The depalmitoylase APT1 directs the asymmetric partitioning of Notch and Wnt signaling during cell division

Asymmetric cell division results in two distinctly fated daughter cells. A molecular hallmark of asymmetric division is the unequal partitioning of cell fate determinants. We have previously established that growth factor signaling promotes protein depalmitoylation to foster polarized protein localization, which, in turn, drives migration and metastasis. We report protein palmitoylation as a key mechanism for the asymmetric partitioning of the cell fate determinants Numb and β-catenin through the activity of the depalmitoylating enzyme APT1. Using point mutations, we showed that specific palmitoylated residues on Numb were required for its asymmetric localization. By live-cell imaging, we showed that reciprocal interactions between APT1 and the Rho family GTPase CDC42 promoted the asymmetric localization of Numb and β-catenin to the plasma membrane. This, in turn, restricted Notch- or Wnt-responsive transcriptional activity to one daughter cell. Moreover, we showed that altering APT1 abundance changed the transcriptional signatures of MDA-MB-231 triple receptor-negative breast cancer cells, similar to changes in Notch and β-catenin-mediated Wnt signaling. We also showed that loss of APT1 depleted a specific subpopulation of tumorigenic cells in colony formation assays. Together, our findings suggest that APT1-mediated depalmitoylation is a major mechanism of asymmetric cell division that maintains Notch- and Wnt-associated protein dynamics, gene expression, and cellular functions.

Stochastic pattern formation and spontaneous polarisation: the linear noise approximation and beyond

We review the mathematical formalism underlying the modelling of stochasticity in biological systems. Beginning with a description of the system in terms of its basic constituents, we derive the mesoscopic equations governing the dynamics which generalise the more familiar macroscopic equations. We apply this formalism to the analysis of two specific noise-induced phenomena observed in biologically inspired models. In the first example, we show how the stochastic amplification of a Turing instability gives rise to spatial and temporal patterns which may be understood within the linear noise approximation. The second example concerns the spontaneous emergence of cell polarity, where we make analytic progress by exploiting a separation of time-scales.