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Detalle de: Direct mapping of nanoscale compositional connectivity on intact cell membranes

Title Direct mapping of nanoscale compositional connectivity on intact cell membranes
Abstract

Lateral segregation of cell membranes is accepted as a primary mechanism for cells to regulate a diversity of cellular functions. In this context, lipid rafts have been conceptualized as organizing principle of biological membranes where underlying cholesterol-mediated selective connectivity must exist even at the resting state. However, such a level of nanoscale compositional connectivity has been challenging to prove. Here we used single-molecule near-field scanning optical microscopy to visualize the nanolandscape of raft ganglioside GM1 after tightening by its ligand cholera toxin (CTxB) on intact cell membranes. We show that CTxB tightening of GM1 is sufficient to initiate a minimal raft coalescence unit, resulting in the formation of cholesterol-dependent GM1 nanodomains < 120 nm in size. This particular arrangement appeared independent of cell type and GM1 expression level on the membrane. Simultaneous dual color high-resolution images revealed that GPI anchored and certain transmembrane proteins were recruited to regions proximal (< 150 nm) to CTxB-GM1 nanodomains without physical intermixing. Together with in silico experiments, our high-resolution data conclusively demonstrate the existence of raft-based interconnectivity at the nanoscale. Such a linked state on resting cell membranes constitutes thus an obligatory step toward the hierarchical evolution of large-scale raft coalescence upon cell activation.

Apa Reference van Zanten, T. S., Gómez, J., Manzo, C., Cambi, A., Buceta, J., Reigada, R., & Garcia-Parajo, M. F. (2010). Direct mapping of nanoscale compositional connectivity on intact cell membranes. Proceedings of the National Academy of Sciences, 107(35), 15437–15442. 10.1073/pnas.1003876107
Doi 10.1073/pnas.1003876107
Publication Date 16 Aug 2010
Publication Type Article
Researcher Javier Buceta
Ontology Mapping
Research Groups TheSiMBioSys (Theoretical and In Silico Modeling of Biological Systems)
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