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Open AccessProtocol

Fast Proteome Identification and Quantification from Data-Dependent Acquisition–Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools

1
Department of Chemistry, University of Wisconsin—Madison, Madison, WI 53706, USA
2
Department of Biomolecular Chemistry, University of Wisconsin—Madison, Madison, WI 53706, USA
3
National Center for Quantitative Biology of Complex Systems, University of Wisconsin—Madison, Madison, WI 53706, USA
Methods Protoc. 2019, 2(1), 8; https://doi.org/10.3390/mps2010008
Received: 26 November 2018 / Revised: 7 January 2019 / Accepted: 15 January 2019 / Published: 17 January 2019
The identification of nearly all proteins in a biological system using data-dependent acquisition (DDA) tandem mass spectrometry has become routine for organisms with relatively small genomes such as bacteria and yeast. Still, the quantification of the identified proteins may be a complex process and often requires multiple different software packages. In this protocol, I describe a flexible strategy for the identification and label-free quantification of proteins from bottom-up proteomics experiments. This method can be used to quantify all the detectable proteins in any DDA dataset collected with high-resolution precursor scans and may be used to quantify proteome remodeling in response to drug treatment or a gene knockout. Notably, the method is statistically rigorous, uses the latest and fastest freely-available software, and the entire protocol can be completed in a few hours with a small number of data files from the analysis of yeast. View Full-Text
Keywords: shotgun proteomics; mass spectrometry; protein quantification; peptide quantification; data-dependent acquisition shotgun proteomics; mass spectrometry; protein quantification; peptide quantification; data-dependent acquisition
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Meyer, J.G. Fast Proteome Identification and Quantification from Data-Dependent Acquisition–Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools. Methods Protoc. 2019, 2, 8.

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