Bacterial genomes in epidemiology--present and future

Comparative sequence analysis elucidates the evolutionary patterns of Yersinia pestis in New Mexico over thirty-two years

Background

Yersinia pestis, a Gram-negative bacterium, is the causative agent of plague. Y. pestis is a zoonotic pathogen that occasionally infects humans and became endemic in the western United States after spreading from California in 1899.

Methods

To better understand evolutionary patterns in Y. pestis from the southwestern United States, we sequenced and analyzed 22 novel genomes from New Mexico. Analytical methods included, assembly, multiple sequences alignment, phylogenetic tree reconstruction, genotype-phenotype correlation, and selection pressure.

Results

We identified four genes, including Yscp and locus tag YPO3944, which contained codons undergoing negative selection. We also observed 42 nucleotide sites displaying a statistically significant skew in the observed residue distribution based on the year of isolation. Overall, the three genes with the most statistically significant variations that associated with metadata for these isolates were sapA, fliC, and argD. Phylogenetic analyses point to a single introduction of Y. pestis into the United States with two subsequent, independent movements into New Mexico. Taken together, these analyses shed light on the evolutionary history of this pathogen in the southwestern US over a focused time range and confirm a single origin and introduction into North America.

Accurate and fast graph-based pangenome annotation and clustering with ggCaller

Bacterial genomes differ in both gene content and sequence mutations, which underlie extensive phenotypic diversity, including variation in susceptibility to antimicrobials or vaccine-induced immunity. To identify and quantify important variants, all genes within a population must be predicted, functionally annotated, and clustered, representing the "pangenome." Despite the volume of genome data available, gene prediction and annotation are currently conducted in isolation on individual genomes, which is computationally inefficient and frequently inconsistent across genomes. Here, we introduce the open-source software graph-gene-caller (ggCaller). ggCaller combines gene prediction, functional annotation, and clustering into a single workflow using population-wide de Bruijn graphs, removing redundancy in gene annotation and resulting in more accurate gene predictions and orthologue clustering. We applied ggCaller to simulated and real-world bacterial data sets containing hundreds or thousands of genomes, comparing it to current state-of-the-art tools. ggCaller has considerable speed-ups with equivalent or greater accuracy, particularly with data sets containing complex sources of error, such as assembly contamination or fragmentation. ggCaller is also an important extension to bacterial genome-wide association studies, enabling querying of annotated graphs for functional analyses. We highlight this application by functionally annotating DNA sequences with significant associations to tetracycline and macrolide resistance in Streptococcus pneumoniae, identifying key resistance determinants that were missed when using only a single reference genome. ggCaller is a novel bacterial genome analysis tool with applications in bacterial evolution and epidemiology.

Genomic epidemiology of clinical ESBL-producing Enterobacteriaceae in a German hospital suggests infections are primarily community- and regionally-acquired

Clinical Enterobacteriaceae isolates that produce extended-spectrum β-lactamases (ESBLs) have been increasingly reported at a global scale. However, comprehensive data on the molecular epidemiology of ESBL-producing strains are limited and few studies have been conducted in non-outbreak situations.We used whole-genome sequencing to describe the population structure of 294 ESBL-producing Escherichia coli and Klebsiella pneumoniae isolates that were recovered from a German community hospital throughout a 1 year sampling period in a non-outbreak situation.We found a high proportion of E. coli isolates (61.5 %) belonged to the globally disseminated extraintestinal pathogenic ST131, whereas a wider diversity of STs was observed among K. pneumoniae isolates. The E. coli ST131 population in this study was shaped by multiple introductions of strains as demonstrated by contextual genomic analysis including ST131 strains from other geographical sources. While no recent common ancestor of the isolates of the current study and other international isolates was found, our clinical isolates clustered with those previously recovered in the region. Furthermore, we found that the isolation of ESBL-producing clinical strains in hospitalized patients could only rarely be associated with likely patient-to-patient transmission, indicating primarily a community and regional acquisition of strains.Further genomic analyses of clinical, carriage and environmental isolates is needed to uncover hidden transmissions and thus discover the most common sources of ESBL-producing pathogen infections in our hospitals.

Systems-Based Approach for Optimization of Assembly-Free Bacterial MLST Mapping

Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turnaround, while aiming at generating two main outcomes: (1) species-level identification and (2) variant mapping at different levels of genotypic resolution for population-based tracking and surveillance, in addition to predicting traits such as antimicrobial resistance (AMR). Multi-locus sequence typing (MLST) aids this process by identifying sequence types (ST) based on seven ubiquitous genome-scattered loci. In this paper, we selected one assembly-dependent and one assembly-free method for ST mapping and applied them with the default settings and ST schemes they are distributed with, and systematically assessed their accuracy and scalability across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens with available MLST databases. Our data show that the optimal k-mer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect the performance and accuracy of the program. Although suitable parameters could be identified for most organisms, there were instances where this program may not be directly deployable in its current format. Next, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis.

Using whole-genome sequence data to examine the epidemiology of antimicrobial resistance in Escherichia coli from wild meso-mammals and environmental sources on swine farms, conservation areas, and the Grand River watershed in southern Ontario, Canada

Antimicrobial resistance (AMR) threatens the health of humans and animals and has repeatedly been detected in wild animal species across the world. This cross-sectional study integrates whole-genome sequence data from Escherichia coli isolates with demonstrated phenotypic resistance that originated from a previous longitudinal wildlife study in southern Ontario, as well as phenotypically resistant E. coli water isolates previously collected as part of a public health surveillance program. The objective of this work was to assess for evidence of possible transmission of antimicrobial resistance determinants between wild meso-mammals, swine manure pits, and environmental sources on a broad scale in the Grand River watershed, and at a local scale—for the subset of samples collected on both swine farms and conservation areas in the previous wildlife study. Logistic regression models were used to assess potential associations between sampling source, location type (swine farm vs. conservation area), and the occurrence of select resistance genes and predicted plasmids. In total, 200 isolates from the following sources were included: water (n = 20), wildlife (n = 73), swine manure pit (n = 31), soil (n = 73), and dumpsters (n = 3). Several genes and plasmid incompatibility types were significantly more likely to be identified on swine farms compared to conservation areas. Conversely, internationally distributed sequence types (e.g., ST131), extended-spectrum beta-lactamase- and AmpC-producing E. coli were isolated in lower prevalences (<10%) and were almost exclusively identified in water sources, or in raccoon and soil isolates obtained from conservation areas. Differences in the odds of detecting resistance genes and predicted plasmids among various sources and location types suggest different primary sources for individual AMR determinants, but, broadly, our findings suggest that raccoons, skunks and opossums in this region may be exposed to AMR pollution via water and agricultural sources, as well as anthropogenic sources in conservation areas.

Using whole-genome sequence data to examine the epidemiology of Salmonella, Escherichia coli and associated antimicrobial resistance in raccoons (Procyon lotor), swine manure pits, and soil samples on swine farms in southern Ontario, Canada

To better understand the contribution of wildlife to the dissemination of Salmonella and antimicrobial resistance in Salmonella and Escherichia coli, we examined whole-genome sequence data from Salmonella and E. coli isolates collected from raccoons (Procyon lotor) and environmental sources on farms in southern Ontario. All Salmonella and phenotypically resistant E. coli collected from raccoons, soil, and manure pits on five swine farms as part of a previous study were included. We assessed for evidence of potential transmission of these organisms between different sources and farms utilizing a combination of population structure assessments (using core-genome multi-locus sequence typing), direct comparisons of multi-drug resistant isolates, and epidemiological modeling of antimicrobial resistance (AMR) genes and plasmid incompatibility (Inc) types. Univariable logistic regression models were fit to assess the impact of source type, farm location, and sampling year on the occurrence of select resistance genes and Inc types. A total of 159 Salmonella and 96 resistant E. coli isolates were included. A diversity of Salmonella serovars and sequence types were identified, and, in some cases, we found similar or identical Salmonella isolates and resistance genes between raccoons, soil, and swine manure pits. Certain Inc types and resistance genes associated with source type were consistently more likely to be identified in isolates from raccoons than swine manure pits, suggesting that manure pits are not likely a primary source of those particular resistance determinants for raccoons. Overall, our data suggest that transmission of Salmonella and AMR determinants between raccoons and swine manure pits is uncommon, but soil-raccoon transmission appears to be occurring frequently. More comprehensive sampling of farms, and assessment of farms with other livestock species, as well as additional environmental sources (e.g., rivers) may help to further elucidate the movement of resistance genes between these various sources.

Phylogeography and resistome of pneumococcal meningitis in West Africa before and after vaccine introduction

Despite contributing to the large disease burden in West Africa, little is known about the genomic epidemiology of Streptococcus pneumoniae which cause meningitis among children under 5 years old in the region. We analysed whole-genome sequencing data from 185 S. pneumoniae isolates recovered from suspected paediatric meningitis cases as part of the World Health Organization (WHO) invasive bacterial diseases surveillance from 2010 to 2016. The phylogeny was reconstructed, accessory genome similarity was computed and antimicrobial-resistance patterns were inferred from the genome data and compared to phenotypic resistance from disc diffusion. We studied the changes in the distribution of serotypes pre- and post-pneumococcal conjugate vaccine (PCV) introduction in the Central and Western sub-regions separately. The overall distribution of non-vaccine, PCV7 (4, 6B, 9V, 14, 18C, 19F and 23F) and additional PCV13 serotypes (1, 3, 5, 6A, 19A and 7F) did not change significantly before and after PCV introduction in the Central region (Fisher's test P value 0.27) despite an increase in the proportion of non-vaccine serotypes to 40 % (n=6) in the post-PCV introduction period compared to 21.9 % (n=14). In the Western sub-region, PCV13 serotypes were more dominant among isolates from The Gambia following the introduction of PCV7, 81 % (n=17), compared to the pre-PCV period in neighbouring Senegal, 51 % (n=27). The phylogeny illustrated the diversity of strains associated with paediatric meningitis in West Africa and highlighted the existence of phylogeographical clustering, with isolates from the same sub-region clustering and sharing similar accessory genome content. Antibiotic-resistance genotypes known to confer resistance to penicillin, chloramphenicol, co-trimoxazole and tetracycline were detected across all sub-regions. However, there was no discernible trend linking the presence of resistance genotypes with the vaccine introduction period or whether the strain was a vaccine or non-vaccine serotype. Resistance genotypes appeared to be conserved within selected sub-clades of the phylogenetic tree, suggesting clonal inheritance. Our data underscore the need for continued surveillance on the emergence of non-vaccine serotypes as well as chloramphenicol and penicillin resistance, as these antibiotics are likely still being used for empirical treatment in low-resource settings. This article contains data hosted by Microreact.

A multisite genomic epidemiology study of Clostridioides difficile infections in the USA supports differential roles of healthcare versus community spread for two common strains

Clostridioides difficile is the leading cause of healthcare-associated infectious diarrhoea. However, it is increasingly appreciated that healthcare-associated infections derive from both community and healthcare environments, and that the primary sites of C. difficile transmission may be strain-dependent. We conducted a multisite genomic epidemiology study to assess differential genomic evidence of healthcare vs community spread for two of the most common C. difficile strains in the USA: sequence type (ST) 1 (associated with ribotype 027) and ST2 (associated with ribotype 014/020). We performed whole-genome sequencing and phylogenetic analyses on 382 ST1 and ST2 C. difficile isolates recovered from stool specimens collected during standard clinical care at 3 geographically distinct US medical centres between 2010 and 2017. ST1 and ST2 isolates both displayed some evidence of phylogenetic clustering by study site, but clustering was stronger and more apparent in ST1, consistent with our healthcare-based study more comprehensively sampling local transmission of ST1 compared to ST2 strains. Analyses of pairwise single-nucleotide variant (SNV) distance distributions were also consistent with more evidence of healthcare transmission of ST1 compared to ST2, with 44 % of ST1 isolates being within two SNVs of another isolate from the same geographical collection site compared to 5.5 % of ST2 isolates (P-value=<0.001). Conversely, ST2 isolates were more likely to have close genetic neighbours across disparate geographical sites compared to ST1 isolates, further supporting non-healthcare routes of spread for ST2 and highlighting the potential for misattributing genomic similarity among ST2 isolates to recent healthcare transmission. Finally, we estimated a lower evolutionary rate for the ST2 lineage compared to the ST1 lineage using Bayesian timed phylogenomic analyses, and hypothesize that this may contribute to observed differences in geographical concordance among closely related isolates. Together, these findings suggest that ST1 and ST2, while both common causes of C. difficile infection in hospitals, show differential reliance on community and hospital spread. This conclusion supports the need for strain-specific criteria for interpreting genomic linkages and emphasizes the importance of considering differences in the epidemiology of circulating strains when devising interventions to reduce the burden of C. difficile infections.

High Risk Clone: A Proposal of Criteria Adapted to the One Health Context with Application to Enterotoxigenic Escherichia coli in the Pig Population

The definition of a high risk clone for antibiotic resistance dissemination was initially established for human medicine. We propose a revised definition of a high risk clone adapted to the One Health context. Then, we applied our criteria to a cluster of enrofloxacin non susceptible ETEC:F4 isolates which emerged in 2013 in diseased pigs in Quebec. The whole genomes of 183 ETEC:F4 strains isolated in Quebec from 1990 to 2018 were sequenced. The presence of virulence and resistance genes and replicons was examined in 173 isolates. Maximum likelihood phylogenetic trees were constructed based on SNP data and clones were identified using a set of predefined criteria. The strains belonging to the clonal lineage ST100/O149:H10 isolated in Quebec in 2013 or later were compared to ETEC:F4 whole genome sequences available in GenBank. Prior to 2000, ETEC:F4 isolates from pigs in Quebec were mostly ST90 and belonged to several serotypes. After 2000, the isolates were mostly ST100/O149:H10. In this article, we demonstrated the presence of a ETEC:F4 high risk clone. This clone (1) emerged in 2013, (2) is multidrug resistant, (3) has a widespread distribution over North America and was able to persist several months on farms, and (4) possesses specific virulence genes. It is crucial to detect and characterize high risk clones in animal populations to increase our understanding of their emergence and their dissemination.

Clinical and molecular characteristics of carbapenem non-susceptible Escherichia coli: A nationwide survey from Oman

The prevalence of carbapenem-resistant Enterobacterales (CRE) in the Arabian Peninsula is predicted to be high, as suggested from published case reports. Of particular concern, is carbapenem-resistant E. coli (CR-EC), due to the importance of this species as a community pathogen. Herein, we conducted a comprehensive molecular characterization of putative CR-EC strains from Oman. We aim to establish a baseline for future molecular monitoring. We performed whole-genome sequencing (WGS) for 35 putative CR-EC. Isolates were obtained from patients at multiple centers in 2015. Genetic relatedness was investigated using several typing approaches such as MLST, SNP calling, phylogroup and CRISPR typing. Maxiuium likelihood SNP-tree was performed by RAxML after variant calling and removal of recombination regions with Snippy and Gubbins, respectively. Resistance genes, plasmid replicon types, virulence genes, and prophage were also characterised. The online databases CGE, CRISPRcasFinder, Phaster and EnteroBase were used for the in silico analyses. Screening for mutations in genes regulating the expression of porins and efflux pump as well as mutations lead to fluoroquinolones resistance were performed with CLC Genomics Workbench. The genetic diversity suggests a polyclonal population structure with 21 sequence types (ST), of which ST38 being the most prevalent (11%). SNPs analysis revealed possible transmission episodes. Whereas, CRISPR typing helped to spot outlier strains belonged to phylogroups other than B2 which was CRISPR-free. The virulent phylogroups B2 and D were detected in 4 and 9 isolates, respectively. In some strains bacteriophages acted as vectors for virulence genes. Regarding resistance to β-lactam, 22 were carbapenemase producers, 3 carbapenem non-susceptible but carbapenemase-negative, 9 resistant to expanded-spectrum cephalosporins, and one isolate with susceptibility to cephalosporins and carbapenems. Thirteen out of the 22 (59%) carbapenemase-producing isolates were NDM and 7 (23%) were OXA-48-like which mirrors the situation in Indian subcontinent. Two isolates co-produced NDM and OXA-48-like enzymes. In total, 80% (28/35) were CTX-M-15 producers and 23% (8/35) featured AmpC. The high-risk subclones ST131-H30Rx/C2, ST410-H24RxC and ST1193-H64RxC were detected, the latter associated with NDM. To our knowledge, this is the first report of ST1193-H64Rx subclone with NDM. In conclusion, strains showed polyclonal population structure with OXA-48 and NDM as the only carbapenemases in CR-EC from Oman. We detected the high-risk subclone ST131-H30Rx/C2, ST410-H24RxC and ST1193-H64RxC. The latter was reported with carbapenemase gene for the first time here.

Hospital-based Surveillance Provides Insights Into the Etiology of Pediatric Bacterial Meningitis in Yaoundé, Cameroon, in the Post-Vaccine Era

Background

Meningitis is endemic to regions of Cameroon outside the meningitis belt including the capital city, Yaoundé. Through surveillance, we studied the etiology and molecular epidemiology of pediatric bacterial meningitis in Yaoundé from 2010 to 2016.

Methods

Lumbar puncture was performed on 5958 suspected meningitis cases; 765 specimens were further tested by culture, latex agglutination, and/or polymerase chain reaction (PCR). Serotyping/grouping, antimicrobial susceptibility testing, and/or whole genome sequencing were performed where applicable.

Results

The leading pathogens detected among the 126 confirmed cases were Streptococcus pneumoniae (93 [73.8%]), Haemophilus influenzae (18 [14.3%]), and Neisseria meningitidis (15 [11.9%]). We identified more vaccine serotypes (19 [61%]) than nonvaccine serotypes (12 [39%]); however, in the latter years non–pneumococcal conjugate vaccine serotypes were more common. Whole genome data on 29 S. pneumoniae isolates identified related strains (<30 single-nucleotide polymorphism difference). All but 1 of the genomes harbored a resistance genotype to at least 1 antibiotic, and vaccine serotypes harbored more resistance genes than nonvaccine serotypes (P < .05). Of 9 cases of H. influenzae, 8 were type b (Hib) and 1 was type f. However, the cases of Hib were either in unvaccinated individuals or children who had not yet received all 3 doses. We were unable to serogroup the N. meningitidis cases by PCR.

Conclusions

Streptococcus pneumoniae remains a leading cause of pediatric bacterial meningitis, and nonvaccine serotypes may play a bigger role in disease etiology in the postvaccine era. There is evidence of Hib disease among children in Cameroon, which warrants further investigation.

Genotypic differences in CC224, CC363, CC449 and CC446 of Moraxella catarrhalis isolates based on whole genome SNP, MLST and PFGE typing

Understanding the evolutionary path of M. catarrhalis from macrolide-susceptible to macrolide-resistant organism, is important for hindering macrolide resistance from propagation. Multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) and whole genome SNP typing (WGST), as useful and practical typing tools, have both advantages and disadvantages. We studied the utility of these 3 typing methods, including the level of agreement, consistency and drawbacks, in characterizing M. catarrhalis clones and clonal complexes. We focused on four clonal complexes [CC224, CC363, CC449 (CCN10) and CC446 (CCN08)] and found that PFGE and WGST had a high level of agreement and a proper consistency of the same clone or very closely related clones, while MLST is less discriminatory for different clones. Furthermore, we also established an evolutionary distance cut-off value for "The same clone". Moreover, we detected macrolide-resistant M. catarrhalis in CC224, which had previously been considered as a macrolide-susceptible clonal complex. A higher number of isolates belonged to ST215 compared to ST446, implying that ST215 is more likely to be the primary founder. Our study also demonstrated that all the four clonal complexes belong to the M. catarrhalis lineage 1, which is considered to be related to increased virulence potential and serum resistance. We also observed that copB II was highly related to CC449 and LOS type B was mainly confined in CC224. In conclusion, these findings provide further insight into the evolutionary characteristics of M. catarrhalis.

Synergistic Activity of Mobile Genetic Element Defences in Streptococcus pneumoniae

A diverse set of mobile genetic elements (MGEs) transmit between Streptococcus pneumoniae cells, but many isolates remain uninfected. The best-characterised defences against horizontal transmission of MGEs are restriction-modification systems (RMSs), of which there are two phase-variable examples in S. pneumoniae. Additionally, the transformation machinery has been proposed to limit vertical transmission of chromosomally integrated MGEs. This work describes how these mechanisms can act in concert. Experimental data demonstrate RMS phase variation occurs at a sub-maximal rate. Simulations suggest this may be optimal if MGEs are sometimes vertically inherited, as it reduces the probability that an infected cell will switch between RMS variants while the MGE is invading the population, and thereby undermine the restriction barrier. Such vertically inherited MGEs can be deleted by transformation. The lack of between-strain transformation hotspots at known prophage att sites suggests transformation cannot remove an MGE from a strain in which it is fixed. However, simulations confirmed that transformation was nevertheless effective at preventing the spread of MGEs into a previously uninfected cell population, if a recombination barrier existed between co-colonising strains. Further simulations combining these effects of phase variable RMSs and transformation found they synergistically inhibited MGEs spreading, through limiting both vertical and horizontal transmission.

A Core Genome Multilocus Sequence Typing Scheme for Enterococcus faecalis

Among enterococci, Enterococcus faecalis occurs ubiquitously, with the highest incidence of human and animal infections. The high genetic plasticity of E. faecalis complicates both molecular investigations and phylogenetic analyses. Whole-genome sequencing (WGS) enables unraveling of epidemiological linkages and putative transmission events between humans, animals, and food. Core genome multilocus sequence typing (cgMLST) aims to combine the discriminatory power of classical multilocus sequence typing (MLST) with the extensive genetic data obtained by WGS. By sequencing a representative collection of 146 E. faecalis strains isolated from hospital outbreaks, food, animals, and colonization of healthy human individuals, we established a novel cgMLST scheme with 1,972 gene targets within the Ridom SeqSphere⁺ software. To test the E. faecalis cgMLST scheme and assess the typing performance, different collections comprising environmental and bacteremia isolates, as well as all publicly available genome sequences from the NCBI and SRA databases, were analyzed. In more than 98.6% of the tested genomes, >95% good cgMLST target genes were detected (mean, 99.2% target genes). Our genotyping results not only corroborate the known epidemiological background of the isolates but exceed previous typing resolution. In conclusion, we have created a powerful typing scheme, hence providing an international standardized nomenclature that is suitable for surveillance approaches in various sectors, linking public health, veterinary public health, and food safety in a true One Health fashion.

Bacterial genome sequencing in clinical microbiology: a pathogen-oriented review

In recent years, whole-genome sequencing (WGS) has been perceived as a technology with the potential to revolutionise clinical microbiology. Herein, we reviewed the literature on the use of WGS for the most commonly encountered pathogens in clinical microbiology laboratories: Escherichia coli and other Enterobacteriaceae, Staphylococcus aureus and coagulase-negative staphylococci, streptococci and enterococci, mycobacteria and Chlamydia trachomatis. For each pathogen group, we focused on five different aspects: the genome characteristics, the most common genomic approaches and the clinical uses of WGS for (i) typing and outbreak analysis, (ii) virulence investigation and (iii) in silico antimicrobial susceptibility testing. Of all the clinical usages, the most frequent and straightforward usage was to type bacteria and to trace outbreaks back. A next step toward standardisation was made thanks to the development of several new genome-wide multi-locus sequence typing systems based on WGS data. Although virulence characterisation could help in various particular clinical settings, it was done mainly to describe outbreak strains. An increasing number of studies compared genotypic to phenotypic antibiotic susceptibility testing, with mostly promising results. However, routine implementation will preferentially be done in the workflow of particular pathogens, such as mycobacteria, rather than as a broadly applicable generic tool. Overall, concrete uses of WGS in routine clinical microbiology or infection control laboratories were done, but the next big challenges will be the standardisation and validation of the procedures and bioinformatics pipelines in order to reach clinical standards.

Advances in Understanding Bacterial Pathogenesis Gained from Whole-Genome Sequencing and Phylogenetics

The development of next-generation sequencing as a cost-effective technology has facilitated the analysis of bacterial population structure at a whole-genome level and at scale. From these data, phylogenic trees have been constructed that define population structures at a local, national, and global level, providing a framework for genetic analysis. Although still at an early stage, these approaches have yielded progress in several areas, including pathogen transmission mapping, the genetics of niche colonization and host adaptation, as well as gene-to-phenotype association studies. Antibiotic resistance has proven to be a major challenge in the early 21(st) century, and phylogenetic analyses have uncovered the dramatic effect that the use of antibiotics has had on shaping bacterial population structures. An update on insights into bacterial evolution from comparative genomics is provided in this review.

SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology

The recent widespread application of whole-genome sequencing (WGS) for microbial disease investigations has spurred the development of new bioinformatics tools, including a notable proliferation of phylogenomics pipelines designed for infectious disease surveillance and outbreak investigation. Transitioning the use of WGS data out of the research laboratory and into the front lines of surveillance and outbreak response requires user-friendly, reproducible and scalable pipelines that have been well validated. Single Nucleotide Variant Phylogenomics (SNVPhyl) is a bioinformatics pipeline for identifying high-quality single-nucleotide variants (SNVs) and constructing a whole-genome phylogeny from a collection of WGS reads and a reference genome. Individual pipeline components are integrated into the Galaxy bioinformatics framework, enabling data analysis in a user-friendly, reproducible and scalable environment. We show that SNVPhyl can detect SNVs with high sensitivity and specificity, and identify and remove regions of high SNV density (indicative of recombination). SNVPhyl is able to correctly distinguish outbreak from non-outbreak isolates across a range of variant-calling settings, sequencing-coverage thresholds or in the presence of contamination. SNVPhyl is available as a Galaxy workflow, Docker and virtual machine images, and a Unix-based command-line application. SNVPhyl is released under the Apache 2.0 license and available at http://snvphyl.readthedocs.io/ or at https://github.com/phac-nml/snvphyl-galaxy.

Multiple Introductions and Recent Spread of the Emerging Human Pathogen Mycobacterium ulcerans across Africa

Buruli ulcer (BU) is an insidious neglected tropical disease. Cases are reported around the world but the rural regions of West and Central Africa are most affected. How BU is transmitted and spreads has remained a mystery, even though the causative agent, Mycobacterium ulcerans, has been known for more than 70 years. Here, using the tools of population genomics, we reconstruct the evolutionary history of M. ulcerans by comparing 165 isolates spanning 48 years and representing 11 endemic countries across Africa. The genetic diversity of African M. ulcerans was found to be restricted due to the bacterium's slow substitution rate coupled with its relatively recent origin. We identified two specific M. ulcerans lineages within the African continent, and inferred that M. ulcerans lineage Mu_A1 existed in Africa for several hundreds of years, unlike lineage Mu_A2, which was introduced much more recently, approximately during the 19th century. Additionally, we observed that specific M. ulcerans epidemic Mu_A1 clones were introduced during the same time period in the three hydrological basins that were well covered in our panel. The estimated time span of the introduction events coincides with the Neo-imperialism period, during which time the European colonial powers divided the African continent among themselves. Using this temporal association, and in the absence of a known BU reservoir or-vector on the continent, we postulate that the so-called "Scramble for Africa" played a significant role in the spread of the disease across the continent.

A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis

Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.

A Primer on Infectious Disease Bacterial Genomics

The number of large-scale genomics projects is increasing due to the availability of affordable high-throughput sequencing (HTS) technologies. The use of HTS for bacterial infectious disease research is attractive because one whole-genome sequencing (WGS) run can replace multiple assays for bacterial typing, molecular epidemiology investigations, and more in-depth pathogenomic studies. The computational resources and bioinformatics expertise required to accommodate and analyze the large amounts of data pose new challenges for researchers embarking on genomics projects for the first time. Here, we present a comprehensive overview of a bacterial genomics projects from beginning to end, with a particular focus on the planning and computational requirements for HTS data, and provide a general understanding of the analytical concepts to develop a workflow that will meet the objectives and goals of HTS projects.

Genomic analysis of the multi-host pathogen Erysipelothrix rhusiopathiae reveals extensive recombination as well as the existence of three generalist clades with wide geographic distribution

Background

Knowledge about how bacterial populations are structured is an important prerequisite for studying their ecology and evolutionary history and facilitates inquiry into host specificity, pathogenicity, geographic dispersal and molecular epidemiology. Erysipelothrix rhusiopathiae is an opportunistic pathogen that is currently reemerging in both the swine and poultry industries globally. This bacterium sporadically causes mortalities in captive marine mammals, and has recently been implicated in large-scale wildlife die-offs. However, despite its economic relevance and broad geographic and host distribution, including zoonotic potential, the global diversity, recombination rates, and population structure of this bacterium remain poorly characterized. In this study, we conducted a broad-scale genomic comparison of E. rhusiopathiae based on a diverse collection of isolates in order to address these knowledge gaps.

Results

Eighty-three E. rhusiopathiae isolates from a range of host species and geographic origins, isolated between 1958 and 2014, were sequenced and assembled using both reference-based mapping and de novo assembly. We found that a high proportion of the core genome (58 %) had undergone recombination. Therefore, we used three independent methods robust to the presence of recombination to define the population structure of this species: a phylogenetic tree based on a set of conserved protein sequences, in silico chromosome painting, and network analysis. All three methods were broadly concordant and supported the existence of three distinct clades within the species E. rhusiopathiae. Although we found some evidence of host and geographical clustering, each clade included isolates from diverse host species and from multiple continents.

Conclusions

Using whole genome sequence data, we confirm recent suggestions that E. rhusiopathiae is a weakly clonal species that has been shaped extensively by homologous recombination. Despite frequent recombination, we can reliably identify three distinct clades that do not clearly segregate by host species or geographic origin. Our results provide an essential baseline for future molecular epidemiological, ecological and evolutionary studies of E. rhusiopathiae and facilitate comparisons to other recombinogenic, multi-host bacteria.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2643-0) contains supplementary material, which is available to authorized users.

Genome Analysis of Listeria monocytogenes Sequence Type 8 Strains Persisting in Salmon and Poultry Processing Environments and Comparison with Related Strains

Listeria monocytogenes is an important foodborne pathogen responsible for the disease listeriosis, and can be found throughout the environment, in many foods and in food processing facilities. The main cause of listeriosis is consumption of food contaminated from sources in food processing environments. Persistence in food processing facilities has previously been shown for the L. monocytogenes sequence type (ST) 8 subtype. In the current study, five ST8 strains were subjected to whole-genome sequencing and compared with five additionally available ST8 genomes, allowing comparison of strains from salmon, poultry and cheese industry, in addition to a human clinical isolate. Genome-wide analysis of single-nucleotide polymorphisms (SNPs) confirmed that almost identical strains were detected in a Danish salmon processing plant in 1996 and in a Norwegian salmon processing plant in 2001 and 2011. Furthermore, we show that L. monocytogenes ST8 was likely to have been transferred between two poultry processing plants as a result of relocation of processing equipment. The SNP data were used to infer the phylogeny of the ST8 strains, separating them into two main genetic groups. Within each group, the plasmid and prophage content was almost entirely conserved, but between groups, these sequences showed strong divergence. The accessory genome of the ST8 strains harbored genetic elements which could be involved in rendering the ST8 strains resilient to incoming mobile genetic elements. These included two restriction-modification loci, one of which was predicted to show phase variable recognition sequence specificity through site-specific domain shuffling. Analysis indicated that the ST8 strains harbor all important known L. monocytogenes virulence factors, and ST8 strains are commonly identified as the causative agents of invasive listeriosis. Therefore, the persistence of this L. monocytogenes subtype in food processing facilities poses a significant concern for food safety.

Genomic Analysis of the Emergence and Rapid Global Dissemination of the Clonal Group 258 Klebsiella pneumoniae Pandemic

Multidrug-resistant Klebsiella pneumoniae producing the KPC carbapenemase have rapidly spread throughout the world, causing severe healthcare-associated infections with limited antimicrobial treatment options. Dissemination of KPC-producing K. pneumoniae is largely attributed to expansion of a single dominant strain, ST258. In this study, we explore phylogenetic relationships and evolution within ST258 and its clonal group, CG258, using whole genome sequence analysis of 167 isolates from 20 countries collected over 17 years. Our results show a common ST258 ancestor emerged from its diverse parental clonal group around 1995 and likely acquired blaKPC prior to dissemination. Over the past two decades, ST258 has remained highly clonal despite diversity in accessory elements and divergence in the capsule polysaccharide synthesis locus. Apart from the large recombination event that gave rise to ST258, few mutations set it apart from its clonal group. However, one mutation occurs in a global transcription regulator. Characterization of outer membrane protein sequences revealed a profile in ST258 that includes a truncated OmpK35 and modified OmpK37. Our work illuminates potential genomic contributors to the pathogenic success of ST258, helps us better understand the global dissemination of this strain, and identifies genetic markers unique to ST258.

Clostridium botulinum Group II Isolate Phylogenomic Profiling Using Whole-Genome Sequence Data

Clostridium botulinum group II isolates (n = 163) from different geographic regions, outbreaks, and neurotoxin types and subtypes were characterized in silico using whole-genome sequence data. Two clusters representing a variety of botulinum neurotoxin (BoNT) types and subtypes were identified by multilocus sequence typing (MLST) and core single nucleotide polymorphism (SNP) analysis. While one cluster included BoNT/B4/F6/E9 and nontoxigenic members, the other comprised a wide variety of different BoNT/E subtype isolates and a nontoxigenic strain. In silico MLST and core SNP methods were consistent in terms of clade-level isolate classification; however, core SNP analysis showed higher resolution capability. Furthermore, core SNP analysis correctly distinguished isolates by outbreak and location. This study illustrated the utility of next-generation sequence-based typing approaches for isolate characterization and source attribution and identified discrete SNP loci and MLST alleles for isolate comparison.

Insights from 20 years of bacterial genome sequencing

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

Phylodynamic analysis of clinical and environmental Vibrio cholerae isolates from Haiti reveals diversification driven by positive selection

Phylodynamic analysis of genome-wide single-nucleotide polymorphism (SNP) data is a powerful tool to investigate underlying evolutionary processes of bacterial epidemics. The method was applied to investigate a collection of 65 clinical and environmental isolates of Vibrio cholerae from Haiti collected between 2010 and 2012. Characterization of isolates recovered from environmental samples identified a total of four toxigenic V. cholerae O1 isolates, four non-O1/O139 isolates, and a novel nontoxigenic V. cholerae O1 isolate with the classical tcpA gene. Phylogenies of strains were inferred from genome-wide SNPs using coalescent-based demographic models within a Bayesian framework. A close phylogenetic relationship between clinical and environmental toxigenic V. cholerae O1 strains was observed. As cholera spread throughout Haiti between October 2010 and August 2012, the population size initially increased and then fluctuated over time. Selection analysis along internal branches of the phylogeny showed a steady accumulation of synonymous substitutions and a progressive increase of nonsynonymous substitutions over time, suggesting diversification likely was driven by positive selection. Short-term accumulation of nonsynonymous substitutions driven by selection may have significant implications for virulence, transmission dynamics, and even vaccine efficacy.

IMPORTANCE

Cholera, a dehydrating diarrheal disease caused by toxigenic strains of the bacterium Vibrio cholerae, emerged in 2010 in Haiti, a country where there were no available records on cholera over the past 100 years. While devastating in terms of morbidity and mortality, the outbreak provided a unique opportunity to study the evolutionary dynamics of V. cholerae and its environmental presence. The present study expands on previous work and provides an in-depth phylodynamic analysis inferred from genome-wide single nucleotide polymorphisms of clinical and environmental strains from dispersed geographic settings in Haiti over a 2-year period. Our results indicate that even during such a short time scale, V. cholerae in Haiti has undergone evolution and diversification driven by positive selection, which may have implications for understanding the global clinical and epidemiological patterns of the disease. Furthermore, the continued presence of the epidemic strain in Haitian aquatic environments has implications for transmission.

Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOB_F12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

Plasmids are difficult to analyze in WGS datasets, due to the fragmented nature of the obtained sequences. We developed a method, called PLACNET, which greatly facilitates this analysis. As an example, we analyzed the plasmidome of E. coli ST131, an ExPEC clonal group involved in human urinary tract infections and septicemia. Relevant variation within this clone (e.g., antibiotic resistance and virulence) is frequently caused by the acquisition and loss of plasmids and other mobile genetic elements. Nevertheless, our knowledge of the ST131 plasmidome is limited to a few antibiotic resistance plasmids and to identification of replicons from known plasmid groups. PLACNET analysis extends the number of sequenced plasmids in ST131, which can be used for comparative genomics, from 11 to 50. The ST131 plasmidome is seemingly huge, encompassing roughly 50% of the main plasmid groups of γ–proteobacteria. MOB_F12/IncF plasmids are apparently the most active players in the dissemination of relevant genetic information.

Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins

The emergence of new sequencing technologies has facilitated the use of bacterial whole genome alignments for evolutionary studies and outbreak analyses. These datasets, of increasing size, often include examples of multiple different mechanisms of horizontal sequence transfer resulting in substantial alterations to prokaryotic chromosomes. The impact of these processes demands rapid and flexible approaches able to account for recombination when reconstructing isolates' recent diversification. Gubbins is an iterative algorithm that uses spatial scanning statistics to identify loci containing elevated densities of base substitutions suggestive of horizontal sequence transfer while concurrently constructing a maximum likelihood phylogeny based on the putative point mutations outside these regions of high sequence diversity. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistically parameterized models of bacterial evolution, and achieves convergence in only a few hours on alignments of hundreds of bacterial genome sequences. Gubbins is appropriate for reconstructing the recent evolutionary history of a variety of haploid genotype alignments, as it makes no assumptions about the underlying mechanism of recombination. The software is freely available for download at github.com/sanger-pathogens/Gubbins, implemented in Python and C and supported on Linux and Mac OS X.

Epidemiologic data and pathogen genome sequences: a powerful synergy for public health

Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional ‘line lists’ (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.

KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes

BACKGROUND

High-throughput DNA sequencing produces vast amounts of data, with millions of short reads that usually have to be mapped to a reference genome or newly assembled. Both reference-based mapping and de novo assembly are computationally intensive, generating large intermediary data files, and thus require bioinformatics skills that are often lacking in the laboratories producing the data. Moreover, many research and practical applications in microbiology require only a small fraction of the whole genome data.

RESULTS

We developed KvarQ, a new tool that directly scans fastq files of bacterial genome sequences for known variants, such as single nucleotide polymorphisms (SNP), bypassing the need of mapping all sequencing reads to a reference genome and de novo assembly. Instead, KvarQ loads "testsuites" that define specific SNPs or short regions of interest in a reference genome, and directly synthesizes the relevant results based on the occurrence of these markers in the fastq files. KvarQ has a versatile command line interface and a graphical user interface. KvarQ currently ships with two "testsuites" for Mycobacterium tuberculosis, but new "testsuites" for other organisms can easily be created and distributed. In this article, we demonstrate how KvarQ can be used to successfully detect all main drug resistance mutations and phylogenetic markers in 880 bacterial whole genome sequences. The average scanning time per genome sequence was two minutes. The variant calls of a subset of these genomes were validated with a standard bioinformatics pipeline and revealed >99% congruency.

CONCLUSION

KvarQ is a user-friendly tool that directly extracts relevant information from fastq files. This enables researchers and laboratory technicians with limited bioinformatics expertise to scan and analyze raw sequencing data in a matter of minutes. KvarQ is open-source, and pre-compiled packages with a graphical user interface are available at http://www.swisstph.ch/kvarq.

A MLVA genotyping scheme for global surveillance of the citrus pathogen Xanthomonas citri pv. citri suggests a worldwide geographical expansion of a single genetic lineage

MultiLocus Variable number of tandem repeat Analysis (MLVA) has been extensively used to examine epidemiological and evolutionary issues on monomorphic human pathogenic bacteria, but not on bacterial plant pathogens of agricultural importance albeit such tools would improve our understanding of their epidemiology, as well as of the history of epidemics on a global scale. Xanthomonas citri pv. citri is a quarantine organism in several countries and a major threat for the citrus industry worldwide. We screened the genomes of Xanthomonas citri pv. citri strain IAPAR 306 and of phylogenetically related xanthomonads for tandem repeats. From these in silico data, an optimized MLVA scheme was developed to assess the global diversity of this monomorphic bacterium. Thirty-one minisatellite loci (MLVA-31) were selected to assess the genetic structure of 129 strains representative of the worldwide pathological and genetic diversity of X. citri pv. citri. Based on Discriminant Analysis of Principal Components (DAPC), four pathotype-specific clusters were defined. DAPC cluster 1 comprised strains that were implicated in the major geographical expansion of X. citri pv. citri during the 20th century. A subset of 12 loci (MLVA-12) resolved 89% of the total diversity and matched the genetic structure revealed by MLVA-31. MLVA-12 is proposed for routine epidemiological identification of X. citri pv. citri, whereas MLVA-31 is proposed for phylogenetic and population genetics studies. MLVA-31 represents an opportunity for international X. citri pv. citri genotyping and data sharing. The MLVA-31 data generated in this study was deposited in the Xanthomonas citri genotyping database (http://www.biopred.net/MLVA/).

Supersize me: how whole-genome sequencing and big data are transforming epidemiology

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Whole-genome sequencing is used for forensic epidemiology.

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Big data can transform forensic epidemiology.

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Clustering, biases, wildlife reservoirs, and emerging infections can all be addressed.

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Phylodynamics approaches to integrate epidemiological and evolutionary data have been highly successful but still face scientific challenges.

In epidemiology, the identification of ‘who infected whom’ allows us to quantify key characteristics such as incubation periods, heterogeneity in transmission rates, duration of infectiousness, and the existence of high-risk groups. Although invaluable, the existence of many plausible infection pathways makes this difficult, and epidemiological contact tracing either uncertain, logistically prohibitive, or both. The recent advent of next-generation sequencing technology allows the identification of traceable differences in the pathogen genome that are transforming our ability to understand high-resolution disease transmission, sometimes even down to the host-to-host scale. We review recent examples of the use of pathogen whole-genome sequencing for the purpose of forensic tracing of transmission pathways, focusing on the particular problems where evolutionary dynamics must be supplemented by epidemiological information on the most likely timing of events as well as possible transmission pathways. We also discuss potential pitfalls in the over-interpretation of these data, and highlight the manner in which a confluence of this technology with sophisticated mathematical and statistical approaches has the potential to produce a paradigm shift in our understanding of infectious disease transmission and control.

Highly polymorphic markers reveal the establishment of an invasive lineage of the citrus bacterial pathogen Xanthomonas citri pv. citri in its area of origin

Investigating the population biology of plant pathogens in their native areas is essential to understand the factors that shape their population structure and favour their spread. Monomorphic pathogens dispatch extremely low genetic diversity in invaded areas, and native areas constitute a major reservoir for future emerging strains. One of these, the gammaproteobacterium Xanthomonas citri pv. citri, causes Asiatic canker and is a considerable threat to citrus worldwide. We studied its population genetic structure by genotyping 555 strains from 12 Vietnam provinces at 14 tandem repeat loci and insertion sequences. Discriminant analysis of principal components identified six clusters. Five of them were composed of endemic strains distributed heterogeneously across sampled provinces. A sixth cluster, VN6, displayed a much lower diversity and a clonal expansion structure, suggesting recent epidemic spread. No differences in aggressiveness on citrus or resistance to bactericides were detected between VN6 and other strains. VN6 likely represents a case of bioinvasion following introduction in a native area likely through contaminated plant propagative material. Highly polymorphic markers are useful for revealing migration patterns of recently introduced populations of a monomorphic bacterial plant pathogen.

Generating whole bacterial genome sequences of low-abundance species from complex samples with IMS-MDA

The study of bacterial populations using whole-genome sequencing is of considerable scientific and clinical interest. However, obtaining bacterial genomic information is not always trivial: the target bacteria may be difficult to culture or uncultured, and they may be found within samples containing complex mixtures of other contaminating microbes and/or host cells, from which it is very difficult to derive robust sequencing data. Here we describe our procedure to generate sufficient DNA for whole-genome sequencing from clinical samples and without the need for culture, as successfully used on the difficult-to-culture, obligate intracellular pathogen Chlamydia trachomatis. Our protocol combines immunomagnetic separation (IMS) for targeted bacterial enrichment with multiple displacement amplification (MDA) for whole-genome amplification (WGA), which is followed by high-throughput sequencing. Compared with other techniques that might be used to generate such data, IMS-MDA is an inexpensive, low-technology and highly transferable process that provides amplified genomic DNA for sequencing from target bacteria in under 5 h, with little hands-on time.

MLST revisited: the gene-by-gene approach to bacterial genomics

Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.

Deciphering the origins and tracking the evolution of cholera epidemics with whole-genome-based molecular epidemiology

The devastating Haitian cholera outbreak that began in October 2010 is the first known cholera epidemic in this island nation. Epidemiological and genomic data have provided strong evidence that United Nations security forces from Nepal introduced toxigenic Vibrio cholerae O1, the cause of epidemic cholera, to Haiti shortly before the outbreak arose. However, some have contended that indigenous V. cholerae contributed to the outbreak. In a recent paper (mBio4:e00398-13, 2013), L. S. Katz et al. explored the nature and rate of changes in this ancient pathogen’s genome during an outbreak, based on whole-genome sequencing of 23 Haitian V. cholerae clinical isolates obtained over a 20-month period. Notably, they detected point mutations, deletions, and inversions but found no insertion of horizontally transmitted DNA, arguing strongly against the idea that autochthonous V. cholerae donated DNA to the outbreak strain. Furthermore, they found that Haitian epidemic V. cholerae isolates were virtually untransformable. Comparative genomic analyses revealed that the Haitian isolates were nearly identical to isolates from Nepal and that the Nepalese-Haitian isolates were distinguishable from isolates circulating elsewhere in the world. Reconstruction of the phylogeny of the Haitian isolates was consistent with a single introduction of V. cholerae to Haiti sometime between late July and late October 2010, dates remarkably concordant with epidemiological observations. In aggregate, this paper provides additional compelling evidence that the V. cholerae strain responsible for the Haitian cholera epidemic came from Nepal and illustrates the power of whole-genome-based analyses for epidemiology, pathogen evolution, and forensics.