The distribution of fitness effects among synonymous mutations in a gene under directional selection

NeMu: a comprehensive pipeline for accurate reconstruction of neutral mutation spectra from evolutionary data

The recognized importance of mutational spectra in molecular evolution is yet to be fully exploited beyond human cancer studies and model organisms. The wealth of intraspecific polymorphism data in the GenBank repository, covering a broad spectrum of genes and species, presents an untapped opportunity for detailed mutational spectrum analysis. Existing methods fall short by ignoring intermediate substitutions on the inner branches of phylogenetic trees and lacking the capability for cross-species mutational comparisons. To address these challenges, we present the NeMu pipeline, available at https://nemu-pipeline.com, a tool grounded in phylogenetic principles designed to provide comprehensive and scalable analysis of mutational spectra. Utilizing extensive sequence data from numerous available genome projects, NeMu rapidly and accurately reconstructs the neutral mutational spectrum. This tool, facilitating the reconstruction of gene- and species-specific mutational spectra, contributes to a deeper understanding of evolutionary mechanisms across the broad spectrum of known species.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.

Mutation Rate and Effective Population Size of the Model Cooperative Bacterium Myxococcus xanthus

Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include effective population size (Ne), genome size, and gametic multicellularity, with the latter being associated with both increased mutation rates and decreased effective population sizes. However, data sufficient to test for possible relationships between microbial multicellularity and mutation rate (µ) are lacking. Here, we report estimates of two key population-genetic parameters, Ne and µ, for Myxococcus xanthus, a bacterial model organism for the study of aggregative multicellular development, predation, and social swarming. To estimate µ, we conducted an ∼400-day mutation accumulation experiment with 46 lineages subjected to regular single colony bottlenecks prior to clonal regrowth. Upon conclusion, we sequenced one clonal-isolate genome per lineage. Given collective evolution for 85,323 generations across all lines, we calculate a per base-pair mutation rate of ∼5.5 × 10-10 per site per generation, one of the highest mutation rates among free-living eubacteria. Given our estimate of µ, we derived Ne at ∼107 from neutral diversity at four-fold degenerate sites across two dozen M. xanthus natural isolates. This estimate is below average for eubacteria and strengthens an already clear negative correlation between µ and Ne in prokaryotes. The higher and lower than average mutation rate and Ne for M. xanthus, respectively, amplify the question of whether any features of its multicellular life cycle-such as group-size reduction during fruiting-body development-or its highly structured spatial distribution have significantly influenced how these parameters have evolved.

The distribution of fitness effects during adaptive walks using a simple genetic network

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

A repertoire of single nucleotide polymorphisms (SNPs) of major fecundity BMPR1B gene among 75 sheep breeds worldwide

The BMPR1B gene is a major determinant of sheep reproductive capacity. Previous studies revealed that Q249R (FecB) is a profound variant of BMPR1B that influences the ovulation rate and litter size in sheep. However, unlike Q249R locus, the full spectrum of single nucleotide polymorphisms (SNPs) within BMPR1B has not been extensively studied. A systematic screen of SNPs in BMPR1B would facilitate the discovery of novel variants that are associated with litter size. This study aimed to investigate SNPs in the BMPR1B gene via whole genome sequence (WGS) data from 2409 individuals of 75 sheep breeds worldwide. Herein, a total of 9688 variants were screened, among which 15 were coding variants and 8 were novel changes. Specifically, we presented the most comprehensive frequency distribution map of the well-known FecB mutation to date. Besides, among the above-mentioned SNPs, one synonymous mutation (g.30050773C > T) was found to be likely under selection and is potentially associated with fecundity in Duolang sheep. Thus, our study greatly expands the variation repertoire of the ovine BMPR1B gene and provides a valuable resource for exploring causative mutations and genetic markers associated with litter size.

CRISPR-Cas9-assisted genome editing in E. coli elevates the frequency of unintended mutations

Cas-assisted lambda Red recombineering techniques have rapidly become a mainstay of bacterial genome editing. Such techniques have been used to construct both individual mutants and massive libraries to assess the effects of genomic changes. We have found that a commonly used Cas9-assisted editing method results in unintended mutations elsewhere in the genome in 26% of edited clones. The unintended mutations are frequently found over 200 kb from the intended edit site and even over 10 kb from potential off-target sites. We attribute the high frequency of unintended mutations to error-prone polymerases expressed in response to dsDNA breaks introduced at the edit site. Most unintended mutations occur in regulatory or coding regions and thus may have phenotypic effects. Our findings highlight the risks associated with genome editing techniques involving dsDNA breaks in E. coli and likely other bacteria and emphasize the importance of sequencing the genomes of edited cells to ensure the absence of unintended mutations.

Fitness benefits of a synonymous substitution in an ancient EF-Tu gene depend on the genetic background

Synonymous mutations are changes to DNA sequence, which occur within translated genes but which do not affect the protein sequence. Although often referred to as silent mutations, evidence suggests that synonymous mutations can affect gene expression, mRNA stability, and even translation efficiency. A collection of both experimental and bioinformatic data has shown that synonymous mutations can impact cell phenotype, yet less is known about the molecular mechanisms and potential of beneficial or adaptive effects of such changes within evolved populations. Here, we report a beneficial synonymous mutation acquired via experimental evolution in an essential gene variant encoding the translation elongation factor protein EF-Tu. We demonstrate that this particular synonymous mutation increases EF-Tu mRNA and protein levels as well as global polysome abundance on RNA transcripts. Although presence of the synonymous mutation is clearly causative of such changes, we also demonstrate that fitness benefits are highly contingent on other potentiating mutations present within the genetic background in which the mutation arose. Our results underscore the importance of beneficial synonymous mutations, especially those that affect levels of proteins that are key for cellular processes.IMPORTANCEThis study explores the degree to which synonymous mutations in essential genes can influence adaptation in bacteria. An experimental system whereby an Escherichia coli strain harboring an engineered translation protein elongation factor-Tu (EF-Tu) was subjected to laboratory evolution. We find that a synonymous mutation acquired on the gene encoding for EF-Tu is conditionally beneficial for bacterial fitness. Our findings provide insight into the importance of the genetic background when a synonymous substitution is favored by natural selection and how such changes have the potential to impact evolution when critical cellular processes are involved.

Laboratory domestication of Lactiplantibacillus plantarum alters some phenotypic traits but causes non-novel genomic impact

AIMS

Laboratory domestication has been negligibly examined in lactic acid bacteria (LAB). Lactiplantibacillus plantarum is a highly studied and industrially relevant LAB. Here, we passaged L. plantarum JGR2 in a complex medium to study the effects of domestication on the phenotypic properties and the acquisition of mutations.

METHODS AND RESULTS

Lactiplantibacillus plantarum JGR2 was passaged in mMRS medium (deMan Rogossa Sharpe supplemented with 0.05% w/v L-cysteine) in three parallel populations for 70 days. One pure culture from each population was studied for various phenotypic properties and genomic alterations. Auto-aggregation of the evolved strains was significantly reduced, and lactic acid production and ethanol tolerance were increased. Other probiotic properties and antibiotic sensitivity were not altered. Conserved synonymous and non-synonymous mutations were observed in mobile element proteins (transposases), β-galactosidase, and phosphoketolases in all three isolates. The evolved strains lost all the repeat regions and some of the functions associated with them. Most of the conserved mutations were found in the genomes of other wild-type strains available in a public database, indicating the non-novel genomic impact of laboratory passaging.

CONCLUSIONS

Laboratory domestication can affect the phenotypic and genotypic traits of L. plantarum and similar studies are necessary for other important species of LAB.

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer

BACKGROUND

Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations.

RESULTS

Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation.

CONCLUSION

Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

Molecular bases for strong phenotypic effects of single synonymous codon substitutions in the E. coli ccdB toxin gene

BACKGROUND

Single synonymous codon mutations typically have only minor or no effects on gene function. Here, we estimate the effects on cell growth of ~ 200 single synonymous codon mutations in an operonic context by mutating almost all positions of ccdB, the 101-residue long cytotoxin of the ccdAB Toxin-Antitoxin (TA) operon to most degenerate codons. Phenotypes were assayed by transforming the mutant library into CcdB sensitive and resistant E. coli strains, isolating plasmid pools, and subjecting them to deep sequencing. Since autoregulation is a hallmark of TA operons, phenotypes obtained for ccdB synonymous mutants after transformation in a RelE toxin reporter strain followed by deep sequencing provided information on the amount of CcdAB complex formed.

RESULTS

Synonymous mutations in the N-terminal region involved in translation initiation showed the strongest non-neutral phenotypic effects. We observe an interplay of numerous factors, namely, location of the codon, codon usage, t-RNA abundance, formation of anti-Shine Dalgarno sequences, predicted transcript secondary structure, and evolutionary conservation in determining phenotypic effects of ccdB synonymous mutations. Incorporation of an N-terminal, hyperactive synonymous mutation, in the background of the single synonymous codon mutant library sufficiently increased translation initiation, such that mutational effects on either folding or termination of translation became more apparent. Introduction of putative pause sites not only affects the translational rate, but might also alter the folding kinetics of the protein in vivo.

CONCLUSION

In summary, the study provides novel insights into diverse mechanisms by which synonymous mutations modulate gene function. This information is useful in optimizing heterologous gene expression in E. coli and understanding the molecular bases for alteration in gene expression that arise due to synonymous mutations.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

A beneficial synonymous substitution in EF-Tu is contingent on genetic background

Synonymous mutations are changes to DNA sequence that occur within translated genes but which do not affect the protein sequence. Although often referred to as silent mutations, evidence suggests that synonymous mutations can affect gene expression, mRNA stability, and even translation efficiency. A collection of both experimental and bioinformatic data has shown that synonymous mutations can impact cell phenotype, yet less is known about the molecular mechanisms and potential of beneficial or adaptive effects of such changes within evolved populations. Here, we report a beneficial synonymous mutation acquired via experimental evolution in an essential gene variant encoding the translation Elongation Factor protein EF-Tu. We demonstrate that this particular synonymous mutation increases EF-Tu mRNA and protein levels, as well as the polysome abundance on global transcripts. Although presence of the synonymous mutation is clearly causative of such changes, we also demonstrate that fitness benefits are highly contingent on other potentiating mutations present within the genetic background in which the mutation arose. Our results underscore the importance of beneficial synonymous mutations, especially those that affect levels of proteins that are key for cellular processes.

Developmental Selection and the Perception of Mutation Bias

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

Evolutionary barriers to horizontal gene transfer in macrophage-associated Salmonella

Horizontal gene transfer (HGT) is a powerful evolutionary force facilitating bacterial adaptation and emergence of novel phenotypes. Several factors, including environmental ones, are predicted to restrict HGT, but we lack systematic and experimental data supporting these predictions. Here, we address this gap by measuring the relative fitness of 44 genes horizontally transferred from Escherichia coli to Salmonella enterica in infection-relevant environments. We estimated the distribution of fitness effects in each environment and identified that dosage-dependent effects across different environments are a significant barrier to HGT. The majority of genes were found to be deleterious. We also found longer genes had stronger negative fitness consequences than shorter ones, showing that gene length was negatively associated with HGT. Furthermore, fitness effects of transferred genes were found to be environmentally dependent. In summary, a substantial fraction of transferred genes had a significant fitness cost on the recipient, with both gene characteristics and the environment acting as evolutionary barriers to HGT.

Fine mapping of a Fusarium crown rot resistant locus on chromosome arm 6HL in barley by exploiting near isogenic lines, transcriptome profiling, and a large near isogenic line-derived population

KEY MESSAGE

This study reported validation and fine mapping of a Fusarium crown rot resistant locus on chromosome arm 6HL in barley using near isogenic lines, transcriptome sequences, and a large near isogenic line-derived population. Fusarium crown rot (FCR), caused by Fusarium pseudograminearum, is a chronic and serious disease affecting cereal production in semi-arid regions globally. The increasing prevalence of this disease in recent years is attributed to the widespread adoption of minimum tillage and stubble retention practices. In the study reported here, we generated eight pairs of near isogenic lines (NILs) targeting a putative QTL (Qcrs.caf-6H) conferring FCR resistance in barley. Assessing the NILs confirmed the large effect of this locus. Aimed to develop markers that can be reliably used in incorporating this resistant allele into breeding programs and identify candidate genes, transcriptomic analyses were conducted against three of the NIL pairs and a large NIL-derived population consisting of 1085 F7 recombinant inbred lines generated. By analyzing the transcriptomic data and the fine mapping population, Qcrs.caf-6H was delineated into an interval of 0.9 cM covering a physical distance of ~ 547 kb. Six markers co-segregating with this locus were developed. Based on differential gene expression and SNP variations between the two isolines among the three NIL pairs, candidate genes underlying the resistance at this locus were detected. These results would improve the efficiency of incorporating the targeted locus into barley breeding programs and facilitate the cloning of causal gene(s) responsible for the resistance.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

The adaptive evolution of cancer driver genes

BACKGROUND

Cancer is a life-threatening disease in humans; yet, cancer genes are frequently reported to be under positive selection. This suggests an evolutionary-genetic paradox in which cancer evolves as a secondary product of selection in human beings. However, systematic investigation of the evolution of cancer driver genes is sparse.

RESULTS

Using comparative genomics analysis, population genetics analysis and computational molecular evolutionary analysis, the evolution of 568 cancer driver genes of 66 cancer types were evaluated at two levels, selection on the early evolution of humans (long timescale selection in the human lineage during primate evolution, i.e., millions of years), and recent selection in modern human populations (~ 100,000 years). Results showed that eight cancer genes covering 11 cancer types were under positive selection in the human lineage (long timescale selection). And 35 cancer genes covering 47 cancer types were under positive selection in modern human populations (recent selection). Moreover, SNPs associated with thyroid cancer in three thyroid cancer driver genes (CUX1, HERC2 and RGPD3) were under positive selection in East Asian and European populations, consistent with the high incidence of thyroid cancer in these populations.

CONCLUSIONS

These findings suggest that cancer can be evolved, in part, as a by-product of adaptive changes in humans. Different SNPs at the same locus can be under different selection pressures in different populations, and thus should be under consideration during precision medicine, especially for targeted medicine in specific populations.

Localized coevolution between microbial predator and prey alters community-wide gene expression and ecosystem function

Closely interacting microbial species pairs (e.g., predator and prey) can become coadapted via reciprocal natural selection. A fundamental challenge in evolutionary ecology is to untangle how coevolution in small species groups affects and is affected by biotic interactions in diverse communities. We conducted an experiment with a synthetic 30-species bacterial community where we experimentally manipulated the coevolutionary history of a ciliate predator and one bacterial prey species from the community. Altering the coevolutionary history of the focal prey species had little effect on community structure or carrying capacity in the presence or absence of the coevolved predator. However, community metabolic potential (represented by per-cell ATP concentration) was significantly higher in the presence of both the coevolved focal predator and prey. This ecosystem-level response was mirrored by community-wide transcriptional shifts that resulted in the differential regulation of nutrient acquisition and surface colonization pathways across multiple bacterial species. Our findings show that the disruption of localized coevolution between species pairs can reverberate through community-wide transcriptional networks even while community composition remains largely unchanged. We propose that these altered expression patterns may signal forthcoming evolutionary and ecological change.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Conversion of Escherichia coli into Mixotrophic CO2 Assimilation with Malate and Hydrogen Based on Recombinant Expression of 2-Oxoglutarate:Ferredoxin Oxidoreductase Using Adaptive Laboratory Evolution

We report the mixotrophic growth of Escherichia coli based on recombinant 2-oxoglutarate:ferredoxin oxidoreductase (OGOR) to assimilate CO₂ using malate as an auxiliary carbon source and hydrogen as an energy source. We employ a long-term (~184 days) two-stage adaptive evolution to convert heterotrophic E. coli into mixotrophic E. coli. In the first stage of evolution with serine, diauxic growth emerges as a prominent feature. At the end of the second stage of evolution with malate, the strain exhibits mixotrophy with CO₂ as an essential substrate for growth. We expect this work will open new possibilities in the utilization of OGOR for microbial CO₂ assimilation and future hydrogen-based electro-microbial conversion.

Deep mutational scanning of essential bacterial proteins can guide antibiotic development

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. Here, we perform deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing, and study the effect of the mutations in their original genomic context. We use more than 17,000 variants of the proteins to interrogate protein function and the importance of individual amino acids in supporting viability. Additionally, we exploit these libraries to study resistance development against antimicrobial compounds that target the selected proteins. Among the three proteins studied, MurA seems to be the superior antimicrobial target due to its low mutational flexibility, which decreases the chance of acquiring resistance-conferring mutations that simultaneously preserve MurA function. Additionally, we rank anti-LpxC lead compounds for further development, guided by the number of resistance-conferring mutations against each compound. Our results show that deep mutational scanning studies can be used to guide drug development, which we hope will contribute towards the development of novel antimicrobial therapies.

Genome-wide sequencing identifies a thermal-tolerance related synonymous mutation in the mussel, Mytilisepta virgata

The roles of synonymous mutations for adapting to stressful thermal environments are of fundamental biological and ecological interests but poorly understood. To study whether synonymous mutations influence thermal adaptation at specific microhabitats, a genome-wide genotype-phenotype association analysis is carried out in the black mussels Mytilisepta virgata. A synonymous mutation of Ubiquitin-specific Peptidase 15 (MvUSP15) is significantly associated with the physiological upper thermal limit. The individuals carrying GG genotype (the G-type) at the mutant locus possess significantly lower heat tolerance compared to the individuals carrying GA and AA genotypes (the A-type). When heated to sublethal temperature, the G-type exhibit higher inter-individual variations in MvUSP15 expression, especially for the mussels on the sun-exposed microhabitats. Taken together, a synonymous mutation in MvUSP15 can affect the gene expression profile and interact with microhabitat heterogeneity to influence thermal resistance. This integrative study sheds light on the ecological importance of adaptive synonymous mutations as an underappreciated genetic buffer against heat stress and emphasizes the importance of integrative studies at a microhabitat scale for evaluating and predicting the impacts of climate change.

Gut to lung translocation and antibiotic mediated selection shape the dynamics of Pseudomonas aeruginosa in an ICU patient

Bacteria have the potential to translocate between sites in the human body, but the dynamics and consequences of within-host bacterial migration remain poorly understood. Here we investigate the link between gut and lung Pseudomonas aeruginosa populations in an intensively sampled ICU patient using a combination of genomics, isolate phenotyping, host immunity profiling, and clinical data. Crucially, we show that lung colonization in the ICU was driven by the translocation of P. aeruginosa from the gut. Meropenem treatment for a suspected urinary tract infection selected for elevated resistance in both the gut and lung. However, resistance was driven by parallel evolution in the gut and lung coupled with organ specific selective pressures, and translocation had only a minor impact on AMR. These findings suggest that reducing intestinal colonization of Pseudomonas may be an effective way to prevent lung infections in critically ill patients.

Recurrent emergence of Klebsiella pneumoniae carbapenem resistance mediated by an inhibitory ompK36 mRNA secondary structure

Outer membrane porins in Gram-negative bacteria facilitate antibiotic influx. In Klebsiella pneumoniae, modifications in the porin OmpK36 are implicated in increasing resistance to carbapenems. An analysis of large K. pneumoniae genome collections, encompassing major healthcare-associated clones, revealed the recurrent emergence of a synonymous cytosine-to-thymine transition at position 25 (25c > t) in ompK36. We show that the 25c > t transition increases carbapenem resistance through depletion of OmpK36 from the outer membrane. The mutation attenuates K. pneumoniae in a murine pneumonia model, which accounts for its limited clonal expansion observed by phylogenetic analysis. However, in the context of carbapenem treatment, the 25c > t transition tips the balance toward treatment failure, thus accounting for its recurrent emergence. Mechanistically, the 25c > t transition mediates an intramolecular messenger RNA (mRNA) interaction between a uracil encoded by 25t and the first adenine within the Shine-Dalgarno sequence. This specific interaction leads to the formation of an RNA stem structure, which obscures the ribosomal binding site thus disrupting translation. While mutations reducing OmpK36 expression via transcriptional silencing are known, we uniquely demonstrate the repeated selection of a synonymous ompK36 mutation mediating translational suppression in response to antibiotic pressure.

The High Mutational Sensitivity of ccdA Antitoxin Is Linked to Codon Optimality

Deep mutational scanning studies suggest that synonymous mutations are typically silent and that most exposed, nonactive-site residues are tolerant to mutations. Here, we show that the ccdA antitoxin component of the Escherichia coli ccdAB toxin-antitoxin system is unusually sensitive to mutations when studied in the operonic context. A large fraction (∼80%) of single-codon mutations, including many synonymous mutations in the ccdA gene shows inactive phenotype, but they retain native-like binding affinity towards cognate toxin, CcdB. Therefore, the observed phenotypic effects are largely not due to alterations in protein structure/stability, consistent with a large region of CcdA being intrinsically disordered. E. coli codon preference and strength of ribosome-binding associated with translation of downstream ccdB gene are found to be major contributors of the observed ccdA mutant phenotypes. In select cases, proteomics studies reveal altered ratios of CcdA:CcdB protein levels in vivo, suggesting that the ccdA mutations likely alter relative translation efficiencies of the two genes in the operon. We extend these results by studying single-site synonymous mutations that lead to loss of function phenotypes in the relBE operon upon introduction of rarer codons. Thus, in their operonic context, genes are likely to be more sensitive to both synonymous and nonsynonymous point mutations than inferred previously.

Paternal factors in recurrent pregnancy loss: an insight through analysis of non-synonymous single-nucleotide polymorphism in human testis-specific chaperone HSPA2 gene

Heat shock protein A2 (HSPA2) is a testis-specific molecular chaperone of the 70 kDa heat shock protein (HSP70) family and reported to play a key role in spermatogenesis as well as in the remodelling of the sperm surface during capacitation. It is established that mice lacking HSPA2 gene are infertile and spermatozoa that fail to interact with the zona pellucida of the oocyte consistently lack HSPA2 protein expression. However, its role in post fertilization events is not fully understood. Owing to the importance of HSPA2 in male reproduction, the present study is undertaken to reveal the association between genetic mutation and phenotypic variation in recurrent pregnancy loss (RPL) patients through an in silico prediction analysis. In this study, we used different computational tools and servers such as SIFT, PolyPhen2, PROVEAN, nsSNPAnalyzer, and SNPs & GO to analyse the functional consequences of the nsSNPs in human HSPA2 gene. The most damaging amino acid variants generated were subjected to I-Mutant 2.0 and ConSurf. Post-translational modifications such as phosphorylation mediated by these deleterious nsSNPs were analysed using NetPhos 2.0, and gene-gene interaction study was conducted using GeneMANIA. Finally, in-depth studies of the nsSNPs were studied through Project HOPE. The findings of the study revealed 18 nsSNPs to be deleterious using a combinatorial bioinformatic approach. Further functional analysis suggests that screening of nsSNP variants of HSPA2 that tend to be conserved and has potential to undergo phosphorylation at critical positions (rs764410231, rs200951589, rs756852956) may be useful for predicting outcome in altered reproductive outcome. The physicochemical alterations and its impact on the structural and functional conformity were determined by Project HOPE. Gene-gene interaction depicts its close association with antioxidant enzyme (SOD1) strongly supporting an inefficient oxidative scavenging regulatory mechanism in the spermatozoa of RPL patients as reported earlier. The present study has thus identified high-risk deleterious nsSNPs of HSPA2 gene and would be beneficial in the diagnosis and prognosis of the paternal effects in RPL patients.

Synonymous mutations in representative yeast genes are mostly strongly non-neutral

Synonymous mutations in protein-coding genes do not alter protein sequences and are thus generally presumed to be neutral or nearly neutral^1-5. Here, to experimentally verify this presumption, we constructed 8,341 yeast mutants each carrying a synonymous, nonsynonymous or nonsense mutation in one of 21 endogenous genes with diverse functions and expression levels and measured their fitness relative to the wild type in a rich medium. Three-quarters of synonymous mutations resulted in a significant reduction in fitness, and the distribution of fitness effects was overall similar-albeit nonidentical-between synonymous and nonsynonymous mutations. Both synonymous and nonsynonymous mutations frequently disturbed the level of mRNA expression of the mutated gene, and the extent of the disturbance partially predicted the fitness effect. Investigations in additional environments revealed greater across-environment fitness variations for nonsynonymous mutants than for synonymous mutants despite their similar fitness distributions in each environment, suggesting that a smaller proportion of nonsynonymous mutants than synonymous mutants are always non-deleterious in a changing environment to permit fixation, potentially explaining the common observation of substantially lower nonsynonymous than synonymous substitution rates. The strong non-neutrality of most synonymous mutations, if it holds true for other genes and in other organisms, would require re-examination of numerous biological conclusions about mutation, selection, effective population size, divergence time and disease mechanisms that rely on the assumption that synoymous mutations are neutral.

Genomics of diversification of Pseudomonas aeruginosa in cystic fibrosis lung-like conditions

Pseudomonas aeruginosa is among the most problematic opportunistic pathogens for adults with cystic fibrosis (CF), causing repeated and resilient infections in the lung and surrounding airways. Evidence suggests that long-term infections are associated with diversification into specialized types but the underlying cause of that diversification and the effect it has on the persistence of infections remains poorly understood. Here, we use evolve-and-resequence experiments to investigate the genetic changes accompanying rapid, de novo phenotypic diversification in lab environments designed to mimic two aspects of human lung ecology: spatial structure and complex nutritional content. After ∼220 generations of evolution, we find extensive genetic variation present in all environments, including those that most closely resemble the CF lung. We use the abundance and frequency of nonsynonymous and synonymous mutations to estimate the ratio of mutations that are selectively neutral (hitchhikers) to those that are under positive selection (drivers). A significantly lower proportion of driver mutations in spatially structured populations suggests that reduced dispersal generates subpopulations with reduced effective population size, decreasing the supply of beneficial mutations and causing more divergent evolutionary trajectories. In addition, we find mutations in a handful of genes typically associated with chronic infection in the CF lung, including one gene associated with antibiotic resistance. This demonstrates that many of the genetic changes considered to be hallmarks of CF lung adaptation can arise as a result of adaptation to a novel environment and do not necessarily require antimicrobial treatment, immune system suppression, or competition from other microbial species to occur.

Kin selection for cooperation in natural bacterial populations

Bacteria secrete many molecules outside the cell, where they provide benefits to other cells. One potential reason for producing these “public goods” is that they benefit closely related cells that share the gene for cooperation (kin selection). While many laboratory studies have supported this hypothesis, there is a lack of evidence that kin selection favors cooperation in natural populations. We examined bacterial genomes from the environment and used population genetics theory to analyze the DNA sequences. Our analyses suggest that public goods cooperation has indeed been favored by kin selection in natural populations.

Bacteria produce a range of molecules that are secreted from the cell and can provide a benefit to the local population of cells. Laboratory experiments have suggested that these “public goods” molecules represent a form of cooperation, favored because they benefit closely related cells (kin selection). However, there is a relative lack of data demonstrating kin selection for cooperation in natural populations of bacteria. We used molecular population genetics to test for signatures of kin selection at the genomic level in natural populations of the opportunistic pathogen Pseudomonas aeruginosa. We found consistent evidence from multiple traits that genes controlling putatively cooperative traits have higher polymorphism and greater divergence and are more likely to harbor deleterious mutations relative to genes controlling putatively private traits, which are expressed at similar rates. These patterns suggest that cooperative traits are controlled by kin selection, and we estimate that the relatedness for social interactions in P. aeruginosa is r = 0.84. More generally, our results demonstrate how molecular population genetics can be used to study the evolution of cooperation in natural populations.

Strong Selection and High Mutation Supply Characterize Experimental Chlorovirus Evolution

Characterizing how viruses evolve expands our understanding of the underlying fundamental processes, such as mutation, selection and drift. One group of viruses whose evolution has not yet been extensively studied is the Phycodnaviridae, a globally abundant family of aquatic large double-stranded (ds) DNA viruses. Here we studied the evolutionary change of Paramecium bursaria chlorella virus 1 during experimental coevolution with its algal host. We used pooled genome sequencing of six independently evolved populations to characterize genomic change over five time points. Across six experimental replicates involving either strong or weak demographic fluctuations, we found single nucleotide polymorphisms (SNPs) at sixty-seven sites. The occurrence of genetic variants was highly repeatable, with just two of the SNPs found in only a single experimental replicate. Three genes A122/123R, A140/145R and A540L showed an excess of variable sites, providing new information about potential targets of selection during Chlorella–Chlorovirus coevolution. Our data indicated that the studied populations were not mutation-limited and experienced strong positive selection. Our investigation highlighted relevant processes governing the evolution of aquatic large dsDNA viruses, which ultimately contributes to a better understanding of the functioning of natural aquatic ecosystems.

Ratios can be misleading for detecting selection

Lukáš Kratochvíl and Michail Rovatsos respond to the recent study by Thibault Leroy and colleagues on island songbirds.

Variation of natural selection in the Amoebozoa reveals heterogeneity across the phylogeny and adaptive evolution in diverse lineages

The evolution and diversity of the supergroup Amoebozoa is complex and poorly understood. The supergroup encompasses predominantly amoeboid lineages characterized by extreme diversity in phenotype, behavior and genetics. The study of natural selection, a driving force of diversification, within and among species of Amoebozoa will play a crucial role in understanding the evolution of the supergroup. In this study, we searched for traces of natural selection based on a set of highly conserved protein-coding genes in a phylogenetic framework from a broad sampling of amoebozoans. Using these genes, we estimated substitution rates and inferred patterns of selective pressure in lineages and sites with various models. We also examined the effect of selective pressure on codon usage bias and potential correlations with observed biological traits and habitat. Results showed large heterogeneity of selection across lineages of Amoebozoa, indicating potential species-specific optimization of adaptation to their diverse ecological environment. Overall, lineages in Tubulinea had undergone stronger purifying selection with higher average substitution rates compared to Discosea and Evosea. Evidence of adaptive evolution was observed in some representative lineages and in a gene (Rpl7a) within Evosea, suggesting potential innovation and beneficial mutations in these lineages. Our results revealed that members of the fast-evolving lineages, Entamoeba and Cutosea, all underwent strong purifying selection but had distinct patterns of codon usage bias. For the first time, this study revealed an overall pattern of natural selection across the phylogeny of Amoebozoa and provided significant implications on their distinctive evolutionary processes.

Genome-wide association study of gastric cancer- and duodenal ulcer-derived Helicobacter pylori strains reveals discriminatory genetic variations and novel oncoprotein candidates

Genome-wide association studies (GWASs) can reveal genetic variations associated with a phenotype in the absence of any hypothesis of candidate genes. The problem of false-positive sites linked with the responsible site might be bypassed in bacteria with a high homologous recombination rate, such as Helicobacter pylori, which causes gastric cancer. We conducted a small-sample GWAS (125 gastric cancer cases and 115 controls) followed by prediction of gastric cancer and control (duodenal ulcer) H. pylori strains. We identified 11 single nucleotide polymorphisms (eight amino acid changes) and three DNA motifs that, combined, allowed effective disease discrimination. They were often informative of the underlying molecular mechanisms, such as electric charge alteration at the ligand-binding pocket, alteration in subunit interaction, and mode-switching of DNA methylation. We also identified three novel virulence factors/oncoprotein candidates. These results provide both defined targets for further informatic and experimental analyses to gain insights into gastric cancer pathogenesis and a basis for identifying a set of biomarkers for distinguishing these H. pylori-related diseases.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

Golden Gate Assembly of Aerobic and Anaerobic Microbial Bioreporters

Microbial bioreporters provide direct insight into cellular processes by producing a quantifiable signal dictated by reporter gene expression. The core of a bioreporter is a genetic circuit in which a reporter gene (or operon) is fused to promoter and regulatory sequences that govern its expression. In this study, we develop a system for constructing novel Escherichia coli bioreporters based on Golden Gate assembly, a synthetic biology approach for the rapid and seamless fusion of DNA fragments. Gene circuits are generated by fusing promoter and reporter sequences encoding yellow fluorescent protein, mCherry, bacterial luciferase, and an anaerobically active flavin-based fluorescent protein. We address a barrier to the implementation of Golden Gate assembly by designing a series of compatible destination vectors that can accommodate the assemblies. We validate the approach by measuring the activity of constitutive bioreporters and mercury and arsenic biosensors in quantitative exposure assays. We also demonstrate anaerobic quantification of mercury and arsenic in biosensors that produce flavin-based fluorescent protein, highlighting the expanding range of redox conditions that can be examined by microbial bioreporters. IMPORTANCE Microbial bioreporters are versatile genetic tools with wide-ranging applications, particularly in the field of environmental toxicology. For example, biosensors that produce a signal output in the presence of a specific analyte offer less costly alternatives to analytical methods for the detection of environmental toxins such as mercury and arsenic. Biosensors of specific toxins can also be used to test hypotheses regarding mechanisms of uptake, toxicity, and biotransformation. In this study, we develop an assembly platform that uses a synthetic biology technique to streamline construction of novel Escherichia coli bioreporters that produce fluorescent or luminescent signals either constitutively or in response to mercury and arsenic exposure. Beyond the synthesis of novel biosensors, our assembly platform can be adapted for numerous applications, including labelling bacteria for fluorescent microscopy, developing gene expression systems, and modifying bacterial genomes.

Molecular signatures of Janthinobacterium lividum from Trinidad support high potential for crude oil metabolism

Background

Janthinobacterium lividum is considered to be a psychrotrophic bacterial species. For the first time in the literature, J. lividum strains were isolated from Trinidad presenting with atypical features - hydrocarbonoclastic and able to survive in a tropical environment.

Methods

Identification of the Trinidad strains was carried out through 16S rRNA phylogenetic analysis. Gene-specific primers were designed to target the VioA which encodes violacein pigment and the EstA/B gene which encodes secreted extracellular lipase. Bioinformatics analyses were carried out on the nucleotide and amino acid sequences of VioA and EstA/B genes of the Trinidad Janthinobacterium strains to assess functionality and phylogenetic relatedness to other Janthinobacterium sequences specifically and more broadly, to other members of the Oxalobacteraceae family of betaproteobacteria.

Results

16S rRNA confirmed the identity of the Trinidad strains as J. lividum and resolved three of the Trinidad strains at the intra-specific level. Typical motility patterns of this species were recorded. VioAp sequences were highly conserved, however, synonymous substitutions located outside of the critical sites for enzyme function were detected for the Trinidad strains. Comparisons with PDB 6g2p model from aa231 to aa406 further indicated no functional disruption of the VioA gene of the Trinidad strains. Phylogeny of the VioA protein sequences inferred placement of all J. lividum taxa into a highly supported species-specific clade (bs = 98%). EstA/Bp sequences were highly conserved, however, synonymous substitutions were detected that were unique to the Trinidad strains. Phylogenetic inference positioned the Trinidad consensus VioA and EstA protein sequences in a clearly distinct branch.

Conclusions

The findings showed that the primary sequence of VioAp and EstA/Bp were unique to the Trinidad strains and these molecular signatures were reflected in phylogenetic inference. Our results supported chemotaxis, possible elective inactivation of VioA gene expression and secreted lipase activity as survival mechanisms of the Trinidad strains in petrogenic conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02346-4.

A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes

Mutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify. In this work, we reveal that a near-deterministic genetic hotspot can be built and broken by a handful of silent mutations. We observe this when studying homologous immotile variants of the bacteria Pseudomonas fluorescens, AR2 and Pf0-2x. AR2 resurrects motility through highly repeatable de novo mutation of the same nucleotide in >95% lines in minimal media (ntrB A289C). Pf0-2x, however, evolves via a number of mutations meaning the two strains diverge significantly during adaptation. We determine that this evolutionary disparity is owed to just 6 synonymous variations within the ntrB locus, which we demonstrate by swapping the sites and observing that we are able to both break (>95% to 0%) and build (0% to 80%) a deterministic mutational hotspot. Our work reveals a key role for silent genetic variation in determining adaptive outcomes.

Population Structure, Genetic Connectivity, and Signatures of Local Adaptation of the Giant Black Tiger Shrimp (Penaeus monodon) throughout the Indo-Pacific Region

The giant black tiger shrimp (Penaeus monodon) is native to the Indo-Pacific and is the second most farmed penaeid shrimp species globally. Understanding genetic structure, connectivity, and local adaptation among Indo-Pacific black tiger shrimp populations is important for informing sustainable fisheries management and aquaculture breeding programs. Population genetic and outlier detection analyses were undertaken using 10,593 genome-wide single nucleotide polymorphisms (SNPs) from 16 geographically disparate Indo-Pacific P. monodon populations. Levels of genetic diversity were highest for Southeast Asian populations and were lowest for Western Indian Ocean (WIO) populations. Both neutral (n = 9,930) and outlier (n = 663) loci datasets revealed a pattern of strong genetic structure of P. monodon corresponding with broad geographical regions and clear genetic breaks among samples within regions. Neutral loci revealed seven genetic clusters and the separation of Fiji and WIO clusters from all other clusters, whereas outlier loci revealed six genetic clusters and high genetic differentiation among populations. The neutral loci dataset estimated five migration events that indicated migration to Southeast Asia from the WIO, with partial connectivity to populations in both oceans. We also identified 26 putatively adaptive SNPs that exhibited significant Pearson correlation (P < 0.05) between minor allele frequency and maximum or minimum sea surface temperature. Matched transcriptome contig annotations suggest putatively adaptive SNPs involvement in cellular and metabolic processes, pigmentation, immune response, and currently unknown functions. This study provides novel genome-level insights that have direct implications for P. monodon aquaculture and fishery management practices.

Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

BACKGROUND

Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest.

METHODS

We analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues.

RESULTS

We identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research.

CONCLUSIONS

Based on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/ . These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.

Green, yellow or black? Genetic differentiation and adaptation signatures in a highly migratory marine turtle

Marine species may exhibit genetic structure accompanied by phenotypic differentiation related to adaptation despite their high mobility. Two shape-based morphotypes have been identified for the green turtle (Chelonia mydas) in the Pacific Ocean: the south-central/western or yellow turtle and north-central/eastern or black turtle. The genetic differentiation between these morphotypes and the adaptation of the black turtle to environmentally contrasting conditions of the eastern Pacific region has remained a mystery for decades. Here we addressed both questions using a reduced-representation genome approach (Dartseq; 9473 neutral SNPs) and identifying candidate outlier loci (67 outlier SNPs) of biological relevance between shape-based morphotypes from eight Pacific foraging grounds (n = 158). Our results support genetic divergence between morphotypes, probably arising from strong natal homing behaviour. Genes and enriched biological functions linked to thermoregulation, hypoxia, melanism, morphogenesis, osmoregulation, diet and reproduction were found to be outliers for differentiation, providing evidence for adaptation of C. mydas to the eastern Pacific region and suggesting independent evolutionary trajectories of the shape-based morphotypes. Our findings support the evolutionary distinctness of the enigmatic black turtle and contribute to the adaptive research and conservation genomics of a long-lived and highly mobile vertebrate.

Effects of synonymous mutations beyond codon bias: The evidence for adaptive synonymous substitutions from microbial evolution experiments

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be 'seen' by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution.

Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria

Synonymous codon substitutions are not always selectively neutral as revealed by several types of analyses, including studies of codon usage patterns among genes. We analyzed codon usage in 13 bacterial genomes sampled from across a large order of bacteria, Enterobacterales, and identified presumptively neutral and selected classes of synonymous substitutions. To estimate substitution rates, given a neutral/selected classification of synonymous substitutions, we developed a flexible [Formula: see text] substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of [Formula: see text] includes only the strictly neutral class of synonymous substitutions. On average, the value of [Formula: see text] under the MSS model was 80% of that under the standard codon model in which all synonymous substitutions are assumed to be neutral. The indication is that conventional [Formula: see text] analyses overestimate these values and thus overestimate the frequency of positive diversifying selection and underestimate the strength of purifying selection. To quantify the strength of selection necessary to explain this reduction, we developed a model of selected compensatory codon substitutions. The reduction in synonymous substitution rate, and thus the contribution that selection makes to codon bias variation among genes, can be adequately explained by very weak selection, with a mean product of population size and selection coefficient, [Formula: see text].

Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes

Background

Genes implicated in tumorigenesis often exhibit diverse sets of genomic variants in the tumor cohorts within which they are frequently mutated. For many genes, neither the transcriptomic effects of these variants nor their relationship to one another in cancer processes have been well-characterized. We sought to identify the downstream expression effects of these mutations and to determine whether this heterogeneity at the genomic level is reflected in a corresponding heterogeneity at the transcriptomic level.

Results

By applying a novel hierarchical framework for organizing the mutations present in a cohort along with machine learning pipelines trained on samples’ expression profiles we systematically interrogated the signatures associated with combinations of mutations recurrent in cancer. This allowed us to catalogue the mutations with discernible downstream expression effects across a number of tumor cohorts as well as to uncover and characterize over a hundred cases where subsets of a gene’s mutations are clearly divergent in their function from the remaining mutations of the gene. These findings successfully replicated across a number of disease contexts and were found to have clear implications for the delineation of cancer processes and for clinical decisions.

Conclusions

The results of cataloguing the downstream effects of mutation subgroupings across cancer cohorts underline the importance of incorporating the diversity present within oncogenes in models designed to capture the downstream effects of their mutations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04147-y.

From genotype to phenotype: adaptations of Pseudomonas aeruginosa to the cystic fibrosis environment

Pseudomonas aeruginosa is one of the main microbial species colonizing the lungs of cystic fibrosis patients and is responsible for the decline in respiratory function. Despite the hostile pulmonary environment, P. aeruginosa is able to establish chronic infections thanks to its strong adaptive capacity. Various longitudinal studies have attempted to compare the strains of early infection with the adapted strains of chronic infection. Thanks to new '-omics' techniques, convergent genetic mutations, as well as transcriptomic and proteomic dysregulations have been identified. As a consequence of this evolution, the adapted strains of P. aeruginosa have particular phenotypes that promote persistent infection.

The Genomic Basis of Rapid Adaptation to Antibiotic Combination Therapy in Pseudomonas aeruginosa

Combination therapy is a common antibiotic treatment strategy that aims at minimizing the risk of resistance evolution in several infectious diseases. Nonetheless, evidence supporting its efficacy against the nosocomial opportunistic pathogen Pseudomonas aeruginosa remains elusive. Identification of the possible evolutionary paths to resistance in multidrug environments can help to explain treatment outcome. For this purpose, we here performed whole-genome sequencing of 127 previously evolved populations of P. aeruginosa adapted to sublethal doses of distinct antibiotic combinations and corresponding single-drug treatments, and experimentally characterized several of the identified variants. We found that alterations in the regulation of efflux pumps are the most favored mechanism of resistance, regardless of the environment. Unexpectedly, we repeatedly identified intergenic variants in the adapted populations, often with no additional mutations and usually associated with genes involved in efflux pump expression, possibly indicating a regulatory function of the intergenic regions. The experimental analysis of these variants demonstrated that the intergenic changes caused similar increases in resistance against single and multidrug treatments as those seen for efflux regulatory gene mutants. Surprisingly, we could find no substantial fitness costs for a majority of these variants, most likely enhancing their competitiveness toward sensitive cells, even in antibiotic-free environments. We conclude that the regulation of efflux is a central target of antibiotic-mediated selection in P. aeruginosa and that, importantly, changes in intergenic regions may represent a usually neglected alternative process underlying bacterial resistance evolution, which clearly deserves further attention in the future.

Fine-scale population structure and evidence for local adaptation in Australian giant black tiger shrimp (Penaeus monodon) using SNP analysis

BACKGROUND

Restrictions to gene flow, genetic drift, and divergent selection associated with different environments are significant drivers of genetic differentiation. The black tiger shrimp (Penaeus monodon), is widely distributed throughout the Indian and Pacific Oceans including along the western, northern and eastern coastline of Australia, where it is an important aquaculture and fishery species. Understanding the genetic structure and the influence of environmental factors leading to adaptive differences among populations of this species is important for farm genetic improvement programs and sustainable fisheries management.

RESULTS

Based on 278 individuals obtained from seven geographically disparate Australian locations, 10,624 high-quality SNP loci were used to characterize genetic diversity, population structure, genetic connectivity, and adaptive divergence. Significant population structure and differentiation were revealed among wild populations (average F_ST = 0.001-0.107; p <  0.05). Eighty-nine putatively outlier SNPs were identified to be potentially associated with environmental variables by using both population differentiation (BayeScan and PCAdapt) and environmental association (redundancy analysis and latent factor mixed model) analysis methods. Clear population structure with similar spatial patterns were observed in both neutral and outlier markers with three genetically distinct groups identified (north Queensland, Northern Territory, and Western Australia). Redundancy, partial redundancy, and multiple regression on distance matrices analyses revealed that both geographical distance and environmental factors interact to generate the structure observed across Australian P. monodon populations.

CONCLUSION

This study provides new insights on genetic population structure of Australian P. monodon in the face of environmental changes, which can be used to advance sustainable fisheries management and aquaculture breeding programs.

Groundwater promotes emergence of asporogenic mutants of emetic Bacillus cereus

Bacillus cereus is a ubiquitous endospore-forming bacterium, which mainly affects humans as a food-borne pathogen. Bacillus cereus can contaminate groundwater used to irrigate food crops. Here, we examined the ability of the emetic strain B. cereus F4810/72 to survive abiotic conditions encountered in groundwater. Our results showed that vegetative B. cereus cells rapidly evolved in a mixed population composed of endospores and asporogenic variants bearing spo0A mutations. One asporogenic variant, VAR-F48, was isolated and characterized. VAR-F48 can survive in sterilized groundwater over a long period in a vegetative form and has a competitive advantage compared to its parental strain. Proteomics analysis allowed us to quantify changes to cellular and exoproteins after 24 and 72 h incubation in groundwater, for VAR-F48 compared to its parental strain. The results revealed a significant re-routing of the metabolism in the absence of Spo0A. We concluded that VAR-F48 maximizes its energy use to deal with oligotrophy, and the emergence of spo0A-mutated variants may contribute to the persistence of emetic B. cereus in natural oligotrophic environments.