Biology subjects

Corander, J.

Publications and source records attributed to Corander, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

PlasmidEC and gplas2: An optimised short-read approach to predict and reconstruct antibiotic resistance plasmids in Escherichia coli

Accurate reconstruction of Escherichia coli antibiotic resistance gene (ARG) plasmids from Illumina sequencing data has proven to be a challenge with current bioinformatic tools. In this work, we present an improved method to reconstruct E. coli plasmids using short reads. We developed plasmidEC, an ensemble classifier that identifies plasmid-derived contigs by combining the output of three different binary classification tools. We showed that plasmidEC is especially suited to classify contigs derived from ARG plasmids with a high recall of 0.941. Additionally, we optimised gplas, a graph-based tool that bins plasmid-predicted contigs into distinct plasmid predictions. Gplas2 is more effective at recovering plasmids with large sequencing coverage variations and can be combined with the output of any binary classifier. The combination of plasmidEC with gplas2 showed a high completeness (median=0.818) and F1-score (median=0.812) when reconstructing ARG plasmids and exceeded the binning capacity of the reference-based method MOB-suite. In the absence of long read data, our method offers an excellent alternative to reconstruct ARG plasmids in E. coli. Data SummaryNo new sequencing data have been generated in this study. All genomes used in this research are publicly available at the GenBank and Sequence Read Archive of the National Center for Biotechnology Information. Accession numbers are specified in Supplementary Materials. Scripts to reproduce the results reported in this manuscript can be accessed at https://gitlab.com/jpaganini/ecoli-binary-classifier. The ensemble classifier, plasmidEC, is publicly available at https://gitlab.com/mmb-umcu/plasmidEC (release 1.3.1), and gplas2 (release 1.0.0) can be found at https://gitlab.com/mmb-umcu/gplas2. Impact StatementEscherichia coli has emerged as a highly pervasive multidrug resistant pathogen on a global scale. The dissemination of resistance is significantly influenced by plasmids, mobile genetic elements that facilitate the transfer of antimicrobial resistance genes within and between diverse bacterial species. Consequently, precise and high-throughput identification of plasmids is imperative for effective genomic surveillance of resistance. However, accurate plasmid reconstruction remains challenging with the use of affordable short-read sequencing data. In this work, we present a novel method to accurately predict and reconstruct E. coli plasmids based on Illumina data. Additionally, we demonstrate that our approach outperforms the reference-based method MOB-suite, especially when reconstructing plasmids carrying antimicrobial resistance genes.

bioinformatics↗

bioRxiv2023

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Population genomics has revolutionised our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that the majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data.

bioinformatics↗

bioRxiv2023

Identification of selective sweeps in bacteria

Selective sweeps occur when a beneficial mutation spreads rapidly throughout the population due to natural selection. Searching for selective sweeps has proved to be one of the most fruitful ways to detect the footprints selection leaves on the genome. With a plethora of detection tools, the study of selective sweeps in eukaryotic systems is a well-established field of research. However, the search for fragment-specific selective sweeps among bacterial strains received little to no attention so far. In our work, we demonstrate that inter-strains locus-specific selective sweeps can be detected in bacteria. We introduce the SINCOPA algorithm, the first phylogeny-based method for soft and incomplete selective sweeps detection. We use SINCOPA to explore inter-strains locus-specific selective sweeps in a dataset containing more than 500 microbial genomes. We observe strong evidence in several loci for locus-specific selective sweeps including genes involved in biofilm formation and others that are related to coping with various unfavorable environmental conditions. SINCOPA is freely accessible as a user-friendly web server application at https://sincopa.tau.ac.il/.

bioinformatics↗

bioRxiv2023

Self-supervised learning for DNA sequences with circular dilated convolutional networks

Due to their intrinsic properties, DNA molecules commonly exhibit long-range interactions along a linear sequence representation. Taking this information into account when modeling DNA sequences is therefore important for obtaining more accurate sequence-based inference. Many deep learning methods have recently been developed for this purpose, but they still suffer from two major issues. First, the existing methods can only handle short DNA fragments, thereby losing longerrange interactions. Second, the current methods require massive supervised labeling while missing most order information within the sequences. Consequently, there is a need to develop an efficient deep neural network modeling framework to extract wide contextual information for more accurate sequence-based inference tasks. Our new framework, named Revolution, takes full DNA sequences as input, without any condensation, and can give accurate predictions for DNA sequences up to 10kbp. In variant effect prediction, our method increases the Area Under the Receiver Operating Characteristics (AUROC) by 19.61% on 49 human tissues on average. Revolution is also demonstrated to work on the plant sequences by improving 2.36% AUROC on average for predicting open chromatin regions (OCRs). The data, models, and code can be freely accessed at https://github.com/wiedersehne/Revolution-DNAPretraining.

bioinformatics↗

bioRxiv2022

Consistent typing of plasmids with the mge-cluster pipeline

Extrachromosomal elements of bacterial cells such as plasmids are notorious for their importance in evolution and adaptation to changing ecology. However, high-resolution population-wide analysis of plasmids has only become accessible recently with the advent of scalable long-read sequencing technology. Current typing methods for the classification of plasmids remain limited in their scope which motivated us to develop a computationally efficient approach to simultaneously recognize novel types and classify plasmids into previously identified groups. Our method can easily handle thousands of input sequences which are compressed using a unitig representation in a de Bruijn graph. We provide an intuitive visualization, classification and clustering scheme that users can explore interactively. This provides a framework that can be easily distributed and replicated, enabling a consistent labelling of plasmids across past, present, and future sequence collections. We illustrate the attractive features of our approach by the analysis of population-wide plasmid data from the opportunistic pathogen Escherichia coli and the distribution of the colistin resistance gene mcr-1.1 in the plasmid population.

bioinformatics↗

bioRxiv2022

Multi-drug resistant E. coli displace commensal E. coli from the intestinal tract, a trait associated with elevated levels of genetic diversity in carbohydrate metabolism genes.

Extra-intestinal pathogenic E. coli (ExPEC) can cause a variety of infections outside of the intestine and are a major causative agent of urinary tract infections. Treatment of these infections is increasingly frustrated by antimicrobial resistance (AMR) diminishing the number of effective therapies available to clinicians. Incidence of multi-drug resistance (MDR) is not uniform across the phylogenetic spectrum of E. coli. Instead AMR is concentrated in select lineages, such as ST131, which are MDR pandemic clones that have spread AMR globally. Using a gnotobiotic mouse model we demonstrate that an MDR E. coli ST131 is capable out-competing and displacing non-MDR E. coli from the gut in vivo. This is achieved in the absence of antibiotic treatment mediating a selective advantage. In mice colonised with non-MDR E. coli strains, challenge with MDR E. coli either by oral gavage or co-housing with MDR E. coli colonized mice results in displacement and dominant intestinal colonization by MDR E. coli ST131. To investigate the genetic basis of this superior gut colonization ability by MDR E. coli, we used a functional pangenomic analysis of 19,571 E. coli genomes revealing that carriage of AMR genes is associated with increased diversity in carbohydrate metabolism genes. The data presented here demonstrate that independent of antibiotic selective pressures, MDR E. coli display a competitive advantage to colonise the mammalian gut and points to a vital role of metabolism in the evolution and success of MDR lineages of E. coli via carriage and spread.

microbiology↗

bioRxiv2022

The population-level impact of Enterococcus faecalis genetics on intestinal colonisation and extraintestinal infection

Enterococcus faecalis is a commensal pathogenic bacterium commonly found in the human gastrointestinal tract and a cause of opportunistic infections typically associated with multidrug resistance. The E. faecalis genetic changes associated with pathogenicity and extraintestinal infection, particularly through gut-to-bloodstream translocation, are poorly understood. Here, we investigate the E. faecalis genetic signatures associated with intestinal colonisation and extraintestinal infection and infection of hospitalised and non-hospitalised individuals using heritability estimation and a genome-wide association study (GWAS). We analysed 750 whole-genome sequences of faecal and bloodstream E. faecalis isolates from hospitalised patients and non-hospitalised individuals, respectively, predominantly in Europe. We found that E. faecalis infection of individuals depending on their hospitalisation status and extraintestinal infection are heritable traits and that [~]24% and [~]34% of their variation is explained by the considered genetic effects, respectively. Further, a GWAS using linear mixed models did not pinpoint any clear enrichment of individual genetic changes in isolates from different isolation sites and individuals with varying hospitalisation statuses, suggesting that these traits are highly polygenic. Altogether, our findings indicate that E. faecalis infection and extraintestinal infection are influenced by variation in genetic, host, and environmental factors, and ultimately the opportunistic pathogenic lifestyle of this versatile host generalist bacterium.

microbiology↗

bioRxiv2022

The highly diverse and complex plasmid population found in Escherichia coli colonising travellers to Laos and their role in antimicrobial resistance gene carriage

Increased colonisation by antimicrobial resistant organisms is closely associated with international travel. This study investigated the diversity of mobile genetic elements involved with antimicrobial resistance (AMR) gene carriage in extended-spectrum beta-lactamase (ESBL) -producing Escherichia coli that colonised travellers to Laos. Long-read sequencing was used to reconstruct complete plasmid sequences from 49 isolates obtained from the daily stool samples of 23 travellers over a three-week period. This method revealed a collection of 105 distinct plasmids, 38.1% of which carried AMR genes. The plasmids in this population were diverse, mostly unreported and included 38 replicon types, with F-type plasmids (n=22) the most prevalent amongst those carrying AMR genes. Fine-scale analysis of all plasmids identified numerous AMR gene contexts and emphasised the importance of IS elements, specifically members of the IS6/IS26 family, in the creation of complex multi-drug resistance regions. We found a concerning convergence of ESBL and colistin resistance determinants, with three plasmids from two different F-type lineages carrying blaCTX-M and mcr genes. The extensive diversity seen here highlights the worrying probability that stable new vehicles for AMR will evolve in E. coli populations that can disseminate internationally through travel networks. Impact StatementThe global spread of AMR is closely associated with international travel. AMR is a severe global concern and has compromised treatment options for many bacterial pathogens, among them pathogens carrying ESBL and colistin resistance genes. Colonising MDR organisms have the potential to cause serious consequences. Infections caused by MDR bacteria are associated with longer hospitalisation, poorer patient outcomes, greater mortality, and higher costs compared to infections with susceptible bacteria. This study elucidates the numerous different types of plasmids carrying AMR genes in colonising ESBL-producing E. coli isolates found in faecal samples from in travellers to Vientiane, Laos. Here we add to known databases of AMR plasmids by adding these MDR plasmids found in Southeast Asia, an area of high AMR prevalence. We characterised novel AMR plasmids including complex ESBL (blaCTX-M) and colistin (mcr) resistance co-carriage plasmids, emphasising the potential exposure of travellers to Laos to a wide variety of mobile genetic elements that may facilitate global AMR spread. This in-depth study has revealed further detail of the numerous factors that may influence AMR transfer, therefore potential routes of AMR spread internationally, and is a step towards finding methods to combat AMR spread. Data SummaryLong-read sequencing data is available through National Center for Biotechnology Information under the BioProject PRJNA853172. Complete plasmid sequences have been uploaded to GenBank with accession numbers in supplementary S1. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

bioRxiv2022

Strong pathogen competition in neonatal gut colonisation

Bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. However, currently we are lacking a population-wide quantification of strain-level colonisation dynamics for many common bacterial pathogens and the relationship of colonisation potential to prevalence in disease is unknown. In addition, it is unclear how ecological factors might be modulating the dynamics. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods leveraging large genomic reference libraries of key pathogens, we performed a characterisation of the competition (co-exclusion and co-presence) and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found a strong inter- and intra-species competition dynamic in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. Additionally, we find no evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups. Our analysis also enables the first unbiased assessment of the strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their potential to cause bloodstream infections. We determined that the established common ExPEC clones ST73 and ST95 are overall significantly more pathogenic than the more recent, globally circulating multi-drug resistant clone ST131, where only a single subclone (ST131-C2) exhibited excess pathogenic potential. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

microbiology↗

bioRxiv2022

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on Generalised Linear Regression that is robust to population structure, sampling bias and errors in the predicted presence/absence of genes. We demonstrate using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analysing several diverse bacterial genome datasets representing major human pathogens. Panstripe is freely available as an R package at https://github.com/gtonkinhill/panstripe.

evolutionary biology↗

bioRxiv2022

Pneumococcal within-host diversity during colonisation, transmission and treatment

Characterising 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 individual infants and their mothers by deep sequencing whole pneumococcal populations from longitudinal nasopharyngeal samples. We demonstrate deep sequencing has unsurpassed sensitivity for detecting multiple colonisation, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared to gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the childs life. Comprehensive treatment data demonstrated infants were at an elevated risk of both the acquisition, and persistent colonisation, of a multidrug resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonisation 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.

genomics↗

bioRxiv2022

Evolution of chlorhexidine susceptibility and of the EfrEF operon among Enterococcus faecalis from diverse environments, clones and time spans

Chlorhexidine (CHX) is widely used to control the spread of pathogens (e.g. human/animal clinical settings, ambulatory care, food industry). E. faecalis, a major nosocomial pathogen, is broadly distributed in diverse hosts and environments facilitating its exposure to CHX over the years. Nevertheless, CHX activity against E. faecalis is understudied. Our goal was to assess CHX activity and the variability of ChlR-EfrEF proteins (associated with CHX tolerance) among 673 field isolates and 1784 E. faecalis genomes from PATRIC database from different sources, time spans, clonal lineages and antibiotic resistance profiles. CHX minimum inhibitory concentrations (MICCHX) and minimum bactericidal concentrations (MBCCHX) against E. faecalis presented normal distributions (0.5-64 mg/L). However, more CHX tolerant isolates were detected in the food chain and recent human infections, suggesting an adaptability of E. faecalis populations in settings where CHX is heavily used. Heterogeneity in ChlR-EfrEF sequences was identified, with isolates harboring incomplete ChlR-EfrEF proteins, particularly the EfrE identified in the ST40 clonal lineage, showing low MICCHX ([≤]1mg/L). Distinct ST40-E. faecalis subpopulations carrying truncated and non-truncated EfrE were detected, the former being predominant in human isolates. This study provides a new insight about CHX susceptibility and ChlR-EfrEF variability within diverse E. faecalis populations. The MICCHX/MBCCHX of more tolerant E. faecalis (MICCHX=8mg/L; MBCCHX=64mg/L) remain lower than in-use concentrations of CHX (>500mg/L). However, CHX increasing use combined with concentration gradients occurring in diverse environments potentially selecting multidrug-resistant strains with different CHX susceptibilities, alert to the importance of monitoring the trends of E. faecalis CHX tolerance within a One-Health approach.

microbiology↗

bioRxiv2021

Mandrake: visualising microbial population structure by embedding millions of genomes into a low-dimensional representation

In less than a decade, population genomics of microbes has progressed from the effort of sequencing dozens of strains to thousands, or even tens of thousands of strains in a single study. There are now hundreds of thousands of genomes available even for a single bacterial species and the number of genomes is expected to continue to increase at an accelerated pace given the advances in sequencing technology and widespread genomic surveillance initiatives. This explosion of data calls for innovative methods to enable rapid exploration of the structure of a population based on different data modalities, such as multiple sequence alignments, assemblies and estimates of gene content across different genomes. Here we present Mandrake, an efficient implementation of a dimensional reduction method tailored for the needs of large-scale population genomics. Mandrake is capable of visualising population structure from millions of whole genomes and we illustrate its usefulness with several data sets representing major pathogens. Our method is freely available both as an analysis pipeline (https://github.com/johnlees/mandrake) and as a browser-based interactive application (https://gtonkinhill.github.io/mandrake-web/).

genomics↗

bioRxiv2021

Genome-wide association, prediction and heritability in bacteria

Advances in whole-genome genotyping and sequencing have allowed genome-wide analyses of association, prediction and heritability in many organisms. However, the application of such analyses to bacteria is still in its infancy, being limited by difficulties including the plasticity of bacterial genomes and their strong population structure. Here we propose, and validate using simulations, a suite of genome-wide analyses for bacteria. We combine methods from human genetics and previous bacterial studies, including linear mixed models, elastic net and LD-score regression, and introduce innovations such as frequency-based allele coding, testing for both insertion/deletion and nucleotide effects and partitioning heritability by genome region. We then analyse three phenotypes of a major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for each of two antibiotics, penicillin and ceftriaxone. We show that these are highly heritable leading to high prediction accuracy, which is explained by many genetic associations identified under good control of population structure effects. In the case of ceftriaxone MIC, these results are surprising because none of the isolates was resistant according to the inhibition zone diameter threshold. We estimate that just over half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes around a quarter of the heritability of ceftriaxone MIC. For the within-host survival phenotype carriage duration, no reliable associations were found but we observed moderate heritability and prediction accuracy, indicating a polygenic trait. While generating important new results for S. pneumoniae, we have critically assessed existing methods and introduced innovations that will be useful for future large-scale population genomics studies to help decipher the genetic architecture of bacterial traits. Author summaryGenome-wide association, prediction and heritability analyses in bacteria are beginning to help unravel the genetic underpinnings of traits such as antimicrobial resistance, virulence, within-host survival and transmissibility. Progress to date is limited by challenges including the effects of strong population structure and variable recombination, and the many gaps in sequence alignments including the absence of entire genes in many isolates. More work is required to critically asses and develop methods for bacterial genomics. We address this task here, using a range of existing methods from bacterial and human genetics, such as linear mixed models, elastic net and LD-score regression. Using simulations, we first validate and then adapt these methods to introduce new analyses, including separate assessment of gap and nucleotide effects, a new allele coding for association analyses and a method to partition heritability into genome regions. We analyse within-host survival and two antimicrobial response traits of Streptococcus pneumoniae, identifying many novel associations while demonstrating good control of population structure and accurate prediction. We present both new results for an important pathogen and methodological advances that will be useful in guiding future studies in bacterial population genomics.

genomics↗

bioRxiv2021

One Health or Three? Transmission modelling of Klebsiella isolates reveals ecological barriers to transmission between humans, animals and the environment

The Klebsiella group is highly diverse both genetically and ecologically, being commonly recovered from humans, livestock, plants, soil, water, and wild animals. Many species are opportunistic pathogens, and can harbour diverse classes of antimicrobial resistance (AMR) genes. K. pneumoniae is responsible for a high public-health burden, due in part to the rapid spread of health-care associated clones that are non-susceptible to carbapenems. Klebsiella thus represents a highly pertinent taxon for assessing the risk to public health posed by animal and environmental reservoirs. Here we report an analysis of 6548 samples and 3,482 genome sequences representing 15 Klebsiella species sampled over a 15-month period from a wide range of clinical, community, animal and environmental settings in and around the city of Pavia, in the northern Italian region of Lombardy. Despite carbapenem-resistant clones circulating at a high frequency in the hospitals, we find no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside of the clinical environment. The non-random distribution of species and strains across sources point to ecological barriers that are likely to limit AMR transmission. Although we find evidence for occasional transmission between settings, hierarchical modelling and intervention analysis suggests that direct transmission from the multiple non-human (animal and environmental) sources included in our sample accounts for less than 1% of hospital disease, with the vast majority of clinical cases originating from other humans.

microbiology↗

bioRxiv2021

A high-throughput multiplexing and selection strategy to complete bacterial genomes

BackgroundBacterial whole-genome sequencing based on short-read sequencing data often results in a draft assembly formed by contiguous sequences. The introduction of long-read sequencing technologies permits to unambiguously bridge those contiguous sequences into complete genomes. However, the elevated costs associated with long-read sequencing frequently limit the number of bacterial isolates that can be long-read sequenced. Here we evaluated the recently released 96 barcoding kit from Oxford Nanopore Technologies (ONT) to generate complete genomes on a high-throughput basis. In addition, we propose a long-read isolate selection strategy that optimizes a representative selection of isolates from large-scale bacterial collections. ResultsDespite an uneven distribution of long-reads per barcode, near-complete chromosomal sequences (assembly contiguity = 0.89) were generated for 96 Escherichia coli isolates with associated short-read sequencing data. The assembly contiguity of the plasmid replicons was even higher (0.98) which indicated the suitability of the multiplexing strategy for studies focused on resolving plasmid sequences. We benchmarked hybrid and ONT-only assemblies and showed that the combination of ONT sequencing data with short-read sequencing data is still highly desirable: (i) to perform an unbiased selection of isolates for long-read sequencing, (ii) to achieve an optimal genome accuracy and completeness, and (iii) to include small plasmids underrepresented in the ONT library. ConclusionsThe proposed long-read isolate selection ensures completing bacterial genomes of isolates that span the genome diversity inherent in large collections of bacterial isolates. We show the potential of using this multiplexing approach to close bacterial genomes on a high-throughput basis.

microbiology↗

bioRxiv2021

Cross-species evolutionary rewiring in the enteric bacterium Campylobacter

Significance StatementGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox. On one hand, promoting adaptation by conferring novel functionality, on the other potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyse natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in epistasis in a recipient genome. This challenges conventional ideas and highlights the possibility of single step evolution by saltation. AbstractRecombination of short DNA fragments via horizontal gene transfer (HGT) can both introduce beneficial alleles and create genomic disharmony through negative epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome. By contrast, for the core genome, interspecific recombination is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and Campylobacter coli, that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings (negative epistasis). However, multiple HGT events enable recovery of the genomes co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred and independently reinstated in a new genetic background - facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

microbiology↗

bioRxiv2021

Different evolutionary trends form the twilight zone of the bacterial pan-genome

The pan-genome is defined as the combined set of all genes in the gene pool of a species. Pan-genome analyses have been very useful in helping to understand different evolutionary dynamics of bacterial species: an open pan-genome often indicates a free-living lifestyle with metabolic versatility, while closed pan-genomes are linked to host-restricted, ecologically specialised bacteria. A detailed understanding of the species pan-genome has also been instrumental in tracking the phylodynamics of emerging drug resistance mechanisms and drug resistant pathogens. However, current approaches to analyse a species pan-genome do not take the species population structure into account, nor do they account for the uneven sampling of different lineages, as is commonplace due to over-sampling of clinically relevant representatives. Here we present the application of a population structure-aware approach for classifying genes in a pan-genome based on within-species distribution. We demonstrate our approach on a collection of 7,500 E. coli genomes, one of the most-studied bacterial species used as a model for an open pan-genome. We reveal clearly distinct groups of genes, clustered by different underlying evolutionary dynamics, and provide a more biologically informed and accurate description of the species pan-genome.

genomics↗