Biology subjects

Mould, K. J.

Publications and source records attributed to Mould, K. J..

4 recordsLinked to original sources

bioRxiv2026

Differential Expression Analysis for Longitudinal Single-Cell RNA-Sequencing Studies Using REBEL

Longitudinal scRNA-seq experiments offer a powerful approach for dissecting temporal gene expression dynamics in individual cell types. However, few methods have been developed specifically to address the unique statistical challenges of repeated measures in scRNA-seq data. Here, we introduce a novel method, REBEL (Repeated measures Empirical Bayes differential Expression analysis using Linear mixed models), for analyzing cell type-specific differential expression in repeated measures scRNA-seq experiments. Using simulation studies, we demonstrate that, relative to conventional repeated measures analysis methods and other scRNA-seq approaches, REBEL controls the false discovery rate and exhibits competitive power across a range of simulation scenarios. We further validate REBEL by analyzing a longitudinal scRNA-seq dataset from patients with B-cell lymphoma receiving chimeric antigen receptor (CAR)-T cell therapy. REBEL is implemented as an R package, available at https://github.com/ewynn610/REBEL.

genomics↗

bioRxiv2025

Spatial Heterogeneity of Macrophages in the Human Lung

RationaleTranscriptionally-defined populations of interstitial macrophages (IMs) and airspace macrophages (AMs) have recently been identified in the human lung. However, the anatomic locations occupied by these populations (i.e. alveoli, pleura, airways, or arteries) have not been fully defined. ObjectivesTo determine the distribution of transcriptionally-defined human macrophages in the major anatomical lung structures and to identify alterations in their distribution and programming induced by cigarette smoking. MethodsSingle-cell RNA sequencing was performed on lung tissue from eight human donors without pulmonary disease (four smokers and four nonsmokers). Microdissection was used to isolate distinct pulmonary anatomical structures from each lung: alveoli, pleura, airways, and arteries. Transcriptional profiles of subpopulations of interstitial macrophages (IMs) and alveolar macrophages (AMs) were analyzed based on their anatomical structure of origin and smoking status. Measurements and Main ResultsFive major IM and five AM subpopulations in human lungs are identified. We demonstrate significant differences in the accumulation patterns of each macrophage subset within anatomical structures, though each subset was detected in each. Immunofluorescent microscopy confirmed anatomical structure-specific accumulation patterns of IMs. ConclusionsIn this study, we highlight key differences in the accumulation of lung macrophage subpopulations in anatomical structures but find programming within macrophage subpopulations is largely conserved, regardless of structure of origin or smoking status. We also detect populations of inflammatory AMs and IMs which accumulate within the airways, but not the alveolar parenchyma, of human cigarette smokers. We introduce a novel three-tiered hierarchy nomenclature to distinguish transcriptionally defined human lung IM subsets as 1{degrees}) Monocyte-like vs Antigen Presenting, 2{degrees}) Quiescent vs Inflammatory, and 3{degrees}) FOLR2high vs FOLR2low. This study is the first to report the fractional accumulation of human lung macrophage subsets by lung anatomical structure. SummaryLung anatomical structure-specific single cell RNA sequencing is introduced to identify and determine the local composition of human lung leukocytes, including 5 populations of human interstitial macrophages.

immunology↗

bioRxiv2025

Simulating Longitudinal Single-cell RNA Sequencing Data with RESCUE

As single-cell RNA-sequencing (scRNA-seq) becomes more widely used in transcriptomic research, complex experimental designs, such as longitudinal studies, become increasingly feasible. Longitudinal scRNA-seq enables the study of transcriptomic changes over time within specific cell types, yet guidance on analytical approaches and resources for study planning, such as power analysis, remains limited. Data simulation is a valuable tool for evaluating analysis method performance and informing study design decisions, including sample size selection. Currently, most scRNA-seq simulation methods simulate cells for a single sample, thus ignoring the between-sample and between-subject variability inherent to longitudinal scRNA-seq data. Here, we introduce RESCUE (REpeated measures Single Cell RNA-seqUEncing data simulation), a novel method that simulates longitudinal scRNA-seq data using a gamma-Poisson frame-work and incorporates additional variability between samples and subjects. We demonstrate our methods ability to reproduce important data properties and demonstrate its application in study planning. RES-CUE is implemented as an R package and is available at https://github.com/ewynn610/RESCUE.

genomics↗

bioRxiv2021

Increased Histone-DNA Complexes and Endothelial-Dependent Thrombin Generation in Severe COVID-19

ObjectiveCoagulopathy in severe COVID-19 is common but poorly understood. The purpose of this study was to determine how SARS-CoV-2 infection impacts histone levels, fibrin structure, and endogenous thrombin potential in the presence and absence of endothelial cells. ApproachWe studied individuals with SARS-CoV-2 infection and acute respiratory distress syndrome at the time of initiation of mechanical ventilation compared to healthy controls. Blood samples were assayed for levels of histone-DNA complexes. Confocal microscopy was used to evaluate fibrin structure in clots formed from recalcified plasma samples using fluorescently-labeled fibrinogen. Endogenous thrombin potential was measured by calibrated automated thrombin assays in the presence of tissue factor and phospholipid (PCPS) or cultured human endothelial cells. ResultsCirculating nucleosomes were elevated in the plasma of COVID-19 patients relative to healthy controls (n=6, each group). COVID-19 patient plasma thrombin generation was also altered. Despite having an increased endogenous thrombin potential, patient plasma samples exhibited prolonged lag times and times to peak thrombin in the presence of added tissue factor and PCPS. Strikingly different results were observed when endothelial cells were used in place of tissue factor and PCPS. Control plasma samples did not generate measurable thrombin (lag time >60 min); in contrast, plasma samples from COVID-19+ patients generated thrombin (mean lag time [~]20 min). Consistent with the observed alterations in thrombin generation, clots from COVID-19 subjects exhibited a denser fibrin network, thinner fibers and lower fibrin resolvability. ConclusionsElevated histones, aberrant fibrin formation, and increased endothelial-dependent thrombin generation in COVID-19 may contribute to coagulopathy. HIGHLIGHTSO_LIHistone-DNA complexes are significantly elevated in the plasma of patients with severe SARS-CoV-2 infection. C_LIO_LIMeasures of thrombin generation by calibrated automated thrombography and fibrin clots formed in situ are altered in severe COVID-19. C_LIO_LIPlasma from COVID-19 patients promotes thrombin generation on cultured endothelial cells in the absence of added tissue factor or phospholipids. C_LIO_LIThe additive effects of histones on thrombin generation and endothelial cell function may play a major role in the thrombotic complications observed in severe SARS-CoV-2 infection. C_LI

biochemistry↗