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Objective: Examine if the gut microbiota composition changes across repeated samples in paediatric-onset multiple sclerosis (MS) or monophasic-acquired demyelinating syndromes (monoADS). Methods: A total of 36 individuals (18 MS/18 monoADS) with ⩾2 stool samples were included. Stool sample-derived DNA was sequenced. Alpha/beta diversities and genus-level taxa were analysed. Results: Mean ages at first sample procurement (MS/monoADS) = 18.0/13.8 years. Median time (months) between first/second samples = 11.2 and second/third = 10.3. Alpha/beta diversities did not differ between stool samples ( p > 0.09), while one genus – Solobacterium did ( p = 0.001). Conclusions: The gut microbiota composition in paediatric-onset MS and monoADS exhibited stability, suggesting that single stool sample procurement is a reasonable first approach.

This study examined the phylogenetic structure of serotype a Haemophilus influenzae (Hia) isolates recovered from patients in Canada. Hia isolates from 490 separate patients and an American Type Culture Collection (ATCC) strain were analyzed by multilocus sequence typing (MLST), with 18 different sequence types (STs) identified. Most (85.7%) Hia patient isolates were typed as ST-23 and another 12.7% belonged to 14 different STs with 6, 5, or 4 MLST gene loci related to ST-23 (ST-23 complex). Core genome single-nucleotide variation phylogeny (SNVPhyl) on whole genome sequence (WGS) data of 121 Hia patient isolates representing all identified STs and the ATCC strain revealed 2 phylogenetic populations, with all the ST-23 complex isolates within 1 population. The other phylogenetic population contained only the ATCC strain and 3 patient isolates. Concatenated hitABC sequences retrieved from WGS data and analyzed by MEGA (Molecular Evolutionary Genetic Analysis) alignment confirmed the phylogeny obtained by SNVPhyl. The sodC gene was found only in isolates in the minor phylogenetic population. The 2 phylogenetic populations of the Canadian Hia isolates are similar to the 2 clonal divisions described for serotype b H. influenzae. Combining MLST, core SNVPhyl, and hitABC gene sequence alignment showed that most (99.4%) Canadian Hia patient isolates belonged to 1 major phylogenetic population.

There is a growing appreciation for the role of the gut microbiome in human health and disease. Aided by advances in sequencing technologies and analytical methods, recent research has shown the healthy gut microbiome to possess considerable diversity and functional capacity. Dysbiosis of the gut microbiota is believed to be involved in the pathogenesis of not only diseases that primarily affect the gastrointestinal tract but also other less obvious diseases, including neurologic, rheumatologic, metabolic, hepatic, and other illnesses. Chronic immune-mediated inflammatory diseases (IMIDs) represent a group of diseases that share many underlying etiological factors including genetics, aberrant immunological responses, and environmental factors. Gut dysbiosis has been reported to be common to IMIDs as a whole, and much effort is currently being directed toward elucidating microbiome-mediated disease mechanisms and their implications for causality. In this review, we discuss gut microbiome studies in several IMIDs and show how these studies can inform our understanding of the role of the gut microbiome in inflammatory bowel disease.

This review aims to highlight recent research on the gut microbiome in IBD and the application of microbiome-modulating therapies for the treatment of IBD including the use of the microbiome as an indicator for disease severity and treatment response. Despite the high number of gut microbiome studies and emerging evidence supporting the gut microbiome’s involvement in disease pathogenesis, no single microorganism has been identified as a pathogenic agent in IBD. Retrospective studies and meta-analyses on antibiotic use in ulcerative colitis and Crohn’s disease and long-term outcomes are conflicting. Similarly, the use of probiotics for the treatment of IBD remains inconclusive; however, some encouraging results are emerging as microbial concoctions are optimized to include beneficial bacterial strains. Fecal microbial transplantation (FMT) is currently emerging as one of the more promising microbiome-modulating IBD therapies. FMT studies in ulcerative colitis have shown improved remission rates compared to placebo; however, relatively small study sample sizes and varied treatment methods, limit definitive conclusions. With clear evidence of an IBD gut dysbiosis, novel therapies to treat and prevent disease relapse will undoubtedly require a microbiome-modulating approach. The complexity and variability of IBD disease pathogenesis (disease phenotype, gut microbiome, host genetic susceptibility, and environmental factors) will likely require a personalized and multidimensional treatment approach where microbiome-modulating therapy is coupled with other therapies to target other IBD disease components.

Current noninvasive methods for colorectal cancer (CRC) screening are not optimized for persons with inflammatory bowel diseases (IBDs), requiring patients to undergo frequent interval screening via colonoscopy. Although colonoscopy-based screening reduces CRC incidence in IBD patients, rates of interval CRC remain relatively high, highlighting the need for more targeted approaches. In recent years, the discovery of disease-specific microbiome signatures for both IBD and CRC has begun to emerge, suggesting that stool-based biomarker detection using metagenomics and other culture-independent technologies may be useful for personalized, early, noninvasive CRC screening in IBD patients. Here we discuss the utility of the stool microbiome as a noninvasive CRC screening tool. Comparing the performance of multiple microbiome-based CRC classifiers, including several multi-cohort meta-analyses, we find that noninvasive detection of colorectal adenomas and carcinomas from microbial biomarkers is an active area of study with promising early results.

Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex PCR and bait capture enrichment. Each method has advantages and disadvantages but a direct comparison with different viral RNA concentrations has not been performed to assess the performance of these approaches. Here we compare Liverpool amplification, ARTIC amplification, and bait capture using clinical diagnostics samples. All libraries were sequenced using an Illumina MiniSeq with data analyzed using a standardized bioinformatics workflow (SARS-CoV-2 Illumina GeNome Assembly Line; SIGNAL). One sample showed poor SARS-CoV-2 genome coverage and consensus, reflective of low viral RNA concentration. In contrast, the second sample had a higher viral RNA concentration, which yielded good genome coverage and consensus. ARTIC amplification showed the highest depth of coverage results for both samples, suggesting this protocol is effective for low concentrations. Liverpool amplification provided a more even read coverage of the SARS-CoV-2 genome, but at a lower depth of coverage. Bait capture enrichment of SARS-CoV-2 cDNA provided results on par with amplification. While only two clinical samples were examined in this comparative analysis, both the Liverpool and ARTIC amplification methods showed differing efficacy for high and low concentration samples. In addition, amplification-free bait capture enriched sequencing of cDNA is a viable method for generating a SARS-CoV-2 genome sequence and for identification of amplification artifacts.

BioHansel performs high-resolution genotyping of bacterial isolates by identifying phylogenetically informative single nucleotide polymorphisms (SNPs), also known as canonical SNPs, in whole genome sequencing (WGS) data. The application uses a fast k-mer matching algorithm to map pathogen WGS data to canonical SNPs contained in hierarchically structured schemas and assigns genotypes based on the detected SNP profile. Using modest computing resources, BioHansel efficiently types isolates from raw sequence reads or assembled contigs in a matter of seconds, making it attractive for use by public health, food safety, environmental, and agricultural authorities that wish to apply WGS methodologies for their surveillance, diagnostics, and research programs. BioHansel currently provides canonical SNP genotyping schemas for four prevalent Salmonella serovars—Typhi, Typhimurium, Enteritidis and Heidelberg—as well as a schema for Mycobacterium tuberculosis. Users can also supply their own schemas for genotyping other organisms. BioHansel’s quality assurance system assesses the validity of the genotyping results and can identify low quality data, contaminated datasets, and misidentified organisms. BioHansel is targeted to support surveillance, source attribution, risk assessment, diagnostics, and rapid screening for public health purposes, such as product recalls. BioHansel is an open source application with packages available for PyPI, Conda, and the Galaxy workflow manager. In summary, BioHansel performs efficient, rapid, accurate, and high-resolution classification of bacterial genomes from sequence reads or assembled contigs on standard computing hardware. BioHansel is suitable for use as a general research tool as well as in fully operationalized WGS workflows at the front lines of infectious disease surveillance, diagnostics, and outbreak investigation and response.Impact statementPublic health, food safety, environmental, and agricultural authorities are currently engaged in a global effort to incorporate whole genome sequencing technologies into their infectious disease research, surveillance, and outbreak investigation programs. Its widespread adoption, however, has been impeded by two major obstacles: the need for high performance computing to generate results and the expert knowledge required to interpret and communicate those results. BioHansel addresses these limitations by rapidly genotyping pathogens from whole genome sequence data in an accurate, simple, familiar, and easily sharable manner using standard computing resources. BioHansel provides a compact and readily interpretable genotype based on canonical SNP genotyping schemas. BioHansel’s genotyping nomenclature encodes the pathogen’s position in its population structure, which simplifies and facilitates its comparison with actively circulating strains and historical strains. The genotyping information provided by BioHansel can identify points of intervention to prevent the spread of pathogenic bacteria, screen for the presence of priority pathogens, and perform source attribution and risk assessment. Thus, BioHansel serves as a readily accessible and powerful WGS method, implementable on a laptop, for genotyping pathogens to detect, monitor, and control the emergence and spread of infectious disease through surveillance, screening, diagnostics, and outbreak investigation and response activities.Data summaryBioHansel is a Python 3 application available as PyPI, Conda Galaxy Tool Shed packages. It is an open source application distributed under the Apache License, Version 2.0. Source code is available at https://github.com/phac-nml/biohansel. The BioHansel user guide is available at https://bio-hansel.readthedocs.io/en/readthedocs/. Supplementary Materials are available at https://github.com/phac-nml/biohansel-manuscript-supplementary-data.The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

Clinical metagenomics (CMg) is the discipline that refers to the sequencing of all nucleic acid material present within a clinical specimen with the intent to recover clinically relevant microbial information. From a diagnostic perspective, next-generation sequencing (NGS) offers the ability to rapidly identify putative pathogens and predict their antimicrobial resistance profiles to optimize targeted treatment regimens. Since the introduction of metagenomics nearly a decade ago, numerous reports have described successful applications in an increasing variety of biological specimens, such as respiratory secretions, cerebrospinal fluid, stool, blood and tissue. Considerable advancements in sequencing and computational technologies in recent years have made CMg a promising tool in clinical microbiology laboratories. Moreover, costs per sample and turnaround time from specimen receipt to clinical management continue to decrease, making the prospect of CMg more feasible. Many difficulties, however, are associated with CMg and warrant further improvements such as the informatics infrastructure and analytical pipelines. Thus, the current review focuses on comprehensively assessing applications of CMg for diagnostic and subtyping purposes. Keywords: Clinical metagenomics, Diagnosis, Clinical microbiology laboratory, Pathogen detection, Culture-independent diagnostic test, Next-generation sequencing

We report high-quality closed reference genomes for 1 bovine strain and 10 human Shiga toxin (Stx)-producing Escherichia coli (STEC) strains from serogroups O26, O45, O91, O103, O104, O111, O113, O121, O145, and O157. We also report draft assemblies, with standardized metadata, for 360 STEC strains isolated from watersheds, animals, farms, food, and human infections.

The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence.

Background Immune-mediated inflammatory disease (IMID) represents a substantial health concern. It is widely recognized that IMID patients are at a higher risk for developing secondary inflammation-related conditions. While an ambiguous etiology is common to all IMIDs, in recent years, considerable knowledge has emerged regarding the plausible role of the gut microbiome in IMIDs. This study used 16S rRNA gene amplicon sequencing to compare the gut microbiota of patients with Crohn’s disease (CD; N = 20), ulcerative colitis (UC; N = 19), multiple sclerosis (MS; N = 19), and rheumatoid arthritis (RA; N = 21) versus healthy controls (HC; N = 23). Biological replicates were collected from participants within a 2-month interval. This study aimed to identify common (or unique) taxonomic biomarkers of IMIDs using both differential abundance testing and a machine learning approach. Results Significant microbial community differences between cohorts were observed (pseudo F = 4.56; p = 0.01). Richness and diversity were significantly different between cohorts (pFDR

SUMMARYAn outbreak of Legionnaires' disease occurred in an inner city district in Calgary, Canada. This outbreak spanned a 3-week period in November–December 2012, and a total of eight cases were identified. Four of these cases were critically ill requiring intensive care admission but there was no associated mortality. All cases tested positive forLegionella pneumophilaserogroup 1 (LP1) by urinary antigen testing. Five of the eight patients were culture positive for LP1 from respiratory specimens. These isolates were further identified as Knoxville monoclonal subtype and sequence subtype ST222. Whole-genome sequencing revealed that the isolates differed by no more than a single vertically acquired single nucleotide variant, supporting a single point-source outbreak. Hypothesis-based environmental investigation and sampling was conducted; however, a definitive source was not identified. Geomapping of case movements within the affected urban sector revealed a 1·0 km common area of potential exposure, which coincided with multiple active construction sites that used water spray to minimize transient dust. This community point-source Legionnaires' disease outbreak is unique due to its ST222 subtype and occurrence in a relatively dry and cold weather setting in Western Canada. This report suggests community outbreaks ofLegionellashould not be overlooked as a possibility during late autumn and winter months in the Northern Hemisphere.

SUMMARY 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.

Lyme disease is emerging in southern Canada due to range expansion of the tick vector, followed by invasion of the agent of Lyme disease Borrelia burgdorferi sensu stricto. Strain diversity, as determined by Multi Locus Sequence Typing, occurs in this zone of emergence, and this may have its origins in adaptation to ecological niches, and have phenotypic consequences for pathogenicity and serological test performance. Sixty-four unique strains were cultured from ticks collected in southern Canada and the genomes sequenced using the Illumina MiSeq platform. A maximum likelihood phylogenetic tree of the chromosome revealed two large clades with multiple subclades. Consistent with previous studies on this species, the clades were not geographically defined, and some Canadian strains were highly divergent from previously sequenced US strains. There was evidence for recombination in the chromosome but this did not affect the phylogeny. Analysis of chromosomal genes indicated that these are under intense purifying selection. Phylogenies of the accessory genome and chromosome were congruent. Therefore strain differences identified in the phylogeny of chromosomal genes likely act as a proxy for genetic determinants of phenotypic differences amongst strains that are harboured in the accessory genome. Further studies on health implications of strain diversity are needed.

SummaryComparative analysis of bacterial plasmids from whole genome sequence (WGS) data generated from short read sequencing is challenging. This is due to the difficulty in identifying contigs harbouring plasmid sequence data, and further difficulty in assembling such contigs into a full plasmid. As such, few software programs and bioinformatics pipelines exist to perform comprehensive comparative analyses of plasmids within and amongst sequenced isolates. To address this gap, we have developed Plasmid Profiler, a pipeline to perform comparative plasmid content analysis without the need forde novoassembly. The pipeline is designed to rapidly identify plasmid sequences by mapping reads to a plasmid reference sequence database. Predicted plasmid sequences are then annotated with their incompatibility group, if known. The pipeline allows users to query plasmids for genes or regions of interest and visualize results as an interactive heat map.Availability and ImplementationPlasmid Profiler is freely available software released under the Apache 2.0 open source software license. A stand-alone version of the entire Plasmid Profiler pipeline is available as a Docker container athttps://hub.docker.com/r/phacnml/plasmidprofiler_0_1_6/.The conda recipe for the Plasmid R package is available at:https://anaconda.org/bioconda/r-plasmidprofilerThe custom Plasmid Profiler R package is also available as a CRAN package athttps://cran.r-project.org/web/packages/Plasmidprofiler/index.htmlGalaxy tools associated with the pipeline are available as a Galaxy tool suite athttps://toolshed.g2.bx.psu.edu/repository?repository_id=55e082200d16a504The source code is available at:https://github.com/phac-nml/plasmidprofilerThe Galaxy implementation is available at:https://github.com/phac-nml/plasmidprofiler-galaxyContactEmail:gary.vandomselaar@canada.caAddress: National Microbiology Laboratory, Public Health Agency of Canada, 1015 Arlington Street, Winnipeg, Manitoba, CanadaSupplementary informationDocumentation:http://plasmid-profiler.readthedocs.io/en/latest/

Aim A comprehensive understanding of the microbial community is necessary to ensure a significant reduction in pathogens during the composting process. Methods and Results Two biosecure, static composting systems containing cattle mortalities were constructed at subzero temperatures. Temperature at each sampling site was measured continuously and samples were grouped as either ≤50 or ≥55°C, based on temperature exposure required for effective pathogen inactivation during composting. High-throughput 454 sequencing was used to characterize the bacterial communities within each sample. Clustering of bacterial communities was observed according to temperature. However, neither richness nor diversity differed between temperature groups. Firmicutes was the most abundant phylum within both temperature groups but was more pronounced (63·6%) in samples ≥55°C (P

MotivationThe 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 lab and into the front lines of surveillance and outbreak response requires user-friendly, reproducible, and scalable pipelines that have been well validated.ResultsSNVPhyl (Single Nucleotide Variant Phylogenomics) is a bioinformatics pipeline for identifying high-quality 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.AvailabilitySNVPhyl 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.

Whereas the infant gut microbiome is the subject of intense study, relatively little is known regarding the nares microbiome in newborns and during early life. This study aimed to survey the typical composition and diversity of human anterior nare microflora for developing infants over time, and to explore how these correlate to their primary caregivers. Single nare swabs were collected at five time points over a one-year period for each subject from infant-caregiver pairs. Our study comprised of 50 infants (recruited at 2 weeks, post delivery) and their 50 primary caregivers. Applying the chaperonin-60 (cpn60) universal target (UT) amplicon as our molecular barcoding marker to census survey the microbial communities, we longitudinally surveyed infant nares microbiota at 5 time points over the course of the first year of life. The inter- and intra-subject diversity was catalogued and compared, both longitudinally and relative to their adult primary caregivers. Although within-subject variability over time and inter-subject variability were both observed, the assessment detected only one or two predominant genera for individual infant samples, belonging mainly to phyla Actinobacteria, Firmicutes, and Proteobacteria. Consistent with previously observed microbial population dynamics in other body sites, the diversity of nares microflora increased over the first year of life and infants showed differential operational taxonomic units (OTUs) relative to their matched primary caregiver. The collected evidence also support that both temporal and seasonal changes occur with respect to carriage of potentially pathogenic bacteria (PPBs), which may influence host predisposition to infection. This pilot study surveying paired infant/caregiver nare microbiomes provides novel longitudinal diversity information that is pertinent to better understanding nare microbiome development in infants.

The advent and widespread application of next-generation sequencing (NGS) technologies to the study of microbial genomes has led to a substantial increase in the number of studies in which whole genome sequencing (WGS) is applied to the analysis of microbial genomic epidemiology. However, microorganisms such as Mycobacterium tuberculosis (MTB) present unique problems for sequencing and downstream analysis based on their unique physiology and the composition of their genomes. In this study, we compare the quality of sequence data generated using the Nextera and TruSeq isolate preparation kits for library construction prior to Illumina sequencing-by-synthesis. Our results confirm that MTB NGS data quality is highly dependent on the purity of the DNA sample submitted for sequencing and its guanine-cytosine content (or GC-content). Our data additionally demonstrate that the choice of library preparation method plays an important role in mitigating downstream sequencing quality issues. Importantly for MTB, the Illumina TruSeq library preparation kit produces more uniform data quality than the Nextera XT method, regardless of the quality of the input DNA. Furthermore, specific genomic sequence motifs are commonly missed by the Nextera XT method, as are regions of especially high GC-content relative to the rest of the MTB genome. As coverage bias is highly undesirable, this study illustrates the importance of appropriate protocol selection when performing NGS studies in order to ensure that sound inferences can be made regarding mycobacterial genomes.

The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using ‘big data’ approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptune’s loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real datasets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci. The software is available for download at: http://github.com/phac-nml/neptune.

Prior to the epidemic that emerged in Haiti in October of 2010, cholera had not been documented in this country. After its introduction, a strain of Vibrio cholerae O1 spread rapidly throughout Haiti, where it caused over 600,000 cases of disease and >7,500 deaths in the first two years of the epidemic. We applied whole-genome sequencing to a temporal series of V. cholerae isolates from Haiti to gain insight into the mode and tempo of evolution in this isolated population of V. cholerae O1. Phylogenetic and Bayesian analyses supported the hypothesis that all isolates in the sample set diverged from a common ancestor within a time frame that is consistent with epidemiological observations. A pangenome analysis showed nearly homogeneous genomic content, with no evidence of gene acquisition among Haiti isolates. Nine nearly closed genomes assembled from continuous-long-read data showed evidence of genome rearrangements and supported the observation of no gene acquisition among isolates. Thus, intrinsic mutational processes can account for virtually all of the observed genetic polymorphism, with no demonstrable contribution from horizontal gene transfer (HGT). Consistent with this, the 12 Haiti isolates tested by laboratory HGT assays were severely impaired for transformation, although unlike previously characterized noncompetent V. cholerae isolates, each expressed hapR and possessed a functional quorum-sensing system. Continued monitoring of V. cholerae in Haiti will illuminate the processes influencing the origin and fate of genome variants, which will facilitate interpretation of genetic variation in future epidemics., IMPORTANCE Vibrio cholerae is the cause of substantial morbidity and mortality worldwide, with over three million cases of disease each year. An understanding of the mode and rate of evolutionary change is critical for proper interpretation of genome sequence data and attribution of outbreak sources. The Haiti epidemic provides an unprecedented opportunity to study an isolated, single-source outbreak of Vibrio cholerae O1 over an established time frame. By using multiple approaches to assay genetic variation, we found no evidence that the Haiti strain has acquired any genes by horizontal gene transfer, an observation that led us to discover that it is also poorly transformable. We have found no evidence that environmental strains have played a role in the evolution of the outbreak strain.

INTRODUCTION: Inflammatory complications following ileal pouch-anal anastomosis (IPAA) for ulcerative colitis (UC) are common and thought to arise through mechanisms similar to de novo onset inflammatory bowel disease. The aim of this study was to determine whether specific organisms in the tissue-associated microbiota are associated with inflammatory pouch complications. METHODS: Patients having previously undergone IPAA were recruited from Mount Sinai Hospital. Clinical and demographic information were collected and a pouchoscopy with biopsy of both the pouch and afferent limb was performed. Patients were classified based on post-surgical phenotype into four outcome groups: familial adenomatous polyposis controls (FAP), no pouchitis, pouchitis, and Crohn's disease-like (CDL). Pyrosequencing of the 16S rRNA V1-V3 hypervariable region, and quantitative PCR for bacteria of interest, were used to identify organisms present in the afferent limb and pouch. Associations with outcomes were evaluated using exact and non-parametric tests of significance. RESULTS: Analysis at the phylum level indicated that Bacteroidetes were detected significantly less frequently (P

Legionella pneumophila is the primary etiologic agent of legionellosis, a potentially fatal respiratory illness. Amongst the sixteen described L. pneumophila serogroups, a majority of the clinical infections diagnosed using standard methods are serogroup 1 (Sg1). This high clinical prevalence of Sg1 is hypothesized to be linked to environmental specific advantages and/or to increased virulence of strains belonging to Sg1. The genetic determinants for this prevalence remain unknown primarily due to the limited genomic information available for non-Sg1 clinical strains. Through a systematic attempt to culture Legionella from patient respiratory samples, we have previously reported that 34% of all culture confirmed legionellosis cases in Ontario (n = 351) are caused by non-Sg1 Legionella. Phylogenetic analysis combining multiple-locus variable number tandem repeat analysis and sequence based typing profiles of all non-Sg1 identified that L. pneumophila clinical strains (n = 73) belonging to the two most prevalent molecular types were Sg6. We conducted whole genome sequencing of two strains representative of these sequence types and one distant neighbour. Comparative genomics of the three L. pneumophila Sg6 genomes reported here with published L. pneumophila serogroup 1 genomes identified genetic differences in the O-antigen biosynthetic cluster. Comparative optical mapping analysis between Sg6 and Sg1 further corroborated this finding. We confirmed an altered O-antigen profile of Sg6, and tested its possible effects on growth and replication in in vitro biological models and experimental murine infections. Our data indicates that while clinical Sg1 might not be better suited than Sg6 in colonizing environmental niches, increased bloodstream dissemination through resistance to the alternative pathway of complement mediated killing in the human host may explain its higher prevalence.