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Controlling intracellular osmolarity is essential to all cellular life. Cells that live in hypo-osmotic environments like freshwater must constantly battle water influx to avoid swelling until they burst. Many eukaryotic cells use contractile vacuoles to collect excess water from the cytosol and pump it out of the cell. Although contractile vacuoles are essential to many species, including important pathogens, the mechanisms that control their dynamics remain unclear. To identify basic principles governing contractile vacuole function, we here investigate the molecular mechanisms of two species with distinct vacuolar morphologies from different eukaryotic lineages—the discobanNaegleria gruberi, and the amoebozoan slime moldDictyostelium discoideum. Using quantitative cell biology we find that, although these species respond differently to osmotic challenges, they both use actin for osmoregulation, as well as vacuolar-type proton pumps for filling contractile vacuoles. We also use analytical modeling to show that cytoplasmic pressure is sufficient to drive water out of contractile vacuoles in these species, similar to findings from the alveolateParamecium multimicronucleatum. Because these three lineages diverged well over a billion years ago, we propose that this represents an ancient eukaryotic mechanism of osmoregulation.

Adhesion between animal cells and the underlying extracellular matrix is challenged during wounding, cell division, and a variety of pathological processes. How cells recover adhesion in the immediate aftermath of detachment from the extracellular matrix remains incompletely understood, due in part to technical limitations. Here, we used acute chemical and mechanical perturbations to examine how epithelial cells respond to partial delamination events. In both cases, we found that cells extended lamellipodia to establish readhesion within seconds of detachment. These lamellipodia were guided by sparse membrane tethers whose tips remained attached to their original points of adhesion, yielding lamellipodia that appear to be qualitatively distinct from those observed during cell migration. In vivo measurements in the context of a zebrafish wound assay showed a similar behavior, in which membrane tethers guided rapidly extending lamellipodia. In the case of mechanical wounding events, cells selectively extended tether-guided lamellipodia in the direction opposite of the pulling force, resulting in the rapid reestablishment of contact with the substrate. We suggest that membrane tether-guided lamellipodial respreading may represent a general mechanism to reestablish tissue integrity in the face of acute disruption.

During actin-based cell migration, the actin cytoskeleton in the lamellipodium both generates and responds to force, which has functional consequences for the ability of the cell to extend protrusions. However, the material properties of the lamellipodial actin network and its response to stress on the timescale of motility are incompletely understood. Here, we describe a dynamic wrinkling phenotype in the lamellipodium of fish keratocytes, in which the actin sheet buckles upward away from the ventral membrane of the cell, forming a periodic pattern of wrinkles perpendicular to the cell's leading edge. Cells maintain an approximately constant wrinkle wavelength over time despite new wrinkle formation and the lateral movement of wrinkles in the cell frame of reference, suggesting that cells have a preferred or characteristic wrinkle wavelength. Generation of wrinkles is dependent upon myosin contractility, and their wavelength scales directly with the density of the actin network and inversely with cell adhesion. These results are consistent with a simple physical model for wrinkling in an elastic sheet under compression and suggest that the lamellipodial cytoskeleton behaves as an elastic material on the timescale of cell migration despite rapid actin turnover.

The motion of chromosomal DNA is essential to many biological processes, including segregation, transcriptional regulation, recombination, and packaging. Physical understanding of these processes would be dramatically enhanced through predictive, quantitative modeling of chromosome dynamics of multiple loci. Using a polymer dynamics framework, we develop a prediction for the correlation in the velocities of two loci on a single chromosome or otherwise connected by chromatin. These predictions reveal that the signature of correlated motion between two loci can be identified by varying the lag time between locus position measurements. In general, this theory predicts that as the lag time interval increases, the dual-loci dynamic behavior transitions from being completely uncorrelated to behaving as an effective single locus. This transition corresponds to the timescale of the stress communication between loci through the intervening segment. This relatively simple framework makes quantitative predictions based on a single timescale fit parameter that can be directly compared to the in vivo motion of fluorescently labeled chromosome loci. Furthermore, this theoretical framework enables the detection of dynamically coupled chromosome regions from the signature of their correlated motion.

A recent burst of dynamic single-cell growth-division data makes it possible to characterize the stochastic dynamics of cell division control in bacteria. Different modeling frameworks were used to infer specific mechanisms from such data, but the links between frameworks are poorly explored, with relevant consequences for how well any particular mechanism can be supported by the data. Here, we describe a simple and generic framework in which two common formalisms can be used interchangeably: (i) a continuous-time division process described by a hazard function and (ii) a discrete-time equation describing cell size across generations (where the unit of time is a cell cycle). In our framework, this second process is a discrete-time Langevin equation with a simple physical analogue. By perturbative expansion around the mean initial size (or inter-division time), we show explicitly how this framework describes a wide range of division control mechanisms, including combinations of time and size control, as well as the constant added size mechanism recently found to capture several aspects of the cell division behavior of different bacteria. As we show by analytical estimates and numerical simulation, the available data are characterized with great precision by the first-order approximation of this expansion. Hence, a single dimensionless parameter defines the strength and the action of the division control. However, this parameter may emerge from several mechanisms, which are distinguished only by higher-order terms in our perturbative expansion. An analytical estimate of the sample size needed to distinguish between second-order effects shows that this is larger than what is available in the current datasets. These results provide a unified framework for future studies and clarify the relevant parameters at play in the control of cell division., 15 pages, 5 figures

c-di-GMP is a bacterial second messenger that is enzymatically synthesized and degraded in response to environmental signals. Cellular processes are affected when c-di-GMP binds to receptors which include proteins that contain the PilZ domain. Although each c-di-GMP synthesis or degradation enzyme metabolizes the same molecule, many of these enzymes can be linked to specific downstream processes. Here we present evidence that c-di-GMP signalling specificity is achieved through differences in affinities of receptor macromolecules. We show that the PilZ domain proteins of Salmonella Typhimurium, YcgR and BcsA, demonstrate a 43-fold difference in their affinity for c-di-GMP. Modulation of the affinities of these proteins altered their activities in a predictable manner in vivo. Inactivation of yhjH, which encodes a predicted c-di-GMP degrading enzyme, increased the fraction of the cellular population that demonstrated c-di-GMP levels high enough to bind to the higher-affinity YcgR protein and inhibit motility, but not high enough to bind to the lower-affinity BcsA protein and stimulate cellulose production. Finally, PilZ domain proteins of Pseudomonas aeruginosa demonstrated a 145-fold difference in binding affinities, suggesting that regulation by binding affinity may be a conserved mechanism that allows organisms with many c-di-GMP binding macromolecules to rapidly integrate multiple environmental signals into one output.

The mean size of exponentially dividing E. coli cells cultured in different nutrient conditions is known to depend on the mean growth rate only. However, the joint fluctuations relating cell size, doubling time and individual growth rate are only starting to be characterized. Recent studies in bacteria (i) revealed the near constancy of the size extension in a single cell cycle (adder mechanism), and (ii) reported a universal trend where the spread in both size and doubling times is a linear function of the population means of these variables. Here, we combine experiments and theory and use scaling concepts to elucidate the constraints posed by the second observation on the division control mechanism and on the joint fluctuations of sizes and doubling times. We found that scaling relations based on the means both collapse size and doubling-time distributions across different conditions, and explain how the shape of their joint fluctuations deviates from the means. Our data on these joint fluctuations highlight the importance of cell individuality: single cells do not follow the dependence observed for the means between size and either growth rate or inverse doubling time. Our calculations show that these results emerge from a broad class of division control mechanisms (including the adder mechanism as a particular case) requiring a certain scaling form of the so-called "division hazard rate function", which defines the probability rate of dividing as a function of measurable parameters. This gives a rationale for the universal body-size distributions observed in microbial ecosystems across many microbial species, presumably dividing with multiple mechanisms. Additionally, our experiments show a crossover between fast and slow growth in the relation between individual-cell growth rate and division time, which can be understood in terms of different regimes of genome replication control., Comment: 39 pages, 7 main figures, 17 supplementary figures

The organizational dynamics of chromosomal DNA are critical to many biological processes including genetic regulation, recombination, condensation, and segregation. The physical understanding of such processes would be greatly improved by predictive, quantitative modeling that can be directly compared to experimental measurements. Previous work has examined or modeled either single locus dynamics or the organization of multiple loci through static or ensemble measurements. New tools in fluorescence microscopy now enable the real-time tracking of several loci simultaneously, requiring additional physical model development to interpret the observed behaviors. Toward this end, we employ a polymer dynamics framework to predict the correlation in the velocities of two loci connected by chromatin. This predictive theory uses a minimal number of fitting parameters and reveals that the signature of correlated motion between loci can be identified by varying the lag time between locus position measurements. Our results predict that as the lag time interval increases, the dual-loci dynamic behavior changes from being uncorrelated to behaving as an effective single locus. This transition is determined by the timescale of the stress communication between loci through the intervening segments. We show that this single transition timescale is the only fit parameter needed to make direct quantitative comparisons to the in vivo motion of fluorescently labeled chromosome loci. We further show that our predictions are qualitatively consistent with recently published experimental measurements of the motion of sets of two loci on a single chromosome in budding yeast during interphase. Furthermore, this theoretical framework enables the detection of dynamically coupled chromosome regions from the signature of their correlated motion.