PT  - JOURNAL ARTICLE
AU  - Galvanetto, Nicola
AU  - Maity, Sourav
AU  - Ilieva, Nina
AU  - Ye, Zhongjie
AU  - Laio, Alessandro
AU  - Torre, Vincent
TI  - Unfolding and identification of membrane proteins from native cell membranes
AID  - 10.1101/732933
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 732933
4099  - http://biorxiv.org/content/early/2019/09/26/732933.short
4100  - http://biorxiv.org/content/early/2019/09/26/732933.full
AB  - Is the mechanical unfolding of proteins just a technological feat applicable only to synthetic preparations or is it applicable to real biological samples? Here, we describe a method providing all the necessary steps to deal with native membranes, from the isolation of the plasma membrane of single cells, to the characterization and identification of the embedded membrane proteins. We combined single-molecule force spectroscopy with an automatic pattern classification of the obtained Force-distance curves, and we provide a Bayesian identification of the unfolded proteins. The Bayesian identification is based on the cross-matching of Mass Spectrometry datasets with proteomic databases (Uniprot, PDB). We applied this method to four cell types where we classified the unfolding of 5-10% of their total content of membrane proteins. The ability to mechanically probe membrane proteins directly in their native membrane enables the phenotyping of different cell types with almost single-cell level of resolution.