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In this study, we investigated the multilocus sequence type (MLST) diversity and population genetics of Campylobacter jejuni isolates collected from the natural waters ( n = 57), wild birds ( n = 37) and zoo animals ( n = 19) in southern Finland, the Helsinki area and the Helsinki Zoo, respectively. On average, we found C. jejuni in 20%, 10.4% or 11.5% of the samples collected from natural waters, wild birds and zoo animals, respectively. High ST diversity was detected in all three sources and 41.2% of the STs were novel, but the multi-host adapted ST-45 was the most common ST detected. The MLST data, supplemented with C. jejuni isolates from domestically acquired human infections ( n = 454), poultry ( n = 208) and bovines ( n = 120), were utilized in a population structure study. The results indicate four groups of strains with varying ecological associations, demonstrating presence of genetically distinct lineages within each of the studied sources. We discovered that the greatest ST overlap occurs between human isolates and isolates from natural waters and poultry, which suggests that the latter two are the most important sources of C. jejuni among domestically acquired infections in Finland. [ABSTRACT FROM AUTHOR]

We monitored populations of two wood ant species,Formica aquiloniaandFormica lugubris, through annual mapping of the colonies in a fragmenting forest landscape from 1966 to 1998. The genetic population structure was studied at the end of the study period by using 12 microsatellite loci. Fragmentation of forest led to a decline and spatial redistribution of populations. Changes in the spatial distribution were particularly pronounced in the highly polygynous (many queens in a single nest) speciesF. aquilonia, whose local populations declined or became extinct, or relocated themselves and colonized new patches. The genetic relationships of the remaining subpopulations indicated the historical developments, revealing the boundaries of the historical populations (high values of genetic differentiation,FST), recolonization histories (genetic affinities revealed by Bayesian analyses) and population decline (reduced variation). Big genetic differences could be detected over short distances, so differentiation also depended on social factors. Our results showed that a genetic study can be reliably used to dissect the recent historical changes underlying the present population structure, and that species with different social structures can respond differently to habitat changes. Combining our demographic and genetic results suggests that habitat fragmentation forms a clear threat on a local scale with large negative effects on ant population viability. [ABSTRACT FROM AUTHOR]

Abstract Background Y. enterocolitica biotype (BT) 1A strains are often isolated from human clinical samples but their contribution to disease has remained a controversial topic. Variation and the population structure among the clinical Y. enterocolitica BT 1A isolates have been poorly characterized. We used multi-locus sequence typing (MLST), 16S rRNA gene sequencing, PCR for ystA and ystB, lipopolysaccharide analysis, phage typing, human serum complement killing assay and analysis of the symptoms of the patients to characterize 298 clinical Y. enterocolitica BT 1A isolates in order to evaluate their relatedness and pathogenic potential. Results A subset of 71 BT 1A strains, selected based on their varying LPS patterns, were subjected to detailed genetic analyses. The MLST on seven house-keeping genes (adk, argA, aroA, glnA, gyrB, thrA, trpE) conducted on 43 of the strains discriminated them into 39 MLST-types. By Bayesian analysis of the population structure (BAPS) the strains clustered conclusively into two distinct lineages, i.e. Genetic groups 1 and 2. The strains of Genetic group 1 were more closely related (97% similarity) to the pathogenic bio/serotype 4/O:3 strains than Genetic group 2 strains (95% similarity). Further comparison of the 16S rRNA genes of the BT 1A strains indicated that altogether 17 of the 71 strains belong to Genetic group 2. On the 16S rRNA analysis, these 17 strains were only 98% similar to the previously identified subspecies of Y. enterocolitica. The strains of Genetic group 2 were uniform in their pathogenecity-related properties: they lacked the ystB gene, belonged to the same LPS subtype or were of rough type, were all resistant to the five tested yersiniophages, were largely resistant to serum complement and did not ferment fucose. The 54 strains in Genetic group 1 showed much more variation in these properties. The most commonly detected LPS types were similar to the LPS types of reference strains with serotypes O:6,30 and O:6,31 (37%), O:7,8 (19%) and O:5 (15%). Conclusions The results of the present study strengthen the assertion that strains classified as Y. enterocolitica BT 1A represent more than one subspecies. Especially the BT 1A strains in our Genetic group 2 commonly showed resistance to human serum complement killing, which may indicate pathogenic potential for these strains. However, their virulence mechanisms remain unknown.

Abstract Background Worldwide effort on sampling and characterization of molecular variation within a large number of human and animal pathogens has lead to the emergence of multi-locus sequence typing (MLST) databases as an important tool for studying the epidemiology and evolution of pathogens. Many of these databases are currently harboring several thousands of multi-locus DNA sequence types (STs) enriched with metadata over traits such as serotype, antibiotic resistance, host organism etc of the isolates. Curators of the databases have thus the possibility of dividing the pathogen populations into subsets representing different evolutionary lineages, geographically associated groups, or other subpopulations, which are defined in terms of molecular similarities and dissimilarities residing within a database. When combined with the existing metadata, such subsets may provide invaluable information for assessing the position of a new set of isolates in relation to the whole pathogen population. Results To enable users of MLST schemes to query the databases with sets of new bacterial isolates and to automatically analyze their relation to existing curated sequences, we introduce here a Bayesian model-based method for semi-supervised classification of MLST data. Our method can use an MLST database as a training set and assign simultaneously any set of query sequences into the earlier discovered lineages/populations, while also allowing some or all of these sequences to form previously undiscovered genetically distinct groups. This tool provides probabilistic quantification of the classification uncertainty and is highly efficient computationally, thus enabling rapid analyses of large databases and sets of query sequences. The latter feature is a necessary prerequisite for an automated access through the MLST web interface. We demonstrate the versatility of our approach by anayzing both real and synthesized data from MLST databases. The introduced method for semi-supervised classification of sets of query STs is freely available for Windows, Mac OS X and Linux operative systems in BAPS 5.4 software which is downloadable at http://web.abo.fi/fak/mnf/mate/jc/software/baps.html. The query functionality is also directly available for the Staphylococcus aureus database at http://www.mlst.net and shortly will be available for other species databases hosted at this web portal. Conclusions We have introduced a model-based tool for automated semi-supervised classification of new pathogen samples that can be integrated into the web interface of the MLST databases. In particular, when combined with the existing metadata, the semi-supervised labeling may provide invaluable information for assessing the position of a new set of query strains in relation to the particular pathogen population represented by the curated database. Such information will be useful both for clinical and basic research purposes.

Abstract Background Since the introduction of large-scale genotyping methods that can be utilized in genome-wide association (GWA) studies for deciphering complex diseases, statistical genetics has been posed with a tremendous challenge of how to most appropriately analyze such data. A plethora of advanced model-based methods for genetic mapping of traits has been available for more than 10 years in animal and plant breeding. However, most such methods are computationally intractable in the context of genome-wide studies. Therefore, it is hardly surprising that GWA analyses have in practice been dominated by simple statistical tests concerned with a single marker locus at a time, while the more advanced approaches have appeared only relatively recently in the biomedical and statistical literature. Results We introduce a novel Bayesian modeling framework for association mapping which enables the detection of multiple loci and their interactions that influence a dichotomous phenotype of interest. The method is shown to perform well in a simulation study when compared to widely used standard alternatives and its computational complexity is typically considerably smaller than that of a maximum likelihood based approach. We also discuss in detail the sensitivity of the Bayesian inferences with respect to the choice of prior distributions in the GWA context. Conclusions Our results show that the Bayesian model averaging approach which explicitly considers gene-gene interactions may improve the detection of disease associated genetic markers in two respects: first, by providing better estimates of the locations of the causal loci; second, by reducing the number of false positives. The benefits are most apparent when the interacting genes exhibit no main effects. However, our findings also illustrate that such an approach is somewhat sensitive to the prior distribution assigned on the model structure.

Abstract Background Campylobacter jejuni is the most common bacterial cause of human gastroenteritis worldwide. Due to the sporadic nature of infection, sources often remain unknown. Multilocus sequence typing (MLST) has been successfully applied to population genetics of Campylobacter jejuni and mathematical modelling can be applied to the sequence data. Here, we analysed the population structure of a total of 250 Finnish C. jejuni isolates from bovines, poultry meat and humans collected in 2003 using a combination of Bayesian clustering (BAPS software) and phylogenetic analysis. Results In the first phase we analysed sequence types (STs) of 102 Finnish bovine C. jejuni isolates by MLST and found a high diversity totalling 50 STs of which nearly half were novel. In the second phase we included MLST data from domestic human isolates as well as poultry C. jejuni isolates from the same time period. Between the human and bovine isolates we found an overlap of 72.2%, while 69% of the human isolates were overlapping with the chicken isolates. In the BAPS analysis 44.3% of the human isolates were found in bovine-associated BAPS clusters and 45.4% of the human isolates were found in the poultry-associated BAPS cluster. BAPS reflected the phylogeny of our data very well. Conclusions These findings suggest that bovines and poultry were equally important as reservoirs for human C. jejuni infections in Finland in 2003. Our results differ from those obtained in other countries where poultry has been identified as the most important source for human infections. The low prevalence of C. jejuni in poultry flocks in Finland could explain the lower attribution of human infection to poultry. Of the human isolates 10.3% were found in clusters not associated with any host which warrants further investigation, with particular focus on waterborne transmission routes and companion animals.

Abstract Background The human gastrointestinal (GI) tract microbiota is characterised by an abundance of uncultured bacteria most often assigned in phyla Firmicutes and Bacteroidetes. Diversity of this microbiota, even though approached with culture independent techniques in several studies, still requires more elucidation. The main purpose of this work was to study whether the genomic percent guanine and cytosine (%G+C) -based profiling and fractioning prior to 16S rRNA gene sequence analysis reveal higher microbiota diversity, especially with high G+C bacteria suggested to be underrepresented in previous studies. Results A phylogenetic analysis of the composition of the human GI microbiota of 23 healthy adult subjects was performed from a pooled faecal bacterial DNA sample by combining genomic %G+C -based profiling and fractioning with 16S rRNA gene cloning and sequencing. A total of 3199 partial 16S rRNA genes were sequenced. For comparison, 459 clones were sequenced from a comparable unfractioned sample. The most important finding was that the proportional amount of sequences affiliating with the phylum Actinobacteria was 26.6% in the %G+C fractioned sample but only 3.5% in the unfractioned sample. The orders Coriobacteriales, Bifidobacteriales and Actinomycetales constituted the 65 actinobacterial phylotypes in the fractioned sample, accounting for 50%, 47% and 3% of sequences within the phylum, respectively. Conclusion This study shows that the %G+C profiling and fractioning prior to cloning and sequencing can reveal a significantly larger proportion of high G+C content bacteria within the clones recovered, compared with the unfractioned sample in the human GI tract. Especially the order Coriobacteriales within the phylum Actinobacteria was found to be more abundant than previously estimated with conventional sequencing studies.

Abstract Background The versatility of DNA copy number amplifications for profiling and categorization of various tissue samples has been widely acknowledged in the biomedical literature. For instance, this type of measurement techniques provides possibilities for exploring sets of cancerous tissues to identify novel subtypes. The previously utilized statistical approaches to various kinds of analyses include traditional algorithmic techniques for clustering and dimension reduction, such as independent and principal component analyses, hierarchical clustering, as well as model-based clustering using maximum likelihood estimation for latent class models. Results While purely algorithmic methods are usually easily applicable, their suboptimal performance and limitations in making formal inference have been thoroughly discussed in the statistical literature. Here we introduce a Bayesian model-based approach to simultaneous identification of underlying tissue groups and the informative amplifications. The model-based approach provides the possibility of using formal inference to determine the number of groups from the data, in contrast to the ad hoc methods often exploited for similar purposes. The model also automatically recognizes the chromosomal areas that are relevant for the clustering. Conclusion Validatory analyses of simulated data and a large database of DNA copy number amplifications in human neoplasms are used to illustrate the potential of our approach. Our software implementation BASTA for performing Bayesian statistical tissue profiling is freely available for academic purposes at http://web.abo.fi/fak/mnf/mate/jc/software/basta.html

Abstract Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at http://web.abo.fi/fak/mnf//mate/jc/software/baps.html.

Abstract Background We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of strains in a data set increases. Results We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites. Conclusion A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/mnf//mate/jc/software/brat.html.

Objectives: Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in the gut of birds and mammals and often infect humans via contaminated food. Rising incidence and antimicrobial resistance (AMR) are a global concern, and there is an urgent need to quantify the main routes to human infection., Methods: During routine US national surveillance (2009-2019), 8856 Campylobacter genomes from human infections and 16,703 from possible sources were sequenced. Using machine learning and probabilistic models, we target genetic variation associated with host adaptation to attribute the source of human infections and estimate the importance of different disease reservoirs., Results: Poultry was identified as the primary source of human infections, responsible for an estimated 68% of cases, followed by cattle (28%), and only a small contribution from wild birds (3%) and pork sources (1%). There was also evidence of an increase in multidrug resistance, particularly among isolates attributed to chickens., Conclusions: National surveillance and source attribution can guide policy, and our study suggests that interventions targeting poultry will yield the greatest reductions in campylobacteriosis and spread of AMR in the US., Data Availability: All sequence reads were uploaded and shared on NCBI's Sequence Read Archive (SRA) associated with BioProjects; PRJNA239251 (CDC / PulseNet surveillance), PRJNA287430 (FSIS surveillance), PRJNA292668 & PRJNA292664 (NARMS) and PRJNA258022 (FDA surveillance). Publicly available genomes, including reference genomes and isolates sampled worldwide from wild birds are associated with BioProject accessions: PRJNA176480, PRJNA177352, PRJNA342755, PRJNA345429, PRJNA312235, PRJNA415188, PRJNA524300, PRJNA528879, PRJNA529798, PRJNA575343, PRJNA524315 and PRJNA689604. Contiguous assemblies of all genome sequences compared are available at Mendeley data (assembled C. coli genomes doi: 10.17632/gxswjvxyh3.1; assembled C. jejuni genomes doi: 10.17632/6ngsz3dtbd.1) and individual project and accession numbers can be found in Supplementary tables S1 and S2, which also includes pubMLST identifiers for assembled genomes. Figshare (10.6084/m9.figshare.20279928). Interactive phylogenies are hosted on microreact separately for C. jejuni (https://microreact.org/project/pascoe-us-cjejuni) and C. coli (https://microreact.org/project/pascoe-us-ccoli)., Competing Interests: Declaration of Competing Interest All authors declare no conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Interpreting the phenotypes of bla SHV alleles in Klebsiella pneumoniae genomes is complex. Whilst all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal bla SHV alleles or additional plasmid-borne bla SHV alleles that have extended-spectrum β-lactamase (ESBL) activity and/or β-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/a changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases [e.g. the National Center for Biotechnology Information (NCBI) Reference Gene Catalog and the β-lactamase database (BLDB)] over the specific functionality of individual sulfhydryl variable (SHV) protein variants. Therefore, the identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific aa substitutions. We then systematically assigned SHV alleles to functional classes (WT, ESBL and BLI resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with the current assignments in the NCBI's Reference Gene Catalog and/or BLDB (21 to WT, 12 to ESBL and 4 to BLI resistant). Phylogenetic and comparative genomic analyses support that (i) SHV-1 (encoded by bla SHV-1 ) is the ancestral chromosomal variant, (ii) ESBL- and BLI-resistant variants have evolved multiple times through parallel substitution mutations, (iii) ESBL variants are mostly mobilized to plasmids and (iv) BLI-resistant variants mostly result from mutations in chromosomal bla SHV . We used matched genome-phenotype data from the KlebNET-GSP AMR Genotype-Phenotype Group to identify 3999 K . pneumoniae isolates carrying one or more bla SHV alleles but no other acquired β-lactamases to assess genotype-phenotype relationships for bla SHV . This collection includes human, animal and environmental isolates collected between 2001 and 2021 from 24 countries. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, whilst most omega-loop substitutions do not. Our data also provide support for the WT assignment of 67 protein variants, including 8 that were noted in public databases as ESBL. These eight variants were reclassified as WT because they lack ESBL-associated mutations, and our phenotype data support susceptibility to third-generation cephalosporins (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164 and SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae ), whereby known and novel bla SHV alleles are classified based on causative mutations. Kleborate v2.4.1 was updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve the understanding of resistance mechanisms.

Background: Nosocomial infections pose a considerable risk to patients who are susceptible, and this is particularly acute in intensive care units when hospital-associated bacteria are endemic. During the first wave of the COVID-19 pandemic, the surge of patients presented a significant obstacle to the effectiveness of infection control measures. We aimed to assess the risks and extent of nosocomial pathogen transmission under a high patient burden by designing a novel bacterial pan-pathogen deep-sequencing approach that could be integrated with standard clinical surveillance and diagnostics workflows., Methods: We did a prospective cohort study in a region of northern Italy that was severely affected by the first wave of the COVID-19 pandemic. Inpatients on both ordinary and intensive care unit (ICU) wards at the San Matteo hospital, Pavia were sampled on multiple occasions to identify bacterial pathogens from respiratory, nasal, and rectal samples. Diagnostic samples collected between April 7 and May 10, 2020 were cultured on six different selective media designed to enrich for Acinetobacter baumannii, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, and DNA from each plate with positive growth was deep sequenced en masse. We used mSWEEP and mGEMS to bin sequencing reads by sequence cluster for each species, followed by mapping with snippy to generate high quality alignments. Antimicrobial resistance genes were detected by use of ARIBA and CARD. Estimates of hospital transmission were obtained from pairwise bacterial single nucleotide polymorphism distances, partitioned by within-patient and between-patient samples. Finally, we compared the accuracy of our binned Acinetobacter baumannii genomes with those obtained by single colony whole-genome sequencing of isolates from the same hospital., Findings: We recruited patients from March 1 to May 7, 2020. The pathogen population among the patients was large and diverse, with 2148 species detections overall among the 2418 sequenced samples from the 256 patients. In total, 55 sequence clusters from key pathogen species were detected at least five times. The antimicrobial resistance gene prevalence was correspondingly high, with key carbapenemase and extended spectrum ß-lactamase genes detected in at least 50 (40%) of 125 patients in ICUs. Using high-resolution mapping to infer transmission, we established that hospital transmission was likely to be a significant mode of acquisition for each of the pathogen species. Finally, comparison with single colony Acinetobacter baumannii genomes showed that the resolution offered by deep sequencing was equivalent to single-colony sequencing, with the additional benefit of detection of co-colonisation of highly similar strains., Interpretation: Our study shows that a culture-based deep-sequencing approach is a possible route towards improving future pathogen surveillance and infection control at hospitals. Future studies should be designed to directly compare the accuracy, cost, and feasibility of culture-based deep sequencing with single colony whole-genome sequencing on a range of bacterial species., Funding: Wellcome Trust, European Research Council, Academy of Finland Flagship program, Trond Mohn Foundation, and Research Council of Norway., Competing Interests: Declaration of interests SWL received Robert Austrian Research Award sponsored by Pfizer, outside of the scope of this study. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis ., (© 2024 Kuronen et al.; Published by Cold Spring Harbor Laboratory Press.)

Multi-drug resistant (MDR) E. coli constitute a major public health burden globally, reaching the highest prevalence in the global south yet frequently flowing with travellers to other regions. However, our comprehension of the entire genetic diversity of E. coli colonising local populations remains limited. We quantified this diversity, its associated antimicrobial resistance (AMR), and assessed the impact of antibiotic use by recruiting 494 outpatients and 423 community dwellers in the Punjab province, Pakistan. Rectal swab and stool samples were cultured on CLED agar and DNA extracted from plate sweeps was sequenced en masse to capture both the genetic and AMR diversity of E. coli. We assembled 5,247 E. coli genomes from 1,411 samples, displaying marked genetic diversity in gut colonisation. Compared with high income countries, the Punjabi population generally showed a markedly different distribution of genetic lineages and AMR determinants, while use of antibiotics elevated the prevalence of well-known globally circulating MDR clinical strains. These findings implicate that longitudinal multi-regional genomics-based surveillance of both colonisation and infections is a prerequisite for developing mechanistic understanding of the interplay between ecology and evolution in the maintenance and dissemination of (MDR) E. coli., (© 2024. The Author(s).)

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive 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 and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome 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 C. 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, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome's 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.IMPORTANCEGenetic 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: 0n 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 analyze 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 functional networks in a recipient genome. The positive impact of two-gene interactions appears to be adaptive by expanding metabolic capacity and facilitating niche shifts through interspecific hybridization. This challenges conventional ideas and highlights the possibility of multiple-step evolution of multi-gene traits by interspecific introgression., Competing Interests: The authors declare no conflict of interest.

The nasopharynx is an important reservoir of disease-associated and antimicrobial-resistant bacterial species. This proof-of-concept study assessed the utility of a combined culture, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), and targeted metagenomic sequencing workflow for the study of the pediatric nasopharyngeal bacterial microbiota. Nasopharyngeal swabs and clinical metadata were collected from Cambodian children during a hospital outpatient visit and then biweekly for 12 weeks. Swabs were cultured on chocolate and blood-gentamicin agar, and all colony morphotypes were identified by MALDI-TOF MS. Metagenomic sequencing was done on a scrape of all colonies from a chocolate agar culture and processed using the mSWEEP pipeline. One hundred one children were enrolled, yielding 620 swabs. MALDI-TOF MS identified 106 bacterial species/40 genera: 20 species accounted for 88.5% (2,190/2,474) of isolates. Colonization by Moraxella catarrhalis (92.1% of children on ≥1 swab), Haemophilus influenzae (87.1%), and Streptococcus pneumoniae (83.2%) was particularly common. In S. pneumoniae -colonized children, a median of two serotypes [inter-quartile range (IQR) 1-2, range 1-4] was detected. For the 21 bacterial species included in the mSWEEP database and identifiable by MALDI-TOF, detection by culture + MALDI-TOF MS and culture + mSWEEP was highly concordant with a median species-level agreement of 96.9% (IQR 86.8%-98.8%). mSWEEP revealed highly dynamic lineage-level colonization patterns for S. pneumoniae which were quite different to those for S. aureus . A combined culture, MALDI-TOF MS, targeted metagenomic sequencing approach for the exploration of the young child nasopharyngeal microbiome was technically feasible, and each component yielded complementary data., Importance: The human upper respiratory tract is an important source of disease-causing and antibiotic-resistant bacteria. However, understanding the interactions and stability of these bacterial populations is technically challenging. We used a combination of approaches to determine colonization patterns over a 3-month period in 101 Cambodian children. The combined approach was feasible to implement, and each component gave complementary data to enable a better understanding of the complex patterns of bacterial colonization., Competing Interests: The authors declare no conflict of interest.

Campylobacter is a leading cause of food-borne gastroenteritis worldwide, linked to the consumption of contaminated poultry meat. Targeting this pathogen at source, vaccines for poultry can provide short-term caecal reductions in Campylobacter numbers in the chicken intestine. However, this approach is unlikely to reduce Campylobacter in the food chain or human incidence. This is likely as vaccines typically target only a subset of the high genomic strain diversity circulating among chicken flocks, and rapid evolution diminishes vaccine efficacy over time. To address this, we used a genomic approach to develop a whole-cell autogenous vaccine targeting isolates harbouring genes linked to survival outside of the host. We hyper-immunised a whole major UK breeder farm to passively target offspring colonisation using maternally-derived antibody. Monitoring progeny, broiler flocks revealed a near-complete shift in the post-vaccination Campylobacter population with an ~50% reduction in isolates harbouring extra-intestinal survival genes and a significant reduction of Campylobacter cells surviving on the surface of meat. Based on these findings, we developed a logistic regression model that predicted that vaccine efficacy could be extended to target 65% of a population of clinically relevant strains. Immuno-manipulation of poultry microbiomes towards less harmful commensal isolates by competitive exclusion, has major potential for reducing pathogens in the food production chain., (© 2024. The Author(s).)

Population genomics has revolutionized 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 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., (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Streptococcus pneumoniae (the pneumococcus) is a globally distributed, human obligate opportunistic bacterial pathogen which, although often carried commensally, is also a significant cause of invasive disease. Apart from multi-drug resistant and virulent clones, the rate and direction of pneumococcal dissemination between different countries remains largely unknown. The ability for the pneumococcus to take a foothold in a country depends on existing population configuration, the extent of vaccine implementation, as well as human mobility since it is a human obligate bacterium. To shed light on its international movement, we used extensive genome data from the Global Pneumococcal Sequencing project and estimated migration parameters between multiple countries in Africa. Data on allele frequencies of polymorphisms at housekeeping-like loci for multiple different lineages circulating in the populations of South Africa, Malawi, Kenya, and The Gambia were used to calculate the fixation index (Fst) between countries. We then further used these summaries to fit migration coalescent models with the likelihood-free inference algorithms available in the ELFI software package. Synthetic datawere additionally used to validate the inference approach. Our results demonstrate country-pair specific migration patterns and heterogeneity in the extent of migration between different lineages. Our approach demonstrates that coalescent models can be effectively used for inferring migration rates for bacterial species and lineages provided sufficiently granular population genomics surveillance data. Further, it can demonstrate the connectivity of respiratory disease agents between countries to inform intervention policy in the longer term., Competing Interests: Conflicts of interest N.J.C. has consulted for Antigen Discovery Inc and Pfizer, and been invited to attend meetings funded by M.S.D. N.J.C. has received an investigator-initiated award from GlaxoSmithKline. No other authors have conflicts of interest to report., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

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 optimized 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 .

Background: The effect of antibiotic usage on the success of multidrug-resistant (MDR) clones in a population remains unclear. With this genomics-based molecular epidemiology study, we aimed to investigate the contribution of antibiotic use to Escherichia coli clone success, relative to intra-strain competition for colonisation and infection., Methods: We sequenced all the available E coli bloodstream infection isolates provided by the British Society for Antimicrobial Chemotherapy (BSAC) from 2012 to 2017 (n=718) and combined these with published data from the UK (2001-11; n=1090) and Norway (2002-17; n=3254). Defined daily dose (DDD) data from the European Centre for Disease Prevention and Control (retrieved on Sept 21, 2021) for major antibiotic classes (β-lactam, tetracycline, macrolide, sulfonamide, quinolone, and non-penicillin β-lactam) were used together with sequence typing, resistance profiling, regression analysis, and non-neutral Wright-Fisher simulation-based modelling to enable systematic comparison of resistance levels, clone success, and antibiotic usage between the UK and Norway., Findings: Sequence type (ST)73, ST131, ST95, and ST69 accounted for 892 (49·3%) of 1808 isolates in the BSAC collection. In the UK, the proportion of ST69 increased between 2001-10 and 2011-17 (p=0·0004), whereas the proportions of ST73 and ST95 did not vary between periods. ST131 expanded quickly after its emergence in 2003 and its prevalence remained consistent throughout the study period (apart from a brief decrease in 2009-10). The extended-spectrum β-lactamase (ESBL)-carrying, globally disseminated MDR clone ST131-C2 showed overall greater success in the UK (154 [56·8%] of 271 isolates in 2003-17) compared with Norway (51 [18·3%] of 278 isolates in 2002-17; p<0·0001). DDD data indicated higher total use of antimicrobials in the UK, driven mainly by the class of non-penicillin β-lactams, which were used between 2·7-times and 5·1-times more in the UK per annum (ratio mean 3·7 [SD 0·8]). This difference was associated with the higher success of the MDR clone ST131-C2 (pseudo-R 2 69·1%). A non-neutral Wright-Fisher model replicated the observed expansion of non-MDR and MDR sequence types under higher DDD regimes., Interpretation: Our study indicates that resistance profiles of contemporaneously successful clones can vary substantially, warranting caution in the interpretation of correlations between aggregate measures of resistance and antibiotic usage. Our study further suggests that in countries with low-to-moderate use of antibiotics, such as the UK and Norway, the extent of non-penicillin β-lactam use modulates rather than determines the success of widely disseminated MDR ESBL-carrying E coli clones. Detailed understanding of underlying causal drivers of success is important for improved control of resistant pathogens., Funding: Trond Mohn Foundation, Marie Skłodowska-Curie Actions, European Research Council, Royal Society, and Wellcome Trust., Competing Interests: Declaration of interests NJC reports support to his institution from GlaxoSmithKline, Pfizer, and Merck (MSD), and personal grants from MRC, outside the submitted work. All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)