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In eukaryotes, the cell volume is observed to be strongly correlated with the nuclear volume. The slope of this correlation depends on the cell type, growth condition, and the physical environment of the cell. We develop a computational model of cell growth and proteome increase, incorporating the kinetics of amino acid import, protein/ribosome synthesis and degradation, and active transport of proteins between the cytoplasm and the nucleoplasm. We also include a simple model of ribosome biogenesis and assembly. Results show that the cell volume is tightly correlated with the nuclear volume, and the cytoplasm-nucleoplasm transport rates strongly influence the cell growth rate as well as the cell/nucleus volume ratio (C/N ratio). Ribosome assembly and the ratio of ribosomal proteins to mature ribosomes also influence the cell volume and the cell growth rate. We find that in order to regulate the cell growth rate and the cell/nucleus volume ratio, the cell must optimally control groups of kinetic and transport parameters together, which could explain the quantitative roles of canonical growth pathways. Finally, although not explicitly demonstrated in this work, we point out that it is possible to construct a detailed proteome distribution using our model and RNAseq data, provided that a quantitative cell division mechanism is known.

Cell migration through 3D extracellular matrices is critical to the normal development of tissues and organs and in disease processes, yet adequate analytical tools to characterize 3D migration are lacking. Here, we quantified the migration patterns of individual fibrosarcoma cells on 2D substrates and in 3D collagen matrices and found that 3D migration does not follow a random walk. Both 2D and 3D migration features a non-Gaussian, exponential mean cell velocity distribution, which we show is primarily a result of cell-to-cell variations. Unlike in the 2D case, 3D cell migration is anisotropic: velocity profiles display different speed and self-correlation processes in different directions, rendering the classical persistent random walk (PRW) model of cell migration inadequate. By incorporating cell heterogeneity and local anisotropy to the PRW model, we predict 3D cell motility over a wide range of matrix densities, which identifies density-independent emerging migratory properties. This analysis also reveals the unexpected robust relation between cell speed and persistence of migration over a wide range of matrix densities.

Active fluid circulation and solute transport are essential functions of living organisms, enabling the efficient delivery of oxygen and nutrients to various physiological compartments. Since fluid circulation occurs in a network, the systemic flux and pressure are not simple outcomes of individual components. Rather, they are emergent properties of network elements and network topology. Moreover, consistent pressure and osmolarity gradients are maintained across compartments such as the kidney, interstitium, and blood vessels. The mechanisms by which these gradients and network properties are established and maintained are unanswered questions in systems physiology. Previous studies have shown that epithelial cells are fluid pumps and can actively generate pressure and osmolarity gradients. The polarization and activity of solute transporters in epithelial cells, which drive fluid flux, are influenced by pressure and osmolarity gradients. Therefore, there is an unexplored coupling between pressure and osmolarity in the circulatory network. In this work, we develop a mathematical framework that integrates the influence of pressure and osmolarity on solute transport. We use this model to explore both cellular fluid transport and systemic circulation. Using a simple network featuring the kidney-vascular interface, we show that our model naturally generates pressure and osmolarity gradients across the kidney, vessels and renal interstitium. While the current model uses this interface as an example, the findings can be generalized to other physiological compartments. This model demonstrates how systemic transport properties can depend on cellular properties and, conversely, how cell states are influenced by systemic properties. When epithelial and endothelial pumps are considered together, we predict how pressures at various points in the network depend on the overall osmolarity of the system. The model can be improved by including physiological geometries and expanding solute species, and highlights the interplay of fluid properties with cell function in living organisms.

Cells respond to physical stimuli, such as stiffness 1 , fluid shear stress 2 and hydraulic pressure 3 , 4 . Extracellular fluid viscosity is a key physical cue that varies under physiological and pathological conditions, such as cancer 5 . However, its influence on cancer biology and the mechanism by which cells sense and respond to changes in viscosity are unknown. Here we demonstrate that elevated viscosity counterintuitively increases the motility of various cell types on two-dimensional surfaces and in confinement, and increases cell dissemination from three-dimensional tumour spheroids. Increased mechanical loading imposed by elevated viscosity induces an actin-related protein 2/3 (ARP2/3)-complex-dependent dense actin network, which enhances Na + /H + exchanger 1 (NHE1) polarization through its actin-binding partner ezrin. NHE1 promotes cell swelling and increased membrane tension, which, in turn, activates transient receptor potential cation vanilloid 4 (TRPV4) and mediates calcium influx, leading to increased RHOA-dependent cell contractility. The coordinated action of actin remodelling/dynamics, NHE1-mediated swelling and RHOA-based contractility facilitates enhanced motility at elevated viscosities. Breast cancer cells pre-exposed to elevated viscosity acquire TRPV4-dependent mechanical memory through transcriptional control of the Hippo pathway, leading to increased migration in zebrafish, extravasation in chick embryos and lung colonization in mice. Cumulatively, extracellular viscosity is a physical cue that regulates both short- and long-term cellular processes with pathophysiological relevance to cancer biology. Elevated viscosity counterintuitively increases the motility of various cell types in vitro and imprints mechanical memory to tumour cells, which enables them to disseminate more efficiently in vivo.

Tissue cells sense and respond to the stiffness of the surface on which they adhere. Precisely how cells sense surface stiffness remains an open question, though various biochemical pathways are critical for a proper stiffness response. Here, based on a simple mechanochemical model of biological friction, we propose a model for cell mechanosensation as opposed to previous more biochemically based models. Our model of adhesion complexes predicts that these cell-surface interactions provide a viscous drag that increases with the elastic modulus of the surface. The force-velocity relation of myosin II implies that myosin generates greater force when the adhesion complexes slide slowly. Then, using a simple cytoskeleton model, we show that an external force applied to the cytoskeleton causes actin filaments to aggregate and orient parallel to the direction of force application. The greater the external force, the faster this aggregation occurs. As the steady-state probability of forming these bundles reflects a balance between the time scale of bundle formation and destruction (because of actin turnover), more bundles are formed when the cytoskeleton time-scale is small (i.e., on stiff surfaces), in agreement with experiment. As these large bundles of actin, called stress fibers, appear preferentially on stiff surfaces, our mechanical model provides a mechanism for stress fiber formation and stiffness sensing in cells adhered to a compliant surface.

In this work, we explore fundamental energy requirements during mammalian cell movement. Starting with the conservation of mass and momentum for the cell cytosol and the actin-network phase, we develop useful identities that compute dissipated energies during extensions of the cell boundary. We analyze 2 complementary mechanisms of cell movement: actin-driven and water-driven. The former mechanism occurs on 2-dimensional cell-culture substrate without appreciable external hydraulic resistance, while the latter mechanism is prominent in confined channels where external hydraulic resistance is high. By considering various forms of energy input and dissipation, we find that the water-driven cell-migration mechanism is inefficient and requires more energy. However, in environments with sufficiently high hydraulic resistance, the efficiency of actin-polymerization-driven cell migration decreases considerably, and the water-based mechanism becomes more efficient. Hence, the most efficient way for cells to move depends on the physical environment. This work can be extended to higher dimensions and has implication for understanding energetics of morphogenesis in early embryonic development and cancer-cell metastasis and provides a physical basis for understanding changing metabolic requirements for cell movement in different conditions.

Convolutional neural networks (ConvNets) have proven to be successful in both the classification and semantic segmentation of cell images. Here we establish a method for cell type classification utilizing images taken with a benchtop microscope directly from cell culture flasks, eliminating the need for a dedicated imaging platform. Significant flask-to-flask morphological heterogeneity was discovered and overcome to support network generalization to novel data. Cell density was found to be a prominent source of heterogeneity even when cells are not in contact. For the same cell types, expert classification was poor for single-cell images and better for multi-cell images, suggesting experts rely on the identification of characteristic phenotypes within subsets of each population. We also introduce Self-Label Clustering (SLC), an unsupervised clustering method relying on feature extraction from the hidden layers of a ConvNet, capable of cellular morphological phenotyping. This clustering approach is able to identify distinct morphological phenotypes within a cell type, some of which are observed to be cell density dependent. Finally, our cell classification algorithm was able to accurately identify cells in mixed populations, showing that ConvNet cell type classification can be a label-free alternative to traditional cell sorting and identification.

Proteins that allow water to move in and out of cells help shape the development of new blood vessels.Proteins that allow water to move in and out of cells help shape the development of new blood vessels.

An influx of water molecules can help immune cells called neutrophils to move to where they are needed in the body.An influx of water molecules can help immune cells called neutrophils to move to where they are needed in the body.

Cell migration regulates diverse (patho)physiological processes, including cancer metastasis. According to the Osmotic Engine Model, polarization of NHE1 at the leading edge of confined cells facilitates water uptake, cell protrusion and motility. The physiological relevance of the Osmotic Engine Model and the identity of molecules mediating cell rear shrinkage remain elusive. Here, we demonstrate that NHE1 and SWELL1 preferentially polarize at the cell leading and trailing edges, respectively, mediate cell volume regulation, cell dissemination from spheroids and confined migration. SWELL1 polarization confers migration direction and efficiency, as predicted mathematically and determined experimentally via optogenetic spatiotemporal regulation. Optogenetic RhoA activation at the cell front triggers SWELL1 re-distribution and migration direction reversal in SWELL1-expressing, but not SWELL1-knockdown, cells. Efficient cell reversal also requires Cdc42, which controls NHE1 repolarization. Dual NHE1/SWELL1 knockdown inhibits breast cancer cell extravasation and metastasis in vivo, thereby illustrating the physiological significance of the Osmotic Engine Model. Cell migration regulates diverse (patho)physiological processes, including cancer metastasis. Here the authors show that the chloride ion channel SWELL1 and the ion exchanger NHE1 are preferentially enriched at the trailing and leading edges, respectively, of migrating cells and regulate cell volume to propel confined cells, favouring breast cancer cell extravasation and metastasis.