Chemotaxis, the directed migration of cells in chemical gradients, is a vital process in normal physiology and in the pathogenesis of many diseases. Chemotactic cells display motility, directional sensing, and polarity. Motility refers to the random extension of pseudopodia, which may be driven by spontaneous actin waves that propagate through the cytoskeleton. Directional sensing is mediated by a system that detects temporal and spatial stimuli and biases motility toward the gradient. Polarity gives cells morphologically and functionally distinct leading and lagging edges by relocating proteins or their activities selectively to the poles. By exploiting the genetic advantages of Dictyostelium, investigators are working out the complex network of interactions between the proteins that have been implicated in the chemotactic processes of motility, directional sensing, and polarity.

PIK3CA , one of the two most frequently mutated oncogenes in human tumors, codes for p110α, the catalytic subunit of a phosphatidylinositol 3-kinase, isoform α (PI3Kα, p110α/p85). Here, we report a 3.0 angstrom resolution structure of a complex between p110α and a polypeptide containing the p110α-binding domains of p85α, a protein required for its enzymatic activity. The structure shows that many of the mutations occur at residues lying at the interfaces between p110α and p85α or between the kinase domain of p110α and other domains within the catalytic subunit. Disruptions of these interactions are likely to affect the regulation of kinase activity by p85 or the catalytic activity of the enzyme, respectively. In addition to providing new insights about the structure of PI3Kα, these results suggest specific mechanisms for the effect of oncogenic mutations in p110α and p85α.

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.

Mutations in oncogenes often promote tumorigenesis by changing the conformation of the encoded proteins, thereby altering enzymatic activity. ThePIK3CAoncogene, which encodes p110α, the catalytic subunit of phosphatidylinositol 3-kinase alpha (PI3Kα), is one of the two most frequently mutated oncogenes in human cancers. We report the structure of the most common mutant of p110α in complex with two interacting domains of its regulatory partner (p85α), both free and bound to an inhibitor (wortmannin). The N-terminal SH2 (nSH2) domain of p85α is shown to form a scaffold for the entire enzyme complex, strategically positioned to communicate extrinsic signals from phosphopeptides to three distinct regions of p110α. Moreover, we found that Arg-1047 points toward the cell membrane, perpendicular to the orientation of His-1047 in the WT enzyme. Surprisingly, two loops of the kinase domain that contact the cell membrane shift conformation in the oncogenic mutant. Biochemical assays revealed that the enzymatic activity of the p110α His1047Arg mutant is differentially regulated by lipid membrane composition. These structural and biochemical data suggest a previously undescribed mechanism for mutational activation of a kinase that involves perturbation of its interaction with the cellular membrane.

It is generally believed that cytoskeletal activities drive random cell migration, whereas signal transduction events initiated by receptors regulate the cytoskeleton to guide cells. However, we find that the cytoskeletal network, involving SCAR/WAVE, Arp 2/3 and actin-binding proteins, is capable of generating only rapid oscillations and undulations of the cell boundary. The signal transduction network, comprising multiple pathways that include Ras GTPases, PI(3)K and Rac GTPases, is required to generate the sustained protrusions of migrating cells. The signal transduction network is excitable, exhibiting wave propagation, refractoriness and maximal response to suprathreshold stimuli, even in the absence of the cytoskeleton. We suggest that cell motility results from coupling of ‘pacemaker’ signal transduction and ‘idling motor’ cytoskeletal networks, and various guidance cues that modulate the threshold for triggering signal transduction events are integrated to control the mode and direction of migration.

Chemotaxis involves the coordinated action of separable but interrelated processes: motility, gradient sensing, and polarization. We have hypothesized that these are mediated by separate modules that account for these processes individually and that, when combined, recreate most of the behaviors of chemotactic cells. Here, we describe a mathematical model where the modules are implemented in terms of reaction-diffusion equations. Migration and the accompanying changes in cellular morphology are demonstrated in simulations using a mechanical model of the cell cortex implemented in the level set framework. The central module is an excitable network that accounts for random migration. The response to combinations of uniform stimuli and gradients is mediated by a local excitation, global inhibition module that biases the direction in which excitability is directed. A polarization module linked to the excitable network through the cytoskeleton allows unstimulated cells to move persistently and, for cells in gradients, to gradually acquire distinct sensitivity between front and back. Finally, by varying the strengths of various feedback loops in the model we obtain cellular behaviors that mirror those of genetically altered cell lines. Chemotaxis is the movement of cells in response to spatial gradients of chemical cues. While single-celled organisms rely on sensing and responding to chemical gradients to search for nutrients, chemotaxis is also an essential component of the mammalian immune system. However, chemotaxis can also be deleterious, since chemotactic tumor cells can lead to metastasis. Due to its importance, understanding the process by which cells sense and respond to chemical gradients has attracted considerable interest. Moreover, because of the complexity of chemotactic signaling, which includes multiple feedback loops and redundant pathways, this has been a research area in which computational models have had a significant impact in understanding experimental findings. Here, we propose a modular description of the signaling network that regulates chemotaxis. The modules describe different processes that are observed in chemotactic cells. In addition to accounting for these behaviors individually, we show that the overall system recreates many features of the directed motion of migrating cells. The signaling described by our modules is implemented as a series of equations, whereas movement and the accompanying cellular deformations are simulated using a mechanical model of the cell and implemented using level set methods, a method that allows simulations of cells as they change morphology.