Stitzinger, S. H. | Search bioRxiv

bioRxiv2026

The Interaction with Nanotopographical Environment regulates nuclear mechanoresponse in mESCs via Histone Demethylase KDM3A

Cell identity is traditionally viewed as a product of biochemical signalling, yet cells are exposed to defined physical landscapes, whose role in fate control remains unclear. In particular, how pluripotent stem cells integrate nanoscale extracellular cues into gene regulatory programs remains poorly understood. Here, we show that biomimetic substrate nanotopography acts as a potent regulator of naive pluripotency in mouse embryonic stem cells (mESCs). Using supersonic cluster beam deposition, we generate substrates with defined nanotopography that recapitulate native features of extracellular matrix. We demonstrate that nanotopography induces a mechanically relaxed cell state characterised by reduced adhesion, cellular and nuclear softening, and altered nuclear architecture. These mechanical changes are coupled with chromatin remodelling, including reduced H3K27me3 and H3K9me2, redistribution of H3K9me3, and increased H3K4me3. Transcriptomic analyses reveal suppression of adhesion- and cytoskeleton-associated programs together with the activation of a naive pluripotency transcriptional signature, including upregulation of Nanog. Mechanistically, we identify the H3K9 demethylase KDM3A as a mechanosensitive epigenetic regulator required for nanotopography-induced Nanog expression. Together, our findings uncover a novel mechanotransductive pathway directly linking extracellular nanotopography to chromatin state and pluripotency control.

molecular biology↗

bioRxiv2021

Cooperativity boosts affinity and specificity of proteins with multiple RNA-binding domains

Numerous cellular processes rely on the binding of proteins with high affinity to specific sets of RNAs. Yet most RNA binding domains display low specificity and affinity, to the extent that for most RNA-binding domains, the enrichment of the best binding motif measured by high-throughput RNA SELEX or RNA bind-n-seq is usually below 10-fold, dramatically lower than that of DNA-binding domains. Here, we develop a thermodynamic model to predict the binding affinity for proteins with any number of RNA-binding domains given the affinities of their isolated domains. For the four proteins in which affinities for individual domains have been measured the model predictions are in good agreement with experimental values. The model gives insight into how proteins with multiple RNA-binding domains can reach affinities and specificities orders of magnitude higher than their individual domains. Our results contribute towards resolving the conundrum of missing specificity and affinity of RNA binding proteins and underscore the need for bioinformatic methods that can learn models for multi-domain RNA binding proteins from high-throughput in-vitro and in-vivo experiments.

molecular biology↗