McMillen, T. | bioRxiv Science

bioRxiv2023

Virulence and genomic diversity among clinical isolates of ST1 (BI/NAP1/027) Clostridioides difficile

Clostridioides difficile (C. difficile), a leading cause of nosocomial infection, produces toxins that damage the colonic epithelium and results in colitis that varies from mild to fulminant. Variation in disease severity is poorly understood and has been attributed to host factors (age, immune competence and intestinal microbiome composition) and/or virulence differences between C. difficile strains, with some, such as the epidemic BI/NAP1/027 (MLST1) strain, being associated with greater virulence. We tested 23 MLST1(ST1) C. difficile clinical isolates for virulence in antibiotic-treated C57BL/6 mice. All isolates encoded a complete Tcd pathogenicity locus and achieved similar colonization densities in mice. Disease severity varied, however, with 5 isolates causing lethal infections, 16 isolates causing a range of moderate infections and 2 isolates resulting in no detectable disease. The avirulent ST1 isolates did not cause disease in highly susceptible Myd88-/- or germ-free mice. Genomic analysis of the avirulent isolates revealed a 69 base-pair deletion in the N-terminus of the cdtR gene, which encodes a response regulator for binary toxin (CDT) expression. Genetic deletion of the 69 base-pair cdtR sequence in the highly virulent ST1 R20291 C. difficile strain rendered it avirulent and reduced toxin gene transcription in cecal contents. Our study demonstrates that a natural deletion within cdtR attenuates virulence in the epidemic ST1 C. difficile strain without reducing colonization and persistence in the gut. Distinguishing strains on the basis of cdtR may enhance the specificity of diagnostic tests for C. difficile colitis.

microbiology↗

bioRxiv2020

A pipeline to characterize local cortical folds by mapping them to human-interpretable shapes

BackgroundVariations in regional cortical folds across individuals have been examined using computationally-derived morphological measures, or by manual characterization procedures that map distinct variants of a regional fold to a set of human-interpretable shapes. Although manual mapping approaches have proven useful for identifying morphological differences of clinical relevance, such procedures are subjective and not amenable to scaling. New MethodWe propose a 3-step pipeline to develop computational models of manual mapping. The steps are: represent regional folds as feature vectors, manually map each feature vector to a shape-variant that the underlying fold represents, and train classifiers to learn the mapping. ResultsFor demonstration, we chose a 2D-problem of detecting within slice discontinuity of medial and lateral sulci of orbitofrontal cortex (OFC); the discontinuity may be visualized as a broken H-shaped pattern, and is fundamental to OFC-type-characterization. The classifiers predicted discontinuities with 86-95% test-accuracy. Comparison with Existing MethodsThere is no existing pipeline that automates a manual characterization process. For the current demonstration problem, we conduct multiple analyses using existing softwares to explain our design decisions, and present guidelines for using the pipeline to examine other regional folds using conventional or non-conventional morphometric measures. ConclusionWe show that this pipeline can be useful for determining axial-slice discontinuity of sulci in the OFC and can learn structural-features that human-raters may rely on during manual-characterization.The pipeline can be used for examining other regional folds and may facilitate discovery of various statistically-reliable 2D or 3D human-interpretable shapes that are embedded throughout the brain.

neuroscience↗