Marta Urbanska

TU Dresden, Dresden and Max Planck Institute for the Science of Light & Max-Planck-Zentrum für Physik und Medizin, Erlangen, Germany

Mechanocytometry Session: Friday, October 1st, 2021: 09:00am-10:30am

De novo identification of universal cell mechanics regulators

Mechanical properties of cells determine their ability to perform many physiological functions, such as migration, cell-fate specification or circulation through vasculature. Identifying molecular factors that govern mechanical phenotype is therefore a subject of immediate relevance. Here we present an approach that enables establishing links between mechanical phenotype changes and the genes responsible for driving them. In particular, we employ an unbiased discriminative network analysis termed PC-corr to associate cell mechanical states, measured by real-time deformability cytometry (RT-DC), with large‑scale transcriptomic datasets across systems ranging from stem cell development to cancer progression, and originating from different murine and human tissues. We identify a conserved module of five genes with putative roles in the regulation of cell stiffness, and demonstrate on four validation datasets in silico that the identified genes can efficiently classify stiff and soft cell states. Finally, we demonstrate experimentally that the top scoring gene, CAV1, changes the mechanical phenotype of cells when silenced or overexpressed. The data-driven approach presented here has the power of de novo identification of genes involved in the regulation of cell mechanics and will extend the toolbox for tuning the mechanical properties of cells on demand to enable biological function or prevent pathologies.