bioRxiv Science⌕ Search

Biology subjects

Boykin, R.

Publications and source records attributed to Boykin, R..

2 recordsLinked to original sources

A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture

Invasive fungal infections are increasingly common and carry high morbidity and mortality, yet fungal diagnostics lag behind bacterial diagnostics in rapidly identifying the causal pathogen. We previously devised a fluorescent hybridization-based assay to identify bacteria within hours directly from blood culture bottles without subculture, called phylogeny-informed rRNA-based strain identification (Phirst-ID). Here, we adapt this approach to unambiguously identify 11 common pathogenic Candida species, including C. auris, with 100% accuracy from laboratory culture (33 of 33 strains in a reference panel, plus 33 of 33 additional isolates tested in a validation panel). In a pilot study on 62 consecutive positive clinical blood cultures from two hospitals that showed yeast on Gram stain, Candida Phirst-ID matched the clinical laboratory result for 58 of 59 specimens represented in the 11-species reference panel, without misclassifying the 3 off-panel species. It also detected mixed Candida species in 2 of these 62 specimens, including the one discordant classification, that were not identified by standard clinical microbiology workflows; in each case the presence of both species was validated by both clinical and experimental data. Finally, in three specimens that grew both bacteria and yeast, we paired our prior bacterial probeset with this new Candida probeset to detect both pathogen types using Phirst-ID. This simple, robust assay can provide accurate Candida identification within hours directly from blood culture bottles, and the conceptual approach holds promise for pan-microbial identification in a single workflow.

microbiology↗

Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling

Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene expression. Here we describe expanding the chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ~10-500 cells. By benchmarking against bulk RNAseq and fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ~100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.

genomics↗