• Bottom-up proteomics;
  • Data-independent analysis;
  • Denaturants;
  • LC-MSE;
  • Membrane proteomics;
  • Technology


To evaluate the implementation of various denaturants and their efficacy in bottom-up membrane proteomic methods using LC-MS analysis, microsomes isolated from tomato roots were treated with MS-compatible surfactants (RapiGest SF Surfactant from Waters and PPS Silent Surfactant from Protein Discovery), a chaotropic reagent (guanidine hydrochloride), and an organic solvent (methanol). Peptides were analyzed in triplicate sample and technical replicates by data-independent LC-MSE analysis. Overall, 2333 unique peptides matching to 662 unique proteins were detected with the order of denaturant method efficacy being RapiGest SF Surfactant, PPS Silent Surfactant, guanidine hydrochloride, and methanol. Using bioinformatic analysis, 103 proteins were determined to be integral membrane proteins. When normalizing the data as a percentage of the overall number of peptides and proteins identified for each method, the order for integral membrane protein identification efficacy was methanol, guanidine hydrochloride, RapiGest SF Surfactant, and PPS Silent Surfactant. Interestingly, only 8% of the proteins were identified in all four methods with the silent surfactants having the greatest overlap at 17%. GRAVY analysis at the protein and peptide level indicated that methanol and guanidine hydrochloride promoted detection of hydrophobic proteins and peptides, respectively; however, trypsin activity in the presence of each denaturant was determined as a major factor contributing to peptide identification by LC-MSE. These results reveal the complementary nature of each denaturant method, which can be used in an integrated approach to provide a more effective bottom-up analysis of membrane proteomes than can be achieved using only a single denaturant.