Stress fibres and the cortex work in tandem

Stress fibres form a fully integrated meshwork with the submembranous contractile actin cortex that generates and propagates traction forces across the entire cell

Tensile Forces and Mechanotransduction at Cell-Cell Junctions

Cell-cell junctions are specializations of the plasma membrane responsible for physically integrating cells into tissues. We are now beginning to appreciate the diverse impacts that mechanical forces exert upon the integrity and function of these junctions. Currently, this is best understood for cadherin-based adherens junctions in epithelia and endothelia, where cell-cell adhesion couples the contractile cytoskeletons of cells together to generate tissue-scale tension. Junctional tension participates in morphogenesis and tissue homeostasis. Changes in tension can also be detected by mechanotransduction pathways that allow cells to communicate with each other. In this review, we discuss progress in characterising the forces present at junctions in physiological conditions; the cellular mechanisms that generate intrinsic tension and detect changes in tension; and, finally, we consider how tissue integrity is maintained in the face of junctional stresses

A question of time: tissue adaptation to mechanical forces.

While much attention has been focused on the force-generating mechanisms responsible for shaping developing embryos, less is known about the ways in which cells in animal tissues respond to mechanical stimuli. Forces will arise within a tissue as the result of processes such as local cell death, growth and division, but they can also be an indirect consequence of morphogenetic movements in neighbouring tissues or be imposed from the outside, for example, by gravity. If not dealt with, the accumulation of stress and the resulting tissue deformation can pose a threat to tissue integrity and structure. Here we follow the time-course of events by which cells and tissues return to their preferred state following a mechanical perturbation. In doing so, we discuss the spectrum of biological and physical mechanisms known to underlie mechanical homeostasis in animal tissues

Stem cell differentiation increases membrane-actin adhesion regulating cell blebability, migration and mechanics

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/K. S. is funded by an EPSRC PhD studentship. S.T. is funded by an EU Marie Curie Intra European Fellowship (GENOMICDIFF)

Biological physics: Liquid crystals in living tissue

Evidence has been found that a biological tissue might behave like a liquid crystal. Even more remarkably, topological defects in this liquid-crystal system seem to influence cell behaviour. A materials physicist and a biologist discuss what the findings mean for researchers in their fields

Automated Deep Lineage Tree Analysis Using a Bayesian Single Cell Tracking Approach

Single-cell methods are beginning to reveal the intrinsic heterogeneity in cell populations, arising from the interplay of deterministic and stochastic processes. However, it remains challenging to quantify single-cell behaviour from time-lapse microscopy data, owing to the difficulty of extracting reliable cell trajectories and lineage information over long time-scales and across several generations. Therefore, we developed a hybrid deep learning and Bayesian cell tracking approach to reconstruct lineage trees from live-cell microscopy data. We implemented a residual U-Net model coupled with a classification CNN to allow accurate instance segmentation of the cell nuclei. To track the cells over time and through cell divisions, we developed a Bayesian cell tracking methodology that uses input features from the images to enable the retrieval of multi-generational lineage information from a corpus of thousands of hours of live-cell imaging data. Using our approach, we extracted 20,000 + fully annotated single-cell trajectories from over 3,500 h of video footage, organised into multi-generational lineage trees spanning up to eight generations and fourth cousin distances. Benchmarking tests, including lineage tree reconstruction assessments, demonstrate that our approach yields high-fidelity results with our data, with minimal requirement for manual curation. To demonstrate the robustness of our minimally supervised cell tracking methodology, we retrieve cell cycle durations and their extended inter- and intra-generational family relationships in 5,000 + fully annotated cell lineages. We observe vanishing cycle duration correlations across ancestral relatives, yet reveal correlated cyclings between cells sharing the same generation in extended lineages. These findings expand the depth and breadth of investigated cell lineage relationships in approximately two orders of magnitude more data than in previous studies of cell cycle heritability, which were reliant on semi-manual lineage data analysis

Fractional viscoelastic models for power-law materials.

Soft materials often exhibit a distinctive power-law viscoelastic response arising from broad distribution of time-scales present in their complex internal structure. A promising tool to accurately describe the rheological behaviour of soft materials is fractional calculus. However, its use in the scientific community remains limited due to the unusual notation and non-trivial properties of fractional operators. This review aims to provide a clear and accessible description of fractional viscoelastic models for a broad audience and to demonstrate the ability of these models to deliver a unified approach for the characterisation of power-law materials. The use of a consistent framework for the analysis of rheological data would help classify the empirical behaviours of soft and biological materials, and better understand their response

Fractional viscoelastic models for power-law materials

Soft materials often exhibit a distinctive power-law viscoelastic response arising from broad distribution of time-scales present in their complex internal structure. A promising tool to accurately describe the rheological behaviour of soft materials is fractional calculus. However, its use in the scientific community remains limited due to the unusual notation and non-trivial properties of fractional operators. This review aims to provide a clear and accessible description of fractional viscoelastic models for a broad audience and to demonstrate the ability of these models to deliver a unified approach for the characterisation of power-law materials. The use of a consistent framework for the analysis of rheological data would help classify the empirical behaviours of soft and biological materials, and better understand their response

Cell-scale biophysical determinants of cell competition in epithelia

How cells with different genetic makeups compete in tissues is an outstanding question in developmental biology and cancer research. Studies in recent years have revealed that cell competition can either be driven by short-range biochemical signalling or by long-range mechanical stresses in the tissue. To date, cell competition has generally been characterised at the population scale, leaving the single-cell-level mechanisms of competition elusive. Here, we use high time-resolution experimental data to construct a multi-scale agent-based model for epithelial cell competition and use it to gain a conceptual understanding of the cellular factors that governs competition in cell populations within tissues. We find that a key determinant of mechanical competition is the difference in homeostatic density between winners and losers, while differences in growth rates and tissue organisation do not affect competition end result. In contrast, the outcome and kinetics of biochemical competition is strongly influenced by local tissue organisation. Indeed, when loser cells are homogenously mixed with winners at the onset of competition, they are eradicated; however, when they are spatially separated, winner and loser cells coexist for long times. These findings suggest distinct biophysical origins for mechanical and biochemical modes of cell competition