Search bioRxiv⌕ Search

bioRxiv · 10.1101/2020.07.30.223149

Quantifying the dynamics of long-range cell-cell mechanical communication

Abstract

Cells sense, manipulate and respond to their mechanical microenvironment in a plethora of physiological processes, yet the understanding of how cells transmit, receive and interpret environmental cues to communicate with distant cells is severely limited due to lack of tools to quantitatively infer the complex tangle of dynamic cell-cell interactions in complicated environments. We present a computational method to systematically infer and quantify long-range cell-cell force transmission through the extracellular matrix (cell-ECM-cell communication) by correlating ECM remodeling fluctuations in between communicating cells and demonstrating that these fluctuations contain sufficient information to define unique signatures that robustly distinguish between different pairs of communicating cells. We demonstrate our method with finite element simulations and live 3D imaging of fibroblasts and cancer cells embedded in fibrin gels. While previous studies relied on the formation of a visible fibrous band extending between cells to inform on mechanical communication, our method detected mechanical propagation even in cases where visible bands never formed. We revealed that while contractility is required, band formation is not necessary, for cell-ECM-cell communication, and that mechanical signals propagate from one cell to another even upon massive reduction in their contractility. Our method sets the stage to measure the fundamental aspects of intercellular long-range mechanical communication in physiological contexts and may provide a new functional readout for high content 3D image-based screening. The ability to infer cell-ECM-cell communication using standard confocal microscopy holds the promise for wide use and democratizing the method.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nahum, A., Koren, Y., Natan, S., Goren, S., Lesman, A., Zaritsky, A.. 2020-07-30. Quantifying the dynamics of long-range cell-cell mechanical communication. https://doi.org/10.1101/2020.07.30.223149

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The yeast Gcn2 protein kinase mediates P-body formation both through its activity with eIF2α and with non-canonical substrates

P-bodies (PBs) are control hubs for RNA processing and storage that form when translation initiation is inhibited, including during stress. In yeast, Gcn2 is the sole eIF2 alpha kinase that inhibits translation initiation in response to diverse stresses. We show that PB formation depends strongly on Gcn2 during amino acid starvation but only partially during oxidative stress. Constitutively active Gcn2 also induces PB formation in unstressed cells. Surprisingly, PBs are still constitutively formed in a gcn3 mutant strain that is insensitive to eIF2 alpha phosphorylation suggesting that Gcn2 also promotes PB formation independently of eIF2 alpha phosphorylation. Analysis of several putative Gcn2-substrates involved in RNA metabolism identified several proteins required for Gcn2-mediated PB formation. Among these, Smu2, which was not previously implicated in PB formation, localises to PBs and is required for stress-induced coalescence of mRNA granules into PBs. Together, our findings indicate that Gcn2 promotes PB formation via two complementary routes: eIF2 alpha phosphorylation, which generates untranslated mRNAs, and Smu2-dependent maturation of mRNA granules into PBs.

cell biology↗

Quantitative Head-to-Tail Analysis Reveals Heterogeneous Cellular Organization and Connexin Expression in the Porcine Sinoatrial Node

Background: The sinoatrial node (SAN) is an integral component of the cardiac conduction system that dictates heart rhythm. Optical mapping studies have demonstrated functional differences between the superior and inferior leading pacemaking sites in the human SAN; however, the mechanistic connections between structure and function in the SAN through intra-tissue and inter-tissue current source-sink relationships have not been fully resolved. Methods: Porcine SAN longitudinal cryosections along the head-to-tail axis were immunostained and analyzed for regional cell organization and connexin (CX) isoform expression. Results: Quantification of pacemaking cardiomyocyte (PCM) density revealed >9-fold more PCMs within a SAN volume than suggested by a widely cited estimate, assuming comparable PCM densities across species. The SAN head region consisted of large PCM clusters with low aspect ratios, high PCM density, low fibroblast density, and PCMs with the highest HCN4 expression and lowest CX40 and CX43 expression. These characteristics are consistent with an electrically well-insulated, strong current-source that supports pacemaking function. Although the SAN tail also exhibited high local PCM density, its smaller PCM clusters, lower HCN4 expression, and higher CX40, CX43, and CX45 expression rendered it a weaker current source. The SAN mid-region exhibited large PCM clusters aligned in the head-to-tail axis and the highest expression of CX40 and CX45, an expression profile that suggests a fast-conducting intra-tissue pathway that electrically links the leading pacemaking sites at the head and tail. The peripheral SAN at the head and tail also exhibited higher CX expression of all isoforms than the central subregions, an organization consistent with enhanced inter-tissue coupling required for proper pacing function. Conclusions: Our data provide novel insights into the distinct regional micro-organization of the SAN along the head-to-tail axis, which through intra-tissue and inter-tissue coupling, likely modulates the balance of current source-sink relationships that supports robust pacemaking and pacing functions.

cell biology↗

Inference of cell division parameters in bacteria under transient growth conditions

Most quantitative models of bacterial cell division assume steady-state growth, yet natural environments are highly dynamic. Here, we infer division control parameters of E. coli from single-cell size trajectories under nonsteady growth. We describe growth as a continuous process interrupted by stochastic divisions, whose propensity depends on cell size and on the size added since birth. Combining an estimation of time-dependent single-cell growth rates with a maximum-likelihood estimator that we previously validated on synthetic data, we obtain time-resolved estimates of the mean added size at division, its noise, and a strategy parameter that measures how added size depends on birth size. This parameter vanishes for the adder, in which cells add, on average, a fixed size regardless of their size at birth, and is negative for sizer-adder control, in which larger-born cells add less size. We apply this approach to published single-cell data covering steady exponential growth, gradual nutrient depletion, and exit from starvation. We implement a time-resolved model selection based on the Akaike information criterion, concluding that the adder is sufficient during steady growth, whereas size dynamics during entry into and exit from stationary phase are better explained by transient deviations toward sizer-adder control. The framework provides a general method to quantify time-resolved changes in the scale, stochasticity, and strategy of division in nonsteady environments.

cell biology↗