Biology subjects

Nanes, B. A.

Publications and source records attributed to Nanes, B. A..

3 recordsLinked to original sources

bioRxiv2026

Perturb-seq resolves physiologic programs and bidirectional regulation of non-canonical NF-κB signaling in epidermal organoids

Regulated keratinocyte differentiation is required for formation of the stratified epidermis and a functional barrier. Understanding genetic drivers of keratinocyte differentiation is crucial for understanding several skin diseases. Perturb-seq is a single-cell CRISPR screen that measures transcriptomic responses to perturbations. To date, Perturb-seq experiments have principally focused on 2-dimensional cell culture models lacking hallmarks of skin development - physiological desmosome formation and barrier function. Here, we leverage Perturb-seq in an epidermal organoid model that recapitulates physiologically relevant differentiation programs. We demonstrate that our perturbations significantly impact diverse differentiation programs and reveal bidirectional function of non-canonical NF-{kappa}B signaling in late keratinocyte differentiation.

genomics↗

bioRxiv2024

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation, and computation. However, 3D cell segmentation, requiring dense annotation of 2D slices still poses significant challenges. Manual labeling of 3D cells to train broadly applicable segmentation models is prohibitive. Even in high- contrast images annotation is ambiguous and time-consuming. Here we develop a theory and toolbox, u- Segment3D, for 2D-to-3D segmentation, compatible with any 2D method generating pixel-based instance cell masks. u-Segment3D translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data, as demonstrated on 11 real-life datasets, >70,000 cells, spanning single cells, cell aggregates, and tissue. Moreover, u-Segment3D is competitive with native 3D segmentation, even exceeding when cells are crowded and have complex morphologies.

bioinformatics↗

bioRxiv2023

Keratin isoform shifts modulate motility signals during wound healing

Keratin intermediate filaments form strong mechanical scaffolds that confer structural stability to epithelial tissues, but the reason this function requires a protein family with 54 isoforms is not understood. During skin wound healing, a shift in keratin isoform expression alters the composition of keratin filaments. How this change modulates cellular function to support epidermal remodeling remains unclear. We report an unexpected effect of keratin isoform variation on kinase signal transduction. Increased expression of wound-associated keratin 6A, but not of steady-state keratin 5, potentiated keratinocyte migration and wound closure without compromising epidermal stability by activating myosin motors. This pathway depended on isoform-specific interaction between intrinsically disordered keratin head domains and non-filamentous vimentin shuttling myosin-activating kinases. These results substantially expand the functional repertoire of intermediate filaments from their canonical role as mechanical scaffolds to include roles as isoform-tuned signaling scaffolds that organize signal transduction cascades in space and time to influence epithelial cell state.

cell biology↗