Mapping Protein-Protein Interactions Using Data-Dependent Acquisition Without Dynamic Exclusion

Abstract

Systematic analysis of affinity-purified samples by liquid chromatography coupled to mass spectrometry (LC-MS) requires high coverage, reproducibility, and sensitivity. Data-independent acquisition (DIA) approaches improve the reproducibility of protein-protein interaction detection by alleviating the stochasticity of data-dependent acquisition (DDA). However, the need for library generation and lack of multiplexing capabilities reduces their throughput, and analysis pipelines are still being optimized. In previous work using cell lysates, a fast MS/MS acquisition method with no dynamic exclusion (noDE) provided a comparable number of identifications and more accurate MS/MS intensity-based quantification than an optimized DDA method with dynamic exclusion (DE). Here, we have further optimized the noDE strategy for the analysis of protein-protein interactions and show that it provides better sensitivity and identifies more high confident interactors than the optimized DDA with DE and DIA approaches. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/480563v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@553e5eorg.highwire.dtl.DTLVardef@71a722org.highwire.dtl.DTLVardef@193e7fborg.highwire.dtl.DTLVardef@1632e4b_HPS_FORMAT_FIGEXP M_FIG C_FIG