Biology subjects

Amador, D.

Publications and source records attributed to Amador, D..

3 recordsLinked to original sources

bioRxiv2026

Glial cell states bias the regeneration of neuron types across the newt life cycle

Salamanders have outstanding regenerative abilities, which tend to decline in post-metamorphic life stages. Among various tissues, these amphibians can regenerate the brain from ependymoglia cells, an adult neural stem cell population. Ependymoglia cells are heterogeneous; yet, whether ependymoglia cell diversity underlies variation of regenerative capacity across brain regions and life cycle stages remains poorly studied. Here we present a cell type comparison of regeneration in the pallium (dorsal telencephalon) of pre- and post-metamorphic newts. We found that ependymoglia cells exist in a continuum of cell states ranging from active proliferation to quiescence across life cycle stages, with a deep quiescence state featuring expression of mammalian astrocyte genes. Ependymoglia cell state changes are associated with a slower onset of proliferation and neurogenesis in post-metamorphic animals. Comparisons with developmental and adult neurogenesis reveal that pallial ependymoglia cells retain regional restrictions but can override temporal fate restrictions in response to an injury, producing neurons that are normally born only in early development. We thus find that brain regeneration in newts is not a simple amplification of adult neurogenesis, but a distinct process where the initial molecular state of ependymoglia cells biases the relative proportions of regenerated neuron types. Our findings establish post-metamorphic newts as a system to study how astrocyte-like glial cells can activate a neurogenic program in response to brain injury.

developmental biology↗

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↗

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↗