MS/MS-Free Protein Identification in Complex Mixtures Using Multiple Enzymes with Complementary Specificity

Abstract

In this work, we present the results of evaluation of a workflow that employs a multienzyme digestion strategy for MS1-based protein identification in "shotgun" proteomic applications. In the proposed strategy, several cleavage reagents of different specificity were used for parallel digestion of the protein sample followed by MS1 and retention time (RT) based search. Proof of principle for the proposed strategy was performed using experimental data obtained for the annotated 48-protein standard. By using the developed approach, up to 90% of proteins from the standard were unambiguously identified. The approach was further applied to HeLa proteome data. For the sample of this complexity, the proposed MS1-only strategy determined correctly up to 34% of all proteins identified using standard MS/MS-based database search. It was also found that the results of MS1-only search were independent of the chromatographic gradient time in a wide range of gradients from 15-120 min. Potentially, rapid MS1-only proteome characterization can be an alternative or complementary to the MS/MS-based "shotgun" analyses in the studies, in which the experimental time is more important than the depth of the proteome coverage.

Boosting MS1-only Proteomics with Machine Learning Allows 2000 Protein Identifications in Single-Shot Human Proteome Analysis Using 5 min HPLC Gradient

“…One of the most time-consuming parts of the analysis is MS/MS data acquisition, which requires using long HPLC gradient times to have enough room for sequential isolation of as many as possible precursor ions from each MS1 spectrum for subsequent fragmentation. A number of methods and approaches to MS/MS-free proteome analysis have been proposed and widely explored starting from the early Accurate Mass and Tag (Time) method [21][22][23][24][25] to a recent truly (e.g., without employing tandem mass spectrometry at any step in the workflow) MS/MS-free realizations 26,27 .…”

MetaProClust-MS1: A tool for clustering metaproteomes using rapid MS1 profiling

“…Because MPC-MS1 was developed for metaproteomics, MPC-MS1 is currently limited to treatment separation and does not identify peptides. However,in the future MPC-MS1 can be extended for protein identification through MS1 features using peptide mass fingerprinting (James et al, 1993; Pappin et al, 1993; Mann et al, 1993; Yeats et al, 1993) and an MS1-only search workflow (Ivanov et al, 2017). However, this approach remains to be tested on complex metaproteomic data and is currently beyond the scope of our study.…”

Versatile and multiplexed mass spectrometry-based absolute quantification with cell-free-synthesized internal standard peptides

“…called such an approach, MS western, originating from a western blotting [26]. MS/MS-free method does not waste time acquiring MS2 and therefore enables short and high-throughput analysis [27]. After processing the peak data and calculation, some peptides show outliers due to miss-cleavages, noisy peaks, or missing peaks.…”