Biology subjects

Bryant, V. L.

Publications and source records attributed to Bryant, V. L..

5 recordsLinked to original sources

bioRxiv2026

Single-cell CRISPR activation screens in primary B cells discover gene regulatory mechanisms for hundreds of autoimmune risk loci.

Genome-wide association studies (GWAS) have discovered thousands of genetic variants linked to autoimmune disease, and yet the molecular pathways underlying autoimmunity have remained elusive. A key challenge is that >90% of identified GWAS risk loci are in non-coding genomic regions making it difficult to predict their relevance to disease. Here, we have curated fine-mapped non-coding risk variants from over 30 different autoimmune traits including common conditions such as systemic lupus erythematosus (SLE), Crohns disease, and multiple sclerosis, and reveal shared genetic signatures between diverse autoimmune diseases. We subsequently performed a high-throughput single-cell multi-omic CRISPR activation screen targeting 763 autoimmune risk loci in primary human B cells (a highly relevant cell type to autoimmune diseases) and discover 524 cis-regulatory target gene effects for 378 risk loci, with many risk loci regulating multiple gene targets. This Single Cell Analysis of Non-coding Distal Autoimmune Loci (SCANDAL) provides a powerful experimental resource linking non-coding risk loci to many disease-relevant genes, including lowly-expressed cytokines and transcription factors for which perturbation effects can be difficult to quantify with other CRISPR-based strategies. We reveal how increased transcriptional activity at one non-coding risk locus can drive transcription at other risk loci within the same regulatory landscape that may be relevant to understand genetic pleiotropy of autoimmune diseases. Finally, we quantified allele-specific effects on target gene expression with massive parallel reporter assays and prime editing to discover a gain-of-function variant associated with SLE that controls expression of the transcription factor REL/cREL which subsequently binds dozens of risk loci and target genes associated with different autoimmune diseases. Our study provides a valuable resource linking non-coding risk loci with their cis-regulatory target genes and advances our understanding of the shared genetic networks and mechanisms involved in autoimmunity.

genomics↗

bioRxiv2025

Functional immune profiling reveals CD4+ T cell dysregulation associated with celiac disease

T cells integrate signals from antigen and co-stimulatory receptors to calibrate the strength and quality of their responses. This signal integration is influenced by genetic background, which can modulate thresholds for immune tolerance and strength of responses to threat. Celiac disease (CeD) is an autoimmune disorder driven by well-defined genetic risk and characterised by immune dysregulation in response to dietary gluten. However, whether sensitivity or response differences in naive T cell programming contributes to disease susceptibility is not known. To investigate such variation, we developed a sensitive quantitative platform, the momentum assay, which combines standardised, T cell activation with subsequent stimulus withdrawal, enabling measurement of T cell proliferation and survival over time. This assay is integrated with the Cyton2 mathematical model to infer underlying cellular timer programs from population-level dynamics. We applied this method to assess whether naive T cells from individuals with celiac disease (CeD) exhibited altered responses compared to healthy donors (HDs). We found that CD4+ but not CD8+ T cells from CeD patients showed a hypo-proliferative response following stimulation, associated with impaired secretion of the proliferative and pro-survival cytokine IL-2. Moreover, surface expression of early activation marker, CD69 remained elevated for longer on CD4+ T cells from CeD donors after stimulus withdrawal, suggesting prolonged activation and subtle alterations in regulatory feedback mechanisms. These findings reveal previously unrecognised quantitative alterations in naive T cell programming in CeD and underscore the utility of model-based analytical frameworks for detecting subtle functional perturbations in complex immune-mediated diseases.

immunology↗

bioRxiv2024

Divergent cytokine and transcriptional signatures control functional T follicular helper cell heterogeneity

Adaptive immune responses protect against multiple classes of pathogens, including viral, bacterial, fungal, and helminth infections. In all these settings, CD4+ T follicular helper (Tfh) cells tailor high-affinity class-switched B cells responses. How Tfh lineage sovereignty is established while allowing for this context-specific functional heterogeneity is unclear. Here, we identify Tfh transcriptional networks in response to diverse infections. While Bcl-6 is the transcriptional linchpin of the core Tfh signature, this is overlayed with pathogen-specific transcriptional modules that shape Tfh function. Cytokine-transcriptional Tfh programing in mouse and human lymphoid tissue demonstrated that type I interferon and TGF{beta} signaling direct individual Tfh subpopulations to instruct B cell output. Here, we provide a transcriptional map and cell surface resource to interrogate Tfh diversity in humans and mice. This resource can be leveraged to further understand the origins of immune flexibility, perform immune monitoring in infection and antibody-mediated diseases and to develop context-specific vaccines. ONE-SENTENCE SUMMARYDalit, Tan and colleagues provide a resource that functionally and transcriptionally profiles T follicular helper cells (Tfh) during diverse pathogen responses to reveal a blueprint for transcriptional flexibility and new tools to interrogate Tfh heterogeneity in mice and humans.

immunology↗

bioRxiv2023

A Risk-reward Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNASeq experiments, facilitating more accurate and cost-effective studies.

genomics↗

bioRxiv2021

MaveDB v2: a curated community database with over three million variant effects from multiplexed functional assays

A central problem in genomics is understanding the effect of individual DNA variants. Multiplexed Assays of Variant Effect (MAVEs) can help address this challenge by measuring all possible single nucleotide variant effects in a gene or regulatory sequence simultaneously. Here we describe MaveDB v2, which has become the database of record for MAVEs. MaveDB now contains a large fraction of published studies, comprising over two hundred datasets and three million variant effect measurements. We created tools and APIs to streamline data submission and access, transforming MaveDB into a hub for the analysis and dissemination of these impactful datasets.

genomics↗