and topology of central metabolism has been evolving under purifying selection over deep time. Central metabolism may similarly evolve under purifying selection during long-term evolution experiments, although it is unclear how long such experiments would have to run (decades, centuries, millennia) before signs of purifying selection on metabolism appear. I hypothesized that central and superessential metabolic enzymes would show evidence of purifying selection in the long-term evolution experiment with Escherichia coli (LTEE). I also hypothesized that enzymes that specialize on single substrates would show stronger evidence of purifying selection in the LTEE than generalist enzymes that catalyze multiple reactions. I tested these hypotheses by analyzing metagenomic time series covering 62,750 generations of the LTEE. I find mixed support for these hypotheses, because the observed patterns of purifying selection are idiosyncratic and population-specific. To explain this finding, I propose the Jenga hypothesis, named after a children's game in which blocks are removed from a tower until it falls. The Jenga hypothesis postulates that loss-of-function mutations degrade costly, redundant, and non-essential metabolic functions. Replicate populations can therefore follow idiosyncratic trajectories of lost redundancies, despite purifying selection on overall function. I tested the Jenga hypothesis by simulating the evolution of 1,000 minimal genomes under strong purifying selection. As predicted, the minimal genomes converge to different metabolic networks. Strikingly, the core genes common to all 1,000 minimal genomes show consistent signatures of purifying selection in the LTEE.