The collection of microbes and their genes that exist within and on the human body, collectively known as the microbiome has emerged as a principal factor in human health and disease. Humans and microbes have established a symbiotic association over time, and perturbations in this association have been linked to several immune-mediated inflammatory diseases (IMID) including inflammatory bowel disease, rheumatoid arthritis, and multiple sclerosis. IMID is a term used to describe a group of chronic, highly disabling diseases that affect different organ systems. Though a cornerstone commonality between IMID is the idiopathic nature of disease, a considerable portion of their pathobiology overlaps including epidemiological co-occurrence, genetic susceptibility loci and environmental risk factors. At present, it is clear that persons with an IMID are at an increased risk for developing comorbidities, including additional IMID. Advancements in sequencing technologies and a parallel explosion of 16S rDNA and metagenomics community profiling studies have allowed for the characterization of microbiomes throughout the human body including the gut, in a myriad of human diseases and in health. The main challenge now is to determine if alterations of gut flora are common between IMID or, if particular changes in the gut community are in fact specific to a single disease. Herein, we review and discuss the relationships between the gut microbiota and IMID.
BackgroundA large, multi-province outbreak of listeriosis associated with ready-to-eat meat products contaminated with Listeria monocytogenes serotype 1/2a occurred in Canada in 2008. Subtyping of outbreak-associated isolates using pulsed-field gel electrophoresis (PFGE) revealed two similar but distinct AscI PFGE patterns. High-throughput pyrosequencing of two L. monocytogenes isolates was used to rapidly provide the genome sequence of the primary outbreak strain and to investigate the extent of genetic diversity associated with a change of a single restriction enzyme fragment during PFGE.ResultsThe chromosomes were collinear, but differences included 28 single nucleotide polymorphisms (SNPs) and three indels, including a 33 kbp prophage that accounted for the observed difference in AscI PFGE patterns. The distribution of these traits was assessed within further clinical, environmental and food isolates associated with the outbreak, and this comparison indicated that three distinct, but highly related strains may have been involved in this nationwide outbreak. Notably, these two isolates were found to harbor a 50 kbp putative mobile genomic island encoding translocation and efflux functions that has not been observed in other Listeria genomes.ConclusionsHigh-throughput genome sequencing provided a more detailed real-time assessment of genetic traits characteristic of the outbreak strains than could be achieved with routine subtyping methods. This study confirms that the latest generation of DNA sequencing technologies can be applied during high priority public health events, and laboratories need to prepare for this inevitability and assess how to properly analyze and interpret whole genome sequences in the context of molecular epidemiology.
Summary: GView is a Java application for viewing and examining prokaryotic genomes in a circular or linear context. It accepts standard sequence file formats and an optional style specification file to generate customizable, publication quality genome maps in bitmap and scalable vector graphics formats. GView features an interactive pan-and-zoom interface, a command-line interface for incorporation in genome analysis pipelines, and a public Application Programming Interface for incorporation in other Java applications.Availability: GView is a freely available application licensed under the GNU Public License. The application, source code, documentation, file specifications, tutorials and image galleries are available at http://gview.caContact: gary.van.domselaar@phac-aspc.gc.ca
BackgroundImmune-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.ResultsSignificant microbial community differences between cohorts were observed (pseudo F = 4.56; p = 0.01). Richness and diversity were significantly different between cohorts (pFDR < 0.001) and were lowest in CD while highest in HC. Abundances of Actinomyces, Eggerthella, Clostridium III, Faecalicoccus, and Streptococcus (pFDR < 0.001) were significantly higher in all disease cohorts relative to HC, whereas significantly lower abundances were observed for Gemmiger, Lachnospira, and Sporobacter (pFDR < 0.001). Several taxa were found to be differentially abundant in IMIDs versus HC including significantly higher abundances of Intestinibacter in CD, Bifidobacterium in UC, and unclassified Erysipelotrichaceae in MS and significantly lower abundances of Coprococcus in CD, Dialister in MS, and Roseburia in RA. A machine learning approach to classify disease versus HC was highest for CD (AUC = 0.93 and AUC = 0.95 for OTU and genus features, respectively) followed by MS, RA, and UC. Gemmiger and Faecalicoccus were identified as important features for classification of subjects to CD and HC. In general, features identified by differential abundance testing were consistent with machine learning feature importance.ConclusionsThis study identified several gut microbial taxa with differential abundance patterns common to IMIDs. We also found differentially abundant taxa between IMIDs. These taxa may serve as biomarkers for the detection and diagnosis of IMIDs and suggest there may be a common component to IMID etiology.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0603-4) contains supplementary material, which is available to authorized users.
One year into the global COVID-19 pandemic, the focus of attention has shifted to the emergence and spread of SARS-CoV-2 variants of concern (VOCs). After nearly a year of the pandemic with little evolutionary change affecting human health, several variants have now been shown to have substantial detrimental effects on transmission and severity of the virus. Public health officials, medical practitioners, scientists, and the broader community have since been scrambling to understand what these variants mean for diagnosis, treatment, and the control of the pandemic through nonpharmaceutical interventions and vaccines. Here we explore the evolutionary processes that are involved in the emergence of new variants, what we can expect in terms of the future emergence of VOCs, and what we can do to minimise their impact.
for a one-Health investigation of antimicrobial resistance (AMR) in Enterococcus spp., isolates from humans and beef cattle along with abattoirs, manured fields, natural streams, and wastewater from both urban and cattle feedlot sources were collected over two years. Species identification of Enterococcus revealed distinct associations across the continuum. Of the 8430 isolates collected, Enterococcus faecium and Enterococcus faecalis were the main species in urban wastewater (90%) and clinical human isolates (99%); Enterococcus hirae predominated in cattle (92%) and feedlot catch-basins (60%), whereas natural streams harbored environmental Enterococcus spp. Wholegenome sequencing of E. faecalis (n = 366 isolates) and E. faecium (n = 342 isolates), revealed source clustering of isolates, indicative of distinct adaptation to their respective environments. phenotypic resistance to tetracyclines and macrolides encoded by tet(M) and erm(B) respectively, was prevalent among Enterococcus spp. regardless of source. for E. faecium from cattle, resistance to β-lactams and quinolones was observed among 3% and 8% of isolates respectively, compared to 76% and 70% of human clinical isolates. clinical vancomycin-resistant E. faecium exhibited high rates of multi-drug resistance, with resistance to all β-lactam, macrolides, and quinolones tested. Differences in the AMR profiles among isolates reflected antimicrobial use practices in each sector of the One-Health continuum. Public concern for antimicrobial use (AMU) and resistance (AMR) in livestock is increasing, as is continuing pressure for industries and governments to address these concerns. Science-based and epidemiologically sound research is critical to drive policy, communication, legislation, and inform consumer choices. To effectively investigate the current state of antimicrobial resistance, holistic One Health approaches are required to determine correlation between AMU and AMR across the human-agriculture-environment continuum. The genus Enterococcus is ubiquitous in nature and member species can be found in a range of habitats including soils, sediments, freshwater, marine water, beach sand, and a variety of plants 1,2. Enterococcus spp. are also common members of the normal gastrointestinal (GI) flora of both livestock and humans 3 , with their concentrations in human and animal feces typically ranging from 10 3-10 7 cells per gram 4-6. Enterococcus spp. are also commonly isolated from water contaminated by sewage or fecal wastes, and are widely used as bacteriological
The emergence of Neisseria gonorrhoeae strains with decreased susceptibility to cephalosporins and azithromycin (AZM) resistance (AZM(r)) represents a public health threat of untreatable gonorrhea infections. Genomic epidemiology through whole-genome sequencing was used to describe the emergence, dissemination, and spread of AZM(r) strains. The genomes of 213 AZM(r) and 23 AZM-susceptible N. gonorrhoeae isolates collected in Canada from 1989 to 2014 were sequenced. Core single nucleotide polymorphism (SNP) phylogenomic analysis resolved 246 isolates into 13 lineages. High-level AZM(r) (MICs ≥ 256 μg/ml) was found in 5 phylogenetically diverse isolates, all of which possessed the A2059G mutation (Escherichia coli numbering) in all four 23S rRNA alleles. One isolate with high-level AZM(r) collected in 2009 concurrently had decreased susceptibility to ceftriaxone (MIC = 0.125 μg/ml). An increase in the number of 23S rRNA alleles with the C2611T mutations (E. coli numbering) conferred low to moderate levels of AZM(r) (MICs = 2 to 4 and 8 to 32 μg/ml, respectively). Low-level AZM(r) was also associated with mtrR promoter mutations, including the -35A deletion and the presence of Neisseria meningitidis-like sequences. Geographic and temporal phylogenetic clustering indicates that emergent AZM(r) strains arise independently and can then rapidly expand clonally in a region through local sexual networks.
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.
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