Biology subjects

Dark, J.

Publications and source records attributed to Dark, J..

4 recordsLinked to original sources

bioRxiv2026

Determinants of cysteine coverage by chemoproteomics

Covalent chemoproteomics has become a powerful route to expanding the druggable proteome, enabling proteome-wide screening of compounds that covalently modify nucleophilic residues, most commonly cysteine. Yet typical experiments detect only 5-18% of the ~250,000 cysteines encoded by the human proteome, and the determinants of this limited coverage remain poorlydefined. Here we combine cysteine featurisation, explainable machine learning (ML) and robust statistical filtering to establish what governs cysteine detectability in iodoacetamide- desthiobiotin (IA-DTB) chemoproteomics. Using a scalable feature-generation pipeline, we computed physicochemical and structural properties for cysteines and the corresponding tryptic peptides and trained models that predict detectability with high accuracy. Shapley analysis identifies protein abundance and intrinsic peptide properties governing LC-MS behaviour as the dominant determinants, whereas cysteine structural descriptors contribute comparatively little, indicating that detection is constrained downstream of probe reactivity. We further introduce a distance-based statistical filter that improves reproducibility across replicates, and show that cell line selection, subcellular fractionation and alternative electrophiles together expand coverage by >30%. More broadly, this work moves optimisation of chemoproteomics workflows from empirical trial-and-error towards rational, data-driven design.

bioinformatics↗

bioRxiv2026

Multimodal Hypersampling of the adult human heart resolves tissue-specific cell states and disease-associated variants

Cardiovascular diseases often arise in anatomically specialised regions of the heart that remain poorly represented in existing single-cell and spatial atlas references. Here we profiled 28 regions of the adult human heart from 36 donors, combining paired single-nucleus RNA and chromatin accessibility assays with spatial transcriptomics. The resulting atlas integrates 1,059,175 expression profiles and 452,614 chromatin accessibility profiles, and defines spatial niches across the heart. In cardiac valves, we identify a valve fibroblast-macrophage niche that is polarised to the non-fibrosa surface and expands with age. Aortic stenosis genetic risk was enriched in inflammatory regulatory programmes of the Valve Fibroblast Immune cell state. In pulmonary veins, we define PITX2+ Myocardial Sleeve Cells, a region-restricted cardiomyocyte population in which a fine-mapped 4q25 atrial fibrillation variant intersects a cell type-specific open chromatin region. In coronary arteries, we resolve a RUNX1-marked synthetic smooth muscle layer in the subintima that provides a molecular identity for diffuse intimal thickening, a constitutive feature of the healthy vessel wall and a substrate for atherosclerosis, and show by perturbation in human smooth muscle cells that RUNX1 promotes cell-cycle entry while restraining inflammatory cytokine gene expression. Finally, allele-specific accessibility together with deep learning models fine-tuned to predict regulatory activity from DNA sequence identify cell type-specific regulatory effects at GWAS loci for atrial fibrillation, coronary artery disease and calcific aortic valve stenosis, including a variant whose Valve Fibroblast-specific effect on the polyamine transporter ATP13A3 is opposite in direction to the effect seen in bulk-tissue eQTL references that lack valve cells. Together with these cardiac sequence models and CardioSleuth, an AI-powered exploration engine for cardiac regulatory effects, this atlas links cardiac anatomy, gene regulation and disease genetics at single-cell resolution. By placing genetic risk in its precise cellular and anatomical context, it provides a foundation for mechanistic disease understanding, cell-state-specific therapeutic target nomination, and improved interpretation of inherited cardiovascular risk to inform future therapy and management.

Cell Biology↗

bioRxiv2023

A cell atlas of the human outflow tract of the heart and its adult derivatives

The outflow tract (OFT) of the heart carries blood away from the heart into the great arteries. During embryogenesis, the OFT divides to form the aorta and pulmonary trunk, creating the double circulation present in mammals. Defects in this area account for one-third of all congenital heart defect cases. Here, we present comprehensive transcriptomic data on the developing OFT at two distinct timepoints (embryonic and fetal) and its adult derivatives, the aortic valves, and use spatial transcriptomics to define the distribution of cell populations. We uncover that distinctive embryonic signatures persist in adult cells and can be used as labels to retrospectively attribute relationships between cells separated by a large time scale. Single-cell regulatory network inference identifies GATA6, a transcription factor linked to common arterial trunk and bicuspid aortic valve, as a key regulator of valve precursor cells. Its downstream network reveals candidate drivers of human cardiac defects and illuminates the molecular mechanisms of both normal and pathological valve development. Our findings define the cellular and molecular signatures of the human OFT and its distinct cell lineages, which is critical for understanding congenital heart defects and developing cardiac tissue for regenerative medicine.

developmental biology↗

bioRxiv2023

Spatially resolved multiomics of human cardiac niches

A cells function is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here, we combine single-cell and spatial transcriptomic data to discover cellular niches within eight regions of the human heart. We map cells to micro-anatomic locations and integrate knowledge-based and unsupervised structural annotations. For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors, and cell interactions using a custom CellPhoneDB.org module. We show that the sinoatrial node is compartmentalised, with a core of pacemaker cells, fibroblasts and glial cells supporting paracrine glutamatergic signalling. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions, providing unexpected mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches which may contribute to infection defence. We define a ventricular myocardial-stress niche enriched for activated fibroblasts and stressed cardiomyocytes, cell states that are expanded in cardiomyopathies. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be deployed to other tissues and organs.

genomics↗