Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter

Genome and Methylome analysis of a phylogenetic novel Campylobacter coli cluster with C. jejuni introgression

The intriguing recent discovery of Campylobacter coli strains, especially of clade 1, that (i) possess mosaic C. coli/C. jejuni alleles, (ii) demonstrate mixed multilocus sequence types (MLSTs) and (iii) have undergone genome-wide introgression has led to the speculation that these two species may be involved in an accelerated rate of horizontal gene transfer that is progressively leading to the merging of both species in a process coined ‘despeciation’. In an MLST-based neighbour-joining tree of a number of C. coli and C. jejuni isolates of different clades, three prominent Campylobacter isolates formed a seemingly separate cluster besides the previously described C. coli and C. jejuni clades. In the light of the suspected, ongoing genetic introgression between the C. coli and C. jejuni species, this cluster of Campylobacter isolates is proposed to present one of the hybrid clonal complexes in the despeciation process of the genus. Specific DNA methylation as well as restriction modification systems are known to be involved in selective uptake of external DNA and their role in such genetic introgression remains to be further investigated. In this study, the phylogeny and DNA methylation of these putative C. coli/C. jejuni hybrid strains were explored, their genomic mosaic structure caused by C. jejuni introgression was demonstrated and basic phenotypic assays were used to characterize these isolates. The genomes of the three hybrid Campylobacter strains were sequenced using PacBio SMRT sequencing, followed by methylome analysis by Restriction-Modification Finder and genome analysis by Parsnp, Smash++ and blast. Additionally, the strains were phenotypically characterized with respect to growth behaviour, motility, eukaryotic cell invasion and adhesion, autoagglutination, biofilm formation, and water survival ability. Our analyses show that the three hybrid Campylobacter strains are clade 1 C. coli strains, which have acquired between 8.1 and 9.1 % of their genome from C. jejuni. The C. jejuni genomic segments acquired are distributed over the entire genome and do not form a coherent cluster. Most of the genes originating from C. jejuni are involved in chemotaxis and motility, membrane transport, cell signalling, or the resistance to toxic compounds such as bile acids. Interspecies gene transfer from C. jejuni has contributed 8.1–9.1% to the genome of three C. coli isolates and initiated the despeciation between C. jejuni and C. coli. Based on their functional annotation, the genes originating from C. jejuni enable the adaptation of the three strains to an intra-intestinal habitat. The transfer of a fused type II restriction-modification system that recognizes the CAYNNNNNCTC/GAGNNNNNRTG motif seems to be the key for the recombination of the C. jejuni genetic material with C. coli genomes.

Genome-wide association studies reveal the role of polymorphisms affecting factor H binding protein expression in host invasion by Neisseria meningitidis

Many invasive bacterial diseases are caused by organisms that are ordinarily harmless components of the human microbiome. Effective interventions against these microbes require an understanding of the processes whereby symbiotic or commensal relationships transition into pathology. Here, we describe bacterial genome-wide association studies (GWAS) of Neisseria meningitidis, a common commensal of the human respiratory tract that is nevertheless a leading cause of meningitis and sepsis. An initial GWAS discovered bacterial genetic variants, including single nucleotide polymorphisms (SNPs), associated with invasive meningococcal disease (IMD) versus carriage in several loci across the meningococcal genome, encoding antigens and other extracellular components, confirming the polygenic nature of the invasive phenotype. In particular, there was a significant peak of association around the fHbp locus, encoding factor H binding protein (fHbp), which promotes bacterial immune evasion of human complement by recruiting complement factor H (CFH) to the meningococcal surface. The association around fHbp with IMD was confirmed by a validation GWAS, and we found that the SNPs identified in the validation affected the 5' region of fHbp mRNA, altering secondary RNA structures, thereby increasing fHbp expression and enhancing bacterial escape from complement-mediated killing. This finding is consistent with the known link between complement deficiencies and CFH variation with human susceptibility to IMD. These observations demonstrate the importance of human and bacterial genetic variation across the fHbp:CFH interface in determining IMD susceptibility, the transition from carriage to disease.

Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugE gene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be the major reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain.

Horizontal gene transfer-mediated bacterial strain variation affects host fitness in Drosophila

Background

How microbes affect host fitness and environmental adaptation has become a fundamental research question in evolutionary biology. To better understand the role of microbial genomic variation for host fitness, we tested for associations of bacterial genomic variation and Drosophila melanogaster offspring number in a microbial Genome Wide Association Study (GWAS).

Results

We performed a microbial GWAS, leveraging strain variation in the genus Gluconobacter, a genus of bacteria that are commonly associated with Drosophila under natural conditions. We pinpoint the thiamine biosynthesis pathway (TBP) as contributing to differences in fitness conferred to the fly host. While an effect of thiamine on fly development has been described, we show that strain variation in TBP between bacterial isolates from wild-caught D. melanogaster contributes to variation in offspring production by the host. By tracing the evolutionary history of TBP genes in Gluconobacter, we find that TBP genes were most likely lost and reacquired by horizontal gene transfer (HGT).

Conclusion

Our study emphasizes the importance of strain variation and highlights that HGT can add to microbiome flexibility and potentially to host adaptation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01124-y.

Human gut-derived B. longum subsp. longum strains protect against aging in a D-galactose-induced aging mouse model

BACKGROUND

Probiotics have been used to regulate the gut microbiota and physiology in various contexts, but their precise mechanisms of action remain unclear.

RESULTS

By population genomic analysis of 418 Bifidobacterium longum strains, including 143 newly sequenced in this study, three geographically distinct gene pools/populations, BLAsia1, BLAsia2, and BLothers, were identified. Genes involved in cell wall biosynthesis, particularly peptidoglycan biosynthesis, varied considerably among the core genomes of the different populations, but accessory genes that contributed to the carbohydrate metabolism were significantly distinct. Although active transmission was observed inter-host, inter-country, inter-city, intra-community, and intra-family, a single B. longum clone seemed to reside within each individual. A significant negative association was observed between host age and relative abundance of B. longum, while there was a strong positive association between host age and strain genotype [e.g., single nucleotide polymorphisms in the arginine biosynthesis pathway]. Further animal experiments performed with the B. longum isolates via using a D-galactose-induced aging mouse model supported these associations, in which B. longum strains with different genotypes in arginine biosynthesis pathway showed divergent abilities on protecting against host aging possibly via their different abilities to modify the metabolism of gut microbes.

CONCLUSIONS

This is the first known example of research on the evolutionary history and transmission of this probiotic species. Our results propose a new mechanistic insight for promoting host longevity via the informed use of specific probiotics or molecules. Video abstract.

Hogwash: three methods for genome-wide association studies in bacteria

Bacterial genome-wide association studies (bGWAS) capture associations between genomic variation and phenotypic variation. Convergence-based bGWAS methods identify genomic mutations that occur independently multiple times on the phylogenetic tree in the presence of phenotypic variation more often than is expected by chance. This work introduces hogwash, an open source R package that implements three algorithms for convergence-based bGWAS. Hogwash additionally contains two burden testing approaches to perform gene or pathway analysis to improve power and increase convergence detection for related but weakly penetrant genotypes. To identify optimal use cases, we applied hogwash to data simulated with a variety of phylogenetic signals and convergence distributions. These simulated data are publicly available and contain the relevant metadata regarding convergence and phylogenetic signal for each phenotype and genotype. Hogwash is available for download from GitHub.

The Avian Pathogenic Escherichia coli (APEC) pathotype is comprised of multiple distinct, independent genotypes

Avian Pathogenic E. coli (APEC) is the causative agent of avian colibacillosis, resulting in economic losses to the poultry industry through morbidity, mortality and carcass condemnation, and impacts the welfare of poultry. Colibacillosis remains a complex disease to manage, hampered by diagnostic and classification strategies for E. coli that are inadequate for defining APEC. However, increased accessibility of whole genome sequencing (WGS) technology has enabled phylogenetic approaches to be applied to the classification of E. coli and genomic characterization of the most common APEC serotypes associated with colibacillosis O1, O2 and O78. These approaches have demonstrated that the O78 serotype is representative of two distinct APEC lineages, ST-23 in phylogroup C and ST-117 in phylogroup G. The O1 and O2 serotypes belong to a third lineage comprised of three sub-populations in phylogroup B2; ST-95, ST-140 and ST-428/ST-429. The frequency with which these genotypes are associated with colibacillosis implicates them as the predominant APEC populations and distinct from those causing incidental or opportunistic infections. The fact that these are disparate clusters from multiple phylogroups suggests that these lineages may have become adapted to the poultry niche independently. WGS studies have highlighted the limitations of traditional APEC classification and can now provide a path towards a robust and more meaningful definition of the APEC pathotype. Future studies should focus on characterizing individual APEC populations in detail and using this information to develop improved diagnostics and interventions.

Genome-wide association study of signature genetic alterations among pseudomonas aeruginosa cystic fibrosis isolates

Pseudomonas aeruginosa (PA) is an opportunistic pathogen that causes diverse human infections including chronic airway infection in patients with cystic fibrosis (CF). Comparing the genomes of CF and non-CF PA isolates has great potential to identify the genetic basis of pathogenicity. To gain a deeper understanding of PA adaptation in CF airways, we performed a genome-wide association study (GWAS) on 1,001 PA genomes. Genetic variations identified among CF isolates were categorized into (i) alterations in protein-coding regions, either large- or small-scale, and (ii) polymorphic variation in intergenic regions. We introduced each CF-associated genetic alteration into the genome of PAO1, a prototype PA strain, and validated the outcomes experimentally. Loci readily mutated among CF isolates included genes encoding a probable sulfatase, a probable TonB-dependent receptor (PA2332~PA2336), L-cystine transporter (YecS, PA0313), and a probable transcriptional regulator (PA5438). A promoter region of a heme/hemoglobin uptake outer membrane receptor (PhuR, PA4710) was also different between the CF and non-CF isolate groups. Our analysis highlights ways in which the PA genome evolves to survive and persist within the context of chronic CF infection.

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

Genome-wide insights into population structure and host specificity of Campylobacter jejuni

The zoonotic pathogen Campylobacter jejuni is among the leading causes of foodborne diseases worldwide. While C. jejuni colonises many wild animals and livestock, persistence mechanisms enabling the bacterium to adapt to host species' guts are not fully understood. In order to identify putative determinants influencing host preferences of distinct lineages, bootstrapping based on stratified random sampling combined with a k-mer-based genome-wide association was conducted on 490 genomes from diverse origins in Germany and Canada. We show a strong association of both the core and the accessory genome characteristics with distinct host animal species, indicating multiple adaptive trajectories defining the evolution of C. jejuni lifestyle preferences in different ecosystems. Here, we demonstrate that adaptation towards a specific host niche ecology is most likely a long evolutionary and multifactorial process, expressed by gene absence or presence and allele variations of core genes. Several host-specific allelic variants from different phylogenetic backgrounds, including dnaE, rpoB, ftsX or pycB play important roles for genome maintenance and metabolic pathways. Thus, variants of genes important for C. jejuni to cope with specific ecological niches or hosts may be useful markers for both surveillance and future pathogen intervention strategies.

Genome-wide association study identifies the virulence-associated marker in Streptococcus suis serotype 2

Streptococcus suis (S. suis) has been reported to be a highly invasive pathogen in swine, which causes severe infections like meningitis, arthritis and septicemia, and also a zoonotic agent for humans. Although many putative virulence factors (VFs) have been identified, the exact and wildly accepted virulence associated marker and pathogenesis mechanism of S. suis are still unclear. To establish connection of the genotypes with virulence phenotypes, we performed an "internal standard" method based on the zebrafish model to assess the virulence phenotypes of S. suis and did the genome-wide association study (GWAS) based on the genomes of 68 S. suis isolates. Through GWAS, a total number of 172 genes were identified. Among these genes, 143 of them distribute in virulent isolates. Further VFs interaction network analysis based on protein-protein interaction database found that 71 genes identified in this study could interact with known VFs and some of them even played an important role as the bridge between known VFs or formed important hub. In addition, 12 genes were found conserved in virulent isolates and 3 genes were conserved in avirulent isolates, 8 genes of the virulent conserved genes were belonging to a srtBCD pili cluster. Considering that sbp2', a member of the srtBCD pili cluster has been reported as a virulence-associated factor, we predict that sbp2' could be a fitness virulence-associated marker of virulent isolates. Taken together, our findings contribute to the insights in S. suis pathogenesis, enhance the knowledge of the genomic evolution of S. suis and provide several novel virulence-associated candidates.

Genetic variation and function: revealing potential factors associated with microbial phenotypes

Innovations in sequencing technology have generated voluminous microbial and host genomic data, making it possible to detect these genetic variations and analyze the function influenced by them. Recently, many studies have linked such genetic variations to phenotypes through association or comparative analysis, which have further advanced our understanding of multiple microbial functions. In this review, we summarized the application of association analysis in microbes like Mycobacterium tuberculosis, focusing on screening of microbial genetic variants potentially associated with phenotypes such as drug resistance, pathogenesis and novel drug targets etc.; reviewed the application of additional comparative genomic or transcriptomic methods to identify genetic factors associated with functions in microbes; expanded the scope of our study to focus on host genetic factors associated with certain microbes or microbiome and summarized the recent host genetic variations associated with microbial phenotypes, including susceptibility and load after infection of HIV, presence/absence of different taxa, and quantitative traits of microbiome, and lastly, discussed the challenges that may be encountered and the apparent or potential viable solutions. Gene-function analysis of microbe and microbiome is still in its infancy, and in order to unleash its full potential, it is necessary to understand its history, current status, and the challenges hindering its development.

Next-generation microbiology: from comparative genomics to gene function

Microbiology is at a turning point in its 120-year history. Widespread next-generation sequencing has revealed genetic complexity among bacteria that could hardly have been imagined by pioneers such as Pasteur, Escherich and Koch. This data cascade brings enormous potential to improve our understanding of individual bacterial cells and the genetic basis of phenotype variation. However, this revolution in data science cannot replace established microbiology practices, presenting the challenge of how to integrate these new techniques. Contrasting comparative and functional genomic approaches, we evoke molecular microbiology theory and established practice to present a conceptual framework and practical roadmap for next-generation microbiology.

Genomic Characterization of Campylobacter jejuni Adapted to the Guinea Pig (Cavia porcellus) Host

Campylobacter jejuni is the leading bacterial cause of gastroenteritis worldwide with excessive incidence in low-and middle-income countries (LMIC). During a survey for C. jejuni from putative animal hosts in a town in the Peruvian Amazon, we were able to isolate and whole genome sequence two C. jejuni strains from domesticated guinea pigs (Cavia porcellus). The C. jejuni isolated from guinea pigs had a novel multilocus sequence type that shared some alleles with other C. jejuni collected from guinea pigs. Average nucleotide identity and phylogenetic analysis with a collection of C. jejuni subsp. jejuni and C. jejuni subsp. doylei suggest that the guinea pig isolates are distinct. Genomic comparisons demonstrated gene gain and loss that could be associated with guinea pig host specialization related to guinea pig diet, anatomy, and physiology including the deletion of genes involved with selenium metabolism, including genes encoding the selenocysteine insertion machinery and selenocysteine-containing proteins.

Exploring the industrial potential of Lactobacillus delbrueckii ssp. bulgaricus by population genomics and genome-wide association study analysis

Lactobacillus delbrueckii ssp. bulgaricus is one of the most commonly used starter cultures for yogurt production. However, how its genetic background affects acid production capacity is unclear. This study investigated the industrial potential of L. delbrueckii ssp. bulgaricus using population genomics and GWAS analysis. To meet our goal, population genetics and functional genomics analyses were performed on 188 newly sequenced L. delbrueckii ssp. bulgaricus strains isolated from naturally fermented dairy products together with 19 genome sequences retrieved from the NCBI database. Four distinct clusters were identified, and they were correlated with the geographical sites where the samples were collected. The GWAS analysis about acidification fermentation results with sucrose-fortified reconstituted skim milk revealed a significant association between l-lactate dehydrogenase (lldD; Ldb2036) and the bacterial acid production rate. Our study has broadened the understanding of the population structure and genetic diversity of L. delbrueckii ssp. bulgaricus by identifying potential targets for further research, development, and use of lactic acid bacteria in the dairy industry.

Interaction analyses based on growth parameters of GWAS between Escherichia coli and Staphylococcus aureus

To accurately explore the interaction mechanism between Escherichia coli and Staphylococcus aureus, we designed an ecological experiment to monoculture and co-culture E. coli and S. aureus. We co-cultured 45 strains of E. coli and S. aureus, as well as each species individually to measure growth over 36 h. We implemented a genome wide association study (GWAS) based on growth parameters (λ, R, A and s) to identify significant single nucleotide polymorphisms (SNPs) of the bacteria. Three commonly used growth regression equations, Logistic, Gompertz, and Richards, were used to fit the bacteria growth data of each strain. Then each equation's Akaike's information criterion (AIC) value was calculated as a commonly used information criterion. We used the optimal growth equation to estimate the four parameters above for strains in co-culture. By plotting the estimates for each parameter across two strains, we can visualize how growth parameters respond ecologically to environment stimuli. We verified that different genotypes of bacteria had different growth trajectories, although they were the same species. We reported 85 and 52 significant SNPs that were associated with interaction in E. coli and S. aureus, respectively. Many significant genes might play key roles in interaction, such as yjjW, dnaK, aceE, tatD, ftsA, rclR, ftsK, fepA in E. coli, and scdA, trpD, sdrD, SAOUHSC_01219 in S. aureus. Our study illustrated that there were multiple genes working together to affect bacterial interaction, and laid a solid foundation for the later study of more complex inter-bacterial interaction mechanisms.

Genome evolution and the emergence of pathogenicity in avian Escherichia coli

Chickens are the most common birds on Earth and colibacillosis is among the most common diseases affecting them. This major threat to animal welfare and safe sustainable food production is difficult to combat because the etiological agent, avian pathogenic Escherichia coli (APEC), emerges from ubiquitous commensal gut bacteria, with no single virulence gene present in all disease-causing isolates. Here, we address the underlying evolutionary mechanisms of extraintestinal spread and systemic infection in poultry. Combining population scale comparative genomics and pangenome-wide association studies, we compare E. coli from commensal carriage and systemic infections. We identify phylogroup-specific and species-wide genetic elements that are enriched in APEC, including pathogenicity-associated variation in 143 genes that have diverse functions, including genes involved in metabolism, lipopolysaccharide synthesis, heat shock response, antimicrobial resistance and toxicity. We find that horizontal gene transfer spreads pathogenicity elements, allowing divergent clones to cause infection. Finally, a Random Forest model prediction of disease status (carriage vs. disease) identifies pathogenic strains in the emergent ST-117 poultry-associated lineage with 73% accuracy, demonstrating the potential for early identification of emergent APEC in healthy flocks.

Revisiting Campylobacter jejuni Virulence and Fitness Factors: Role in Sensing, Adapting, and Competing

Campylobacter jejuni is the leading cause of bacterial foodborne gastroenteritis world wide and represents a major public health concern. Over the past two decades, significant progress in functional genomics, proteomics, enzymatic-based virulence profiling (EBVP), and the cellular biology of C. jejuni have improved our basic understanding of this important pathogen. We review key advances in our understanding of the multitude of emerging virulence factors that influence the outcome of C. jejuni–mediated infections. We highlight, the spatial and temporal dynamics of factors that promote C. jejuni to sense, adapt and survive in multiple hosts. Finally, we propose cohesive research directions to obtain a comprehensive understanding of C. jejuni virulence mechanisms.

Mechanisms That Shape Microbial Pangenomes

Analyses of multiple whole-genome sequences from the same species have revealed that differences in gene content can be substantial, particularly in prokaryotes. Such variation has led to the recognition of pangenomes, the complete set of genes present in a species - consisting of core genes, present in all individuals, and accessory genes whose presence is variable. Questions now arise about how pangenomes originate and evolve. We describe how gene content variation can arise as a result of the combination of several processes, including random drift, selection, gain/loss balance, and the influence of ecological and epistatic interactions. We believe that identifying the contributions of these processes to pangenomes will need novel theoretical approaches and empirical data.

Efficient association mapping from k-mers-An application in finding sex-specific sequences

Genome wide association studies (GWAS) attempt to map genotypes to phenotypes in organisms. This is typically performed by genotyping individuals using microarray or by aligning whole genome sequencing reads to a reference genome. Both approaches require knowledge of a reference genome which hinders their application to organisms with no or incomplete reference genomes. This caveat can be removed by using alignment-free association mapping methods based on k-mers from sequencing reads. Here we present an improved implementation of an alignment free association mapping method. The new implementation is faster and includes additional features to make it more flexible than the original implementation. We have tested our implementation on an E. Coli ampicillin resistance dataset and observe improvement in execution time over the original implementation while maintaining accuracy in results. We also demonstrate that the method can be applied to find sex specific sequences.

Population Biology and Comparative Genomics of Campylobacter Species

The zoonotic pathogen Campylobacter is the leading cause for bacterial foodborne infections in humans. Campylobacters are most commonly transmitted via the consumption of undercooked poultry meat or raw milk products. The decreasing costs of whole genome sequencing enabled large genome-based analyses of the evolution and population structure of this pathogen, as well as the development of novel high-throughput molecular typing methods. Here, we review the evolutionary development and the population diversity of the two most clinically relevant Campylobacter species; C. jejuni and C. coli. The state-of-the-art phylogenetic studies showed clustering of C. jejuni lineages into host specialists and generalists with coexisting lifestyles in chicken and livestock-associated hosts, as well as the separation of C. coli isolates of riparian origin (waterfowl, water) from C. coli isolated from clinical and farm-related samples. We will give an overview of recombination between both species and the potential impact of horizontal gene transfer on host adaptation in Campylobacter. Additionally, this review briefly places the current knowledge of the population structure of other Campylobacter species such as C. lari, C. concisus and C. upsaliensis into perspective. We also provide an overview of how molecular typing methods such as multilocus sequence typing (MLST) and whole genome MLST have been used to detect and trace Campylobacter outbreaks along the food chain.

Phylogenetic Methods for Genome-Wide Association Studies in Bacteria

Genome-wide association studies in bacteria have great potential to deliver a better understanding of the genetic basis of many biologically important phenotypes, including antibiotic resistance, pathogenicity, and host adaptation. Such studies need however to account for the specificities of bacterial genomics, especially in terms of population structure, homologous recombination, and genomic plasticity. A powerful way to tackle this challenge is to use a phylogenetic approach, which is based on long-standing methodology for the evolutionary analysis of bacterial genomic data. Here we present both the theoretical and practical aspects involved in the use of phylogenetic methods for bacterial genome-wide association studies.

Dissecting seed pigmentation-associated genomic loci and genes by employing dual approaches of reference-based and k-mer-based GWAS with 438 Glycine accessions

The soybean is agro-economically the most important among all cultivated legume crops, and its seed color is considered one of the most attractive factors in the selection-by-breeders. Thus, genome-wide identification of genes and loci associated with seed colors is critical for the precision breeding of crop soybeans. To dissect seed pigmentation-associated genomic loci and genes, we employed dual approaches by combining reference-based genome-wide association study (rbGWAS) and k-mer-based reference-free GWAS (rfGWAS) with 438 Glycine accessions. The dual analytical strategy allowed us to identify four major genomic loci (designated as SP1-SP4 in this study) associated with the seed colors of soybeans. The k-mer analysis enabled us to find an important recombination event that occurred between subtilisin and I-cluster B in the soybean genome, which could describe a special structural feature of ii allele within the I locus (SP3). Importantly, mapping analyses of both mRNAs and small RNAs allowed us to reveal that the subtilisin-CHS1/CHS3 chimeric transcripts generate and act as an initiator towards 'mirtron (i.e., intron-harboring miRNA precursor)'-triggered silencing of chalcone synthase (CHS) genes. Consequently, the results led us to propose a working model of 'mirtron-triggered gene silencing (MTGS)' to elucidate a long-standing puzzle in the genome-wide CHS gene silencing mechanism. In summary, our study reports four major genomic loci, lists of key genes and genome-wide variations that are associated with seed pigmentation in soybeans. In addition, we propose that the MTGS mechanism plays a crucial role in the genome-wide silencing of CHS genes, thereby suggesting a clue to currently predominant soybean cultivars with the yellow seed coat. Finally, this study will provide a broad insight into the interactions and correlations among seed color-associated genes and loci within the context of anthocyanin biosynthetic pathways.

Genome-Wide Identification of Host-Segregating Single-Nucleotide Polymorphisms for Source Attribution of Clinical Campylobacter coli Isolates

Campylobacter is among the most common causes of gastroenteritis worldwide. Campylobacter jejuni and Campylobacter coli are the most common species causing human disease. DNA sequence-based methods for strain characterization have focused largely on C. jejuni, responsible for 80 to 90% of infections, meaning that C. coli epidemiology has lagged behind. Here, we have analyzed the genome of 450 C. coli isolates to determine genetic markers that can discriminate isolates sampled from 3 major reservoir hosts (chickens, cattle, and pigs). These markers then were applied to identify the source of infection of 147 C. coli strains from French clinical cases. Using STRUCTURE software, 259 potential host-segregating markers were revealed by probabilistic characterization of single-nucleotide polymorphism (SNP) frequency variation in strain collections from three different hosts. These SNPs were found in 41 genes or intergenic regions, mostly coding for proteins involved in motility and membrane functions. Source attribution of clinical isolates based on the differential presence of these markers confirmed chickens as the most common source of C. coli infection in France.IMPORTANCE Genome-wide and source attribution studies based on Campylobacter species have shown their importance for the understanding of foodborne infections. Although the use of multilocus sequence typing based on 7 genes from C. jejuni is a powerful method to structure populations, when applied to C. coli, results have not clearly demonstrated its robustness. Therefore, we aim to provide more accurate data based on the identification of single-nucleotide polymorphisms. Results from this study reveal an important number of host-segregating SNPs, found in proteins involved in motility, membrane functions, or DNA repair systems. These findings offer new, interesting opportunities for further study of C. coli adaptation to its environment. Additionally, the results demonstrate that poultry is potentially the main reservoir of C. coli in France.

Reference-free Association Mapping from Sequencing Reads Using k-mers

Association mapping is the process of linking phenotypes with genotypes. In genome wide association studies (GWAS), individuals are first genotyped using microarrays or by aligning sequenced reads to reference genomes. However, both these approaches rely on reference genomes which limits their application to organisms with no or incomplete reference genomes. To address this, reference free association mapping methods have been developed. Here we present the protocol of an alignment free method for association studies which is based on counting k-mers in sequenced reads, testing for associations between k-mers and the phenotype of interest, and local assembly of the k-mers of statistical significance. The method can map associations of categorical phenotypes to sequence and structural variations without requiring prior sequencing of reference genomes.

Bacterial genome-wide association study of hyper-virulent pneumococcal serotype 1 identifies genetic variation associated with neurotropism

Hyper-virulent Streptococcus pneumoniae serotype 1 strains are endemic in Sub-Saharan Africa and frequently cause lethal meningitis outbreaks. It remains unknown whether genetic variation in serotype 1 strains modulates tropism into cerebrospinal fluid to cause central nervous system (CNS) infections, particularly meningitis. Here, we address this question through a large-scale linear mixed model genome-wide association study of 909 African pneumococcal serotype 1 isolates collected from CNS and non-CNS human samples. By controlling for host age, geography, and strain population structure, we identify genome-wide statistically significant genotype-phenotype associations in surface-exposed choline-binding (P = 5.00 × 10-08) and helicase proteins (P = 1.32 × 10-06) important for invasion, immune evasion and pneumococcal tropism to CNS. The small effect sizes and negligible heritability indicated that causation of CNS infection requires multiple genetic and other factors reflecting a complex and polygenic aetiology. Our findings suggest that certain pathogen genetic variation modulate pneumococcal survival and tropism to CNS tissue, and therefore, virulence for meningitis.

Genomic epidemiology of Campylobacter jejuni associated with asymptomatic pediatric infection in the Peruvian Amazon

Campylobacter is the leading bacterial cause of gastroenteritis worldwide and its incidence is especially high in low- and middle-income countries (LMIC). Disease epidemiology in LMICs is different compared to high income countries like the USA or in Europe. Children in LMICs commonly have repeated and chronic infections even in the absence of symptoms, which can lead to deficits in early childhood development. In this study, we sequenced and characterized C. jejuni (n = 62) from a longitudinal cohort study of children under the age of 5 with and without diarrheal symptoms, and contextualized them within a global C. jejuni genome collection. Epidemiological differences in disease presentation were reflected in the genomes, specifically by the absence of some of the most common global disease-causing lineages. As in many other countries, poultry-associated strains were likely a major source of human infection but almost half of local disease cases (15 of 31) were attributable to genotypes that are rare outside of Peru. Asymptomatic infection was not limited to a single (or few) human adapted lineages but resulted from phylogenetically divergent strains suggesting an important role for host factors in the cryptic epidemiology of campylobacteriosis in LMICs.

Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Discovery of genetic variants underlying bacterial phenotypes and the prediction of phenotypes such as antibiotic resistance are fundamental tasks in bacterial genomics. Genome-wide association study (GWAS) methods have been applied to study these relations, but the plastic nature of bacterial genomes and the clonal structure of bacterial populations creates challenges. We introduce an alignment-free method which finds sets of loci associated with bacterial phenotypes, quantifies the total effect of genetics on the phenotype, and allows accurate phenotype prediction, all within a single computationally scalable joint modeling framework. Genetic variants covering the entire pangenome are compactly represented by extended DNA sequence words known as unitigs, and model fitting is achieved using elastic net penalization, an extension of standard multiple regression. Using an extensive set of state-of-the-art bacterial population genomic data sets, we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. Compared to those of previous approaches, which test each genotype-phenotype association separately for each variant and apply a significance threshold, the variants selected by our joint modeling approach overlap substantially.IMPORTANCE Being able to identify the genetic variants responsible for specific bacterial phenotypes has been the goal of bacterial genetics since its inception and is fundamental to our current level of understanding of bacteria. This identification has been based primarily on painstaking experimentation, but the availability of large data sets of whole genomes with associated phenotype metadata promises to revolutionize this approach, not least for important clinical phenotypes that are not amenable to laboratory analysis. These models of phenotype-genotype association can in the future be used for rapid prediction of clinically important phenotypes such as antibiotic resistance and virulence by rapid-turnaround or point-of-care tests. However, despite much effort being put into adapting genome-wide association study (GWAS) approaches to cope with bacterium-specific problems, such as strong population structure and horizontal gene exchange, current approaches are not yet optimal. We describe a method that advances methodology for both association and generation of portable prediction models.

Genome-Scale Metabolic Model Driven Design of a Defined Medium for Campylobacter jejuni M1cam

Campylobacter jejuni, the most frequent cause of food-borne bacterial gastroenteritis, is a fastidious organism when grown in the laboratory. Oxygen is required for growth, despite the presence of the metabolic mechanism for anaerobic respiration. Amino acid auxotrophies are variably reported and energy metabolism can occur through several electron donor/acceptor combinations. Overall, the picture is one of a flexible, but vulnerable metabolism. To understand Campylobacter metabolism, we have constructed a fully curated, metabolic model for the reference organism M1 (our variant is M1cam) and validated it through laboratory experiments. Our results show that M1cam is auxotrophic for methionine, niacinamide, and pantothenate. There are complete biosynthesis pathways for all amino acids except methionine and it can produce energy, but not biomass, in the absence of oxygen. M1cam will grow in DMEM/F-12 defined media but not in the previously published Campylobacter specific defined media tested. Using the model, we identified potential auxotrophies and substrates that may improve growth. With this information, we designed simple defined media containing inorganic salts, the auxotrophic substrates, L-methionine, niacinamide, and pantothenate, pyruvate and additional amino acids L-cysteine, L-serine, and L-glutamine for growth enhancement. Our defined media supports a 1.75-fold higher growth rate than Brucella broth after 48 h at 37°C and sustains the growth of other Campylobacter jejuni strains. This media can be used to design reproducible assays that can help in better understanding the adaptation, stress resistance, and the virulence mechanisms of this pathogen. We have shown that with a well-curated metabolic model it is possible to design a media to grow this fastidious organism. This has implications for the investigation of new Campylobacter species defined through metagenomics, such as C. infans.

Agricultural intensification and the evolution of host specialism in the enteric pathogen Campylobacter jejuni

Modern agriculture has dramatically changed the distribution of animal species on Earth. Changes to host ecology have a major impact on the microbiota, potentially increasing the risk of zoonotic pathogens being transmitted to humans, but the impact of intensive livestock production on host-associated bacteria has rarely been studied. Here, we use large isolate collections and comparative genomics techniques, linked to phenotype studies, to understand the timescale and genomic adaptations associated with the proliferation of the most common food-born bacterial pathogen (Campylobacter jejuni) in the most prolific agricultural mammal (cattle). Our findings reveal the emergence of cattle specialist C. jejuni lineages from a background of host generalist strains that coincided with the dramatic rise in cattle numbers in the 20th century. Cattle adaptation was associated with horizontal gene transfer and significant gene gain and loss. This may be related to differences in host diet, anatomy, and physiology, leading to the proliferation of globally disseminated cattle specialists of major public health importance. This work highlights how genomic plasticity can allow important zoonotic pathogens to exploit altered niches in the face of anthropogenic change and provides information for mitigating some of the risks posed by modern agricultural systems.

Identifying genetic variants underlying phenotypic variation in plants without complete genomes

Structural variants and presence/absence polymorphisms are common in plant genomes, yet they are routinely overlooked in genome-wide association studies (GWAS). Here, we expand the type of genetic variants detected in GWAS to include major deletions, insertions and rearrangements. We first use raw sequencing data directly to derive short sequences, k-mers, that mark a broad range of polymorphisms independently of a reference genome. We then link k-mers associated with phenotypes to specific genomic regions. Using this approach, we reanalyzed 2,000 traits in Arabidopsis thaliana, tomato and maize populations. Associations identified with k-mers recapitulate those found with SNPs, but with stronger statistical support. Importantly, we discovered new associations with structural variants and with regions missing from reference genomes. Our results demonstrate the power of performing GWAS before linking sequence reads to specific genomic regions, which allows the detection of a wider range of genetic variants responsible for phenotypic variation.

Comparative genomics in infectious disease

With more than one million bacterial genome sequences uploaded to public databases in the last 25 years, genomics has become a powerful tool for studying bacterial biology. Here, we review recent approaches that leverage large numbers of whole genome sequences to decipher the spread and pathogenesis of bacterial infectious diseases.

Benchmarking bacterial genome-wide association study methods using simulated genomes and phenotypes

Genome-wide association studies (GWASs) have the potential to reveal the genetics of microbial phenotypes such as antibiotic resistance and virulence. Capitalizing on the growing wealth of bacterial sequence data, microbial GWAS methods aim to identify causal genetic variants while ignoring spurious associations. Bacteria reproduce clonally, leading to strong population structure and genome-wide linkage, making it challenging to separate true 'hits' (i.e. mutations that cause a phenotype) from non-causal linked mutations. GWAS methods attempt to correct for population structure in different ways, but their performance has not yet been systematically and comprehensively evaluated under a range of evolutionary scenarios. Here, we developed a bacterial GWAS simulator (BacGWASim) to generate bacterial genomes with varying rates of mutation, recombination and other evolutionary parameters, along with a subset of causal mutations underlying a phenotype of interest. We assessed the performance (recall and precision) of three widely used single-locus GWAS approaches (cluster-based, dimensionality-reduction and linear mixed models, implemented in plink, pyseer and gemma) and one relatively new multi-locus model implemented in pyseer, across a range of simulated sample sizes, recombination rates and causal mutation effect sizes. As expected, all methods performed better with larger sample sizes and effect sizes. The performance of clustering and dimensionality reduction approaches to correct for population structure were considerably variable according to the choice of parameters. Notably, the multi-locus elastic net (lasso) approach was consistently amongst the highest-performing methods, and had the highest power in detecting causal variants with both low and high effect sizes. Most methods reached the level of good performance (recall >0.75) for identifying causal mutations of strong effect size [log odds ratio (OR) ≥2] with a sample size of 2000 genomes. However, only elastic nets reached the level of reasonable performance (recall=0.35) for detecting markers with weaker effects (log OR ~1) in smaller samples. Elastic nets also showed superior precision and recall in controlling for genome-wide linkage, relative to single-locus models. However, all methods performed relatively poorly on highly clonal (low-recombining) genomes, suggesting room for improvement in method development. These findings show the potential for multi-locus models to improve bacterial GWAS performance. BacGWASim code and simulated data are publicly available to enable further comparisons and benchmarking of new methods.

Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

BACKGROUND

We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control.

RESULTS

The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and > 3,000,000 k-mers, indicating adequate performance of the algorithms used.

CONCLUSIONS

To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

Food-to-Humans Bacterial Transmission

Microorganisms vehiculated by food might benefit health, cause minimal change within the equilibrium of the host microbial community or be associated with foodborne diseases. In this chapter we will focus on human pathogenic bacteria for which food is conclusively demonstrated as their transmission mode to human. We will describe the impact of foodborne diseases in public health, the reservoirs of foodborne pathogens (the environment, human and animals), the main bacterial pathogens and food vehicles causing human diseases, and the drivers for the transmission of foodborne diseases related to the food-chain, host or bacteria features. The implication of food-chain (foodborne pathogens and commensals) in the transmission of resistance to antibiotics relevant to the treatment of human infections is also evidenced. The multiplicity and interplay of drivers related to intensification, diversification and globalization of food production, consumer health status, preferences, lifestyles or behaviors, and bacteria adaptation to different challenges (stress tolerance and antimicrobial resistance) from farm to human, make the prevention of bacteria-food-human transmission a modern and continuous challenge. A global One Health approach is mandatory to better understand and minimize the transmission pathways of human pathogens, including multidrug-resistant pathogens and commensals, through food-chain.

Koutsoumanis K, Allende A, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Hilbert F, Lindqvist R, Nauta M, Peixe L, Ru G, Simmons M, Skandamis P, Suffredini E, Jenkins C, Malorny B, Ribeiro Duarte AS, Torpdahl M, da Silva Felício MT, Guerra B, Rossi M, Herman L. Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms

This Opinion considers the application of whole genome sequencing (WGS) and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne pathogens. WGS offers the highest level of bacterial strain discrimination for food‐borne outbreak investigation and source‐attribution as well as potential for more precise hazard identification, thereby facilitating more targeted risk assessment and risk management. WGS improves linking of sporadic cases associated with different food products and geographical regions to a point source outbreak and can facilitate epidemiological investigations, allowing also the use of previously sequenced genomes. Source attribution may be favoured by improved identification of transmission pathways, through the integration of spatial‐temporal factors and the detection of multidirectional transmission and pathogen–host interactions. Metagenomics has potential, especially in relation to the detection and characterisation of non‐culturable, difficult‐to‐culture or slow‐growing microorganisms, for tracking of hazard‐related genetic determinants and the dynamic evaluation of the composition and functionality of complex microbial communities. A SWOT analysis is provided on the use of WGS and metagenomics for Salmonella and Shigatoxin‐producing Escherichia coli (STEC) serotyping and the identification of antimicrobial resistance determinants in bacteria. Close agreement between phenotypic and WGS‐based genotyping data has been observed. WGS provides additional information on the nature and localisation of antimicrobial resistance determinants and on their dissemination potential by horizontal gene transfer, as well as on genes relating to virulence and biological fitness. Interoperable data will play a major role in the future use of WGS and metagenomic data. Capacity building based on harmonised, quality controlled operational systems within European laboratories and worldwide is essential for the investigation of cross‐border outbreaks and for the development of international standardised risk assessments of food‐borne microorganisms.

Biofilm Formation of Listeria monocytogenes Strains Under Food Processing Environments and Pan-Genome-Wide Association Study

Concerns about food contamination by Listeria monocytogenes are on the rise with increasing consumption of ready-to-eat foods. Biofilm production of L. monocytogenes is presumed to be one of the ways that confer its increased resistance and persistence in the food chain. In this study, a collection of isolates from foods and food processing environments (FPEs) representing persistent, prevalent, and rarely detected genotypes was evaluated for biofilm forming capacities including adhesion and sessile biomass production under diverse environmental conditions. The quantity of sessile biomass varied according to growth conditions, lineage, serotype as well as genotype but association of clonal complex (CC) 26 genotype with biofilm production was evidenced under cold temperature. In general, relative biofilm productivity of each strain varied inconsistently across growth conditions. Under our experimental conditions, there were no clear associations between biofilm formation efficiency and persistent or prevalent genotypes. Distinct extrinsic factors affected specific steps of biofilm formation. Sudden nutrient deprivation enhanced cellular adhesion while a prolonged nutrient deficiency impeded biofilm maturation. Salt addition increased biofilm production, moreover, nutrient limitation supplemented by salt significantly stimulated biofilm formation. Pan-genome-wide association study (Pan-GWAS) assessed genetic composition with regard to biofilm phenotypes for the first time. The number of reported genes differed depending on the growth conditions and the number of common genes was low. However, a broad overview of the ontology contents revealed similar patterns regardless of the conditions. Functional analysis showed that functions related to transformation/competence and surface proteins including Internalins were highly enriched.

Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale

BACKGROUND

Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv).

RESULTS

Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively.

CONCLUSIONS

Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

Pathogenomics of Emerging Campylobacter Species

Campylobacter is among the four main causes of gastroenteritis worldwide and has increased in both developed and developing countries over the last 10 years. The vast majority of reported Campylobacter infections are caused by Campylobacter jejuni and, to a lesser extent, C. coli; however, the increasing recognition of other emerging Campylobacter pathogens is urgently demanding a better understanding of how these underestimated species cause disease, transmit, and evolve. In parallel to the enhanced clinical awareness of campylobacteriosis due to improved diagnostic protocols, the application of high-throughput sequencing has increased the number of whole-genome sequences available to dozens of strains of many emerging campylobacters. This has allowed for comprehensive comparative pathogenomic analyses for several species, such as C. fetus and C. concisus These studies have started to reveal the evolutionary forces shaping their genomes and have brought to light many genomic features related to pathogenicity in these neglected species, promoting the development of new tools and approaches relevant for clinical microbiology. Despite the need for additional characterization of genomic diversity in emerging campylobacters, the increasing body of literature describing pathogenomic studies on these species deserves to be discussed from an integrative perspective. This review compiles the current knowledge and highlights future work toward deepening our understanding about genome dynamics and the mechanisms governing the evolution of pathogenicity in emerging Campylobacter species, which is urgently needed to develop strategies to prevent or control the spread of these pathogens.

Domestication of Campylobacter jejuni NCTC 11168

Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterized isolates among laboratories has run in parallel with research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. Campylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first Campylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C. jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates, identified previously to have aberrant phenotypes, varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37 °C, invasion of chicken and human cell lines, and susceptibility to ampicillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains. This article contains data hosted by Microreact.

Whole-genome comparative analysis of Campylobacter jejuni strains isolated from patients with diarrhea in northeastern Poland

BACKGROUND

Campylobacter jejuni is the leading cause of bacterial gastroenteritis (campylobacteriosis) in humans worldwide, and the most frequent pathogen associated with Guillain-Barré syndrome (GBS) and Miller-Fisher syndrome (MFS). The study was designed in order to assess similarities between genomes of Campylobacter jejuni strains, isolated from children suffering from acute diarrhea in northeastern Poland, in comparison to C. jejuni genomes stored in public databases. The analysis involved phylogeny, resistome and virulome. In addition, the Campylobacter PubMLST database was used to estimate the prevalence of the analyzed C. jejuni sequence type (STs) in other countries.

RESULTS

Campylobacter jejuni ST50, ST257 and ST51 represented 5.3%, 4.5% and 2.2% of the PubMLST records, respectively. Overall, strains representing the STs showed common resistance to tetracyclines (51.3%) and fluoroquinolones (31.8%), mediated through the tetO gene (98.2%) and point mutation (T86I) in the gyrA gene (100%). However, the latter was present in all our isolates. The major differences in virulence patterns concerned serotypes, lipooligosaccharide (LOS) classes and certain clinically relevant genes.

CONCLUSIONS

Campylobacter jejuni ST50, ST51 and ST257 are among the top ten of STs isolated in Europe. WGS revealed diversity of serotypes and LOS classes in ST50 strains, that deserves further clinical and epidemiological investigations as it might be related to a risk of post-infectious neurological sequels such as Guillain-Barré syndrome. Additionally, the results implicate lower pathogenic potential and distinct transmission chains or reservoirs for C. jejuni ST51 isolates responsible for campylobacteriosis in northeastern Poland.

Source attribution of Campylobacter jejuni shows variable importance of chicken and ruminants reservoirs in non-invasive and invasive French clinical isolates

Campylobacter jejuni is the most common cause of bacterial gastroenteritis worldwide. Mainly isolated from stool samples, C. jejuni can also become invasive. C. jejuni belongs to the commensal microbiota of a number of hosts, and infection by this bacterium can sometimes be traced back to exposure to a specific source. Here we genome sequenced 200 clinical isolates (2010–2016) and analyzed them with 701 isolate genomes from human infection, chicken, ruminants and the environment to examine the relative contribution of different reservoirs to non-invasive and invasive infection in France. Host-segregating genetic markers that can discriminate C. jejuni source were used with STRUCTURE software to probabilistically attribute the source of clinical strains. A self-attribution correction step, based upon the accuracy of source apportionment within each potential reservoir, improved attribution accuracy of clinical strains and suggested an important role for ruminant reservoirs in non-invasive infection and a potentially increased contribution of chicken as a source of invasive isolates. Structured sampling of Campylobacter in the clinic and from potential reservoirs provided evidence for variation in the contribution of different infection sources over time and an important role for non-poultry reservoirs in France. This provides a basis for ongoing genomic epidemiology surveillance and targeted interventions.

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of 'omics' techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

Comparative Transcriptomic Profiling of Yersinia enterocolitica O:3 and O:8 Reveals Major Expression Differences of Fitness- and Virulence-Relevant Genes Indicating Ecological Separation

Yersinia enterocolitica is a major diarrheal pathogen and is associated with a large range of gut-associated diseases. Members of this species have evolved into different phylogroups with genotypic variations. We performed the first characterization of the Y. enterocolitica transcriptional landscape and tracked the consequences of the genomic variations between two different pathogenic phylogroups by comparing their RNA repertoire, promoter usage, and expression profiles under four different virulence-relevant conditions. Our analysis revealed major differences in the transcriptional outputs of the closely related strains, pointing to an ecological separation in which one is more adapted to an environmental lifestyle and the other to a mostly mammal-associated lifestyle. Moreover, a variety of pathoadaptive alterations, including alterations in acid resistance genes, colonization factors, and toxins, were identified which affect virulence and host specificity. This illustrates that comparative transcriptomics is an excellent approach to discover differences in the functional output from closely related genomes affecting niche adaptation and virulence, which cannot be directly inferred from DNA sequences.

Yersinia enterocolitica is a zoonotic pathogen and an important cause of bacterial gastrointestinal infections in humans. Large-scale population genomic analyses revealed genetic and phenotypic diversity of this bacterial species, but little is known about the differences in the transcriptome organization, small RNA (sRNA) repertoire, and transcriptional output. Here, we present the first comparative high-resolution transcriptome analysis of Y. enterocolitica strains representing highly pathogenic phylogroup 2 (serotype O:8) and moderately pathogenic phylogroup 3 (serotype O:3) grown under four infection-relevant conditions. Our transcriptome sequencing (RNA-seq) approach revealed 1,299 and 1,076 transcriptional start sites and identified strain-specific sRNAs that could contribute to differential regulation among the phylogroups. Comparative transcriptomics further uncovered major gene expression differences, in particular, in the temperature-responsive regulon. Multiple virulence-relevant genes are differentially regulated between the two strains, supporting an ecological separation of phylogroups with certain niche-adapted properties. Strong upregulation of the ystA enterotoxin gene in combination with constitutive high expression of cell invasion factor InvA further showed that the toxicity of recent outbreak O:3 strains has increased. Overall, our report provides new insights into the specific transcriptome organization of phylogroups 2 and 3 and reveals gene expression differences contributing to the substantial phenotypic differences that exist between the lineages.

IMPORTANCEYersinia enterocolitica is a major diarrheal pathogen and is associated with a large range of gut-associated diseases. Members of this species have evolved into different phylogroups with genotypic variations. We performed the first characterization of the Y. enterocolitica transcriptional landscape and tracked the consequences of the genomic variations between two different pathogenic phylogroups by comparing their RNA repertoire, promoter usage, and expression profiles under four different virulence-relevant conditions. Our analysis revealed major differences in the transcriptional outputs of the closely related strains, pointing to an ecological separation in which one is more adapted to an environmental lifestyle and the other to a mostly mammal-associated lifestyle. Moreover, a variety of pathoadaptive alterations, including alterations in acid resistance genes, colonization factors, and toxins, were identified which affect virulence and host specificity. This illustrates that comparative transcriptomics is an excellent approach to discover differences in the functional output from closely related genomes affecting niche adaptation and virulence, which cannot be directly inferred from DNA sequences.

Using a Systems Biology Approach To Study Host-Pathogen Interactions

The rapid development of genomics and other "-omics" approaches has significantly impacted how we have investigated host-pathogen interactions since the turn of the millennium. Technologies such as next-generation sequencing, stem cell biology, and high-throughput proteomics have transformed the scale and sensitivity with which we interrogate biological samples. These approaches are impacting experimental design in the laboratory and transforming clinical management in health care systems. Here, we review this area from the perspective of research on bacterial pathogens.

Panton-Valentine leucocidin is the key determinant of Staphylococcus aureus pyomyositis in a bacterial GWAS

Pyomyositis is a severe bacterial infection of skeletal muscle, commonly affecting children in tropical regions, predominantly caused by Staphylococcus aureus. To understand the contribution of bacterial genomic factors to pyomyositis, we conducted a genome-wide association study of S. aureus cultured from 101 children with pyomyositis and 417 children with asymptomatic nasal carriage attending the Angkor Hospital for Children, Cambodia. We found a strong relationship between bacterial genetic variation and pyomyositis, with estimated heritability 63.8% (95% CI 49.2–78.4%). The presence of the Panton–Valentine leucocidin (PVL) locus increased the odds of pyomyositis 130-fold (p=10^-17.9). The signal of association mapped both to the PVL-coding sequence and to the sequence immediately upstream. Together these regions explained over 99.9% of heritability (95% CI 93.5–100%). Our results establish staphylococcal pyomyositis, like tetanus and diphtheria, as critically dependent on a single toxin and demonstrate the potential for association studies to identify specific bacterial genes promoting severe human disease.

Certain bacteria that normally live on the skin or in the nose without causing problems can sometimes lead to diseases elsewhere in the body. For example, the bacterium Staphylococcus aureus can cause blood infections or a severe and painful infection of the muscle called pyomyositis, which is very common in children who live in the tropics.

Scientists believe that pyomyositis happens when S. aureus bacteria in the blood stream infect the muscles. Some strains of this bacteria are more likely to cause such infections, but why is unclear. One potential cause is a toxin produced by some S. aureus bacteria called Panton-Valentine leucocidin (PVL). So far, studies looking at whether PVL-producing bacteria are more likely to cause pyomyositis have had conflicting results.

Now, Young et al. show that the gene for PVL is always present in S. aureus strains that cause pyomyosistis in Cambodian children, but is rarely found in S. aureus taken from the noses of their healthy counterparts. In the experiments, bacteria were collected from 101 children with pyomyositis and from the noses of 417 healthy children at the Angkor Hospital for Children in Cambodia over a 5-year period. The DNA in these bacteria were compared using very sensitive genetic techniques. The comparisons showed having the gene for PVL increased the odds of having pyomyositis 130-fold, showing that this one toxin likely accounts for much of the risk of developing this disease.

If more studies confirm the link between PVL and pyomyositis, developing vaccines that block the gene for PVL might be one way to protect children in the tropics from developing this infection. Treating children with pyomyositis with antibiotics that reduce the production of the PVL toxin may also be helpful.

Whole-genome sequencing of bloodstream Staphylococcus aureus isolates does not distinguish bacteraemia from endocarditis

Most Staphylococcus aureus isolates can cause invasive disease given the right circumstances, but it is unknown if some isolates are more likely to cause severe infections than others. S. aureus bloodstream isolates from 120 patients with definite infective endocarditis and 121 with S. aureus bacteraemia without infective endocarditis underwent whole-genome sequencing. Genome-wide association analysis was performed using a variety of bioinformatics approaches including SNP analysis, accessory genome analysis and k-mer based analysis. Core and accessory genome analyses found no association with either of the two clinical groups. In this study, the genome sequences of S. aureus bloodstream isolates did not discriminate between bacteraemia and infective endocarditis. Based on our study and the current literature, it is not convincing that a specific S. aureus genotype is clearly associated to infective endocarditis in patients with S. aureus bacteraemia.