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. 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. 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.

A panel of 24 methicillin-resistant Staphylococcus aureus strains was distributed to 15 laboratories in Canada to evaluate their in-house pulsed-field gel electrophoresis (PFGE) protocols and interpretation criteria. Attempts to compare fingerprint images using computer-aided analysis were not successful due to variability in individual laboratory PFGE protocols. In addition, individual site interpretation of the fingerprint patterns was inadequate, as 7 of 13 sites (54%) made at least one error in interpreting the fingerprints from the panel. A 2-day standardized PFGE protocol (culture to gel image) was developed and distributed to all of the sites. Each site was requested to use the standardized protocol on five strains from the original panel. Thirteen sites submitted gel images for comparisons. The protocol demonstrated excellent reproducibility and allowed interlaboratory comparisons with Molecular Analyst DST software (Bio-Rad) and 1.5% band tolerance.

Matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry represents a revolution in the rapid identification of bacterial and fungal pathogens in the clinical microbiology laboratory. Recently, MALDI-TOF has been applied directly to positive blood culture bottles for the rapid identification of pathogens, leading to reductions in turnaround time and potentially beneficial patient impacts. The development of a commercially available extraction kit (Bruker Sepsityper) for use with the Bruker MALDI BioTyper has facilitated the processing required for identification of pathogens directly from positive from blood cultures. We report the results of an evaluation of the accuracy, cost, and turnaround time of this method for 61 positive monomicrobial and 2 polymicrobial cultures representing 26 species. The Bruker MALDI BioTyper with the Sepsityper gave a valid (score, >1.7) identification for 85.2% of positive blood cultures with no misidentifications. The mean reduction in turnaround time to identification was 34.3 h ( P < 0.0001) in the ideal situation where MALDI-TOF was used for all blood cultures and 26.5 h in a more practical setting where conventional identification or identification from subcultures was required for isolates that could not be directly identified by MALDI-TOF. Implementation of a MALDI-TOF-based identification system for direct identification of pathogens from blood cultures is expected to be associated with a marginal increase in operating costs for most laboratories. However, the use of MALDI-TOF for direct identification is accurate and should result in reduced turnaround time to identification.

Clostridium difficile -associated diarrhea (CAD) is a very common nosocomial infection that contributes significantly to patient morbidity and mortality as well as to the cost of hospitalization. Previously, strains of toxin A-negative, toxin B-positive C. difficile were not thought to be associated with clinically significant disease. This study reports the characterization of a toxin A-negative, toxin B-positive strain of C. difficile that was responsible for a recently described nosocomial outbreak of CAD. Analysis of the seven patient isolates from the outbreak by pulsed-field gel electrophoresis indicated that this outbreak was due to transmission of a single strain of C. difficile . Our characterization of this strain (HSC98) has demonstrated that the toxin A gene lacks 1.8 kb from the carboxy repetitive oligopeptide (CROP) region but apparently has no other major deletions from other regions of the toxin A or toxin B gene. The remaining 1.3-kb fragment of the toxin A CROP region from strain HSC98 showed 98% sequence homology with strain 1470, previously reported by M. Weidmann in 1997 (GenBank accession number Y12616 ), suggesting that HSC98 is toxinotype VIII. The HSC98 strain infecting patients involved in this outbreak produced the full spectrum of clinical illness usually associated with C. difficile -associated disease. This pathogenic spectrum was manifest despite the inability of this strain to alter tight junctions as determined by using in vitro tissue culture testing, which suggested that no functional toxin A was produced by this strain.