Our next Lunch & Learn will be held Thursday, January 23, in Howey N201/202. Lunch will be served at 12:00 noon followed by a talk from 12:30 to 1:30 pm.
The speaker for this event will be Indy Badvaram from the Banerjee Lab.
Title: Physics of membrane curvature sensing by proteins
Abstract: Proteins that sense biomembrane curvature on the micron-scale, such as septins, have amphipathic helices that embed themselves into the membrane bilayer. Recent experiments have revealed that even a single nanometer-sized septin protein exhibits different binding rates to membranes supported on glass beads with different micron-scale curvatures, even though the protein is orders of magnitude smaller than the beads. This sensing ability is especially surprising since curvature-sensing proteins must deal with persistent thermal fluctuations of the membrane, leading to discrepancies between the curvature of the underlying bead and the local membrane curvature sensed instantaneously by the protein.
Using continuum models of fluctuating membranes, we first investigate whether it is feasible for a protein acting as a stationary perfect observer of the membrane to accurately sense micron-scale shape either by measuring local membrane curvature or by using bilayer lipid packing densities as a proxy. To do this, we develop algorithms to simulate lipid density and membrane shape fluctuations. We derive physical limits to the sensing efficacy of a protein — quantified as a signal-to-noise ratio — in terms of protein size, membrane thickness, membrane bending modulus, membrane-substrate adhesion strength, bead size, etc. To explain the experimental protein-bead association rates, we develop two classes of predictive models: i) for proteins that maximally associate to a preferred curvature, and ii) for proteins with enhanced association rates above a threshold curvature. We find that the experimentally observed sensing efficacy is close to the theoretical sensing limits imposed on a septin-sized protein.
To understand the localization of lipid density sensing proteins, we model a diffusing membrane protein with an energetic preference for a particular local lipid packing density, as well as protein bending and area compressibility moduli that differ from the host membrane. We investigate the protein’s diffusion through a freely fluctuating membrane and observe that a lipid density preference can lead to reduced diffusion coefficients. From our simulations, we obtain probability distributions of the protein’s location on a membrane when the membrane is adhered to a sinusoidally-shaped substrate. The protein’s localization to sinusoidal peaks is dictated by the protein’s mechanical properties relative to the host membrane, and the strength of lipid density preference influences the protein’s mean first passage time when crossing neighboring peaks.
