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.

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.

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.

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.

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.

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.

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.

Characterization of Factors Affecting the Detection Limit of EGFR p.T790M in Circulating Tumor DNA.

OBJECTIVE: Circulating tumor DNA is a promising noninvasive tool for cancer monitoring. One of the challenges in applying this tool is the detection of low-frequency mutations. The detection limit of these mutations varies between different molecular methods. The aim of this study is to characterize the factors affecting the limit of detection for epidermal growth factor receptor p.T790M mutation in circulating tumor DNA of patients with lung adenocarcinoma. METHODS: DNA was extracted from plasma samples of 102 patients. For sequencing the DNA, we used 2 different next-generation sequencing-based platforms: Ion Torrent Personal Genome Machine (56 cases) and Roche/454 (46 cases). Serially diluted synthetic DNA samples carrying the p.T790M mutation were sequenced using the Ion Torrent Personal Genome Machine for validation. Limit of detection was determined through the analysis of non-hot-spot nonreference reads, which were regarded as sequencing artifacts. RESULTS: The frequency of the non-hot-spot nonreference reads was higher in Ion Torrent Personal Genome Machine compared to Roche/454 (0.07% ± 0.08% and 0.03% ± 0.06%, respectively, P < .001). We found that different base type substitutions occur with different frequency. Since the base substitution leading to p.T790M mutation is C>T transition, its frequency was used to determine the limit of detection for the assay. Based on the C>T non-hot-spot nonreference allele frequency, we found that the limit of detection is 0.18% in Ion Torrent Personal Genome Machine and 0.1% in Roche/454. Based on these values, 48% and 56% of the cases were positive for T790M mutation in Ion Torrent Personal Genome Machine and Roche/454 groups, respectively. Agreement between duplicates was 76% in Ion Torrent Personal Genome Machine and 72% in Roche/454. Using serially diluted synthetic DNA samples carrying the p.T790M mutation, we could identify mutations with allele frequency of 0.18% or more using the Ion Torrent Personal Genome Machine, supporting our approach to determine the detection limit. CONCLUSION: Both the sequencing platform and the specific nucleotide change affect the limit of detection and should therefore be determined in the validation process of new assays.

The Codon Usage of Lowly Expressed Genes Is Subject to Natural Selection.

Codon usage bias affects the genomes of organisms from all kingdoms of life and results from both background substitution biases and natural selection. Natural selection on codon usage to increase translation accuracy and efficiency has long been known to affect gene sequences. Such selection is stronger on highly, compared with lowly expressed genes, resulting in higher levels of codon bias within genes with higher expression levels. Additionally, selection on translation accuracy affects more strongly codons encoding conserved amino acids, since these will more often affect protein folding and/or function. By applying tests of selection on the gene sequences of the bacterium Escherichia coli, we demonstrate that both highly and lowly expressed genes display signals of selection on codon usage. Such signals are found for both conserved and less conserved amino acid positions, even within the 10% of E. coli genes expressed at the lowest levels. We further demonstrate experimentally that single synonymous codon replacements within a lowly expressed, essential gene can carry substantial effects on bacterial fitness. Combined, our results demonstrate that even within genes expressed at relatively low levels there is substantial selection on codon usage and that single synonymous codon replacements within such genes can have a marked effect on bacterial fitness.

Similar levels of gene content variation observed for Pseudomonas syringae populations extracted from single and multiple host species.

Bacterial strains of the same species collected from different hosts frequently exhibit differences in gene content. In the ubiquitous plant pathogen Pseudomonas syringae, more than 30% of genes encoded by each strain are not conserved among strains colonizing other host species. Although they are often implicated in host specificity, the role of this large fraction of the genome in host-specific adaptation is largely unexplored. Here, we sought to relate variation in gene content between strains infecting different species to variation that persists between strains on the same host. We fully sequenced a collection of P. syringae strains collected from wild Arabidopsis thaliana populations in the Midwestern United States. We then compared patterns of variation observed in gene content within these A. thaliana-isolated strains to previously published P. syringae sequence from strains collected on a diversity of crop species. We find that strains collected from the same host, A. thaliana, differ in gene content by 21%, 2/3 the level of gene content variation observed across strains collected from different hosts. Furthermore, the frequency with which specific genes are present among strains collected within the same host and among strains collected from different hosts is highly correlated. This implies that most gene content variation is maintained irrespective of host association. At the same time, we identify specific genes whose presence is important for P. syringae's ability to flourish within A. thaliana. Specifically, the A. thaliana strains uniquely share a genomic island encoding toxins active against plants and surrounding microbes, suggesting a role for microbe-microbe interactions in dictating the abundance within this host. Overall, our results demonstrate that while variation in the presence of specific genes can affect the success of a pathogen within its host, the majority of gene content variation is not strongly associated with patterns of host use.

Horizontally Acquired Genes Are Often Shared between Closely Related Bacterial Species.

Horizontal gene transfer (HGT) serves as an important source of innovation for bacterial species. We used a pangenome-based approach to identify genes that were horizontally acquired by four closely related bacterial species, belonging to the Enterobacteriaceae family. This enabled us to examine the extent to which such closely related species tend to share horizontally acquired genes. We find that a high percent of horizontally acquired genes are shared among these closely related species. Furthermore, we demonstrate that the extent of sharing of horizontally acquired genes among these four closely related species is predictive of the extent to which these genes will be found in additional bacterial species. Finally, we show that acquired genes shared by more species tend to be better optimized for expression within the genomes of their new hosts. Combined, our results demonstrate the existence of a large pool of frequently horizontally acquired genes that have distinct characteristics from horizontally acquired genes that are less frequently shared between species.

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.

Human host range of Mycobacterium tuberculosis.

A new study demonstrates that the most widespread lineage of the causative agent of tuberculosis consists of both globally distributed and geographically restricted sublineages. The geographically restricted sublineages are likely able to infect only specific human populations, whereas the globally distributed ones likely have a broader human host range.

Bacterial intra-species gene loss occurs in a largely clocklike manner mostly within a pool of less conserved and constrained genes.

Gene loss is a major contributor to the evolution of bacterial gene content. Gene loss may occur as a result of shifts in environment leading to changes in the intensity and/or directionality of selection applied for the maintenance of specific genes. Gene loss may also occur in a more neutral manner, when gene functions are lost that were not subject to strong selection to be maintained, irrespective of changes to environment. Here, we used a pangenome-based approach to investigate patterns of gene loss across 15 bacterial species. We demonstrate that gene loss tends to occur mostly within a pool of genes that are less constrained within species, even in those strains from which they are not lost, and less conserved across bacterial species. Our results indicate that shifts in selection, resulting from shifts in environment are not required to explain the majority of gene loss events occurring within a diverse collection of bacterial species. Caution should therefore be taken when attributing differences in gene content to differences in environment.

The Somatic Nature of Cancer Allows It to Affect Highly Constrained Genes.

Cancer is special among genetic disorders in two major ways: first, cancer is a disease of the most basic of cellular functions, such as cell proliferation, differentiation, and the maintenance of genomic integrity. Second, in contrast to most genetic disorders that are mediated by germline (hereditary) mutations, cancer is largely a somatic disease. Here we show that these two traits are not detached and that it is the somatic nature of cancer that allows it to affect the most basic of cellular functions. We begin by demonstrating that cancer genes are both more functionally central (as measured by their patterns of expression and protein interaction) and more evolutionarily constrained than non-cancer genetic disease genes. We then compare genes that are only modified somatically in cancer (hereinafter referred to as "somatic cancer genes") to those that can also be modified in a hereditary manner, contributing to cancer development (hereinafter referred to as "hereditary cancer genes"). We show that both somatic and hereditary cancer genes are much more functionally central than genes contributing to non-cancer genetic disorders. At the same time, hereditary cancer genes are only as constrained as non-cancer hereditary disease genes, while somatic cancer genes tend to be much more constrained in evolution. Thus, it appears that it is the somatic nature of cancer that allows it to modify the most constrained genes and, therefore, affect the most basic of cellular functions.

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains.

BACKGROUND: The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. RESULTS: In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that the percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. CONCLUSIONS: Our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.

Variation in KRAS driver substitution distributions between tumor types is determined by both mutation and natural selection.

Different tumor types vary greatly in their distribution of driver substitutions. Here, we analyzed how mutation and natural selection contribute to differences in the distribution of KRAS driver substitutions between lung, colon and pancreatic adenocarcinomas. We were able to demonstrate that both differences in mutation and differences in selection drive variation in the distribution of KRAS driver substitutions between tumor types. By accounting for the effects of mutation on the distribution of KRAS driver substitutions, we could identify specific KRAS driver substitutions that are more favored by selection in specific tumor types. Such driver substitutions likely improve fitness most when they occur within the context of the tumor type in which they are preferentially favored. Fitting with this, we found that driver substitutions that are more favored by natural selection in a specific type of tumor tend to associate with worse clinical outcomes specifically in that type of tumor.

Mutation--The Engine of Evolution: Studying Mutation and Its Role in the Evolution of Bacteria.

Mutation is the engine of evolution in that it generates the genetic variation on which the evolutionary process depends. To understand the evolutionary process we must therefore characterize the rates and patterns of mutation. Starting with the seminal Luria and Delbruck fluctuation experiments in 1943, studies utilizing a variety of approaches have revealed much about mutation rates and patterns and about how these may vary between different bacterial strains and species along the chromosome and between different growth conditions. This work provides a critical overview of the results and conclusions drawn from these studies, of the debate surrounding some of these conclusions, and of the challenges faced when studying mutation and its role in bacterial evolution.