Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures

An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data

With the development of sequencing technology and analytic tools, studying within-species variations enhances the understanding of microbial biological processes. Nevertheless, most existing methods designed for strain-level analysis lack the capability to concurrently assess both strain proportions and genome-wide single nucleotide variants (SNVs) across longitudinal metagenomic samples. In this study, we introduce LongStrain, an integrated pipeline for the analysis of large-scale metagenomic data from individuals with longitudinal or repeated samples. In LongStrain, we first utilize two efficient tools, Kraken2 and Bowtie2, for the taxonomic classification and alignment of sequencing reads, respectively. Subsequently, we propose to jointly model strain proportions and shared haplotypes across samples within individuals. This approach specifically targets tracking a primary strain and a secondary strain for each subject, providing their respective proportions and SNVs as output. With extensive simulation studies of a microbial community and single species, our results demonstrate that LongStrain is superior to two genotyping methods and two deconvolution methods across a majority of scenarios. Furthermore, we illustrate the potential applications of LongStrain in the real data analysis of The Environmental Determinants of Diabetes in the Young study and a gastric intestinal metaplasia microbiome study. In summary, the proposed analytic pipeline demonstrates marked statistical efficiency over the same type of methods and has great potential in understanding the genomic variants and dynamic changes at strain level. LongStrain and its tutorial are freely available online at https://github.com/BoyanZhou/LongStrain.

IMPORTANCE

The advancement in DNA-sequencing technology has enabled the high-resolution identification of microorganisms in microbial communities. Since different microbial strains within species may contain extreme phenotypic variability (e.g., nutrition metabolism, antibiotic resistance, and pathogen virulence), investigating within-species variations holds great scientific promise in understanding the underlying mechanism of microbial biological processes. To fully utilize the shared genomic variants across longitudinal metagenomics samples collected in microbiome studies, we develop an integrated analytic pipeline (LongStrain) for longitudinal metagenomics data. It concurrently leverages the information on proportions of mapped reads for individual strains and genome-wide SNVs to enhance the efficiency and accuracy of strain identification. Our method helps to understand strains' dynamic changes and their association with genome-wide variants. Given the fast-growing longitudinal studies of microbial communities, LongStrain which streamlines analyses of large-scale raw sequencing data should be of great value in microbiome research communities.

Evolution of evolvability in rapidly adapting populations

Mutations can alter the short-term fitness of an organism, as well as the rates and benefits of future mutations. While numerous examples of these evolvability modifiers have been observed in rapidly adapting microbial populations, existing theory struggles to predict when they will be favoured by natural selection. Here we develop a mathematical framework for predicting the fates of genetic variants that modify the rates and benefits of future mutations in linked genomic regions. We derive analytical expressions showing how the fixation probabilities of these variants depend on the size of the population and the diversity of competing mutations. We find that competition between linked mutations can dramatically enhance selection for modifiers that increase the benefits of future mutations, even when they impose a strong direct cost on fitness. However, we also find that modest direct benefits can be sufficient to drive evolutionary dead ends to fixation. Our results suggest that subtle differences in evolvability could play an important role in shaping the long-term success of genetic variants in rapidly evolving microbial populations.

Genomic evidence of Escherichia coli gut population diversity translocation in leukemia patients

Escherichia coli, a commensal species of the human gut, is an opportunistic pathogen that can reach extra-intestinal compartments, including the bloodstream and the bladder, among others. In non-immunosuppressed patients, purifying or neutral evolution of E. coli populations has been reported in the gut. Conversely, it has been suggested that when migrating to extra-intestinal compartments, E. coli genomes undergo diversifying selection as supported by strong evidence for adaptation. The level of genomic polymorphism and the size of the populations translocating from gut to extra-intestinal compartments is largely unknown. To gain insights into the pathophysiology of these translocations, we investigated the level of polymorphism and the evolutionary forces acting on the genomes of 77 E. coli isolated from various compartments in three immunosuppressed patients. Each patient had a unique strain, which was a mutator in one case. In all instances, we observed that translocation encompasses much of the genomic diversity present in the gut. The same signature of selection, whether purifying or diversifying, and as anticipated, neutral for mutator isolates, was observed in both the gut and bloodstream. Additionally, we found a limited number of non-specific mutations among compartments for non-mutator isolates. In all cases, urine isolates were dominated by neutral selection. These findings indicate that substantial proportions of populations are undergoing translocation and that they present a complex compartment-specific pattern of selection at the patient level.IMPORTANCEIt has been suggested that intra and extra-intestinal compartments differentially constrain the evolution of E. coli strains. Whether host particular conditions, such as immunosuppression, could affect the strain evolutionary trajectories remains understudied. We found that, in immunosuppressed patients, large fractions of E. coli gut populations are translocating with variable modifications of the signature of selection for commensal and pathogenic isolates according to the compartment and/or the patient. Such multiple site sampling should be performed in large cohorts of patients to gain a better understanding of E. coli extra-intestinal diseases.

Navigating collateral sensitivity: insights into the mechanisms and applications of antibiotic resistance trade-offs

The swift rise of antibiotic resistance, coupled with limited new antibiotic discovery, presents a significant hurdle to global public health, demanding innovative therapeutic solutions. Recently, collateral sensitivity (CS), the phenomenon in which resistance to one antibiotic increases vulnerability to another, has come to light as a potential path forward in this attempt. Targeting either unidirectional or reciprocal CS holds promise for constraining the emergence of drug resistance and notably enhancing treatment outcomes. Typically, the alteration of bacterial physiology, such as bacterial membrane potential, expression of efflux pumps, cell wall structures, and endogenous enzymatic actions, are involved in evolved collateral sensitivity. In this review, we present a thorough overview of CS in antibiotic therapy, including its definition, importance, and underlying mechanisms. We describe how CS can be exploited to prevent the emergence of resistance and enhance the results of treatment, but we also discuss the challenges and restrictions that come with implementing this practice. Our review underscores the importance of continued exploration of CS mechanisms in the broad spectrum and clinical validation of therapeutic approaches, offering insights into its role as a valuable tool in combating antibiotic resistance.

zol & fai: large-scale targeted detection and evolutionary investigation of gene clusters

Many universally and conditionally important genes are genomically aggregated within clusters. Here, we introduce fai and zol, which together enable large-scale comparative analysis of different types of gene clusters and mobile-genetic elements (MGEs), such as biosynthetic gene clusters (BGCs) or viruses. Fundamentally, they overcome a current bottleneck to reliably perform comprehensive orthology inference at large scale across broad taxonomic contexts and thousands of genomes. First, fai allows the identification of orthologous instances of a query gene cluster of interest amongst a database of target genomes. Subsequently, zol enables reliable, context-specific inference of ortholog groups for individual protein-encoding genes across gene cluster instances. In addition, zol performs functional annotation and computes a variety of evolutionary statistics for each inferred ortholog group. Importantly, in comparison to tools for visual exploration of homologous relationships between gene clusters, zol can scale to thousands of gene cluster instances and produce detailed reports that are easy to digest. To showcase fai and zol, we apply them for: (i) longitudinal tracking of a virus in metagenomes, (ii) discovering novel population-level genetic insights of two common BGCs in the fungal species Aspergillus flavus, and (iii) uncovering large-scale evolutionary trends of a virulence-associated gene cluster across thousands of genomes from a diverse bacterial genus.

Drivers of diversification in fungal pathogen populations

To manage and treat chronic fungal diseases effectively, we require an improved understanding of their complexity. There is an increasing appreciation that chronic infection populations are often heterogeneous due to diversification and drift, even within a single microbial species. Genetically diverse populations can contribute to persistence and resistance to treatment by maintaining cells with different phenotypes capable of thriving in these dynamic environments. In chronic infections, fungal pathogens undergo prolonged challenges that can drive trait selection to convergent adapted states through restricted access to critical nutrients, assault by immune effectors, competition with other species, and antifungal drugs. This review first highlights the various genetic and epigenetic mechanisms that promote diversity in pathogenic fungal populations and provide an additional barrier to assessing the actual heterogeneity of fungal infections. We then review existing studies of evolution and genetic heterogeneity in fungal populations from lung infections associated with the genetic disease cystic fibrosis. We conclude with a discussion of open research questions that, once answered, may aid in diagnosing and treating chronic fungal infections.

Population sequencing for diversity and transmission analyses

Genomic diversity in a pathogen population is the foundation for evolution and adaptations in virulence, drug resistance, pathogenesis, and immune evasion. Characterizing, analyzing, and understanding population-level diversity is also essential for epidemiological and forensic tracking of sources and revealing detailed pathways of transmission and spread. For bacteria, culturing, isolating, and sequencing the large number of individual colonies required to adequately sample diversity can be prohibitively time-consuming and expensive. While sequencing directly from a mixed population will show variants among reads, they cannot be linked to reveal allele combinations associated with particular traits or phylogenetic inheritance patterns. Here, we describe the theory and method of how population sequencing directly from a mixed sample can be used in conjunction with sequencing a very small number of colonies to describe the phylogenetic diversity of a population without haplotype reconstruction. To demonstrate the utility of population sequencing in capturing phylogenetic diversity, we compared isogenic clones to population sequences of Burkholderia pseudomallei from the sputum of a single patient. We also analyzed population sequences of Staphylococcus aureus derived from different people and different body sites. Sequencing results confirm our ability to capture and characterize phylogenetic diversity in our samples. Our analyses of B. pseudomallei populations led to the surprising discovery that the pathogen population is highly structured in sputum, suggesting that for some pathogens, sputum sampling may preserve structuring in the lungs and thus present a non-invasive alternative to understanding colonization, movement, and pathogen/host interactions. Our analyses of S. aureus samples show how comparing phylogenetic diversity across populations can reveal directionality of transmission between hosts and across body sites, demonstrating the power and utility for characterizing the spread of disease and identification of reservoirs at the finest levels. We anticipate that population sequencing and analysis can be broadly applied to accelerate research in a broad range of fields reliant on a foundational understanding of population diversity.

Analysis of In-Patient Evolution of Escherichia coli Reveals Potential Links to Relapse of Bone and Joint Infections

Bone and joint infections (BJIs) are difficult to treat and affect a growing number of patients, in which relapses are observed in 10-20% of case. These relapses, which call for prolonged antibiotic treatment and increase resistance emergence risk, may originate from ill-understood adaptation of the pathogen to the host. Here, we investigated 3 pairs of Escherichia coli strains from BJI cases and their relapses to unravel adaptations within patients. Whole-genome comparison presented evidence for positive selection and phenotypic characterization showed that biofilm formation remained unchanged, contrary to what is usually described in such cases. Although virulence was not modified, we identified the loss of 2 virulence factors contributing to immune system evasion in one of the studied strains. Other strategies, including global growth optimization and colicin production, likely allowed the strains to outcompete competitors. This work highlights the variety of strategies allowing in-patient adaptation in BJIs.

Fast and accurate variant identification tool for sequencing-based studies

BACKGROUND

Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness.

RESULTS

We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations.

CONCLUSIONS

We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

De novo mutations mediate phenotypic switching in an opportunistic human lung pathogen

Bacteria evolving within human hosts encounter selective tradeoffs that render mutations adaptive in one context and deleterious in another. Here, we report that the cystic fibrosis-associated pathogen Burkholderia dolosa overcomes in-human selective tradeoffs by acquiring successive point mutations that alternate phenotypes. We sequenced the whole genomes of 931 respiratory isolates from two recently infected patients and an epidemiologically-linked, chronically-infected patient. These isolates are contextualized using 112 historical genomes from the same outbreak strain. Within both newly infected patients, diverse parallel mutations that disrupt O-antigen expression quickly arose, comprising 29% and 63% of their B. dolosa communities by 3 years. The selection for loss of O-antigen starkly contrasts with our previous observation of parallel O-antigen-restoring mutations after many years of chronic infection in the historical outbreak. Experimental characterization revealed that O-antigen loss increases uptake in immune cells while decreasing competitiveness in the mouse lung. We propose that the balance of these pressures, and thus whether O-antigen expression is advantageous, depends on tissue localization and infection duration. These results suggest that mutation-driven alternation during infection may be more frequent than appreciated and is underestimated without dense temporal sampling.

Within-Host Evolution of Bacterial Pathogens in Acute and Chronic Infection

Bacterial pathogens undergo remarkable adaptive change in response to the selective forces they encounter during host colonization and infection. Studies performed over the past few decades have demonstrated that many general evolutionary processes can be discerned during the course of host adaptation, including genetic diversification of lineages, clonal succession events, convergent evolution, and balanced fitness trade-offs. In some cases, elevated mutation rates resulting from mismatch repair or proofreading deficiencies accelerate evolution, and active mobile genetic elements or phages may facilitate genome plasticity. The host immune response provides another critical component of the fitness landscapes guiding adaptation, and selection operating on pathogens at this level may lead to immune evasion and the establishment of chronic infection. This review summarizes recent advances in this field, with a special focus on different forms of bacterial genome plasticity in the context of infection, and considers clinical consequences of adaptive changes for the host.

Pseudomonas syringae coffee blight is associated with the horizontal transfer of plasmid-encoded type III effectors

The emergence of new pathogens is an ongoing threat to human health and agriculture. While zoonotic spillovers received considerable attention, the emergence of crop diseases is less well studied. Here, we identify genomic factors associated with the emergence of Pseudomonas syringae bacterial blight of coffee. Fifty-three P. syringae strains from diseased Brazilian coffee plants were sequenced. Comparative and evolutionary analyses were used to identify loci associated with coffee blight. Growth and symptomology assays were performed to validate the findings. Coffee isolates clustered in three lineages, including primary phylogroups PG3 and PG4, and secondary phylogroup PG11. Genome-wide association study of the primary PG strains identified 37 loci, including five effectors, most of which were encoded on a plasmid unique to the PG3 and PG4 coffee strains. Evolutionary analyses support the emergence of coffee blight in PG4 when the coffee-associated plasmid and associated effectors derived from a divergent plasmid carried by strains associated with other hosts. This plasmid was only recently transferred into PG3. Natural diversity and CRISPR-Cas9 plasmid curing were used to show that strains with the coffee-associated plasmid grow to higher densities and cause more severe disease symptoms in coffee. This work identifies possible evolutionary mechanisms underlying the emergence of a new lineage of coffee pathogens.

Biofilm antimicrobial susceptibility testing: where are we and where could we be going?

Our knowledge about the fundamental aspects of biofilm biology, including the mechanisms behind the reduced antimicrobial susceptibility of biofilms, has increased drastically over the last decades. However, this knowledge has so far not been translated into major changes in clinical practice. While the biofilm concept is increasingly on the radar of clinical microbiologists, physicians, and healthcare professionals in general, the standardized tools to study biofilms in the clinical microbiology laboratory are still lacking; one area in which this is particularly obvious is that of antimicrobial susceptibility testing (AST). It is generally accepted that the biofilm lifestyle has a tremendous impact on antibiotic susceptibility, yet AST is typically still carried out with planktonic cells. On top of that, the microenvironment at the site of infection is an important driver for microbial physiology and hence susceptibility; but this is poorly reflected in current AST methods. The goal of this review is to provide an overview of the state of the art concerning biofilm AST and highlight the knowledge gaps in this area. Subsequently, potential ways to improve biofilm-based AST will be discussed. Finally, bottlenecks currently preventing the use of biofilm AST in clinical practice, as well as the steps needed to get past these bottlenecks, will be discussed.

Small-molecule activators of a bacterial signaling pathway inhibit virulence

The Burkholderia genus encompasses multiple human pathogens, including potential bioterrorism agents, that are often extensively antibiotic resistant. The FixLJ pathway in Burkholderia is a two-component system that regulates virulence. Previous work showed that fixLJ mutations arising during chronic infection confer increased virulence while decreasing the activity of the FixLJ pathway. We hypothesized that small-molecule activators of the FixLJ pathway could serve as anti-virulence therapies. Here, we developed a high-throughput assay that screened over 28,000 compounds and identified 11 that could specifically active the FixLJ pathway. Eight of these compounds, denoted Burkholderia Fix Activator (BFA) 1-8, inhibited the intracellular survival of Burkholderia in THP-1-dervived macrophages in a fixLJ-dependent manner without significant toxicity. One of the compounds, BFA1, inhibited the intracellular survival in macrophages of multiple Burkholderia species. Predictive modeling of the interaction of BFA1 with Burkholderia FixL suggests that BFA1 binds to the putative ATP/ADP binding pocket in the kinase domain, indicating a potential mechanism for pathway activation. These results indicate that small-molecule FixLJ pathway activators are promising anti-virulence agents for Burkholderia and define a new paradigm for antibacterial therapeutic discovery.

Comparison of genomic diversity between single and pooled Staphylococcus aureus colonies isolated from human colonization cultures

The most common approach to sampling the bacterial populations within an infected or colonized host is to sequence genomes from a single colony obtained from a culture plate. However, it is recognized that this method does not capture the genetic diversity in the population. Sequencing a mixture of several colonies (pool-seq) is a better approach to detect population heterogeneity, but it is more complex to analyse due to different types of heterogeneity, such as within-clone polymorphisms, multi-strain mixtures, multi-species mixtures and contamination. Here, we compared 8 single-colony isolates (singles) and pool-seq on a set of 2286 Staphylococcus aureus culture samples to identify features that can distinguish pure samples, samples undergoing intraclonal variation and mixed strain samples. The samples were obtained by swabbing 3 body sites on 85 human participants quarterly for a year, who initially presented with a methicillin-resistant S. aureus skin and soft-tissue infection (SSTI). We compared parameters such as sequence quality, contamination, allele frequency, nucleotide diversity and pangenome diversity in each pool to those for the corresponding singles. Comparing singles from the same culture plate, we found that 18% of sample collections contained mixtures of multiple multilocus sequence types (MLSTs or STs). We showed that pool-seq data alone could predict the presence of multi-ST populations with 95% accuracy. We also showed that pool-seq could be used to estimate the number of intra-clonal polymorphic sites in the population. Additionally, we found that the pool may contain clinically relevant genes such as antimicrobial resistance markers that may be missed when only examining singles. These results highlight the potential advantage of analysing genome sequences of total populations obtained from clinical cultures rather than single colonies.

Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data

Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs - two hosts in which infection was transmitted from one to the other - is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within-host single nucleotide variants (iSNVs) are maintained over multiple transmission steps and present a model for inferring the likelihood that a given pair of sequenced samples are linked by transmission. In this work we show that, beyond the presence and absence of within-host variants, differences arising in the relative abundance of iSNVs (allelic frequency) can infer transmission pairs more precisely. Our approach further highlights the critical role bottlenecks play in reserving the within-host diversity during transmission.

Intraspecific microdiversity and ecological drivers of lactic acid bacteria in naturally fermented milk ecosystem

Traditional fermented milks are produced by inoculating technique, which selects well-adapted microorganisms that have been passed on through generations. Few reports have used naturally fermented milks as model ecosystems to investigate the mechanism of formation of intra-species microbial diversity. Here, we isolated and whole-genome-sequenced a total of 717 lactic acid bacterial isolates obtained from 12 independent naturally fermented milks collect from 12 regions across five countries. We further analyzed the within-sample intra-species phylogenies of 214 Lactobacillus helveticus isolates, 97 Lactococcus lactis subsp. lactis isolates, and 325 Lactobacillus delbrueckii subsp. bulgaricus isolates. We observed a high degree of intra-species genomic and functional gene diversity within-/between-sample(s). Single nucleotide polymorphism-based phylogenetic reconstruction revealed great within-sample intra-species heterogeneity, evolving from multiple lineages. Further phylogenetic reconstruction (presence-absence gene profile) revealed within-sample inter-clade functional diversity (based on carbohydrate-active enzyme- and peptidase-encoding genes) in all three investigated species/subspecies. By identifying and mapping clade-specific genes of intra-sample clades of the three species/subspecies to the respective fermented milk metagenome, we found extensive potential inter-/intra-species horizontal gene transfer events. Finally, the microbial composition of the samples is closely linked to the nucleotide diversity of the respective species/subspecies. Overall, our results contribute to the conservation of lactic acid bacteria resources, providing ecological insights into the microbial ecosystem of naturally fermented dairy products.

Native microbiome dominates over host factors in shaping the probiotic genetic evolution in the gut

Probiotics often acquire potentially adaptive mutations in vivo, gaining new functional traits through gut selection. While both the host and microbiome can contribute to probiotics' genetic evolution, separating the microbiome and the host's contribution to such selective pressures remains challenging. Here, we introduced germ-free (GF) and specific pathogen-free (SPF) mouse models to track how probiotic strains, i.e., Lactiplantibacillus plantarum HNU082 (Lp082) and Bifidobacterium animalis subsp. lactis V9 (BV9), genetically evolved under selection pressures derived from host factors alone and both host and microbial ecological factors. Notably, compared to the genome of a probiotic strain before consumption, the host only elicited <15 probiotic mutations in probiotic genomes that emerged in the luminal environment of GF mice, while a total of 840 mutations in Lp082 mutants and 21,579 mutations in BV9 were found in SPF mice, <0.25% of those derived from both factors that were never captured by other experimental evolution studies, indicating that keen microbial competitions exhibited the predominant evolutionary force in shaping probiotic genetic composition (>99.75%). For a given probiotic, functional genes occurring in potentially adaptive mutations induced by hosts (GF mice) were all shared with those found in mutants of SPF mice. Collectively, the native microbiome consistently drove a more rapid and divergent genetic evolution of probiotic strains in seven days of colonization than host factors did. Our study further laid a theoretical foundation for genetically engineering probiotics for better gut adaptation through in vitro artificial gut ecosystems without the selection pressures derived from host factors.

Taxonomic Profiling of Fecal and Intestinal Microbiota in the African Turquoise Killifish Nothobranchius furzeri

Killifish are emerging as a new laboratory system in which to study a range of questions, from the genetic basis of embryo dormancy to life history trait evolution, age-dependent neurodegeneration, and the connection between microbial community structure and biology of aging. Over the past decade, advances in high-throughput sequencing have helped uncover the vast diversity of microbial communities present in environmental samples and on host epithelia. Here, we describe an optimized protocol to study the taxonomic composition of intestinal and fecal microbiota in laboratory-raised as well as natural killifish populations and provide comprehensive step-by-step instructions for tissue sampling, high-throughput genomic DNA extraction, and the generation of 16S V3V4 rRNA and 16S V4 rRNA gene libraries.

Integrating Pool-seq uncertainties into demographic inference

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures

The longstanding model is that most bloodstream infections (BSIs) are caused by a single organism. We perform whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrate that BCs contain mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibit phenotypes that are potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identify mixed fluconazole-susceptible and -resistant populations. Diversity in drug susceptibility is likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants are fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a population-based model of C. glabrata genotypic and phenotypic diversity during BSIs.

Genomic Analyses of Longitudinal Mycobacterium abscessus Isolates in a Multicenter Cohort Reveal Parallel Signatures of In-Host Adaptation

BACKGROUND

Nontuberculous mycobacteria (NTM) are ubiquitous in the environment and an increasingly frequent cause of opportunistic infections. Mycobacterium abscessus complex (MABC) is one of the major NTM lung pathogens that disproportionately colonize and infect the lungs of individuals with cystic fibrosis (CF). MABC infection can persist for years, and antimicrobial treatment is frequently ineffective.

METHODS

We sequenced the genomes of 175 isolates longitudinally collected from 30 patients with MABC lung infection. We contextualized our cohort amidst the broader MABC phylogeny and investigated genes undergoing parallel adaptation across patients. Finally, we tested the phenotypic consequences of parallel mutations by conducting antimicrobial resistance and mercury-resistance assays.

RESULTS

We identified highly related isolate pairs across hospital centers with low likelihood of transmission. We further annotated nonrandom parallel mutations in 22 genes and demonstrated altered macrolide susceptibility co-occurring with a nonsynonymous whiB1 mutation. Finally, we highlighted a 23-kb mercury-resistance plasmid whose loss during chronic infection conferred phenotypic susceptibility to organic and nonorganic mercury compounds.

CONCLUSIONS

We characterized parallel genomic processes through which MABC is adapting to promote survival within the host. The within-lineage polymorphisms we observed have phenotypic effects, potentially benefiting fitness in the host at the putative detriment of environmental survival.

Comparison of genomic diversity between single and pooled Staphylococcus aureus colonies isolated from human colonisation cultures

The most common approach to sampling the bacterial populations within an infected or colonised host is to sequence genomes from a single colony obtained from a culture plate. However, it is recognized that this method does not capture the genetic diversity in the population. An alternative is to sequence a mixture containing multiple colonies ("pool-seq"), but this has the disadvantage that it is a non-homogeneous sample, making it difficult to perform specific experiments. We compared differences in measures of genetic diversity between eight single-colony isolates (singles) and pool-seq on a set of 2286 S. aureus culture samples. The samples were obtained by swabbing three body sites on 85 human participants quarterly for a year, who initially presented with a methicillin-resistant S. aureus skin and soft-tissue infection (SSTI). We compared parameters such as sequence quality, contamination, allele frequency, nucleotide diversity and pangenome diversity in each pool to the corresponding singles. Comparing singles from the same culture plate, we found that 18% of sample collections contained mixtures of multiple Multilocus sequence types (MLSTs or STs). We showed that pool-seq data alone could predict the presence of multi-ST populations with 95% accuracy. We also showed that pool-seq could be used to estimate the number of polymorphic sites in the population. Additionally, we found that the pool may contain clinically relevant genes such as antimicrobial resistance markers that may be missed when only examining singles. These results highlight the potential advantage of analysing genome sequences of total populations obtained from clinical cultures rather than single colonies.

On-person adaptive evolution of Staphylococcus aureus during treatment for atopic dermatitis

The opportunistic pathogen Staphylococcus aureus frequently colonizes the inflamed skin of people with atopic dermatitis (AD) and worsens disease severity by promoting skin damage. Here, we show, by longitudinally tracking 23 children treated for AD, that S. aureus adapts via de novo mutations during colonization. Each patient's S. aureus population is dominated by a single lineage, with infrequent invasion by distant lineages. Mutations emerge within each lineage at rates similar to those of S. aureus in other contexts. Some variants spread across the body within months, with signatures of adaptive evolution. Most strikingly, mutations in capsule synthesis gene capD underwent parallel evolution in one patient and across-body sweeps in two patients. We confirm that capD negativity is more common in AD than in other contexts, via reanalysis of S. aureus genomes from 276 people. Together, these findings highlight the importance of the mutation level when dissecting the role of microbes in complex disease.

One population, multiple lifestyles: Commensalism and pathogenesis in the human mycobiome

Candida auris and Candida albicans can result in invasive fungal diseases. And yet, these species can stably and asymptomatically colonize human skin and gastrointestinal tracts. To consider these disparate microbial lifestyles, we first review factors shown to influence the underlying microbiome. Structured by the damage response framework, we then consider the molecular mechanisms deployed by C. albicans to switch between commensal and pathogenic lifestyles. Next, we explore this framework with C. auris to highlight how host physiology, immunity, and/or antibiotic receipt are associated with progression from colonization to infection. While treatment with antibiotics increases the risk that an individual will succumb to invasive candidiasis, the underlying mechanisms remain unclear. Here, we describe several hypotheses that may explain this phenomenon. We conclude by highlighting future directions integrating genomics with immunology to advance our understanding of invasive candidiasis and human fungal disease.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures

The longstanding paradigm is that most bloodstream infections (BSIs) are caused by a single organism. We performed whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrated that BCs contained mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibited phenotypes that were potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identified mixed fluconazole-susceptible and â€"resistant populations. Diversity in drug susceptibility was likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants were fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a new population-based paradigm of C. glabrata genotypic and phenotypic diversity during BSIs.

Within-Host Genotypic and Phenotypic Diversity of Contemporaneous Carbapenem-Resistant Klebsiella pneumoniae from Blood Cultures of Patients with Bacteremia

It is unknown whether bacterial bloodstream infections (BSIs) are commonly caused by single organisms or mixed microbial populations. We hypothesized that contemporaneous carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from blood cultures of individual patients are genetically and phenotypically distinct. We determined short-read whole-genome sequences of 10 sequence type 258 (ST258) CRKP strains from blood cultures in each of 6 patients (Illumina HiSeq). Strains clustered by patient by core genome and pan-genome phylogeny. In 5 patients, there was within-host strain diversity by gene mutations, presence/absence of antibiotic resistance or virulence genes, and/or plasmid content. Accessory gene phylogeny revealed strain diversity in all 6 patients. Strains from 3 patients underwent long-read sequencing for genome completion (Oxford Nanopore) and phenotypic testing. Genetically distinct strains within individuals exhibited significant differences in carbapenem and other antibiotic responses, capsular polysaccharide (CPS) production, mucoviscosity, and/or serum killing. In 2 patients, strains differed significantly in virulence during mouse BSIs. Genetic or phenotypic diversity was not observed among strains recovered from blood culture bottles seeded with index strains from the 3 patients and incubated in vitro at 37°C. In conclusion, we identified genotypic and phenotypic variant ST258 CRKP strains from blood cultures of individual patients with BSIs, which were not detected by the clinical laboratory or in seeded blood cultures. The data suggest a new paradigm of CRKP population diversity during BSIs, at least in some patients. If validated for BSIs caused by other bacteria, within-host microbial diversity may have implications for medical, microbiology, and infection prevention practices and for understanding antibiotic resistance and pathogenesis. IMPORTANCE The long-standing paradigm for pathogenesis of bacteremia is that, in most cases, a single organism passes through a bottleneck and establishes itself in the bloodstream (single-organism hypothesis). In keeping with this paradigm, standard practice in processing positive microbiologic cultures is to test single bacterial strains from morphologically distinct colonies. This study is the first genome-wide analysis of within-host diversity of Klebsiella pneumoniae strains recovered from individual patients with bloodstream infections (BSIs). Our finding that positive blood cultures comprised genetically and phenotypically heterogeneous carbapenem-resistant K. pneumoniae strains challenges the single-organism hypothesis and suggests that at least some BSIs are caused by mixed bacterial populations that are unrecognized by the clinical laboratory. The data support a model of pathogenesis in which pressures in vivo select for strain variants with particular antibiotic resistance or virulence attributes and raise questions about laboratory protocols and treatment decisions directed against single strains.

Detecting bacterial adaptation within individual microbiomes

The human microbiome harbours a large capacity for within-person adaptive mutations. Commensal bacterial strains can stably colonize a person for decades, and billions of mutations are generated daily within each person's microbiome. Adaptive mutations emerging during health might be driven by selective forces that vary across individuals, vary within an individual, or are completely novel to the human population. Mutations emerging within individual microbiomes might impact the immune system, the metabolism of nutrients or drugs, and the stability of the community to perturbations. Despite this potential, relatively little attention has been paid to the possibility of adaptive evolution within complex human-associated microbiomes. This review discusses the promise of studying within-microbiome adaptation, the conceptual and technical limitations that may have contributed to an underappreciation of adaptive de novo mutations occurring within microbiomes to date, and methods for detecting recent adaptive evolution. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Adaptation and Evolution of Pathogens in the Cystic Fibrosis Lung

As opposed to acute respiratory infections, the persistent bacterial infections of the lung that characterize cystic fibrosis (CF) provide ample time for bacteria to evolve and adapt. The process of adaptation is recorded in mutations that accumulate over time in the genomes of the infecting bacteria. Some of these mutations lead to obvious phenotypic differences such as antibiotic resistance or the well-known mucoid phenotype of Pseudomonas aeruginosa. Other mutations may be just as important but harder to detect such as increased mutation rates, cell surface changes, and shifts in metabolism and nutrient acquisition. Remarkably, many of the adaptations occur again and again in different patients, signaling that bacteria are adapting to solve specific challenges in the CF respiratory tract. This parallel evolution even extends across distinct bacterial species. This review addresses the bacterial systems that are known to change in long-term CF infections with a special emphasis on cross-species comparisons. Consideration is given to how adaptation may impact health in CF, and the possible evolutionary mechanisms that lead to the repeated parallel adaptations.

Persisting uropathogenic Escherichia coli lineages show signatures of niche-specific within-host adaptation mediated by mobile genetic elements

Large-scale genomic studies have identified within-host adaptation as a hallmark of bacterial infections. However, the impact of physiological, metabolic, and immunological differences between distinct niches on the pathoadaptation of opportunistic pathogens remains elusive. Here, we profile the within-host adaptation and evolutionary trajectories of 976 isolates representing 119 lineages of uropathogenic Escherichia coli (UPEC) sampled longitudinally from both the gastrointestinal and urinary tracts of 123 patients with urinary tract infections. We show that lineages persisting in both niches within a patient exhibit increased allelic diversity. Habitat-specific selection results in niche-specific adaptive mutations and genes, putatively mediating fitness in either environment. Within-lineage inter-habitat genomic plasticity mediated by mobile genetic elements (MGEs) provides the opportunistic pathogen with a mechanism to adapt to the physiological conditions of either habitat, and reduced MGE richness is associated with recurrence in gut-adapted UPEC lineages. Collectively, our results establish niche-specific adaptation as a driver of UPEC within-host evolution.

Microbial experimental evolution in a massively multiplexed and high-throughput era

Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.

Phylogenetic Characterization and Genome Sequence Analysis of Burkholderia glumae Strains Isolated in Thailand as the Causal Agent of Rice Bacterial Panicle Blight

Burkholderia glumae is one of the most critical rice-pathogenic bacteria, and it causes bacterial panicle blight (BPB) in rice plants. In 2017, BPB symptoms were observed from rice fields in Chiang Rai, Northern Thailand. Sixty-one isolates obtained from the symptomatic panicles of rice were initially identified as B. glumae by polymerase chain reaction (PCR) using species-specific primers. Among them, six selected strains isolated from the susceptible japonica rice cultivar DOA2 were characterized in terms of morpho-physiology, pathology, phylogenetics, and genomics. Our genome sequence analysis of the six selected strains revealed the presence of multiple prophages, which may reflect the high level of diversity in this bacterial species through dynamic horizontal gene transfer processes, including phage infection. This notion was supported by the results of phylogenetic and phylogenomic analyses, which showed the formation of several subgroups not related to the years of isolation or the geographical origins. This study reports the isolation of B. glumae as the causal pathogen of BPB disease in japonica rice in Thailand and provides genomic resources to better understand the biology and diversity of this plant pathogenic bacterium. Further studies with a vast collection of B. glumae strains from various rice-growing regions around the world are needed to elucidate the evolution, variability, and lifestyle of the pathogen.

Detecting Genetic Variation of Colonizing Streptococcus agalactiae Genomes in Humans: A Precision Protocol

Deciphering the genotypic diversity of within-individual pathogens and verifying the evolutionary model can help elucidate resistant genotypes, virulent subpopulations, and the mechanism of opportunistic pathogenicity. However, observed polymorphic mutations (PMs) are rare and difficult to be detected in the “dominant-lineage” model of bacterial infection due to the low frequency. The four pooled group B Streptococcus (GBS) samples were collected from the genital tracts of healthy pregnant women, and the pooled samples and the isogenic controls were genomically sequenced. Using the PMcalling program, we detected the PMs in samples and compared the results between two technical duplicates, GBS-M001T and GBS-M001C. Tested with simulated datasets, the PMcalling program showed high sensitivity especially in low-frequency PMs and reasonable specificity. The genomic sequence data from pooled samples of GBS colonizing carrier pregnant women were analyzed, and few high-frequency PMs and some low-frequency PMs were discovered, indicating a dominant-lineage evolution model. The PMs mainly were nonsynonymous and enriched in quorum sensing, glycolysis/gluconeogenesis, ATP-binding cassette (ABC) transporters, etc., suggesting antimicrobial or environmental selective pressure. The re-analysis of the published Burkholderia dolosa data showed a diverse-community model, and only a few low-frequency PMs were shared between different individuals. Genes of general control non-repressible 5-related N-acetyltransferases family, major facilitator superfamily (MFS) transporter, and ABC transporter were positive selection candidates. Our findings indicate an unreported nature of the dominant-lineage model of GBS colonization in healthy women, and a formerly not observed mutation pool in a colonized microbial community, possibly maintained by selection pressure.

Immunosuppression broadens evolutionary pathways to drug resistance and treatment failure during Acinetobacter baumannii pneumonia in mice

Acinetobacter baumannii is increasingly refractory to antibiotic treatment in healthcare settings. As is true of most human pathogens, the genetic path to antimicrobial resistance (AMR) and the role that the immune system plays in modulating AMR during disease are poorly understood. Here we reproduced several routes to fluoroquinolone resistance, performing evolution experiments using sequential lung infections in mice that are replete with or depleted of neutrophils, providing two key insights into the evolution of drug resistance. First, neutropenic hosts acted as reservoirs for the accumulation of drug resistance during drug treatment. Selection for variants with altered drug sensitivity profiles arose readily in the absence of neutrophils, while immunocompetent animals restricted the appearance of these variants. Secondly, antibiotic treatment failure in the immunocompromised host was shown to occur without clinically defined resistance, an unexpected result that provides a model for how antibiotic failure occurs clinically in the absence of AMR. The genetic mechanism underlying both these results is initiated by mutations activating the drug egress pump regulator AdeL, which drives persistence in the presence of antibiotic. Therefore, antibiotic persistence mutations present a two-pronged risk during disease, causing drug treatment failure in the immunocompromised host while simultaneously increasing the emergence of high-level AMR.

Population genetics of polymorphism and divergence in rapidly evolving populations

In rapidly evolving populations, numerous beneficial and deleterious mutations can arise and segregate within a population at the same time. In this regime, evolutionary dynamics cannot be analyzed using traditional population genetic approaches that assume that sites evolve independently. Instead, the dynamics of many loci must be analyzed simultaneously. Recent work has made progress by first analyzing the fitness variation within a population, and then studying how individual lineages interact with this traveling fitness wave. However, these "traveling wave" models have previously been restricted to extreme cases where selection on individual mutations is either much faster or much slower than the typical coalescent timescale Tc. In this work, we show how the traveling wave framework can be extended to intermediate regimes in which the scaled fitness effects of mutations (Tcs) are neither large nor small compared to one. This enables us to describe the dynamics of populations subject to a wide range of fitness effects, and in particular, in cases where it is not immediately clear which mutations are most important in shaping the dynamics and statistics of genetic diversity. We use this approach to derive new expressions for the fixation probabilities and site frequency spectra of mutations as a function of their scaled fitness effects, along with related results for the coalescent timescale Tc and the rate of adaptation or Muller's ratchet. We find that competition between linked mutations can have a dramatic impact on the proportions of neutral and selected polymorphisms, which is not simply summarized by the scaled selection coefficient Tcs. We conclude by discussing the implications of these results for population genetic inferences.

Rapid expansion and extinction of antibiotic resistance mutations during treatment of acute bacterial respiratory infections

Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5–12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.

It remains unclear how rapid antibiotic switching affects the evolution of antibiotic resistance in individual patients. Here, Chung et al. combine short- and long-read sequencing and resistance phenotyping of 420 serial isolates of Pseudomonas aeruginosa collected from the onset of respiratory infection, and show that rare resistance mutations can increase by nearly 40-fold over 5–12 days in response to antibiotic changes, while mutations conferring resistance to antibiotics not administered diminish and even go to extinction.

Mutation bias shapes the spectrum of adaptive substitutions

How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Anatomy promotes neutral coexistence of strains in the human skin microbiome

What enables strains of the same species to coexist in a microbiome? Here, we investigate whether host anatomy can explain strain co-residence of Cutibacterium acnes, the most abundant species on human skin. We reconstruct on-person evolution and migration using whole-genome sequencing of C. acnes colonies acquired from healthy subjects, including from individual skin pores, and find considerable spatial structure at the level of pores. Although lineages (sets of colonies separated by <100 mutations) with in vitro fitness differences coexist within centimeter-scale regions, each pore is dominated by a single lineage. Moreover, colonies from a pore typically have identical genomes. An absence of adaptive signatures suggests a genotype-independent source of low within-pore diversity. We therefore propose that pore anatomy imposes random single-cell bottlenecks; the resulting population fragmentation reduces competition and promotes coexistence. Our findings suggest that therapeutic interventions involving pore-dwelling species might focus on removing resident populations over optimizing probiotic fitness.

Comparative Population Genetics in the Human Gut Microbiome

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

The nutritional environment is sufficient to select coexisting biofilm and quorum-sensing mutants of Pseudomonas aeruginosa

The evolution of bacterial populations during infections can be influenced by various factors including available nutrients, the immune system, and competing microbes, rendering it difficult to identify the specific forces that select on evolved traits. The genomes of Pseudomonas aeruginosa isolated from the airway of patients with cystic fibrosis (CF), for example, have revealed commonly mutated genes, but which phenotypes led to their prevalence is often uncertain. Here, we focus on effects of nutritional components of the CF airway on genetic adaptations by P. aeruginosa grown in either well-mixed (planktonic) or biofilm-associated conditions. After only 80 generations of experimental evolution in a simple medium with glucose, lactate, and amino acids, all planktonic populations diversified into lineages with mutated genes common to CF infections: morA, encoding a regulator of biofilm formation, or lasR, encoding a quorum sensing regulator that modulates the expression of virulence factors. Although mutated quorum sensing is often thought to be selected in vivo due to altered virulence phenotypes or social cheating, isolates with lasR mutations demonstrated increased fitness when grown alone and outcompeted the ancestral PA14 strain. Nonsynonymous SNPs in morA increased fitness in a nutrient concentration-dependent manner during planktonic growth and surprisingly also increased biofilm production. Populations propagated in biofilm conditions also acquired mutations in loci associated with chronic infections, including lasR and cyclic-di-GMP regulators roeA and wspF. These findings demonstrate that nutrient conditions and biofilm selection are sufficient to select mutants with problematic clinical phenotypes including increased biofilm and altered quorum sensing. Importance Pseudomonas aeruginosa produces dangerous chronic infections that are known for their rapid diversification and recalcitrance to treatment. We performed evolution experiments to identify adaptations selected by two specific aspects of the CF respiratory environment: nutrient levels and surface attachment. Propagation of P. aeruginosa in nutrients present within the CF airway was sufficient to drive diversification into subpopulations with identical mutations in regulators of biofilm and quorum sensing to those arising during infection. Thus, the adaptation of opportunistic pathogens to nutrients found in the host may select mutants with phenotypes that complicate treatment and clearance of infection.

Pneumococcal within-host diversity during colonization, transmission and treatment

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

Genomic diversity of Helicobacter pylori populations from different regions of the human stomach

Individuals infected with Helicobacter pylori harbor unique and diverse populations of quasispecies, but diversity between and within different regions of the human stomach and the process of bacterial adaptation to each location are not yet well understood. We applied whole-genome deep sequencing to characterize the within- and between-stomach region genetic diversity of H. pylori populations from paired antrum and corpus biopsies of 15 patients, along with single biopsies from one region of an additional 3 patients, by scanning allelic diversity. We combined population deep sequencing with more conventional sequencing of multiple H. pylori single colony isolates from individual biopsies to generate a unique dataset. Single colony isolates were used to validate the scanning allelic diversity pipelines. We detected extensive population allelic diversity within the different regions of each patient's stomach. Diversity was most commonly found within non-coding, hypothetical, outer membrane, restriction modification system, virulence, lipopolysaccharide biosynthesis, efflux systems, and chemotaxis-associated genes. Antrum and corpus populations from the same patient grouped together phylogenetically, indicating that most patients were initially infected with a single strain, which then diversified. Single colonies from the antrum and corpus of the same patients grouped into distinct clades, suggesting mechanisms for within-location adaptation across multiple H. pylori isolates from different patients. The comparisons made available by combined sequencing and analysis of isolates and populations enabled comprehensive analysis of the genetic changes associated with H. pylori diversification and stomach region adaptation.

A population-level strain genotyping method to study pathogen strain dynamics in human infections

A hallmark of chronic bacterial infections is the long-term persistence of 1 or more pathogen species at the compromised site. Repeated detection of the same bacterial species can suggest that a single strain or lineage is continually present. However, infection with multiple strains of a given species, strain acquisition and loss, and changes in strain relative abundance can occur. Detecting strain-level changes and their effects on disease is challenging because most methods require labor-intensive isolate-by-isolate analyses, and thus, only a few cells from large infecting populations can be examined. Here, we present a population-level method for enumerating and measuring the relative abundance of strains called population multi-locus sequence typing (PopMLST). The method exploits PCR amplification of strain-identifying polymorphic loci, next-generation sequencing to measure allelic variants, and informatic methods to determine whether variants arise from sequencing errors or low-abundance strains. These features enable PopMLST to simultaneously interrogate hundreds of bacterial cells that are cultured en masse from patient samples or are present in DNA directly extracted from clinical specimens without ex vivo culture. This method could be used to detect epidemic or super-infecting strains, facilitate understanding of strain dynamics during chronic infections, and enable studies that link strain changes to clinical outcomes.

Combining Ivacaftor and Intensive Antibiotics Achieves Limited Clearance of Cystic Fibrosis Infections

Drugs called CFTR modulators improve the physiologic defect underlying cystic fibrosis (CF) and alleviate many disease manifestations. However, studies to date indicate that chronic lung infections that are responsible for most disease-related mortality generally persist. Here, we investigated whether combining the CFTR modulator ivacaftor with an intensive 3.5-month antibiotic course could clear chronic Pseudomonas aeruginosa or Staphylococcus aureus lung infections in subjects with R117H-CFTR, who are highly ivacaftor-responsive. Ivacaftor alone improved CFTR activity, and lung function and inflammation within 48 h, and reduced P. aeruginosa and S. aureus pathogen density by ∼10-fold within a week. Antibiotics produced an additional ∼10-fold reduction in pathogen density, but this reduction was transient in subjects who remained infected. Only 1/5 P. aeruginosa-infected and 1/7 S. aureus-infected subjects became persistently culture-negative after the combined treatment. Subjects appearing to clear infection did not have particularly favorable baseline lung function or inflammation, pathogen density or antibiotic susceptibility, or bronchiectasis scores on CT scans, but they did have remarkably low sweat chloride values before and after ivacaftor. All persistently P. aeruginosa-positive subjects remained infected by their pretreatment strain, whereas subjects persistently S. aureus-positive frequently lost and gained strains. This work suggests chronic CF infections may resist eradication despite marked and rapid modulator-induced improvements in lung infection and inflammation parameters and aggressive antibiotic treatment.

Evaluation of Antimicrobial Susceptibility Testing Methods for Burkholderia cenocepacia and Burkholderia multivorans Isolates from Cystic Fibrosis Patients

The Burkholderia cepacia complex (BCC) is known for causing serious lung infections in people with cystic fibrosis (CF). These infections can require lung transplantation, eligibility for which may be guided by antimicrobial susceptibility testing (AST). While the Clinical and Laboratory Standards Institute recommends AST for BCC, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) does not, due to poor method performance and correlation with clinical outcomes. Furthermore, limited data exist on the performance of automated AST methods for BCC. To address these issues, reproducibility and accuracy were evaluated for disk diffusion (DD), broth microdilution (BMD), and MicroScan WalkAway using 50 B. cenocepacia and 50 B. multivorans isolates collected from people with CF. The following drugs were evaluated in triplicate: chloramphenicol (CAM), ceftazidime (CAZ), meropenem (MEM), trimethoprim-sulfamethoxazole (TMP-SMX), minocycline (MIN), levofloxacin (LVX), ciprofloxacin (CIP), and piperacillin-tazobactam (PIP-TAZ). BMD reproducibility was ≥ 95% for MEM and MIN only, and MicroScan WalkAway reproducibility was similar to BMD. DD reproducibility was < 90% for all drugs tested when a 3 mm cut-off was applied. When comparing the accuracy of DD to BMD, only MEM met all acceptance criteria. TMP-SMX and LVX had high minor errors, CAZ had unacceptable very major errors (VME), and MIN, PIP-TAZ, and CIP had both unacceptable minor errors and VMEs. For MicroScan WalkAway, no drugs met acceptance criteria. Analyses also showed that errors were not attributed to one species. In general, our data agree with EUCAST recommendations.

Bacterial genomic epidemiology with mixed samples

Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

Rapid methicillin resistance diversification in Staphylococcus epidermidis colonizing human neonates

Early in life, infants are colonized with multiple bacterial strains whose differences in gene content can have important health consequences. Metagenomics-based approaches have revealed gene content differences between different strains co-colonizing newborns, but less is known about the rate, mechanism, and phenotypic consequences of gene content diversification within strains. Here, focusing on Staphylococcus epidermidis, we whole-genome sequence and phenotype more than 600 isolates from newborns. Within days of birth, infants are co-colonized with a highly personalized repertoire of S. epidermidis strains, which are spread across the newborn body. Comparing the genomes of multiple isolates of each strain, we find very little evidence of adaptive evolution via single-nucleotide polymorphisms. By contrast, we observe gene content differences even between otherwise genetically identical cells, including variation of the clinically important methicillin resistance gene, mecA, suggesting rapid gene gain and loss events at rates higher than point mutations. Mapping the genomic architecture of structural variants by long-read Nanopore sequencing, we find that deleted regions were always flanked by direct repeats, consistent with site-specific recombination. However, we find that even within a single genetic background, recombination occurs at multiple, often non-canonical repeats, leading to the rapid evolution of patient-specific diverse structural variants in the SCCmec island and to differences in antibiotic resistance.

Single-genome sequencing reveals within-host evolution of human malaria parasites

Population genomics of bulk malaria infections is unable to examine intrahost evolution; therefore, most work has focused on the role of recombination in generating genetic variation. We used single-cell sequencing protocol for low-parasitaemia infections to generate 406 near-complete single Plasmodium vivax genomes from 11 patients sampled during sequential febrile episodes. Parasite genomes contain hundreds of de novo mutations, showing strong signatures of selection, which are enriched in the ApiAP2 family of transcription factors, known targets of adaptation. Comparing 315 P. falciparum single-cell genomes from 15 patients with our P. vivax data, we find broad complementary patterns of de novo mutation at the gene and pathway level, revealing the importance of within-host evolution during malaria infections.

Bacterial evolution during human infection: Adapt and live or adapt and die

Microbes are constantly evolving. Laboratory studies of bacterial evolution increase our understanding of evolutionary dynamics, identify adaptive changes, and answer important questions that impact human health. During bacterial infections in humans, however, the evolutionary parameters acting on infecting populations are likely to be much more complex than those that can be tested in the laboratory. Nonetheless, human infections can be thought of as naturally occurring in vivo bacterial evolution experiments, which can teach us about antibiotic resistance, pathogenesis, and transmission. Here, we review recent advances in the study of within-host bacterial evolution during human infection and discuss practical considerations for conducting such studies. We focus on 2 possible outcomes for de novo adaptive mutations, which we have termed "adapt-and-live" and "adapt-and-die." In the adapt-and-live scenario, a mutation is long lived, enabling its transmission on to other individuals, or the establishment of chronic infection. In the adapt-and-die scenario, a mutation is rapidly extinguished, either because it carries a substantial fitness cost, it arises within tissues that block transmission to new hosts, it is outcompeted by more fit clones, or the infection resolves. Adapt-and-die mutations can provide rich information about selection pressures in vivo, yet they can easily elude detection because they are short lived, may be more difficult to sample, or could be maladaptive in the long term. Understanding how bacteria adapt under each of these scenarios can reveal new insights about the basic biology of pathogenic microbes and could aid in the design of new translational approaches to combat bacterial infections.