Cellular senescence is a prominent accomplice of aging. The expression of gene p16ink4a has been established as a biomarker of cellular senescence in humans and animal models. However, it has not been extensively studied in clinical settings in the context of natural aging and the development of age-related diseases. Here, we report the results of a natural aging study that provided an assessment of cellular senescence and a battery of measures of clinical status, quality of life (QOL), and physical performance in 250 community-dwelling participants across age continuum. This report focused on analyzing predictive relationships between cellular senescence and different clinical assessments. Our results suggest that clinical labs and QOL assessments produce distinct groupings of participants, yet both have strong predictive associations with p16ink4a. Furthermore, the highest accuracy of p16ink4a prediction requires subsets of measurements representing diverse aspects of each assessment, pointing towards a system-level role of p16ink4a. Our analysis also led to an assessment-based composite indexes that strongly correlate with p16ink4a expression. Our study underscores p16ink4a's association with both earlier signs of physiological decline (based on clinical labs) and the later onset of health issues limiting the quality of life.

Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction–diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.

Rho-GTPases are central regulators within a complex signaling network that controls cytoskeletal organization and cell movement. The network includes multiple GTPases, such as the most studied Rac1, Cdc42, and RhoA, along with their numerous effectors that provide mutual regulation through feedback loops. Here we investigate the temporal and spatial relationship between Rac1 and Cdc42 during membrane ruffling, using a simulation model that couples GTPase signaling with cell morphodynamics and captures the GTPase behavior observed with FRET-based biosensors. We show that membrane velocity is regulated by the kinetic rate of GTPase activation rather than the concentration of active GTPase. Our model captures both uniform and polarized ruffling. We also show that cell-type specific time delays between Rac1 and Cdc42 activation can be reproduced with a single signaling motif, in which the delay is controlled by feedback from Cdc42 to Rac1. The resolution of our simulation output matches those of time-lapsed recordings of cell dynamics and GTPase activity. Our data-driven modeling approach allows us to validate simulation results with quantitative precision using the same pipeline for the analysis of simulated and experimental data.

In this work, we developed a computational model of Rho-GTPase activity and applied it to investigate actin wave dynamics in cell cortex. Here we focused on cell-level dynamics of cortical actin in oocytes of two organisms: Patiria miniata (starfish) and Xenopus laevis (frog). The model showed a defining role of the early low-activity phase of pattern formation in the development of long-term, high-activity wave dynamics. To our best knowledge, such low-activity dynamics was not described before, however different paths of its destabilization explain GTPase activity at the later experimentally observable phase.

The septin cytoskeleton has been demonstrated to interact with other cytoskeletal components to regulate various cellular processes, including cell migration. However, the mechanisms of how septin regulates cell migration are not fully understood. In this study, we use the highly migratory neural crest cells of frog embryos to examine the role of septin filaments in cell migration. We found that septin filaments are required for the proper migration of neural crest cells by controlling both the speed and the direction of cell migration. We further determined that septin filaments regulate these features of cell migration by interacting with actin stress fibers. In neural crest cells, septin filaments co-align with actin stress fibers, and the loss of septin filaments leads to impaired stability and contractility of actin stress fibers. In addition, we showed that a partial loss of septin filaments leads to drastic changes in the orientations of newly formed actin stress fibers, suggesting that septin filaments help maintain the persistent orientation of actin stress fibers during directed cell migration. Lastly, our study revealed that these activities of septin filaments depend on Cdc42ep1, which colocalizes with septin filaments in the center of neural crest cells. Cdc42ep1 interacts with septin filaments in a reciprocal manner, with septin filaments recruiting Cdc42ep1 to the cell center and Cdc42ep1 supporting the formation of septin filaments.

The Rho family GTPases are molecular switches that regulate cytoskeletal dynamics and cell movement through a complex spatiotemporal organization of their activity. In Patiria miniata (starfish) oocytes under in vitro experimental conditions (with overexpressed Ect2, induced expression of Δ90 cyclin B, and roscovitine treatment), such activity generates multiple co-existing regions of coherent propagation of actin waves. Here we use computational modeling to investigate the development and properties of such wave domains. The model reveals that the formation of wave domains requires a balance between the activation and inhibition in the Rho signaling motif. Intriguingly, the development of the wave domains is preceded by a stage of low-activity quasi-static patterns, which may not be readily observed in experiments. Spatiotemporal patterns of this stage and the different paths of their destabilization define the behavior of the system in the later high-activity (observable) stage. Accounting for a strong intrinsic noise allowed us to achieve good quantitative agreement between simulated dynamics in different parameter regimes of the model and different wave dynamics in Patiria miniata and wild type Xenopus laevis (frog) data. For quantitative comparison of simulated and experimental results, we developed an automated method of wave domain detection, which revealed a sharp reversal in the process of pattern formation in starfish oocytes. Overall, our findings provide an insight into spatiotemporal regulation of complex and diverse but still computationally reproducible cell-level actin dynamics.

Cells polarize their growth or movement in many different physiological contexts. A key driver of polarity is the Rho GTPase Cdc42, which when activated becomes clustered or concentrated at polar sites. Multiple models for polarity establishment have been proposed. All of them rely on positive feedback to reinforce regions of high Cdc42 activity. Positive feedback can lead to bistability, a scenario in which cells can exist in either a polarized or unpolarized state under identical external conditions. Determining if the signaling circuit that drives Cdc42 polarity is bistable would provide important information about the mechanism that underlies polarity establishment and insights into the design features required for proper cellular function. We studied polarity establishment during the mating response of yeast. Using microfluidics to precisely control the temporal profile of mating pheromone and live-cell imaging to monitor the polarity process in single living cells, we found that the polarity circuit of yeast shows hysteresis, a characteristic feature of bistable systems. Our analysis also revealed that cells exposed to high pheromone concentrations rapidly lose polarity following a precipitous removal of pheromone. We used a reaction-diffusion model for polarity establishment to demonstrate that delayed negative regulation is sufficient to explain our experimental results. [Media: see text] [Media: see text] [Media: see text] [Media: see text].

A number of vascular diseases are associated with abnormal development of blood vessels. Dysregulated formation of blood vessels in the brain leading to Cerebral Cavernous Malformation (CCM) may predispose affected individuals to stroke even in the early years of their lives. Although coordinated behavior of endothelial cells is of central importance to embryonic development and maintenance of vascular homeostasis after birth, the underlying mechanisms of this biomechanical process remain poorly understood. In this work, we use a biophysical simulation model to dissect the mechanisms contributing to an emergent behavior of the multicellular system in the context of endothelial tube formation.Our cell model explicitly includes the dynamics of protrusions, by which cells interact with each other and the extracellular matrix, and an elastic cell body that moves and changes its shape in response to the mechanical forces resulting from these interactions. We inform and validate the model by imaging the collective dynamics of endothelial cells during tube formation both under wild-type conditions and with the knockdown of each of three CCM genes (krit1, ccm2, and pdcd10). This approach allowed us to bridge the single-cell and multi-cell scales of the system's description and dissect the differential effects of CCM proteins on the biomechanics of the coordinated cell behavior. Specifically, we showed that an imbalance of cell-cell (upon PDCD10 loss) or cell-ECM (upon KRIT1 loss) adhesion explains the distinct defects in the tubular structures of the CCM1 and CCM3 phenotypes. Furthermore, we showed that the incomplete rescue of the CCM phenotypes by the Rho kinase inhibition is explained by additional perturbations of the cell biomechanics unrelated to the deficiency of CCM proteins but involving the modulation of cell spreading, protrusion contractility, and the efficiency of long-range cell-cell sensing.

Cell migration is an essential and highly regulated process in the development and maintenance of multicellular organisms. During embryogenesis, large groups of cells migrate in a coordinated manner contributing to the formation of tissues and organs. In the adult, cell migration also occurs in wound healing, immune response, and tumor spreading. However, despite its critical importance in human physiology and decades of research efforts, cell migration remains a poorly understood phenomenon, mainly because it is a result of a complex and highly dynamic interplay between structural and regulatory cell components modulated by extracellular microenvironment and mechanochemical interactions with other cells. Our computational approach is based on a hybrid (agent-based/systems-dynamics) model that couples (1) a representation of the signaling network as a set of reaction-diffusion equations in a moving domain (the cell), (2) actin dynamics that drives changes in cell shape (protrusive activity), (3) a spatiotemporal stochastic model of adhesion complexes (formation, maturation, and disassembly), and (4) cell interaction with the extracellular environment (cell-cell and cell-matrix attachments). The model generates an output in a form of a time-lapsed image record matching the resolution of microscopy data, which allows for a direct comparison of the simulation results and the experiments. Using this model we were able to reproduce closely a number of experimentally observed processes, including the formation of actin waves leading to cell ruffling, the formation of a polarization front leading to both random-walk migration and the persistent directional motion, and the motion of a cluster of weakly interacting cells. This broadly applicable computational methodology can be used for generating and testing mechanistic hypotheses that capture the complexity of the cross-talk between the environment-dependent cell signaling and the cytoskeletal machinery in studies of both individual and collective cell migration.

At early stages of organismal development, endothelial cells self-organize into complex networks subsequently giving rise to mature blood vessels. The compromised collective behavior of endothelial cells leads to the development of a number of vascular diseases, many of which can be life-threatening. Cerebral cavernous malformation is an example of vascular diseases caused by abnormal development of blood vessels in the brain. Despite numerous efforts to date, enlarged blood vessels (cavernomas) can be effectively treated only by risky and complex brain surgery. In this work, we use a comprehensive simulation model to dissect the mechanisms contributing to an emergent behavior of the multicellular system. By tightly integrating computational and experimental approaches we gain a systems-level understanding of the basic mechanisms of vascular tubule formation, its destabilization, and pharmacological rescue, which may facilitate the development of new strategies for manipulating collective endothelial cell behavior in the disease context.

Dendritic spines are small postsynaptic compartments of excitatory synapses in the vertebrate brain that are modified during learning, aging, and neurological disorders. The formation and modification of dendritic spines depend on rapid assembly and dynamic remodeling of the actin cytoskeleton in this highly compartmentalized space, but the precise mechanisms remain to be fully elucidated. In this study, we report that spatiotemporal enrichment of actin monomers (G-actin) in dendritic spines regulates spine development and plasticity. We first show that dendritic spines contain a locally enriched pool of G-actin that can be regulated by synaptic activity. We further find that this G-actin pool functions in spine development and its modification during synaptic plasticity. Mechanistically, the relatively immobile G-actin pool in spines depends on the phosphoinositide PI(3,4,5)P3 and involves the actin monomer–binding protein profilin. Together, our results have revealed a novel mechanism by which dynamic enrichment of G-actin in spines regulates the actin remodeling underlying synapse development and plasticity.