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Fast Proteome Identification and Quantification from Data-Dependent Acquisition–Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools
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 an...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469856/ https://www.ncbi.nlm.nih.gov/pubmed/31008411 http://dx.doi.org/10.3390/mps2010008 |
Sumario: | 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. |
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