Biology subjects

White, R. J.

Publications and source records attributed to White, R. J..

3 recordsLinked to original sources

bioRxiv2018

Inpatient mobility to predict hospital-onset Clostridium difficile: a network approach

With hospital-onset Clostridium difficile Infection (CDI) still a common occurrence in the U.S., this paper examines the relationship between unit-wide CDI susceptibility and inpatient mobility and creates a predictive measure of CDI called \"Contagion Centrality\". A mobility network was constructed using two years of patient electronic health record (EHR) data within a 739-bed hospital (Jan. 2013 - Dec. 2014; n=72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. Closeness centrality was a statistically significant measure associated with unit susceptibility (p-value < 0.05), highlighting the importance of incoming patient mobility in CDI prevention at the unit-level. Contagion Centrality (CC) was calculated using incoming inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. This measure is statistically significant (p-value <0.05) with our outcome of hospital-onset CDI cases, and captures the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create an easily interpretable and informative clinical tool showing this relationship and risk of hospital-onset CDI in real-time. Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak, and thus provide clinicians and infection prevention staff with advanced warning and specific location data to concentrate prevention efforts.

epidemiology↗

bioRxiv2018

The gene regulatory basis of genetic compensation during neural crest induction

BackgroundThe neural crest (NC) is a vertebrate-specific cell type that contributes to a wide range of different tissues across all three germ layers. The gene regulatory network (GRN) responsible for the formation of neural crest is conserved across vertebrates. Central to the induction of the NC GRN are AP-2 and SoxE transcription factors but detailed interactions within the network remain to be resolved.\n\nResultsWe have used gene knockout and RNA sequencing strategies to dissect NC differentiation in zebrafish. We establish that initiation of the NC GRN takes place just after genome activation. We genetically ablate the NC using double mutants of tfap2a;tfap2c or remove specific subsets of the NC with sox10 and mitfa knockouts and characterise genome-wide gene expression levels across multiple time points. We find that although a single allele of tfap2c is capable of maintaining early NC induction and differentiation in the absence of tfap2a function, expression of many target genes remains abnormal and sensitive to tfap2 dosage. This separation of morphological and molecular phenotypes identifies a core set of genes required for early NC development. Using gene knockouts, we associate previously uncharacterised genes with pigment cell development and establish a role for maternal Hippo signalling in melanocyte differentiation.\n\nConclusionsStepwise genetic ablation of the NC identifies the core gene module required for neural crest induction. This work extends and refines the NC GRN while also uncovering the complex transcriptional basis of genetic compensation via paralogues.

developmental biology↗

bioRxiv2017

A high-resolution mRNA expression time course of embryonic development in zebrafish

We have produced an mRNA expression time course of zebrafish development across 18 time points from 1-cell to 5 days post-fertilisation sampling individual and pools of embryos. Using poly(A) pulldown stranded RNA-seq and a 3' end transcript counting method we characterise the temporal expression profiles of 23,642 genes. We identify temporal and functional transcript co-variance that associates 5,024 unnamed genes with distinct developmental time points. Specifically, a class of over 100 previously uncharacterised zinc finger domain containing genes, located on the long arm of chromosome 4, is expressed in a sharp peak during zygotic genome activation. The data reveal complex and widespread differential use of exons and previously unidentified 3' ends across development, new primary microRNA transcripts and temporal divergence of gene paralogues generated in the teleost genome duplication. To make this dataset a useful baseline reference, the data are accessible to browse and download at Expression Atlas and Ensembl.

developmental biology↗