Membrane recognition by an ER lipid sensor complex

Cellular membranes are 10.000 times thinner than a human hair yet composed of thousands of distinct lipids and proteins. A significant portion of the human genome encodes for machineries producing, modifying and degrading membrane lipids. Because of their stunning diversity it is extremely challenging to study lipid function and the purpose of lipid diversity remains elusive. What is known, however, is that numerous devastating diseases such as Parksinsons, Alzheimerssand cancercorrelate with perturbed membranelipid compositions. A disorder in lipid metabolism is also a major cause of the metabolic syndrome, leading to disease states including type 2 diabetes and cardiovascular diseases. The molecular role of lipids in the pathogenesis of these diseases, however, remains poorly understood. This proposal aims to reveal the molecular mechanism underlying the cellular decision between membrane growth and fat storage. When does a cell decide to resume growth and to store fat instead? And how does a cell orchestrate the challenging task to reprogram its lipid metabolism from growth to storage? These important questions will be addressed in the model organism bakers yeast (Saccharomyces cerevisiae), whose metabolism is remarkably similar to human cancer cells. The research focuses on phosphatidic acid, a class of lipid molecules with a tremendous potential to control these cellular decisions: only when phosphatidic acid is abundant, the cell will invest its energy to grow new membranes. The cellular response to this class of signaling lipids it mediated by a sensor protein, called Opi1, communicating the phosphatidic acid content to the nucleus. The dynamic behavior of this sensor molecule will be studied using fluorescence microscopic inspections and Opi1 mutant variants with designed properties to tune the cellular response to metabolic stress. Using Opi1, the key regulator of lipid metabolism in yeast, as a show box, this proposal aims at a better understanding of the fundamental mechanisms underlying membrane recognition. The characterization of Opi1s peculiar properties will provide a new perspective for the rational design of specific lipid sensors with high selectivity to distinct organellar membranes.

No additional funding sources recorded.