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Kymographs are graphical representations of spatial position over time, which are often used in biology to visualise the motion of fluorescent particles, molecules, vesicles, or organelles moving along a predictable path. Although in kymographs tracks of individual particles are qualitatively easily distinguished, their automated quantitative analysis is much more challenging. Kymographs often exhibit low signal-to-noise-ratios (SNRs), and available tools that automate their analysis usually require manual supervision. Here we developed KymoButler, a Deep Learning-based software to automatically track dynamic processes in kymographs. We demonstrate that KymoButler performs as well as expert manual data analysis on kymographs with complex particle trajectories from a variety of different biological systems. The software was packaged in a web-based ‘one-click’ application for use by the wider scientific community (http://kymobutler.deepmirror.ai). Our approach significantly speeds up data analysis, avoids unconscious bias, and represents another step towards the widespread adaptation of Machine Learning techniques in biological data analysis., eLife digest Many molecules and structures within cells have to move about to do their job. Studying these movements is important to understand many biological processes, including the development of the brain or the spread of viruses. Kymographs are images that represent the movement of particles in time and space. Unfortunately, tracing the lines that represent movement in kymographs of biological particles is hard to do automatically, so currently this analysis is done by hand. Manually annotating kymographs is tedious, time-consuming and prone to the researcher’s unconscious bias. In an effort to simplify the analysis of kymographs, Jakobs et al. have developed KymoButler, a software tool that can do it automatically. KymoButler uses artificial intelligence to trace the lines in a kymograph and extract the information about particle movement. It speeds up analysis of kymographs by between 50 and 250 times, and comparisons show that it is as reliable as manual analysis. KymoButler is also significantly more effective than any previously existing automatic kymograph analysis programme. To make KymoButler accessible, Jakobs et al. have also created a website with a drag-and-drop facility that allows researchers to easily use the tool. KymoButler has been tested in many areas of biological research, from quantifying the movement of molecules in neurons to analysing the dynamics of the scaffolds that help cells keep their shape. This variety of applications showcases KymoButler’s versatility, and its potential applications. Jakobs et al. are further contributing to the field of machine learning in biology with ‘deepmirror.ai’, an online hub with the goal of accelerating the adoption of artificial intelligence in biology.

BACKGROUND & AIMS: In vitro, several data indicate that cell function can be regulated by the mechanical properties of cells and of the microenvironment. Cells measure these features by developing forces via their actomyosin cytoskeleton, and respond accordingly by transducing forces into biochemical signals that instruct cell behavior. Among these, the transcriptional coactivators YAP/TAZ recently emerged as key factors mediating multiple responses to actomyosin contractility. However, whether mechanical cues regulate adult liver tissue homeostasis, and whether this occurs through YAP/TAZ, remains largely unaddressed. METHODS & RESULTS: Here we show that the F-actin capping protein CAPZ is a critical negative regulator of actomyosin contractility and mechanotransduction. Capzb inactivation alters stress fiber and focal adhesion dynamics leading to enhanced myosin activity, increased cellular traction forces, and increased liver stiffness. In vitro, this rescues YAP from inhibition by a small geometry; in vivo, inactivation of Capzb in the adult mouse liver induces YAP activation in parallel to the Hippo pathway, causing extensive hepatocyte proliferation and leading to striking organ overgrowth. Moreover, Capzb is required for the maintenance of the differentiated hepatocyte state, for metabolic zonation, and for gluconeogenesis. In keeping with changes in tissue mechanics, inhibition of the contractility regulator ROCK, or deletion of the Yap1 mechanotransducer, reverse the phenotypes emerging in Capzb-null livers. CONCLUSIONS: These results indicate a previously unrecognized role for CAPZ in tuning the mechanical properties of cells and tissues, which is required in hepatocytes for the maintenance of the differentiated hepatocyte state and to regulate organ size. More in general, it indicates for the first time a physiological role of mechanotransduction in maintaining tissue homeostasis in mammals. LAY SUMMARY: The mechanical properties of cells and tissues (i.e. whether they are soft or stiff) are thought to be important regulators of cell behavior. A recent advancement in our understanding of these phenomena has been the identification of YAP and TAZ as key factors mediating the biological responses of cells to mechanical signals in vitro. However, whether the mechanical properties of cells and/or the mechanical regulation of YAP/TAZ are relevant for mammalian tissue physiology remains unknown. Here we challenge this issue by genetic inactivation of CAPZ, a protein that regulates the cytoskeleton, i.e. the cells' scaffold by which they sense mechanical cues. We found that inactivation of CAPZ alters cells' and liver tissue's mechanical properties, leading to YAP hyperactivation. In turn, this profoundly alters liver physiology, causing organ overgrowth, defects in liver cell differentiation and metabolism. These results reveal a previously uncharacterized role for mechanical signals for the maintenance of adult liver homeostasis.

Cell division plays an important role in animal tissue morphogenesis, which depends, critically, on the orientation of divisions. In isolated adherent cells, the orientation of mitotic spindles is sensitive to interphase cell shape and the direction of extrinsic mechanical forces. In epithelia, the relative importance of these two factors is challenging to assess. To do this, we used suspended monolayers devoid of ECM, where divisions become oriented following a stretch, allowing the regulation and function of epithelial division orientation in stress relaxation to be characterized. Using this system, we found that divisions align better with the long, interphase cell axis than with the monolayer stress axis. Nevertheless, because the application of stretch induces a global realignment of interphase long axes along the direction of extension, this is sufficient to bias the orientation of divisions in the direction of stretch. Each division redistributes the mother cell mass along the axis of division. Thus, the global bias in division orientation enables cells to act collectively to redistribute mass along the axis of stretch, helping to return the monolayer to its resting state. Further, this behavior could be quantitatively reproduced using a model designed to assess the impact of autonomous changes in mitotic cell mechanics within a stretched monolayer. In summary, the propensity of cells to divide along their long axis preserves epithelial homeostasis by facilitating both stress relaxation and isotropic growth without the need for cells to read or transduce mechanical signals.