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.

Wound swab quality grading is dependent on Gram smear screening approach.

Superficial skin swab collections are inherently low-quality and may be of little clinical value due to their poor sensitivity and specificity. Clinical microbiology laboratories can use Gram smears to screen and differentiate higher and lower quality specimens to direct the extent of potential pathogen work up, including antimicrobial susceptibility testing (AST). We compared the impact of two different smear grading approaches to our current reporting practices for superficial wound swab cultures. Two variations of the Q score methodology (low power under 10X (QS10) and high power under 100X (QS100) were compared to our existing oil immersion method (OM100) (100X). We further evaluated the QS100 method by scoring superficial swab smears previously screened by OM100 from cultures submitted between November 2018 and December 2019. No significant difference in the number of low-quality specimens (N = 50) was identified by QS10 or QS100 grading (N = 9; 18%; N = 8; 16% respectively). Among 968 additional QS100 screened smears, 67 (6.9%) low quality swabs were identified and 7.4% fewer organisms (76/1020 organisms) would require reporting with AST. Implementing the Q score for superficial wound swab cultures would provide minimal improvements in their clinical relevance, laboratory quality and efficiency in our laboratory due to the low number of poor-quality swabs received.

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.

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.

Real-Time RT-PCR Allelic Discrimination Assay for Detection of N501Y Mutation in the Spike Protein of SARS-CoV-2 Associated with B.1.1.7 Variant of Concern.

The N501Y amino acid mutation caused by a single point substitution A23063T in the spike gene of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is possessed by three variants of concern (VOCs), B.1.1.7, B.1.351, and P.1. A rapid screening tool using this mutation is important for surveillance during the coronavirus disease 2019 (COVID-19) pandemic. We developed and validated a single nucleotide polymorphism real-time reverse transcription PCR assay using allelic discrimination of the spike gene N501Y mutation to screen for potential variants of concern and differentiate them from SARS-CoV-2 lineages without the N501Y mutation. A total of 160 clinical specimens positive for SARS-CoV-2 were characterized as mutant (N501Y) or N501 wild type by Sanger sequencing and were subsequently tested with the N501Y single nucleotide polymorphism real-time reverse transcriptase PCR assay. Our assay, compared to Sanger sequencing for single nucleotide polymorphism detection, demonstrated positive percent agreement of 100% for all 57 specimens displaying the N501Y mutation, which were confirmed by Sanger sequencing to be typed as A23063T, including one specimen with mixed signal for wild type and mutant. Negative percent agreement was 100% in all 103 specimens typed as N501 wild type, with A23063 identified as wild type by Sanger sequencing. The identification of circulating SARS-CoV-2 lineages carrying an N501Y mutation is critical for surveillance purposes. Current identification methods rely primarily on Sanger sequencing or whole-genome sequencing, which are time consuming, labor intensive, and costly. The assay described herein is an efficient tool for high-volume specimen screening for SARS-CoV-2 VOCs and for selecting specimens for confirmatory Sanger or whole-genome sequencing. IMPORTANCE During the coronavirus disease 2019 (COVID-19) pandemic, several variants of concern (VOCs) have been detected, for example, B.1.1.7, B.1.351, P.1, and B.1.617.2. The VOCs pose a threat to public health efforts to control the spread of the virus. As such, surveillance and monitoring of these VOCs is of the utmost importance. Our real-time RT-PCR assay helps with surveillance by providing an easy method to quickly survey SARS-CoV-2 specimens for VOCs carrying the N501Y single nucleotide polymorphism (SNP). Samples that test positive for the N501Y mutation in the spike gene with our assay can be sequenced to identify the lineage. Thus, our assay helps to focus surveillance efforts and decrease turnaround times.

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.

Impact of coronavirus disease 2019 (COVID-19) pre-test probability on positive predictive value of high cycle threshold severe acute respiratory coronavirus virus 2 (SARS-CoV-2) real-time reverse transcription polymerase chain reaction (RT-PCR) test results.

OBJECTIVES: Performance characteristics of SARS-CoV-2 nucleic acid detection assays are understudied within contexts of low pre-test probability, including screening asymptomatic persons without epidemiological links to confirmed cases, or asymptomatic surveillance testing. SARS-CoV-2 detection without symptoms may represent presymptomatic or asymptomatic infection, resolved infection with persistent RNA shedding, or a false-positive test. This study assessed the positive predictive value of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) assays by retesting positive specimens from 5 pre-test probability groups ranging from high to low with an alternate assay. METHODS: In total, 122 rRT-PCR positive specimens collected from unique patients between March and July 2020 were retested using a laboratory-developed nested RT-PCR assay targeting the RNA-dependent RNA polymerase (RdRp) gene followed by Sanger sequencing. RESULTS: Significantly fewer (15.6%) positive results in the lowest pre-test probability group (facilities with institution-wide screening having ≤3 positive asymptomatic cases) were reproduced with the nested RdRp gene RT-PCR assay than in each of the 4 groups with higher pre-test probability (individual group range, 50.0%-85.0%). CONCLUSIONS: Large-scale SARS-CoV-2 screening testing initiatives among low pre-test probability populations should be evaluated thoroughly prior to implementation given the risk of false-positive results and consequent potential for harm at the individual and population level.

The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes.

OBJECTIVE: To examine the gut microbiota in individuals with and without pediatric-onset multiple sclerosis (MS). METHODS: We compared stool-derived microbiota of Canadian Pediatric Demyelinating Disease Network study participants ≤21 years old, with MS (disease-modifying drug [DMD] exposed and naïve) or monophasic acquired demyelinating syndrome [monoADS] (symptom onset <18 years), and unaffected controls. All were ≥30 days without antibiotics or corticosteroids. V4 region 16S RNA gene-derived amplicon sequence variants (Illumina MiSeq) were assessed using negative binomial regression and network analyses; rate ratios were age- and sex-adjusted (aRR). RESULTS: Thirty-two MS, 41 monoADS (symptom onset [mean] = 14.0 and 6.9 years) and 36 control participants were included; 75%/56%/58% were female, with mean ages at stool sample = 16.5/13.8/15.1 years, respectively. Nine MS cases (28%) were DMD-naïve. Although microbiota diversity (alpha, beta) did not differ between participants (p > 0.1), taxa-level and gut community networks did. MS (vs. monoADS) exhibited > fourfold higher relative abundance of the superphylum Patescibacteria (aRR = 4.2;95%CI:1.6-11.2, p = 0.004, Q = 0.01), and lower abundances of short-chain fatty acid (SCFA)-producing Lachnospiraceae (Anaerosporobacter) and Ruminococcaceae (p, Q < 0.05). DMD-naïve MS cases were depleted for Clostridiales vadin-BB60 (unnamed species) versus either DMD-exposed, controls (p, Q < 0.01), or monoADS (p = 0.001, Q = 0.06) and exhibited altered community connectedness (p < 10-9 Kruskal-Wallis), with SCFA-producing taxa underrepresented. Consistent taxa-level findings from an independent US Network of Pediatric MS Centers case/control (n = 51/42) cohort included >eightfold higher abundance for Candidatus Stoquefichus and Tyzzerella (aRR = 8.8-12.8, p < 0.05) in MS cases and 72%-80% lower abundance of SCFA-producing Ruminococcaceae-NK4A214 (aRR = 0.38-0.2, p ≤ 0.01). INTERPRETATION: Gut microbiota community structure, function and connectivity, and not just individual taxa, are of likely importance in MS.

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.

Antimicrobial susceptibility profiles of invasive isolates of anaerobic bacteria from a large Canadian reference laboratory: 2012-2019.

Anaerobic bacteria can cause severe and life threatening infections. Susceptibility data are relatively limited on anaerobic organisms despite the clinical importance in guiding empiric treatment of infections. To determine antimicrobial susceptibility profiles of clinically significant anaerobic bacteria, isolates obtained from sterile sites submitted to Public Health Ontario Laboratory (2012-2019) were included in this study (N = 5712). Cefoxitin, clindamycin, metronidazole, meropenem, penicillin and piperacillin-tazobactam were tested using the gradient strip method with MICs interpreted based on Clinical and Laboratory Standards Institute guidelines. Bacteroides spp. (N = 958; 16.7%), Clostridium spp. (N = 798; 14.0%), Cutibacterium spp. (N =659; 11.5%) and Actinomyces spp. (N = 551; 7.0%) were the most commonly isolated genera. Bacteroides fragilis isolates were susceptible to cefoxitin (88.4%), clindamycin (68.4%), metronidazole (96.0%), meropenem (99.0%) and piperacillin-tazobactam (98.4%). Other Bacteroides spp. showed reduced susceptibility to several antimicrobials. Clostridium spp. isolates were susceptible to penicillin (69.7%), clindamycin (69.7%) and cefoxitin (76.3%); C. perfringens and C. ramosum showed distinct susceptibility profiles. Susceptibility rates among anaerobes remained relatively unchanged over 8 years with a few exceptions: C. perfringens susceptibility to clindamycin decreased from 91.3% to 60% (p = 0.03); Clostridium spp. susceptibility to penicillin similarly decreased from 82.1% to 65.9% (p = 0.03); Eggerthella spp. susceptibility to piperacillin-tazobactam decreased from 100% to 24.3% (p < 0.001); B. fragilis group susceptibility to cefoxitin decreased from 70.4% to 48.2% (p = 0.05); and Parabacteroides spp. susceptibility to piperacillin-tazobactam decreased from 100% to 25% (p = 0.01). Our findings underscore the need for ongoing surveillance and periodic monitoring of antimicrobial resistance in order to guide empiric therapy.

Clinically Important Toxins in Bacterial Infection: Utility of Laboratory Detection.

The elaboration of proteins that damage host cells is fundamental to the pathogenesis of many bacterial pathogens. The clinical significance of many bacterial toxins is well recognized, and routine detection is necessary to confirm definitive diagnosis for some types of infectious diseases. Determining the clinical significance of a toxin involves many factors, including the toxin's prevalence, virulence, and role in disease pathogenesis. While essential from a diagnostic perspective, toxin detection has the potential to be important for patient management decision making, as well as infection prevention and control measures. This review focuses on the history, epidemiology, pathogenesis, clinical presentation, and management of infections associated with well-defined, clinically important toxins (such as Shiga toxin-producing Escherichia coli), as well as those that are less well defined (such as Staphylococcus aureus' Panton-Valentine leukocidin) where detection may yield clinically important information.

Assessment of Inter-Laboratory Variation in the Characterization and Analysis of the Mucosal Microbiota in Crohn's Disease and Ulcerative Colitis.

BACKGROUND: In studies evaluating the microbiome, numerous factors can contribute to technical variability. These factors include DNA extraction methodology, sequencing protocols, and data analysis strategies. We sought to evaluate the impact these factors have on the results obtained when the sequence data are independently generated and analyzed by different laboratories. METHODS: To evaluate the effect of technical variability, we used human intestinal biopsy samples resected from individuals diagnosed with an inflammatory bowel disease (IBD), including Crohn's disease (n = 12) and ulcerative colitis (n = 10), and those without IBD (n = 10). Matched samples from each participant were sent to three laboratories and studied using independent protocols for DNA extraction, library preparation, targeted-amplicon sequencing of a 16S rRNA gene hypervariable region, and processing of sequence data. We looked at two measures of interest - Bray-Curtis PERMANOVA R 2 values and log2 fold-change estimates of the 25 most-abundant taxa - to assess variation in the results produced by each laboratory, as well the relative contribution to variation from the different extraction, sequencing, and analysis steps used to generate these measures. RESULTS: The R 2 values and estimated differential abundance associated with diagnosis were consistent across datasets that used different DNA extraction and sequencing protocols, and within datasets that pooled samples from multiple protocols; however, variability in bioinformatic processing of sequence data led to changes in R 2 values and inconsistencies in taxonomic assignment and abundance estimates. CONCLUSION: Although the contribution of DNA extraction and sequencing methods to variability were observable, we find that results can be robust to the various extraction and sequencing approaches used in our study. Differences in data processing methods have a larger impact on results, making comparison among studies less reliable and the combined analysis of bioinformatically processed samples nearly impossible. Our results highlight the importance of making raw sequence data available to facilitate combined and comparative analyses of published studies using common data processing protocols. Study methodologies should provide detailed data processing methods for validation, interpretability, reproducibility, and comparability.

The multiple sclerosis gut microbiota: A systematic review.

BACKGROUND: To systematically review and synthesize the literature on the multiple sclerosis (MS) gut microbiota composition as compared to persons without MS. METHODS: We systematically searched MEDLINE, EMBASE, and Web of Science databases for relevant published articles (2008-2018). RESULTS: Of 415 articles identified ten fulfilled criteria. All studies used a case-control design, six sourced participants from the US, two Germany, one Italy, and one Japan. Nine focused exclusively on adults and one on children, totaling 286 MS and 296 control participants. Over 90% of cases had relapsing-remitting MS; disease duration ranged from 10.6 ±â€¯6.5 months to 15.3 ±â€¯8.6 years (mean±SD). Nine studies examined stool and one evaluated duodenal mucosa. Diverse platforms were used to quantify microbes: Illumina MiSeq, Roche 454, microarray, and fluorescence in situ hybridization. None of eight studies reported a significant alpha-diversity differences between cases and controls. Two of seven studies reported a difference in beta-diversity (P ≤ 0.002). At the taxa-level, ≥2 studies observed: lower relative abundance of Prevotella, Faecalibacterium prausnitzii, Bacteroides coprophilus, Bacteroides fragilis, and higher Methanobrevibacter and Akkermansia muciniphila in MS cases versus controls. Exposure to an immunomodulatory drug (IMD), relative to no exposure, was associated with individual taxonomic differences in three of three studies. CONCLUSION: Gut microbiota diversity did not differ between MS cases and controls in the majority of studies. However, taxonomic differences were found, with consistent patterns emerging across studies. Longitudinal studies are warranted to elucidate the relationship between IMD exposure and differences in the gut microbiota composition.

The Gut Microbiome in Inflammatory Bowel Disease: Lessons Learned From Other Immune-Mediated Inflammatory Diseases.

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.

The Gut Microbiome as a Target for IBD Treatment: Are We There Yet?

PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.

A comparative study of the gut microbiota in immune-mediated inflammatory diseases-does a common dysbiosis exist?

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 < 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. CONCLUSIONS: This 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.

Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation.

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.