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Coincidence detection of proteins and lipids in regulation of cellular membrane dynamics

Periodic Reporting for period 1 - CODE (Coincidence detection of proteins and lipids in regulation of cellular membrane dynamics)

Reporting period: 2019-01-01 to 2020-06-30

An overarching principle in the biology of eukaryotic cells is that distinct proteins and lipids localise to distinct cellular membranes to perform compartment‐specific functions. A long‐standing question has been how such specific localisation is achieved. In the present proposal we will investigate the hypothesis that coincidence detection of proteins and lipids is a major mechanism to achieve specificity in cytosol‐tomembrane recruitment of proteins and their complexes. We will use mathematical modelling to model molecular kinetics of coincidence detection and predict the relationship between coincidence detection
and protein localisation, and we will investigate coincidence detection of the membrane lipid phosphatidylinositol 3‐phosphate (PI3P) and various proteins as a paradigm for how coincidence detection controls protein localisation, membrane contact site formation, and membrane dynamics. We will screen
for new coincidence detectors using bioinformatics, quantitative proteomics and molecular biology approaches. Candidates from the screen will be verified experimentally as genuine coincidence detectors, and their functions in cellular membrane dynamics will be identified using genome editing and newly developed imaging methods. Artificial coincidence detectors with novel specificities will be created by genetic engineering, and these will be used for detection and manipulation of membrane dynamics processes. Engineered coincidence detectors will then be used as components of artificial cells with chemotactic properties. The success of this project will not only establish a theoretical framework for a fundamental principle in cell biology but also provide new potential pharmacological targets and novel tools in cell biology and biotechnology.
During the first 18 months of the project we have been working on computer modelling of coincidence detection (SP1), validation of models (SP2), and identification of new coincidence detectors (SP3). The main results so far is an initial mathematical model for coincidence detection. Experimental verification of this model is still in progress. We have identified a novel coincidence detector, WDFY2, which coincidenctly detects the lipid phosphatidylinositol 3-phosphate in conjunction with high membrane curvature.
From our mathematical modelling, we are now in position to predict the biophysical parameters that promote coincidence detection, and we have identified new candidate coincidence detectors. In the remaining part of the project we will validate the models, characterize the newly identified coincidence detectors biochemically, and make artificial coincidence detectors for use as biosensors, membrane remodellers, and constituents of artificial cells.