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Mol Cell Proteomics. 2017 Dec;16(12):2296-2309. doi: 10.1074/mcp.RA117.000314. Epub 2017 Oct 25.

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

Author information

1
From the ‡Biognosys, Wagistrasse 21, 8952 Schlieren, Switzerland.
2
§Thermo Fisher Scientific, 28199 Bremen, Germany.
3
¶Somatosensory Signaling and Systems Biology Group, Max Planck Institute of Experimental Medicine, Hermann-Rein-Strasse 3, 37075 Goettingen, Germany.
4
From the ‡Biognosys, Wagistrasse 21, 8952 Schlieren, Switzerland. lukas.reiter@biognosys.com.

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 experience-induced synaptic strength in the murine somatosensory cortex 1-barrel field. This work shows that parallel mass spectrometry enables proteome profiling for discovery with high coverage, reproducibility, precision and scalability.

PMID:
29070702
PMCID:
PMC5724188
DOI:
10.1074/mcp.RA117.000314
[Indexed for MEDLINE]
Free PMC Article

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