Biology subjects

Woappi, Y.

Publications and source records attributed to Woappi, Y..

3 recordsLinked to original sources

bioRxiv2026

4D multimodal wound healing atlas reveals organ-level controls of repair phase transitions

Deep skin wounds demand tightly coordinated communication across diverse tissue systems, yet knowledge of the molecular logic governing organ-scale injury response remains incomplete. Existing wound atlases profile fragments of this process, capturing limited tissue groups and healing phases, obscuring how whole organs synchronize repair. Here, we present the Organ-Scale Wound Healing Atlas (OWHA), a 4D multimodal omnibus that integrates snRNA-seq, scRNA-seq, CITE-seq and high-definition spatial transcriptomics to reconstruct the complete spatial and temporal choreography of mammalian wound healing at single cell resolution. OWHA profiles over 725,000 murine single-cell and spatial transcriptomes encompassing the entire wound healing process from early to late healing phases across the vast skin microanatomical tissue niches. This omnibus overcomes long-standing technical limitations, enabling robust resolution of adipocytes, Schwann cells, fragile epithelial intermediates, and over 100 precisely annotated cell states, including populations missed in prior wound databases. This revealed that wound repair proceeds through sharp transcriptional and cellular inflection points driven by Central Orchestrator populations that coordinate healing via synchronized transcriptional activation and direct cross-tissue signaling. Key among these is a Sox6+ Tspear+ Il20ra+ keratinocyte subpopulation (Basal IV), detectable only through snRNA-seq but entirely missed by conventional wound atlasing. After injury, Basal IV cells deviate from canonical differentiation programs and adopt a neurovasculogenic signaling state during the proliferation phase, forming a transient spatially privileged regulatory hub at the wound edge. This epithelial-anchored niche spatially aligns Basal IV keratinocytes with proliferative endothelial cells, Pericytes, and Repair Schwann Cells, synchronizing re-epithelialization, angiogenesis, and neurite guidance. Mechanistically, this is orchestrated by a conserved Sema3C-Nrp1/Nrp2 axis that coordinates epithelial-vascular-neuronal crosstalk at the wound site. Cross-species integration confirms that the Basal IV/SEMA3C axis is conserved in human skin, yet undetected by conventional scRNA-seq human atlases due to dissociation-induced artifacts - underscoring the critical need for multimodal atlasing to accurately capture organ-scale physiology. Notably, the Basal IV/SEMA3C circuitry is selectively disrupted in human diabetic wounds, but topical Sema3C treatments restores peri-wound angiogenic sprouting and accelerates re-epithelialization of diabetic ulcers in vivo. OWHA establishes the first 4D, organ-scale molecular blueprint of mammalian wound healing, creating a foundational platform for decoding systems-level principles of repair and regeneration for tissue wounds.

cell biology↗

bioRxiv2025

RESTRICT-seq enables time-gated CRISPR screens and uncovers novel epigenetic dependencies of SCC resistance

Cancer cell evasion of therapy is a highly adaptive process that undermines the efficacy of many treatment strategies. A significant milestone in the study of these mechanisms has been the advent of pooled CRISPR knockout screens, which enable high-throughput, genome-wide interrogations of tumor dependencies and synthetic lethal interactions, advancing our understanding of how cancer cells adapt to and evade therapies. However, the utility of this approach diminishes when applied to dynamic biological contexts, where processes are transient and sensitive to routine cell culture manipulations that introduce noise and limit meaningful discoveries. To overcome these limitations, we present RESTRICT-seq, a next-generation pooled screening methodology that restricts Cas9 nuclear activation in controlled, repeated cycles. By confining Cas9 catalytic activity to strict temporal windows, RESTRICT-seq mitigates undesired fitness penalties that accumulate throughout CRISPR screens. When benchmarked against conventional pooled screens and standard inducible CRISPR protocols, RESTRICT-seq revealed significantly fewer divergent cell clones and increased signal-to-noise ratio, overcoming a key limitation of traditional methods. Leveraging RESTRICT-seq, we conducted a comprehensive functional survey of the druggable mammalian epigenome, uncovering several elusive epigenetic drivers of treatment resistance in cutaneous squamous cell carcinoma (cSCC). This revealed PAK1 as a previously unrecognized mediator of cSCC resistance in human and mouse SCC, offering new insights into a prognostic marker and therapeutic target of high clinical significance. Our findings establish RESTRICT-seq as a powerful tool for extending the applicability of pooled CRISPR screens to dynamic and previously intractable biological contexts.

cancer biology↗

bioRxiv2024

Patches: A Representation Learning framework for Decoding Shared and Condition-Specific Transcriptional Programs in Wound Healing

Single-cell genomics enables the study of cell states and cell state transitions across biological conditions like aging, drug treatment, or injury. However, existing computational methods often struggle to simultaneously disentangle shared and condition-specific transcriptional patterns, particularly in experimental designs with missing data, unmatched cell populations, or complex attribute combinations. To address these challenges, Patches identifies universal transcriptomic features alongside condition-dependent variations in scRNA-seq data. Using conditional subspace learning, Patches enables robust integration, cross-condition prediction, and biologically interpretable representations of gene expression. Unlike prior methods, Patches excels in experimental designs with multiple attributes, such as age, treatment, and temporal dynamics, distinguishing general cellular mechanisms from condition-dependent changes. We applied Patches to both simulated data and real transcriptomic datasets from skin injury models, focusing on the effects of aging and drug treatment. Patches revealed shared wound healing patterns and condition-specific changes in cell behavior and extracellular matrix remodeling. These insights deepen our understanding of tissue repair and can identify potential biomarkers for therapeutic interventions, particularly in contexts where the experimental design is complicated by missing or difficult-to-collect data.

genomics↗