Escherichia coli adaptation under prolonged resource exhaustion is characterized by extreme parallelism and frequent historical contingency.

Like many other non-sporulating bacterial species, Escherichia coli is able to survive prolonged periods of resource exhaustion, by entering a state of growth called long-term stationary phase (LTSP). In July 2015, we initiated a set of evolutionary experiments aimed at characterizing the dynamics of E. coli adaptation under LTSP. In these experiments populations of E. coli were allowed to initially grow on fresh rich media, but were not provided with any new external growth resources since their establishment. Utilizing whole genome sequencing data obtained for hundreds of clones sampled at 12 time points spanning the first six years of these experiments, we reveal several novel aspects of the dynamics of adaptation. First, we show that E. coli continuously adapts genetically, up to six years under resource exhaustion, through the highly convergent accumulation of mutations. We further show that upon entry into LTSP, long-lasting lineages are established. This lineage structure is in itself convergent, with similar lineages arising across independently evolving populations. The high parallelism with which adaptations occur under LTSP, combined with the LTSP populations' lineage structure, enable us to screen for pairs of loci displaying a significant association in the occurrence of mutations, suggestive of a historical contingency. We find that such associations are highly frequent and that a third of convergently mutated loci are involved in at least one such association. Combined our results demonstrate that LTSP adaptation is characterized by remarkably high parallelism and frequent historical contingency.

Metabolic adaptation to consume butyrate under prolonged resource exhaustion.

Bacteria must often survive following the exhaustion of their external growth resources. Fitting with this need, many bacterial species that cannot sporulate, can enter a state known as long term stationary phase (LTSP) in which they can persist for years within spent media. Several recent studies have revealed the dynamics of genetic adaptation of Escherichia coli under LTSP. Yet, the metabolic consequences of such genetic adaptation were not addressed. Here, we characterized the metabolic changes LTSP populations experience, over the first 32 days under LTSP. This allowed us to link genetic adaptations observed in a convergent manner across LTSP populations back to their metabolic adaptive effect. Specifically, we demonstrate that through the acquisition of mutations combinations in specific sets of metabolic genes, E. coli acquires the ability to consume the short chain fatty acid butyrate. Intriguingly, this fatty acid is not initially present within the rich media we used in this study. Instead, it is E. coli itself that produces butyrate during its initial growth within fresh rich media. The mutations that enable butyrate consumption allow E. coli to grow on butyrate. However, the clones carrying these mutations rapidly decrease in frequency, once the butyrate is consumed, likely reflecting an associated cost to fitness. Yet despite this, E. coli populations show a remarkable capability of maintaining these genotypes at low frequency, as standing variation. This in turn allows them to more rapidly re-adapt to consume butyrate, once it again becomes available to them.

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains.

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

Dynamics of Adaptation During Three Years of Evolution Under Long-Term Stationary Phase.

Many bacterial species that cannot sporulate, such as the model bacterium Escherichia coli, can nevertheless survive for years, following exhaustion of external resources, in a state termed long-term stationary phase (LTSP). Here we describe the dynamics of E. coli adaptation during the first three years spent under LTSP. We show that during this time, E. coli continuously adapts genetically through the accumulation of mutations. For nonmutator clones, the majority of mutations accumulated appear to be adaptive under LTSP, reflected in an extremely convergent pattern of mutation accumulation. Despite the rapid and convergent manner in which populations adapt under LTSP, they continue to harbor extensive genetic variation. The dynamics of evolution of mutation rates under LTSP are particularly interesting. The emergence of mutators affects overall mutation accumulation rates as well as the mutational spectra and the ultimate spectrum of adaptive alleles acquired under LTSP. With time, mutators can evolve even higher mutation rates through the acquisition of additional mutation rate-enhancing mutations. Different mutator and nonmutator clones within a single population and time point can display extreme variation in their mutation rates, resulting in differences in both the dynamics of adaptation and their associated deleterious burdens. Despite these differences, clones that vary greatly in their mutation rates tend to coexist within their populations for many years, under LTSP.

Antibiotic-Independent Adaptive Effects of Antibiotic Resistance Mutations.

Antibiotic usage selects for the accumulation and spread of antibiotic-resistant bacteria. However, resistance can also accumulate in the absence of antibiotic exposure. Antibiotics are often designed to target widely distributed regulatory housekeeping genes. The targeting of such genes enables these antibiotics to be useful against a wider variety of pathogens. This review highlights work suggesting that regulatory housekeeping genes of the type targeted by many antibiotics function as hubs of adaptation to conditions unrelated to antibiotic exposure. As a result of this, some mutations to the regulatory housekeeping gene targets of antibiotics confer both antibiotic resistance and an adaptive effect unrelated to antibiotic exposure. Such antibiotic-independent adaptive effects of resistance mutations may substantially affect the dynamics of antibiotic resistance accumulation and spread.

Rapid Genetic Adaptation during the First Four Months of Survival under Resource Exhaustion.

Many bacteria, including the model bacterium Escherichia coli can survive for years within spent media, following resource exhaustion. We carried out evolutionary experiments, followed by whole genome sequencing of hundreds of evolved clones to study the dynamics by which E. coli adapts during the first 4 months of survival under resource exhaustion. Our results reveal that bacteria evolving under resource exhaustion are subject to intense selection, manifesting in rapid mutation accumulation, enrichment in functional mutation categories and extremely convergent adaptation. In the most striking example of convergent adaptation, we found that across five independent populations adaptation to conditions of resource exhaustion occurs through mutations to the three same specific positions of the RNA polymerase core enzyme. Mutations to these three sites are strongly antagonistically pleiotropic, in that they sharply reduce exponential growth rates in fresh media. Such antagonistically pleiotropic mutations, combined with the accumulation of additional mutations, severely reduce the ability of bacteria surviving under resource exhaustion to grow exponentially in fresh media. We further demonstrate that the three positions at which these resource exhaustion mutations occur are conserved for the ancestral E. coli allele, across bacterial phyla, with the exception of nonculturable bacteria that carry the resource exhaustion allele at one of these positions, at very high frequencies. Finally, our results demonstrate that adaptation to resource exhaustion is not limited by mutational input and that bacteria are able to rapidly adapt under resource exhaustion in a temporally precise manner through allele frequency fluctuations.

Cancer evolution is associated with pervasive positive selection on globally expressed genes.

Cancer is an evolutionary process in which cells acquire new transformative, proliferative and metastatic capabilities. A full understanding of cancer requires learning the dynamics of the cancer evolutionary process. We present here a large-scale analysis of the dynamics of this evolutionary process within tumors, with a focus on breast cancer. We show that the cancer evolutionary process differs greatly from organismal (germline) evolution. Organismal evolution is dominated by purifying selection (that removes mutations that are harmful to fitness). In contrast, in the cancer evolutionary process the dominance of purifying selection is much reduced, allowing for a much easier detection of the signals of positive selection (adaptation). We further show that, as a group, genes that are globally expressed across human tissues show a very strong signal of positive selection within tumors. Indeed, known cancer genes are enriched for global expression patterns. Yet, positive selection is prevalent even on globally expressed genes that have not yet been associated with cancer, suggesting that globally expressed genes are enriched for yet undiscovered cancer related functions. We find that the increased positive selection on globally expressed genes within tumors is not due to their expression in the tissue relevant to the cancer. Rather, such increased adaptation is likely due to globally expressed genes being enriched in important housekeeping and essential functions. Thus, our results suggest that tumor adaptation is most often mediated through somatic changes to those genes that are important for the most basic cellular functions. Together, our analysis reveals the uniqueness of the cancer evolutionary process and the particular importance of globally expressed genes in driving cancer initiation and progression.

POGO-DB--a database of pairwise-comparisons of genomes and conserved orthologous genes.

POGO-DB (http://pogo.ece.drexel.edu/) provides an easy platform for comparative microbial genomics. POGO-DB allows users to compare genomes using pre-computed metrics that were derived from extensive computationally intensive BLAST comparisons of >2000 microbes. These metrics include (i) average protein sequence identity across all orthologs shared by two genomes, (ii) genomic fluidity (a measure of gene content dissimilarity), (iii) number of 'orthologs' shared between two genomes, (iv) pairwise identity of the 16S ribosomal RNA genes and (v) pairwise identity of an additional 73 marker genes present in >90% prokaryotes. Users can visualize these metrics against each other in a 2D plot for exploratory analysis of genome similarity and of how different aspects of genome similarity relate to each other. The results of these comparisons are fully downloadable. In addition, users can download raw BLAST results for all or user-selected comparisons. Therefore, we provide users with full flexibility to carry out their own downstream analyses, by creating easy access to data that would normally require heavy computational resources to generate. POGO-DB should prove highly useful for researchers interested in comparative microbiology and benefit the microbiome/metagenomic communities by providing the information needed to select suitable phylogenetic marker genes within particular lineages.

Elevated mutagenesis does not explain the increased frequency of antibiotic resistant mutants in starved aging colonies.

The frequency of mutants resistant to the antibiotic rifampicin has been shown to increase in aging (starved), compared to young colonies of Escherichia coli. These increases in resistance frequency occur in the absence of any antibiotic exposure, and similar increases have also been observed in response to additional growth limiting conditions. Understanding the causes of such increases in the frequency of resistance is important for understanding the dynamics of antibiotic resistance emergence and spread. Increased frequency of rifampicin resistant mutants in aging colonies is cited widely as evidence of stress-induced mutagenesis (SIM), a mechanism thought to allow bacteria to increase mutation rates upon exposure to growth-limiting stresses. At the same time it has been demonstrated that some rifampicin resistant mutants are relatively fitter in aging compared to young colonies, indicating that natural selection may also contribute to increased frequency of rifampicin resistance in aging colonies. Here, we demonstrate that the frequency of mutants resistant to both rifampicin and an additional antibiotic (nalidixic-acid) significantly increases in aging compared to young colonies of a lab strain of Escherichia coli. We then use whole genome sequencing to demonstrate conclusively that SIM cannot explain the observed magnitude of increased frequency of resistance to these two antibiotics. We further demonstrate that, as was previously shown for rifampicin resistance mutations, mutations conferring nalidixic acid resistance can also increase fitness in aging compared to young colonies. Our results show that increases in the frequency of antibiotic resistant mutants in aging colonies cannot be seen as evidence of SIM. Furthermore, they demonstrate that natural selection likely contributes to increases in the frequency of certain antibiotic resistance mutations, even when no selection is exerted due to the presence of antibiotics.

Strong purifying selection at synonymous sites in D. melanogaster.

Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population sequencing data to show that, contrary to this expectation, 22% of four-fold synonymous (4D) sites in Drosophila melanogaster evolve under very strong selective constraint while few, if any, appear to be under weak constraint. Linking polymorphism with divergence data, we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny. The function underlying the inferred strong constraint appears to be separate from splicing enhancers, nucleosome positioning, and the translational optimization generating canonical codon bias. The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression, particularly in the mid-late embryo, pupae, and adult developmental stages. Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways. Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila, the role of synonymous sites in genetic disease and adaptation should be reevaluated.

Pseudomonas putida Dynamics of Adaptation under Prolonged Resource Exhaustion.

Many nonsporulating bacterial species survive prolonged resource exhaustion, by entering a state termed long-term stationary phase. Here, we performed long-term stationary phase evolutionary experiments on the bacterium Pseudomonas putida, followed by whole-genome sequencing of evolved clones. We show that P. putida is able to persist and adapt genetically under long-term stationary phase. We observed an accumulation of mutations within the evolving P. putida populations. Within each population, independently evolving lineages are established early on and persist throughout the 4-month-long experiment. Mutations accumulate in a highly convergent manner, with similar loci being mutated across independently evolving populations. Across populations, mutators emerge, that due to mutations within mismatch repair genes developed a much higher rate of mutation than other clones with which they coexisted within their respective populations. While these general dynamics of the adaptive process are quite similar to those we previously observed in the model bacterium Escherichia coli, the specific loci that are involved in adaptation only partially overlap between P. putida and E. coli.

Evidence that mutation is universally biased towards AT in bacteria.

Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content.

General rules for optimal codon choice.

Different synonymous codons are favored by natural selection for translation efficiency and accuracy in different organisms. The rules governing the identities of favored codons in different organisms remain obscure. In fact, it is not known whether such rules exist or whether favored codons are chosen randomly in evolution in a process akin to a series of frozen accidents. Here, we study this question by identifying for the first time the favored codons in 675 bacteria, 52 archea, and 10 fungi. We use a number of tests to show that the identified codons are indeed likely to be favored and find that across all studied organisms the identity of favored codons tracks the GC content of the genomes. Once the effect of the genomic GC content on selectively favored codon choice is taken into account, additional universal amino acid specific rules governing the identity of favored codons become apparent. Our results provide for the first time a clear set of rules governing the evolution of selectively favored codon usage. Based on these results, we describe a putative scenario for how evolutionary shifts in the identity of selectively favored codons can occur without even temporary weakening of natural selection for codon bias.

Rapid Adaptation Often Occurs through Mutations to the Most Highly Conserved Positions of the RNA Polymerase Core Enzyme.

Mutations to the genes encoding the RNA polymerase core enzyme (RNAPC) and additional housekeeping regulatory genes were found to be involved in adaptation, in the context of numerous evolutionary experiments, in which bacteria were exposed to diverse selective pressures. This provides a conundrum, as the housekeeping genes that were so often mutated in response to these diverse selective pressures tend to be among the genes that are most conserved in their sequences across the bacterial phylogeny. In order to further examine this apparent discrepancy, we characterized the precise positions of the RNAPC involved in adaptation to a large variety of selective pressures. We found that RNAPC lab adaptations tended to occur at positions displaying traits associated with higher selective constraint. Specifically, compared to other RNAPC positions, positions involved in adaptation tended to be more conserved in their sequences within bacteria, were more often located within defined protein domains, and were located closer to the complex's active site. Higher sequence conservation was also found for resource exhaustion adaptations occurring within additional housekeeping genes. Combined, our results demonstrate that the positions that change most readily in response to well-defined selective pressures exerted in lab environments are often also those that evolve most slowly in nature.

Reversion is most likely under high mutation supply when compensatory mutations do not fully restore fitness costs.

The dynamics of adaptation, reversion, and compensation have been central topics in microbial evolution, and several studies have attempted to resolve the population genetics underlying how these dynamics occur. However, questions remain regarding how certain features-the evolution of mutators and whether compensatory mutations alleviate costs fully or partially-may influence the evolutionary dynamics of compensation and reversion. In this study, we attempt to explain findings from experimental evolution by utilizing computational and theoretical approaches toward a more refined understanding of how mutation rate and the fitness effects of compensatory mutations influence adaptive dynamics. We find that high mutation rates increase the probability of reversion toward the wild type when compensation is only partial. However, the existence of even a single fully compensatory mutation is associated with a dramatically decreased probability of reversion to the wild type. These findings help to explain specific results from experimental evolution, where compensation was observed in nonmutator strains, but reversion (sometimes with compensation) was observed in mutator strains, indicating that real-world compensatory mutations are often unable to fully alleviate the costs associated with adaptation. Our findings emphasize the potential role of the supply and quality of mutations in crafting the dynamics of adaptation and reversal, with implications for theoretical population genetics and for biomedical contexts like the evolution of antibiotic resistance.

Freshwater microbial metagenomes sampled across different water body characteristics, space and time in Israel.

Freshwater bodies are critical components of terrestrial ecosystems. The microbial communities of freshwater ecosystems are intimately linked water quality. These microbes interact with, utilize and recycle inorganic elements and organic matter. Here, we present three metagenomic sequence datasets (total of 182.9 Gbp) from different freshwater environments in Israel. The first dataset is from diverse freshwater bodies intended for different usages - a nature reserve, irrigation and aquaculture facilities, a tertiary wastewater treatment plant and a desert rainfall reservoir. The second represents a two-year time-series, collected during 2013-2014 at roughly monthly intervals, from a water reservoir connected to an aquaculture facility. The third is from several time-points during the winter and spring of 2015 in Lake Kinneret, including a bloom of the cyanobacterium Microcystis sp. These datasets are accompanied by physical, chemical, and biological measurements at each sampling point. We expect that these metagenomes will facilitate a wide range of comparative studies that seek to illuminate new aspects of freshwater microbial ecosystems and inform future water quality management approaches.

High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography.

Mycobacterium tuberculosis infects one third of the human world population and kills someone every 15 seconds. For more than a century, scientists and clinicians have been distinguishing between the human- and animal-adapted members of the M. tuberculosis complex (MTBC). However, all human-adapted strains of MTBC have traditionally been considered to be essentially identical. We surveyed sequence diversity within a global collection of strains belonging to MTBC using seven megabase pairs of DNA sequence data. We show that the members of MTBC affecting humans are more genetically diverse than generally assumed, and that this diversity can be linked to human demographic and migratory events. We further demonstrate that these organisms are under extremely reduced purifying selection and that, as a result of increased genetic drift, much of this genetic diversity is likely to have functional consequences. Our findings suggest that the current increases in human population, urbanization, and global travel, combined with the population genetic characteristics of M. tuberculosis described here, could contribute to the emergence and spread of drug-resistant tuberculosis.

Small RNAs encoded within genetic islands of Salmonella typhimurium show host-induced expression and role in virulence.

The emergence of pathogenic strains of enteric bacteria and their adaptation to unique niches are associated with the acquisition of foreign DNA segments termed 'genetic islands'. We explored these islands for the occurrence of small RNA (sRNA) encoding genes. Previous systematic screens for enteric bacteria sRNAs were mainly carried out using the laboratory strain Escherichia coli K12, leading to the discovery of approximately 80 new sRNA genes. These searches were based on conservation within closely related members of enteric bacteria and thus, sRNAs, unique to pathogenic strains were excluded. Here we describe the identification and characterization of 19 novel unique sRNA genes encoded within the 'genetic islands' of the virulent strain Salmonella typhimurium. We show that the expression of many of the island-encoded genes is associated with stress conditions and stationary phase. Several of these sRNA genes are induced when Salmonella resides within macrophages. One sRNA, IsrJ, was further examined and found to affect the translocation efficiency of virulence-associated effector proteins into nonphagocytic cells. In addition, we report that unlike the majority of the E. coli sRNAs that are trans regulators, many of the island-encoded sRNAs affect the expression of cis-encoded genes. Our study suggests that the island encoded sRNA genes play an important role within the network that regulates bacterial adaptation to environmental changes and stress conditions and thus controls virulence.

Adaptations Accumulated under Prolonged Resource Exhaustion Are Highly Transient.

Many nonsporulating bacterial species can survive for years within exhausted growth media in a state termed long-term stationary phase (LTSP). We have been carrying out evolutionary experiments aimed at elucidating the dynamics of genetic adaptation under LTSP. We showed that Escherichia coli adapts to prolonged resource exhaustion through the highly convergent acquisition of mutations. In the most striking example of such convergent adaptation, we observed that across all independently evolving LTSP populations, over 90% of E. coli cells carry mutations to one of three specific sites of the RNA polymerase core enzyme (RNAPC). These LTSP adaptations reduce the ability of the cells carrying them to grow once fresh resources are again provided. Here, we examine how LTSP populations recover from costs associated with their adaptation once resources are again provided to them. We demonstrate that due to the ability of LTSP populations to maintain high levels of standing genetic variation during adaptation, costly adaptations are very rapidly purged from the population once they are provided with fresh resources. We further demonstrate that recovery from costs acquired during adaptation under LTSP occurs more rapidly than would be possible if LTSP adaptations had fixed during the time populations spent under resource exhaustion. Finally, we previously reported that under LTSP, some clones develop a mutator phenotype, greatly increasing their mutation accumulation rates. Here, we show that the mechanisms by which populations recover from costs associated with fixed adaptations may depend on mutator status.IMPORTANCE Many bacterial species can survive for decades under starvation, following the exhaustion of external growth resources. We have previously shown that bacteria genetically adapt under these conditions in a manner that reduces their ability to grow once resources again become available. Here, we study how populations that have been subject to very prolonged resource exhaustion recover from costs associated with their adaptation. We demonstrate that rapid adaptations acquired under prolonged starvation tend to be highly transient, rapidly reducing in frequency once bacteria are no longer starved. Our results shed light on the longer-term consequences of bacterial survival under prolonged starvation. More generally, these results may also be applicable to understanding longer-term consequences of rapid adaptation to additional conditions as well.

Culture Volume Influences the Dynamics of Adaptation under Long-Term Stationary Phase.

Escherichia coli and many other bacterial species, which are incapable of sporulation, can nevertheless survive within resource exhausted media by entering a state termed long-term stationary phase (LTSP). We have previously shown that E. coli populations adapt genetically under LTSP in an extremely convergent manner. Here, we examine how the dynamics of LTSP genetic adaptation are influenced by varying a single parameter of the experiment-culture volume. We find that culture volume affects survival under LTSP, with viable counts decreasing as volumes increase. Across all volumes, mutations accumulate with time, and the majority of mutations accumulated demonstrate signals of being adaptive. However, positive selection appears to affect mutation accumulation more strongly at higher, compared with lower volumes. Finally, we find that several similar genes are likely involved in adaptation across volumes. However, the specific mutations within these genes that contribute to adaptation can vary in a consistent manner. Combined, our results demonstrate how varying a single parameter of an evolutionary experiment can substantially influence the dynamics of observed adaptation.