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DOI 10.3791/64243

Медицинская библиотека · Journal of visualized experiments : JoVE · 2022

Single-molecule Diffusion and Assembly on Polymer-crowded Lipid Membranes.

Maurya Satyaghosh, Rai Vishwesh Haricharan, Upasani Aditya, Umrao Saurabh, Parwana Diksha, Roy Rahul

СтатьяVideo-Audio MediaПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Cellular membranes are highly crowded environments for biomolecular reactions and signaling. Yet, most in vitro experiments probing protein interaction with lipids employ naked bilayer membranes. Such systems lack the complexities of crowding by membrane-embedded proteins and glycans and exclude the associated volume effects encountered on cellular membrane surfaces. Also, the negatively charged glass surface onto which the lipid bilayers are formed prevents the free diffusion of transmembrane biomolecules. Here, we present a well-characterized polymer-lipid membrane as a mimic for crowded lipid membranes. This protocol utilizes polyethylene glycol (PEG)-conjugated lipids as a generalized approach for incorporating crowders into the supported lipid bilayer (SLB). First, a cleaning procedure of the microscopic slides and coverslips for performing single-molecule experiments is presented. Next, methods for characterizing the PEG-SLBs and performing single-molecule experiments of the binding, diffusion, and assembly of biomolecules using single-molecule tracking and photobleaching are discussed. Finally, this protocol demonstrates how to monitor the nanopore assembly of bacterial pore-forming toxin Cytolysin A (ClyA) on crowded lipid membranes with single-molecule photobleaching analysis. MATLAB codes with example datasets are also included to perform some of the common analyses such as particle tracking, extracting diffusive behavior, and subunit counting.

Для цитирования: Maurya Satyaghosh, Rai Vishwesh Haricharan, Upasani Aditya, Umrao Saurabh, Parwana Diksha, Roy Rahul. Single-molecule Diffusion and Assembly on Polymer-crowded Lipid Membranes.. Journal of visualized experiments : JoVE. 2022. DOI: 10.3791/64243.

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