Biology subjects

Holman, D.

Publications and source records attributed to Holman, D..

4 recordsLinked to original sources

bioRxiv2026

Single-cell profiling reveals stromal niche and α5β1 regulation of neutrophil phenotypes in ulcerative colitis

Background and Aims: Fibroblast-neutrophil interactions are implicated in ulcerative colitis (UC) treatment resistance, but whether fibroblasts modify neutrophil inflammatory activity remains unclear. We investigated responses to fibroblast exposure, stromal depletion, and 5{beta}1-directed treatment. Methods: We integrated human and mouse colonic single-cell RNA sequencing (scRNA-seq), spatial protein profiling (CODEX), fibroblast-neutrophil coculture, and dextran sulfate sodium (DSS) mouse colitis with fibroblast activation protein (FAP) ablation or 5{beta}1-directed treatment. Readouts included cellular representation and protein fluorescence via flow cytometry, neutrophil extracellular trap (NET)-associated elastase activity, RNA programs and epithelial responses using scRNA-seq. Results: Inflamed UC tissue contained higher fractions of inflammatory fibroblasts and oncostatin M (OSM)- and CXCR4-associated neutrophils. Inflammatory fibroblasts had higher FAP-5{beta}1 module scores, and proximity to FAP-high fibroblasts was associated with higher neutrophil OSM and CXCR4 fluorescence. UC fibroblasts increased neutrophil OSM, CXCR4 and myeloperoxidase (MPO) fluorescence and NET-associated elastase activity relative to control fibroblasts, while 5{beta}1-directed treatment attenuated these responses. Both mouse FAP ablation and 5{beta}1 blockade in DSS colitis reduced histologic inflammation and overall neutrophil frequency. Ablation broadly reduced recovered neutrophil representation, whereas blockade increased OSM-positive and PADI4-positive percentages within neutrophils despite lower MPO fluorescence within these subsets. Both interventions were associated with lower epithelial chemokine scores but distinct absorptive and mucus/secretory responses. Conclusions: Fibroblast exposure modifies neutrophil inflammatory phenotype and effector-associated activity, identifying candidate therapeutic pathways in UC. Evaluating these responses alongside neutrophil representation and tissue inflammation could inform pharmacodynamic assessment of stromal-directed therapies.

immunology↗

bioRxiv2025

Identification of protective human monoclonal antibodies using a K18 hACE2 transgenic mouse SARS-CoV-2 challenge model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), uses human angiotensin converting enzyme 2 (hACE2) as its obligate receptor for cell entry. The K18 hACE2 transgenic mouse line, which expresses hACE2 under control of the human keratin 18 (K18) promoter, is used as an animal model for the study of COVID-19 pathogenesis. Here, we evaluate this model in the screening of human monoclonal antibody (hmAb) therapies against SARS-CoV-2. We included 206 hmAbs from the Coronavirus Immunotherapeutic Consortium Database (CoVIC-DB) and identified many that protected against a lethal challenge with the virus. Our data showed that mouse weight change from day 5 onward highly correlated with survival. Many of the protective hmAb candidates we identified also showed strong viral neutralization and spike protein (SP) binding when measured in vitro; however, in many cases, in vitro assays failed to identify protective hmAbs, suggesting that the mouse model may capture characteristics of the hmAbs that other methods cannot. Our findings demonstrate the relevance of including in vivo models for the characterization of therapeutics against SARS-CoV-2, as these improve both accuracy and expediency in the screening process.

immunology↗

bioRxiv2022

Infection with Listeria monocytogenes alters the placental transcriptome and eicosanome

IntroductionPlacental infection and inflammation are risk factors for adverse pregnancy outcomes, including preterm labor. However, the mechanisms underlying these outcomes are poorly understood. MethodsTo study this response, we have employed a pregnant mouse model of placental infection caused by the bacterial pathogen Listeria monocyogenes, which infects the human placenta. Through in vivo bioluminescence imaging, we confirm the presence of placental infection and quantify relative infection levels. Infected and control placentas were collected on embryonic day 18 for RNA sequencing to evaluate gene expression signatures associated with infection by Listeria. ResultsWe identified an enrichment of genes associated with eicosanoid biosynthesis, suggesting an increase in eicosanoid production in infected tissues. Because of the known importance of eicosanoids in inflammation and timing of labor, we quantified eicosanoid levels in infected and uninfected placentas using semi-targeted mass spectrometry. We found a significant increase in the concentrations of several key eicosanoids: leukotriene B4, lipoxin A4, prostaglandin A2, prostaglandin D2, and eicosatrienoic acid. DiscussionOur study provides a likely explanation for dysregulation of the timing of labor following placental infection. Further, our results suggest potential biomarkers of placental pathology and targets for clinical intervention.

developmental biology↗

bioRxiv2018

DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis.

A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large omics or systems biology data sets used by teams of analysts working in collaboration. In such instances it is important to ensure all analysts use the same version of a data set for their analyses. Yet, instantiating relational databases and standard operating procedures can be unwieldy, with high \"startup\" costs and poor adherence to procedures when they deviate substantially from an analysts usual work-flow. Ideally a reproducible research work-flow should fit naturally into an individuals existing work-flow, with minimal disruption. Here, we provide an overview of how we have leveraged popular open source tools, including Bioconductor, Rmarkdown, git version control, R, and specifically Rs package system combined with a new tool DataPackageR, to implement a lightweight reproducible research work-flow for preprocessing large data sets, suitable for sharing among small-to-medium sized teams of computational scientists. Our primary contribution is the DataPackageR tool, which decouples time-consuming data processing from data analysis while leaving a traceable record of how raw data is processed into analysis-ready data sets. The software ensures packaged data objects are properly documented and performs checksum verification of these along with basic package version management, and importantly, leaves a record of data processing code in the form of package vignettes. Our group has implemented this work-flow to manage, analyze and report on pre-clinical immunological trial data from multi-center, multi-assay studies for the past three years.

bioinformatics↗