Biological networks, such as those describing gene regulation, signal transduction, and neural synapses, are representations of large-scale dynamic systems. Discovery of organizing principles of biological networks can be enhanced by embracing the notion that there is a deep interplay between network structure and system dynamics. Recently, many structural characteristics of these non-random networks have been identified, but dynamical implications of the features have not been explored comprehensively. We demonstrate by exhaustive computational analysis that a dynamical property—stability or robustness to small perturbations—is highly correlated with the relative abundance of small subnetworks (network motifs) in several previously determined biological networks. We propose that robust dynamical stability is an influential property that can determine the non-random structure of biological networks.

Cells have an internal compass that enables them to move along shallow chemical gradients. As amoeboid cells migrate, signaling events such as Ras and PI3K activation occur spontaneously on pseudopodia. Uniform stimuli trigger a symmetric response, whereupon cells stop and round up; then localized patches of activity appear as cells spread. Finally cells adapt and resume random migration. In contrast, chemotactic gradients continuously direct signaling events to the front of the cell. Local-excitation, global-inhibition (LEGI) and reaction–diffusion models have captured some of these features of chemotaxing cells, but no system has explained the complex response kinetics, sensitivity to shallow gradients, or the role of recently observed propagating waves within the actin cytoskeleton. We report here that Ras and PI3K activation move in phase with the cytoskeleton events and, drawing on all of these observations, propose the LEGI-biased excitable network hypothesis. We formulate a model that simulates most of the behaviors of chemotactic cells: In the absence of stimulation, there are spontaneous spots of activity. Stimulus increments trigger an initial burst of patches followed by localized secondary events. After a few minutes, the system adapts, again displaying random activity. In gradients, the activity patches are directed continuously and selectively toward the chemoattractant, providing an extraordinary degree of amplification. Importantly, by perturbing model parameters, we generate distinct behaviors consistent with known classes of mutants. Our study brings together heretofore diverse observations on spontaneous cytoskeletal activity, signaling responses to temporal stimuli, and spatial gradient sensing into a unified scheme.

Mechanical forces direct a host of cellular and tissue processes. Although much emphasis has been placed on cell-adhesion complexes as force sensors, the forces must nevertheless be transmitted through the cortical cytoskeleton. Yet how the actin cortex senses and transmits forces and how cytoskeletal proteins interact in response to the forces is poorly understood. Here, by combining molecular and mechanical experimental perturbations with theoretical multiscale modelling, we decipher cortical mechanosensing from molecular to cellular scales. We show that forces are shared between myosin II and different actin crosslinkers, with myosin having potentiating or inhibitory effects on certain crosslinkers. Different types of cell deformation elicit distinct responses, with myosin and α-actinin responding to dilation, and filamin mainly reacting to shear. Our observations show that the accumulation kinetics of each protein may be explained by its molecular mechanisms, and that protein accumulation and the cell’s viscoelastic state can explain cell contraction against mechanical load.