Mechanosensitive FHL2 tunes endothelial function.

Endothelial tissues are essential mechanosensors in the vasculature and facilitate adaptation to various blood flow-induced mechanical cues. Defects in endothelial mechanoresponses can perturb tissue remodelling and functions leading to cardiovascular disease progression. In this context, the precise mechanisms of endothelial mechanoresponses contributing to normal and diseased tissue functioning remain elusive. Here, we sought to uncover how flow-mediated transcriptional regulation drives endothelial mechanoresponses in healthy and atherosclerotic-prone tissues. Using bulk RNA sequencing, we identify novel mechanosensitive genes in response to healthy unidirectional flow (UF) and athero-prone disturbed flow (DF). We find that the transcription as well as protein expression of Four-and-a-half LIM protein 2 (FHL2) are enriched in athero-prone DF both in vitro and in vivo. We then demonstrate that the exogenous expression of FHL2 is necessary and sufficient to drive discontinuous adherens junction morphology and increased tissue permeability. This athero-prone phenotype requires the force-sensitive binding of FHL2 to actin. In turn, the force-dependent localisation of FHL2 to stress fibres promotes microtubule dynamics to release the RhoGEF, GEF-H1, and activate the Rho-ROCK pathway. Thus, we unravelled a novel mechanochemical feedback wherein force-dependent FHL2 localisation promotes hypercontractility. This misregulated mechanoresponse creates highly permeable tissues, depicting classic hallmarks of atherosclerosis progression. Overall, we highlight crucial functions for the FHL2 force-sensitivity in tuning multi-scale endothelial mechanoresponses.

Machine learning interpretable models of cell mechanics from protein images.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.

Epithelial tissue confinement inhibits cell growth and leads to volume-reducing divisions.

Cell proliferation is a central process in tissue development, homeostasis, and disease, yet how proliferation is regulated in the tissue context remains poorly understood. Here, we introduce a quantitative framework to elucidate how tissue growth dynamics regulate cell proliferation. Using MDCK epithelial monolayers, we show that a limiting rate of tissue expansion creates confinement that suppresses cell growth; however, this confinement does not directly affect the cell cycle. This leads to uncoupling between rates of cell growth and division in epithelia and, thereby, reduces cell volume. Division becomes arrested at a minimal cell volume, which is consistent across diverse epithelia in vivo. Here, the nucleus approaches the minimum volume capable of packaging the genome. Loss of cyclin D1-dependent cell-volume regulation results in an abnormally high nuclear-to-cytoplasmic volume ratio and DNA damage. Overall, we demonstrate how epithelial proliferation is regulated by the interplay between tissue confinement and cell-volume regulation.

Zyxin is all you need: machine learning adherent cell mechanics.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. No systematic strategy currently exists to infer large-scale physical properties of a cell from its many molecular components. This is a significant obstacle to understanding biophysical processes such as cell adhesion and migration. Here, we develop a data-driven biophysical modeling approach to learn the mechanical behavior of adherent cells. We first train neural networks to predict forces generated by adherent cells from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion protein, such as zyxin, are sufficient to predict forces and generalize to unseen biological regimes. This protein field alone contains enough information to yield accurate predictions even if forces themselves are generated by many interacting proteins. We next develop two approaches - one explicitly constrained by physics, the other more agnostic - that help construct data-driven continuum models of cellular forces using this single focal adhesion field. Both strategies consistently reveal that cellular forces are encoded by two different length scales in adhesion protein distributions. Beyond adherent cell mechanics, our work serves as a case study for how to integrate neural networks in the construction of predictive phenomenological models in cell biology, even when little knowledge of the underlying microscopic mechanisms exist.

Dia1 coordinates differentiation and cell sorting in a stratified epithelium.

Although implicated in adhesion, only a few studies address how the actin assembly factors guide cell positioning in multicellular tissues. The formin, Dia1, localizes to the proliferative basal layer of the epidermis. In organotypic cultures, Dia1 depletion reduced basal cell density and resulted in stratified tissues with disorganized differentiation and proliferative markers. Since crowding induces differentiation in epidermal tissues, we hypothesized that Dia1 is essential to reach densities amenable to differentiation before or during stratification. Consistent with this, forced crowding of Dia1-deficient cells rescued transcriptional abnormalities. We find Dia1 promotes rapid growth of lateral cell-cell adhesions, necessary for the construction of a highly crowded monolayer. In aggregation assays, cells sorted into distinct layers based on Dia1 expression status. These results suggest that as basal cells proliferate, reintegration and packing of Dia1-positive daughter cells is favored, whereas Dia1-negative cells tend to delaminate to a suprabasal compartment. This work elucidates the role of formin expression patterns in constructing distinct cellular domains within stratified epithelia.

Cell cycle-dependent active stress drives epithelia remodeling.

Epithelia have distinct cellular architectures which are established in development, reestablished after wounding, and maintained during tissue homeostasis despite cell turnover and mechanical perturbations. In turn, cell shape also controls tissue function as a regulator of cell differentiation, proliferation, and motility. Here, we investigate cell shape changes in a model epithelial monolayer. After the onset of confluence, cells continue to proliferate and change shape over time, eventually leading to a final architecture characterized by arrested motion and more regular cell shapes. Such monolayer remodeling is robust, with qualitatively similar evolution in cell shape and dynamics observed across disparate perturbations. Here, we quantify differences in monolayer remodeling guided by the active vertex model to identify underlying order parameters controlling epithelial architecture. When monolayers are formed atop an extracellular matrix with varied stiffness, we find the cell density at which motion arrests varies significantly, but the cell shape remains constant, consistent with the onset of tissue rigidity. In contrast, pharmacological perturbations can significantly alter the cell shape at which tissue dynamics are arrested, consistent with varied amounts of active stress within the tissue. Across all experimental conditions, the final cell shape is well correlated to the cell proliferation rate, and cell cycle inhibition immediately arrests cell motility. Finally, we demonstrate cell cycle variation in junctional tension as a source of active stress within the monolayer. Thus, the architecture and mechanics of epithelial tissue can arise from an interplay between cell mechanics and stresses arising from cell cycle dynamics.

A DNA-based voltmeter for organelles.

The role of membrane potential in most intracellular organelles remains unexplored because of the lack of suitable tools. Here, we describe Voltair, a fluorescent DNA nanodevice that reports the absolute membrane potential and can be targeted to organelles in live cells. Voltair consists of a voltage-sensitive fluorophore and a reference fluorophore for ratiometry, and acts as an endocytic tracer. Using Voltair, we could measure the membrane potential of different organelles in situ in live cells. Voltair can potentially guide the rational design of biocompatible electronics and enhance our understanding of how membrane potential regulates organelle biology.

Essential role of the Crk family-dosage in DiGeorge-like anomaly and metabolic homeostasis.

CRK and CRKL (CRK-like) encode adapter proteins with similar biochemical properties. Here, we show that a 50% reduction of the family-combined dosage generates developmental defects, including aspects of DiGeorge/del22q11 syndrome in mice. Like the mouse homologs of two 22q11.21 genes CRKL and TBX1, Crk and Tbx1 also genetically interact, thus suggesting that pathways shared by the three genes participate in organogenesis affected in the syndrome. We also show that Crk and Crkl are required during mesoderm development, and Crk/Crkl deficiency results in small cell size and abnormal mesenchyme behavior in primary embryonic fibroblasts. Our systems-wide analyses reveal impaired glycolysis, associated with low Hif1a protein levels as well as reduced histone H3K27 acetylation in several key glycolysis genes. Furthermore, Crk/Crkl deficiency sensitizes MEFs to 2-deoxy-D-glucose, a competitive inhibitor of glycolysis, to induce cell blebbing. Activated Rapgef1, a Crk/Crkl-downstream effector, rescues several aspects of the cell phenotype, including proliferation, cell size, focal adhesions, and phosphorylation of p70 S6k1 and ribosomal protein S6. Our investigations demonstrate that Crk/Crkl-shared pathways orchestrate metabolic homeostasis and cell behavior through widespread epigenetic controls.

Author Correction: A pH-correctable, DNA-based fluorescent reporter for organellar calcium.

The originally published paper has been updated to include the following new reference, added as ref. 18: Albrecht, T., Zhao, Y., Nguyen, T. H., Campbell, R. E. & Johnson, J. D. Fluorescent biosensors illuminate calcium levels within defined beta-cell endosome subpopulations. Cell Calcium 57, 263-274 (2015). Subsequent references have been renumbered in the reference list and throughout the text. Minor text changes were made in the sentence in which this new reference is first cited: "Previous attempts used endocytic tracers bearing either pH- or Ca2+-sensitive dyes to serially measure population-averaged pH and apparent Ca2+ in different batches of cells, thus scrambling information from individual endosomes13-17" in the original introduction was changed to "Previous attempts used endocytic tracers bearing either pH- or Ca2+-sensitive dyes13-17 or fluorescent-protein-based sensors18 to serially measure population-averaged pH and apparent Ca2+ in different batches of cells, thus scrambling information from individual endosomes." These changes have been made in the HTML and PDF versions of the article.

A pH-correctable, DNA-based fluorescent reporter for organellar calcium.

It is extremely challenging to quantitate lumenal Ca2+ in acidic Ca2+ stores of the cell because all Ca2+ indicators are pH sensitive, and Ca2+ transport is coupled to pH in acidic organelles. We have developed a fluorescent DNA-based reporter, CalipHluor, that is targetable to specific organelles. By ratiometrically reporting lumenal pH and Ca2+ simultaneously, CalipHluor functions as a pH-correctable Ca2+ reporter. By targeting CalipHluor to the endolysosomal pathway, we mapped lumenal Ca2+ changes during endosomal maturation and found a surge in lumenal Ca2+ specifically in lysosomes. Using lysosomal proteomics and genetic analysis, we found that catp-6, a Caenorhabditis elegans homolog of ATP13A2, was responsible for lysosomal Ca2+ accumulation-an example of a lysosome-specific Ca2+ importer in animals. By enabling the facile quantification of compartmentalized Ca2+, CalipHluor can expand the understanding of subcellular Ca2+ importers.

Subcellular Nanorheology Reveals Lysosomal Viscosity as a Reporter for Lysosomal Storage Diseases.

We describe a new method to measure viscosity within subcellular organelles of a living cell using nanorheology. We demonstrate proof of concept by measuring viscosity in lysosomes in multiple cell types and disease models. The lysosome is an organelle responsible for the breakdown of complex biomolecules. When different lysosomal proteins are defective, they are unable to break down specific biological substrates, which get stored within the lysosome, causing about 70 fatal diseases called lysosomal storage disorders (LSDs). Although the buildup of storage material is critical to the pathology of these diseases, methods to monitor cargo accumulation in the lysosome are lacking for most LSDs. Using passive particle tracking nanorheology and fluorescence recovery after photobleaching, we report that viscosity in the lysosome increases significantly during cargo accumulation in several LSD models. In a mammalian cell culture model of Niemann Pick C, lysosomal viscosity directly correlates with the levels of accumulated cholesterol. We also observed increased viscosity in diverse LSD models in Caenorhabditis elegans, revealing that lysosomal viscosity is a powerful reporter with which to monitor substrate accumulation in LSDs for new diagnostics or to assay therapeutic efficacy.