Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.

Molecular & Cellular Proteomics : MCP
Roland BrudererLukas Reiter

Abstract

Comprehensive, reproducible and precise analysis of large sample cohorts is one of the key objectives of quantitative proteomics. Here, we present an implementation of data-independent acquisition using its parallel acquisition nature that surpasses the limitation of serial MS2 acquisition of data-dependent acquisition on a quadrupole ultra-high field Orbitrap mass spectrometer. In deep single shot data-independent acquisition, we identified and quantified 6,383 proteins in human cell lines using 2-or-more peptides/protein and over 7100 proteins when including the 717 proteins that were identified on the basis of a single peptide sequence. 7739 proteins were identified in mouse tissues using 2-or-more peptides/protein and 8121 when including the 382 proteins that were identified based on a single peptide sequence. Missing values for proteins were within 0.3 to 2.1% and median coefficients of variation of 4.7 to 6.2% among technical triplicates. In very complex mixtures, we could quantify 10,780 proteins and 12,192 proteins when including the 1412 proteins that were identified based on a single peptide sequence. Using this optimized DIA, we investigated large-protein networks before and after the critical period for whisker expe...Continue Reading

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Aug 15, 2018·Molecular & Cellular Proteomics : MCP·Nicolai BacheMatthias Mann
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Datasets Mentioned

BETA
PXD005573

Methods Mentioned

BETA
reversed phase chromatography

Software Mentioned

Biognosys
DAVID
Spectronaut Viewer
Spectronaut
mProphet
MaxQuant
DDA
Mfuzz
DIA

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