Studying variations in CEACAM1 nanoscale organization, structure and dynamics, in different CEACAM1 isoforms and mutantsAmine Driouchi
Amine Driouchi1, 4; Scott Gray-Owen2; Christopher M. Yip1, 3, 4
1. Department of Biochemistry, University of Toronto; 2. Department of Molecular Genetics, University of Toronto; 3. Department of Chemical Engineering and Applied Chemistry, University of Toronto; 4. Institute of Biomaterials and Biomedical Engineering, University of Toronto
CEACAMs are cell surface glycoproteins involved in homo- and hetero-philic intercellular interactions that control cellular growth, differentiation, tumourigenesis, inflammation and infection. There is growing evidence regarding the role that CEACAM1 isoforms play in regulating interactions between various cell types. In particular, given its potential as a tumour suppressor or immunomodulator, CEACAM1 is being targeted in clinical trials. However, there remain clear challenges owing to observation that different CEACAM1 isoforms display cell-type specific preferential expression patterns under different physiological conditions. Moreover, the ability of CEACAMs to form dimers and higher-order oligomers, which are thought to impact regulation of intercellular signals, adds considerable complexity to our understanding of its functional role(s).
Super resolution microscopy has enabled the quantitative characterization of the nanoscale distribution of many membrane proteins, including their ability to form both micro- and nano-scale clusters. However, clustering and self-association are not necessarily the same and mapping how oligomeric state impact clustering and / or the oligomeric state of the proteins within a cluster is of particular interest to many. We report here on the development and application of a correlative STORM/homoFRET strategy to study CEACAM1 isoforms and mutants. This approach exploits eYFP for homoFRET measurements, an Alexa Fluor 647 (AF647) labeled an anti-eYFP single domain antibody (nanobody) for dSTORM, and Voronoi tessalation to perform cluster analysis of dSTORM dataset. Building on these data, we have also applied co-localization approaches to measure the CEACAM1 association to lipid-ordered regions, ezrin, and actin. We have further explored the use of single particle tracking (SPT) and mean square displacement analysis (MSD) to characterize CEACAM1 dynamics as a function of oligomeric state and location. These studies have helped develop a more fulsome perspective on the structure, association, and dynamics of this important class of membrane proteins.