The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology.

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This Portal has been coupled with other resources like Viral AI and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this Portal, including its contextual data not available elsewhere, and the 'Duotang', a web platform that presents key genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Assessment of dietary intake and its inflammatory potential in persons with pediatric-onset multiple sclerosis.

OBJECTIVE: To compare diet and the modified dietary inflammatory index (mDII) between individuals with pediatric-onset multiple sclerosis (PoMS), monophasic acquired demyelinating syndromes (monoADS), and controls. METHODS: The association between diet, mDII, and disease status was examined in 131 individuals with PoMS/monoADS/controls (38/45/48) using logistic regression. RESULTS: The associations between diet and PoMS were modest, reaching significance for whole grain intake (adjusted odds ratio, aOR=0.964, 95 % confidence intervals, CI:0.934-0.995) but not mDII (aOR=1.20, 95 %CI:0.995-1.46) versus controls. No findings for monoADS reached significance versus controls. CONCLUSIONS: Individuals with PoMS, but not monoADS, had lower dietary whole grain intake than controls.

Short-chain fatty acid producers in the gut are associated with pediatric multiple sclerosis onset.

OBJECTIVE: The relationship between multiple sclerosis and the gut microbiome has been supported by animal models in which commensal microbes are required for the development of experimental autoimmune encephalomyelitis. However, observational study findings in humans have only occasionally converged when comparing multiple sclerosis cases and controls which may in part reflect confounding by comorbidities and disease duration. The study of microbiome in pediatric-onset multiple sclerosis offers unique opportunities as it is closer to biological disease onset and minimizes confounding by comorbidities and environmental exposures. METHODS: A multicenter case-control study in which 35 pediatric-onset multiple sclerosis cases were 1:1 matched to healthy controls on age, sex, self-reported race, ethnicity, and recruiting site. Linear mixed effects models, weighted correlation network analyses, and PICRUSt2 were used to identify microbial co-occurrence networks and for predicting functional abundances based on marker gene sequences. RESULTS: Two microbial co-occurrence networks (one reaching significance after adjustment for multiple comparisons; q < 0.2) were identified, suggesting interdependent bacterial taxa that exhibited association with disease status. Both networks indicated a potentially protective effect of higher relative abundance of bacteria observed in these clusters. Functional predictions from the significant network suggested a contribution of short-chain fatty acid producers through anaerobic fermentation pathways in healthy controls. Consistent family-level findings from an independent Canadian-US study (19 case/control pairs) included Ruminococaccaeae and Lachnospiraceae (p < 0.05). Macronutrient intake was not significantly different between cases and controls, minimizing the potential for dietary confounding. INTERPRETATION: Our results suggest that short-chain fatty acid producers may be important contributors to multiple sclerosis onset.

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

OBJECTIVE: To identify gut microbiome features associated with MRI lesion burden in persons with pediatric-onset multiple sclerosis (symptom onset <18 years). METHODS: A cross-sectional study involving the Canadian Paediatric Demyelinating Disease Network study participants. Gut microbiome features (alpha diversity, phylum- and genus-level taxa) were derived using 16S rRNA sequencing from stool samples. T1- and T2-weighted lesion volumes were measured on brain MRI obtained within 6 months of stool sample procurement. Associations between the gut microbiota and MRI metrics (cube-root-transformed) were assessed using standard and Lasso regression models. RESULTS: Thirty-four participants were included; mean ages at symptom onset and MRI were 15.1 and 19.0 years, respectively, and 79% were female. The T1- and T2-weighted lesion volumes were not significantly associated with alpha diversity (age and sex-adjusted p > 0.08). At the phylum level, high Tenericutes (relative abundance) was associated with higher T1 and T2 volumes (ß coefficient = 0.25, 0.37) and high Firmicutes, Patescibacteria or Actinobacteria with lower lesion volumes (ß coefficient = -0.30 to -0.07). At the genus level, high Ruminiclostridium, whereas low Coprococcus 3 and low Erysipelatoclostridium were associated with higher lesion volumes. INTERPRETATION: Our study characterized the gut microbiota features associated with MRI lesion burden in pediatric-onset MS, shedding light onto possible pathophysiological mechanisms.

Effect of Antimicrobial Use in Conventional Versus Natural Cattle Feedlots on the Microbiome and Resistome.

Antimicrobial use (AMU) in the livestock industry has been associated with increased levels of antimicrobial resistance. Recently, there has been an increase in the number of "natural" feedlots in the beef cattle sector that raise cattle without antibiotics. Shotgun metagenomics was employed to characterize the impact of AMU in feedlot cattle on the microbiome, resistome, and mobilome. Sequenced fecal samples identified a decline (q < 0.01) in the genera Methanobrevibacter and Treponema in the microbiome of naturally vs. conventionally raised feedlot cattle, but this difference was not (q > 0.05) observed in catch basin samples. No differences (q > 0.05) were found in the class-level resistome between feedlot practices. In fecal samples, decreases from conventional to natural (q < 0.05) were noted in reads for the antimicrobial-resistant genes (ARGs) mefA, tet40, tetO, tetQ, and tetW. Plasmid-associated ARGs were more common in feces from conventional than natural feedlot cattle. Interestingly, more chromosomal- than plasmid-associated macrolide resistance genes were observed in both natural and conventional feedlots, suggesting that they were more stably conserved than the predominately plasmid-associated tetracycline resistance genes. This study suggests that generationally selected resistomes through decades of AMU persist even after AMU ceases in natural production systems.

Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements.

Antimicrobial resistance genes (ARGs) can be transferred between members of a bacterial population by mobile genetic elements (MGE). Understanding the risk of these transfer events is important in monitoring and predicting antimicrobial resistance (AMR), especially in the context of a One Health Continuum. However, there is no universally accepted method for detection of ARGs and MGEs, and especially for determining their linkages. This study used publicly available shotgun metagenomic DNA short-read (Illumina, 100 bp paired-end) sequence data from samples across the One Health Continuum (including beef cattle composite feces from feedlots, catch basin water at feedlots, agricultural soil from feedlot manured surrounding fields, and urban/municipal sewage influent from two municipal wastewater treatment plants) to develop a workflow to identify and associate ARGs and MGEs. ARG- and MGE-based targeted-assemblies with available short-read data were unable to meet this analysis goal. In contrast, de novo assembly of contigs provided enough sequence context to associate ARGs and MGEs, without compromising discovery rate. However, to estimate the relative abundance of these elements, unassembled sequence data must still be used.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach.

BACKGROUND: The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq. RESULTS: In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2. CONCLUSIONS: A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Proksee: in-depth characterization and visualization of bacterial genomes.

Proksee (https://proksee.ca) provides users with a powerful, easy-to-use, and feature-rich system for assembling, annotating, analysing, and visualizing bacterial genomes. Proksee accepts Illumina sequence reads as compressed FASTQ files or pre-assembled contigs in raw, FASTA, or GenBank format. Alternatively, users can supply a GenBank accession or a previously generated Proksee map in JSON format. Proksee then performs assembly (for raw sequence data), generates a graphical map, and provides an interface for customizing the map and launching further analysis jobs. Notable features of Proksee include unique and informative assembly metrics provided via a custom reference database of assemblies; a deeply integrated high-performance genome browser for viewing and comparing analysis results at individual base resolution (developed specifically for Proksee); an ever-growing list of embedded analysis tools whose results can be seamlessly added to the map or searched and explored in other formats; and the option to export graphical maps, analysis results, and log files for data sharing and research reproducibility. All these features are provided via a carefully designed multi-server cloud-based system that can easily scale to meet user demand and that ensures the web server is robust and responsive.

The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded ß-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.

Source of human milk (mother or donor) is more important than fortifier type (human or bovine) in shaping the preterm infant microbiome.

Milk fortifiers help meet the nutritional needs of preterm infants receiving their mother's own milk (MOM) or donor human milk. We conducted a randomized clinical trial (NCT03214822) in 30 very low birth weight premature neonates comparing bovine-derived human milk fortifier (BHMF) versus human-derived fortifier (H2MF). We found that fortifier type does not affect the overall microbiome, although H2MF infants were less often colonized by an unclassified member of Clostridiales Family XI. Secondary analyses show that MOM intake is strongly associated with weight gain and microbiota composition, including Bifidobacterium, Veillonella, and Propionibacterium enrichment. Finally, we show that while oxidative stress (urinary F2-isoprostanes) is not affected by fortifier type or MOM intake, fecal calprotectin is higher in H2MF infants and lower in those consuming more MOM. Overall, the source of human milk (mother versus donor) appears more important than the type of milk fortifier (human versus bovine) in shaping preterm infant gut microbiota.

Genomic Characterization of Enterococcus hirae From Beef Cattle Feedlots and Associated Environmental Continuum.

Enterococci are commensal bacteria of the gastrointestinal tract of humans, animals, and insects. They are also found in soil, water, and plant ecosystems. The presence of enterococci in human, animal, and environmental settings makes these bacteria ideal candidates to study antimicrobial resistance in the One-Health continuum. This study focused on Enterococcus hirae isolates (n = 4,601) predominantly isolated from beef production systems including bovine feces (n = 4,117, 89.5%), catch-basin water (n = 306, 66.5%), stockpiled bovine manure (n = 24, 0.5%), and natural water sources near feedlots (n = 145, 32%), and a few isolates from urban wastewater (n = 9, 0.2%) denoted as human-associated environmental samples. Antimicrobial susceptibility profiling of a subset (n = 1,319) of E. hirae isolates originating from beef production systems (n = 1,308) showed high resistance to tetracycline (65%) and erythromycin (57%) with 50.4% isolates harboring multi-drug resistance, whereas urban wastewater isolates (n = 9) were resistant to nitrofurantoin (44.5%) and tigecycline (44.5%) followed by linezolid (33.3%). Genes for tetracycline (tetL, M, S/M, and O/32/O) and macrolide resistance erm(B) were frequently found in beef production isolates. Antimicrobial resistance profiles of E. hirae isolates recovered from different environmental settings appeared to reflect the kind of antimicrobial usage in beef and human sectors. Comparative genomic analysis of E. hirae isolates showed an open pan-genome that consisted of 1,427 core genes, 358 soft core genes, 1701 shell genes, and 7,969 cloud genes. Across species comparative genomic analysis conducted on E. hirae, Enterococcus faecalis and Enterococcus faecium genomes revealed that E. hirae had unique genes associated with vitamin production, cellulose, and pectin degradation, traits which may support its adaptation to the bovine digestive tract. E. faecium and E. faecalis more frequently harbored virulence genes associated with biofilm formation, iron transport, and cell adhesion, suggesting niche specificity within these species.

Universal antibody targeting the highly conserved fusion peptide provides cross-protection in mice.

Influenza is a major public health concern causing millions of hospitalizations every year. The current vaccines need annual updating based on prediction of likely strains in the upcoming season. However, mismatches between vaccines and the actual circulating viruses can occur, reducing vaccine effectiveness significantly because of the remarkably high rate of mutation in the viral glycoprotein, hemagglutinin (HA). Clearly, it would be of great interest to determine the potential role of universally conserved epitopes in inducing protective immunity. Here, an antibody against the 14-aa fusion peptide sequence at the N-terminus of the HA2 subunit (Uni-1) was investigated for its ability to elicit antibody-dependent cellular cytotoxicity (ADCC) in vitro and cross-protection against lethal infection in animals. Uni-1, known to neutralize influenza type A (IAV) in vitro, was found to induce strong ADCC against diverse influenza viruses, including human and avian IAVs and both lineages of type B (IBV). The ADCC effects against human IAVs by Uni-1 was comparable to ADCC induced by well-characterized antibodies, F10 and FI6V3. Importantly, mice treated with Uni-1 were protected against lethal challenge of IAV and IBV. These results revealed the versatile effector functions of this universal antibody against markedly diverse strains of both IAV and IBV.

The fusion peptide is the only universally conserved epitope in both IAV and IBVMono-specific universal antibody induces strong ADCC against human and avian IAVMono-specific universal antibody induces strong ADCC against IBV from both genetic lineages of IBVThe antibody has bi-functional effector functions against several influenza viruses.

The metabolic potential of the paediatric-onset multiple sclerosis gut microbiome.

BACKGROUND: The aim of this study was to examine the gut microbiome's metabolic potential in paediatric-onset MS patients (symptom onset <18 years). METHODS: We included 17 MS participants and 20 controls similar for sex, age, race, and stool consistency from the Canadian Paediatric Demyelinating Disease Network study. Stool-derived gut metagenome gene abundances were used to estimate relative abundances and turnover scores of individual microbial metabolites and the composition and diversity of carbohydrate-active enzymes (CAZymes). MS participants and controls were compared using the Wilcoxon rank-sum test, as were the disease-modifying drug (DMD) exposed and naïve MS participants. RESULTS: The median age(s) at MS symptom onset=16.1 years (interquartile range [IQR]=1.7), and at stool sample procurement=16.9/15.8 years (IQR=2.0/1.4), for the MS participants/controls. Most MS and control participants were girls (80-82%). Five (29%) of the MS participants had never been exposed to a DMD pre-stool sample and 12 (71%) had (7 to beta-interferon and 5 glatiramer acetate). While the relative abundance of metabolites did not differ between MS participants and controls, turnover scores did. MS participants had a greater potential to metabolize lipopolysaccharides than controls (score difference=1.6E-04, p = 0.034) but lower potential to metabolize peptidoglycan molecules and starch (score differences<2.2E-02, p<0.040). Further, although CAZymes diversity did not differ (p>0.050), starch-degrading subfamilies were underrepresented in MS participants versus controls (relative abundance differences >-0.34, p<0.040) and in the DMD exposed verses DMD naïve MS participants (relative abundance differences>-0.20, p<0.049). CONCLUSION: Paediatric-onset MS participants had an altered gut microbiome-related metabolic potential compared to controls, including higher breakdown of lipopolysaccharide molecules, but lower resistant starch metabolism.

The need for linked genomic surveillance of SARS-CoV-2.

Genomic surveillance during the coronavirus disease 2019 (COVID-19) pandemic has been key to the timely identification of virus variants with important public health consequences, such as variants that can transmit among and cause severe disease in both vaccinated or recovered individuals. The rapid emergence of the Omicron variant highlighted the speed with which the extent of a threat must be assessed. Rapid sequencing and public health institutions' openness to sharing sequence data internationally give an unprecedented opportunity to do this; however, assessing the epidemiological and clinical properties of any new variant remains challenging. Here we highlight a "band of four" key data sources that can help to detect viral variants that threaten COVID-19 management: 1) genetic (virus sequence) data; 2) epidemiological and geographic data; 3) clinical and demographic data; and 4) immunization data. We emphasize the benefits that can be achieved by linking data from these sources and by combining data from these sources with virus sequence data. The considerable challenges of making genomic data available and linked with virus and patient attributes must be balanced against major consequences of not doing so, especially if new variants of concern emerge and spread without timely detection and action.

Stability of the gut microbiota in persons with paediatric-onset multiple sclerosis and related demyelinating diseases.

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.

Colorectal Cancer Screening in Inflammatory Bowel Diseases-Can Characterization of GI Microbiome Signatures Enhance Neoplasia Detection?

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.

Metagenomic Analysis of the Pediatric-Onset Multiple Sclerosis Gut Microbiome.

BACKGROUND AND OBJECTIVES: Little is known of the functional potential of the gut microbiome in pediatric-onset multiple sclerosis (MS). We performed metagenomic analyses using stool samples from individuals with pediatric-onset MS and unaffected controls. METHODS: Persons ≤21 years old enrolled in the Canadian Pediatric Demyelinating Disease Network providing a stool sample were eligible. Twenty patients with MS (McDonald criteria) with symptom onset <18 years were matched to 20 controls by sex, age (±3 years), stool consistency, and race. Microbial taxonomy and functional potentials were estimated from stool sample-derived metagenomic reads and compared by disease status (MS vs controls) and disease-modifying drug (DMD) exposure using alpha diversity, relative abundance, and prevalence using Wilcoxon rank sum, ALDEx2, and Fisher exact tests, respectively. RESULTS: Individuals with MS were aged 13.6 years (mean) at symptom onset and 8 were DMD-naive. Mean ages at stool sample were 16.1 and 15.4 years for MS and control participants, respectively; 80% were girls. Alpha diversity of enzymes and proteins did not differ by disease or DMD status (p > 0.20), but metabolic pathways, gene annotations, and microbial taxonomy did. Individuals with MS (vs controls) exhibited higher methanogenesis prevalence (odds ratio 10, p = 0.044) and Methanobrevibacter abundance (log2 fold change [LFC] 1.7, p = 0.0014), but lower homolactic fermentation abundance (LFC -0.48, p = 0.039). Differences by DMD status included lower phosphate butyryl transferase for DMD-naive vs exposed patients with MS (LFC -1.0, p = 0.033). DISCUSSION: The gut microbiome's functional potential and taxonomy differed between individuals with pediatric-onset MS vs controls, including higher prevalence of a methane-producing pathway from Archaea and depletion of the lactate fermentation pathway. DMD exposure was associated with butyrate-producing enzyme enrichment. Together these findings indicate that the gut microbiome of individuals with MS may have a disturbed functional potential.

Combining analytical epidemiology and genomic surveillance to identify risk factors associated with the spread of antimicrobial resistance in Salmonella enterica subsp. enterica serovar Heidelberg.

Antimicrobial resistance (AMR) has become a critical threat to public health worldwide. The use of antimicrobials in food and livestock agriculture, including the production of poultry, is thought to contribute to the dissemination of antibiotic resistant bacteria (ARB) and the genes and plasmids that confer the resistant phenotype (ARG). However, the relative contribution of each of these processes to the emergence of resistant pathogens in poultry production and their potential role in the transmission of resistant pathogens in human infections, requires a deeper understanding of the dynamics of ARB and ARG in food production and the factors involved in the increased risk of transmission.

Microbiome-Mediated Immune Signaling in Inflammatory Bowel Disease and Colorectal Cancer: Support From Meta-omics Data.

Chronic intestinal inflammation and microbial dysbiosis are hallmarks of colorectal cancer (CRC) and inflammatory bowel diseases (IBD), such as Crohn's disease and ulcerative colitis. However, the mechanistic relationship between gut dysbiosis and disease has not yet been fully characterized. Although the "trigger" of intestinal inflammation remains unknown, a wealth of evidence supports the role of the gut microbiome as a mutualistic pseudo-organ that significantly influences intestinal homeostasis and is capable of regulating host immunity. In recent years, culture-independent methods for assessing microbial communities as a whole (termed meta-omics) have grown beyond taxonomic identification and genome characterization (metagenomics) into new fields of research that collectively expand our knowledge of microbiomes. Metatranscriptomics, metaproteomics, and metabolomics are meta-omics techniques that aim to describe and quantify the functional activity of the gut microbiome. Uncovering microbial metabolic contributions in the context of IBD and CRC using these approaches provides insight into how the metabolic microenvironment of the GI tract shapes microbial community structure and how the microbiome, in turn, influences the surrounding ecosystem. Immunological studies in germ-free and wild-type mice have described several host-microbiome interactions that may play a role in autoinflammation. Chronic colitis is a precursor to CRC, and changes in the gut microbiome may be an important link triggering the neoplastic process in chronic colitis. In this review, we describe several microbiome-mediated mechanisms of host immune signaling, such as short-chain fatty acid (SCFA) and bile acid metabolism, inflammasome activation, and cytokine regulation in the context of IBD and CRC, and discuss the supporting role for these mechanisms by meta-omics data.