Protection against Clostridioides difficile disease by a naturally avirulent C. difficile strain.

Clostridioides difficile (C. difficile) strains belonging to the epidemic BI/NAP1/027 (RT027) group have been associated with increased transmissibility and disease severity. In addition to the major toxin A and toxin B virulence factors, RT027 strains also encode the CDT binary toxin. Our lab previously identified a toxigenic RT027 isolate, ST1-75, that is avirulent in mice despite densely colonizing the colon. Here, we show that coinfecting mice with the avirulent ST1-75 and virulent R20291 strains protects mice from colitis due to rapid clearance of the virulent strain and persistence of the avirulent strain. Although avirulence of ST1-75 is due to a mutation in the cdtR gene, which encodes a response regulator that modulates the production of all three C. difficile toxins, the ability of ST1-75 to protect against acute colitis is not directly attributable to the cdtR mutation. Metabolomic analyses indicate that the ST1-75 strain depletes amino acids more rapidly than the R20291 strain and supplementation with amino acids ablates ST1-75's competitive advantage, suggesting that the ST1-75 strain limits the growth of virulent R20291 bacteria by amino acid depletion. Since the germination kinetics and sensitivity to the co-germinant glycine are similar for the ST1-75 and R20291 strains, our results identify the rapidity of in vivo nutrient depletion as a mechanism providing strain-specific, virulence-independent competitive advantages to different BI/NAP1/027 strains. They also suggest that the ST1-75 strain may, as a biotherapeutic agent, enhance resistance to CDI in high-risk patients.

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94-99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24-36 h faster than standard workflows, with <4 h assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.

Rapid identification and phylogenetic classification of diverse bacterial pathogens in a multiplexed hybridization assay targeting ribosomal RNA.

Rapid bacterial identification remains a critical challenge in infectious disease diagnostics. We developed a novel molecular approach to detect and identify a wide diversity of bacterial pathogens in a single, simple assay, exploiting the conservation, abundance, and rich phylogenetic content of ribosomal RNA in a rapid fluorescent hybridization assay that requires no amplification or enzymology. Of 117 isolates from 64 species across 4 phyla, this assay identified bacteria with >89% accuracy at the species level and 100% accuracy at the family level, enabling all critical clinical distinctions. In pilot studies on primary clinical specimens, including sputum, blood cultures, and pus, bacteria from 5 different phyla were identified.