Munc18-1 orchestrates SNARE complex assembly together with Munc13-1 to mediate neurotransmitter release. Munc18-1 binds to synaptobrevin, but the relevance of this interaction and its relation to Munc13 function are unclear. NMR experiments now show that Munc18-1 binds specifically and non-specifically to synaptobrevin. Specific binding is inhibited by a L348R mutation in Munc18-1 and enhanced by a D326K mutation designed to disrupt the 'furled conformation' of a Munc18-1 loop. Correspondingly, the activity of Munc18-1 in reconstitution assays that require Munc18-1 and Munc13-1 for membrane fusion is stimulated by the D326K mutation and inhibited by the L348R mutation. Moreover, the D326K mutation allows Munc13-1-independent fusion and leads to a gain-of-function in rescue experiments in C. elegans unc-18 nulls. Together with previous studies, our data support a model whereby Munc18-1 acts as a template for SNARE complex assembly and autoinhibition of synaptobrevin binding contributes to enabling regulation of neurotransmitter release by Munc13-1.
- Josep Rizo
- Josep Rizo
- Shuzo Sugita
- Josep Rizo
- Josep Rizo
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Axel T Brunger, Stanford University Medical Center, United States
© 2017, Sitarska et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Single-molecule force spectroscopy (SMFS) uses the cantilever tip of an atomic force microscopy (AFM) to apply a force able to unfold a single protein. The obtained force-distance curve encodes the unfolding pathway, and from its analysis it is possible to characterize the folded domains. SMFS has been mostly used to study the unfolding of purified proteins, in solution or reconstituted in a lipid bilayer. Here, we describe a pipeline for analyzing membrane proteins based on SMFS, which involves the isolation of the plasma membrane of single cells and the harvesting of force-distance curves directly from it. We characterized and identified the embedded membrane proteins combining, within a Bayesian framework, the information of the shape of the obtained curves, with the information from mass spectrometry and proteomic databases. The pipeline was tested with purified/reconstituted proteins and applied to five cell types where we classified the unfolding of their most abundant membrane proteins. We validated our pipeline by overexpressing four constructs, and this allowed us to gather structural insights of the identified proteins, revealing variable elements in the loop regions. Our results set the basis for the investigation of the unfolding of membrane proteins in situ, and for performing proteomics from a membrane fragment.
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