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Okoniewski, M.

Publications and source records attributed to Okoniewski, M..

3 recordsLinked to original sources

Integrin-identity shapes and mechanotemporally encodes the fibroblast transcriptome

Fibroblast transcriptomic states reflect physiological and pathological tissue contexts, yet the upstream determinants that stabilize these states remain poorly defined. Integrins mediate extracellular matrix (ECM) adhesion and biochemical signaling, but whether they encode mechanical constraints into stable transcriptomic programs is unclear. Using engineered mouse fibroblasts, bulk and single-cell transcriptomics, and controlled micromechanical confinement, we show that integrins can shape the transcriptomic landscape. The bulk transcriptome of fibroblasts expressing V- and {beta}1-class indicates a shared mechanosensitive baseline, except when these integrin classes are expressed individually. We also found integrin-specific gene clusters, including {beta}1-class integrin-dependent enrichment of Areg, Epha7, Lhpp and Igf2r, which regulate development, regeneration and disease, and altered YAP1 targeted gene expression. At single-cell resolution under confinement, {beta}1-class integrins sustain a progenitor-associated program, whereas their loss or V-class enrichment promotes a constitutively activated state linked to injury repair and wound healing. Mechanical confinement and confinement duration further reshapes these states in an integrin-identity-dependent manner. Our findings establish integrin-identity as a determinant of how fibroblasts transduce mechanotemporal inputs from the cell surface to the nucleus.

Cell Biology↗

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

bioinformatics↗

Temporal and sequential transcriptional dynamics define lineage shifts in corticogenesis

The cerebral cortex contains billions of neurons, and their disorganization or misspecification leads to neurodevelopmental disorders. Understanding how the plethora of projection neuron subtypes are generated by cortical neural stem cells (NSCs) is a major challenge. Here, we focused on elucidating the transcriptional landscape of murine embryonic NSCs, basal progenitors (BPs) and newborn neurons (NBNs) throughout cortical development. We uncover dynamic shifts in transcriptional space over time, and heterogeneity within each progenitor population. We identified signature hallmarks of NSC, BP and NBN clusters, and predict active transcriptional nodes and networks that contribute to neural fate specification. We find that the expression of receptors, ligands and downstream pathway components is highly dynamic over time and throughout the lineage implying differential responsiveness to signals. Thus, we provide an expansive compendium of gene expression during cortical development that will be an invaluable resource for studying neural developmental processes and neurodevelopmental disorders.

neuroscience↗