Mapping differential interactomes by affinity purification coupled with data independent mass spectrometry acquisition

Characterizing changes in protein-protein interactions associated with sequence variants (e.g. disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies where cost and time are major considerations. To this end, we have coupled AP to data-independent mass spectrometric acquisition (SWATH), and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. Here, we use AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes, and propose a scalable pipeline for systems biology studies

Comprehensive analytical strategy for biomarker identification based on liquid chromatography coupled to mass spectrometry and new candidate confirmation tools

A comprehensive analytical LC-MS(/MS) platform for low weight biomarkers molecule in biological fluids is described. Two complementary retention mechanisms were used in HPLC by optimizing the chromatographic conditions for a reversed-phase column and a hydrophilic interaction chromatography column. LC separation was coupled to mass spectrometry by using an electrospray ionization operating in positive polarity mode. This strategy enables us to correctly retain and separate hydrophobic as well as polar analytes. For that purpose artificial model study samples were generated with a mixture of 38 well characterized compounds likely to be present in biofluids. The set of compounds was used as a standard aqueous mixture or was spiked into urine at different concentration levels to investigate the capability of the LC-MS(/MS) platform to detect variations across biological samples. Unsupervised data analysis by principal component analysis was performed and followed by principal component variable grouping to find correlated variables. This tool allows us to distinguish three main groups whose variables belong to (a) background ions (found in all type of samples), (b) ions distinguishing urine samples from aqueous standard and blank samples, (c) ions related to the spiked compounds. Interpretation of these groups allows us to identify and eliminate isotopes, adducts, fragments, etc. and to generate a reduced list of m/z candidates. This list is then submitted to the prototype MZSearcher software tool which simultaneously searches several lists of potential metabolites extracted from metabolomics databases (e.g., KEGG, HMDB, etc) to propose biomarker candidates. Structural confirmation of these candidates was done off-line by fraction collection followed by nanoelectrospray infusion to provide high quality MS/MS data for spectral database queries

Ultra-fast proteomics with Scanning SWATH

Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 \ub5l min ) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5–5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies. –