Membrane proteins enable communication between a cell and its environment. Though critically important for health and the most targeted class of proteins for treating a range of illnesses, they are notoriously difficult to study. In this project, we will develop a new technology that will make it possible to better understand how membrane proteins function, enabling a deeper understanding of the many life processes that rely on their activity and empowering the development of drugs.
One type of membrane protein is the integral membrane proteins, which have regions that cross the outer lipid membrane of the cell at least once (and often several times). They represent nearly one quarter of the proteins in our bodies. Another type is the membrane-associated proteins, which perform their vital cellular functions, such as signalling and transport, when they interact with the membrane.
One reason why membrane proteins are difficult to study is that they require a hydrophobic environment, i.e. the lipid bilayer, for stability and function, but lipid bilayers are difficult to recreate outside the cell. Existing systems that mimic cellular membranes differ from cells in shape and composition, so they cannot be relied on to induce the behaviour that proteins display in cells. Data collection challenges pose another difficulty. Existing techniques provide only snapshots in time, rather than tracking dynamics, or they require fluorescent labels, which may disrupt protein function and produce data that can be difficult to quantify.
We aim to overcome these challenges by developing, optimising and applying Dynamic Mass Photometry (DMP), a label-free approach for the imaging, tracking and mass measurement of individual membrane proteins and their complexes in lipid membranes. The approach builds on mass photometry, a technology we developed that enables single-molecule mass imaging of proteins and their interactions in solution. Our first objective will be to develop the experimental setup and data analysis approach for DMP, which will enable us to translate the existing mass photometry platform to measuring membrane proteins. We will use supported lipid bilayers, where proteins can freely diffuse and interact, and we can selectively modify the lipid composition to suit individual membrane proteins and mimic different tissue cell types. Next, we will advance DMP to study two different types of membrane proteins that we have studied extensively in solution, enabling us to assess the degree to which the behaviour found in solution is representative of that on or in a bilayer membrane. First, we will quantify the assembly and interaction dynamics of dynamin, a membrane-associated protein that plays a central role in cellular trafficking. Second, we will investigate the angiotensin converting enzyme-2 (ACE2) receptor, which is central to SARS-CoV-2 infection in humans due to its binding to the spike glycoprotein. This work will be carried out by our team of biophysicists at the University of Oxford's newly established Kavli Institute for NanoScience Discovery.
DMP will make it possible to establish a detailed quantitative picture of the interactions and assembly of membrane proteins in their natural setting - bringing unprecedented insight to a critical class of proteins. Meanwhile, the analysis approach developed will be broadly applicable to any system where understanding the mass, interaction, dynamics and diffusion of biomolecules is valuable, but currently not possible. Applying DMP to different types of membrane proteins will demonstrate how it can be used, while shedding light on mechanisms of biological function, and, critically, the role of the membrane in those processes. Applying DMP to pathogen-host-cell interfaces, exemplified with the study of SARS-CoV-2 spike and ACE2, will provide unprecedented understanding of how viruses engage human cells and open a new route for developing drugs that block these interactions.
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