Cofilin is a pH sensor for actin free barbed end formation: role of phosphoinositide binding

Newly generated actin free barbed ends at the front of motile cells provide sites for actin filament assembly driving membrane protrusion. Growth factors induce a rapid biphasic increase in actin free barbed ends, and we found both phases absent in fibroblasts lacking H+ efflux by the Na-H exchanger NHE1. The first phase is restored by expression of mutant cofilin-H133A but not unphosphorylated cofilin-S3A. Constant pH molecular dynamics simulations and nuclear magnetic resonance (NMR) reveal pH-sensitive structural changes in the cofilin C-terminal filamentous actin binding site dependent on His133. However, cofilin-H133A retains pH-sensitive changes in NMR spectra and severing activity in vitro, which suggests that it has a more complex behavior in cells. Cofilin activity is inhibited by phosphoinositide binding, and we found that phosphoinositide binding is pH-dependent for wild-type cofilin, with decreased binding at a higher pH. In contrast, phosphoinositide binding by cofilin-H133A is attenuated and pH insensitive. These data suggest a molecular mechanism whereby cofilin acts as a pH sensor to mediate a pH-dependent actin filament dynamics

Autocrine HBEGF expression promotes breast cancer intravasation, metastasis and macrophage-independent invasion in vivo

Increased expression of HBEGF in ER negative breast tumors is correlated with enhanced metastasis to distant organ sites and more rapid disease recurrence upon removal of the primary tumor. Our previous work has demonstrated a paracrine loop between breast cancer cells and macrophages in which the tumor cells are capable of stimulating macrophages through the secretion of CSF-1 while the tumor associated macrophages (TAMs) in turn aid in tumor cell invasion by secreting EGF. To determine how the autocrine expression of EGFR ligands by carcinoma cells would affect this paracrine loop mechanism, and in particular whether tumor cell invasion depends on spatial ligand gradients generated by TAMs, we generated cell lines with increased HBEGF expression. We find that autocrine HBEGF expression enhanced in vivo intravasation and metastasis, and resulted in a novel phenomenon in which macrophages were no longer required for in vivo invasion of breast cancer cells. In vitro studies revealed that expression of HBEGF enhanced invadopodium formation, thus providing a mechanism for cell autonomous invasion. The increased invadopodium formation was directly dependent on EGFR signaling, as demonstrated by a rapid decrease in invadopodia upon inhibition of autocrine HBEGF/EGFR signaling as well as inhibition of signaling downstream of EGFR activation. HBEGF expression also resulted in enhanced invadopodium function via upregulation of MMP2 and MMP9 expression. We conclude that high levels of HBEGF expression can short-circuit the tumor cell/macrophage paracrine invasion loop, resulting in enhanced tumor invasion that is independent of macrophage signaling

A user’s guide to PDE models for chemotaxis

Mathematical modelling of chemotaxis (the movement of biological cells or organisms in response to chemical gradients) has developed into a large and diverse discipline, whose aspects include its mechanistic basis, the modelling of specific systems and the mathematical behaviour of the underlying equations. The Keller-Segel model of chemotaxis (Keller and Segel in J Theor Biol 26:399–415, 1970; 30:225– 234, 1971) has provided a cornerstone for much of this work, its success being a consequence of its intuitive simplicity, analytical tractability and capacity to replicate key behaviour of chemotactic populations. One such property, the ability to display “auto-aggregation”, has led to its prominence as a mechanism for self-organisation of biological systems. This phenomenon has been shown to lead to finite-time blow-up under certain formulations of the model, and a large body of work has been devoted to determining when blow-up occurs or whether globally existing solutions exist. In this paper, we explore in detail a number of variations of the original Keller–Segel model. We review their formulation from a biological perspective, contrast their patterning properties, summarise key results on their analytical properties and classify their solution form. We conclude with a brief discussion and expand on some of the outstanding issues revealed as a result of this work