Fast Proteome Identification and Quantification from Data-Dependent Acquisition-Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools.
Jesse G MeyerPublished in: Methods and protocols (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.
Keyphrases
- tandem mass spectrometry
- ultra high performance liquid chromatography
- high performance liquid chromatography
- high resolution
- liquid chromatography
- simultaneous determination
- gas chromatography
- label free
- mass spectrometry
- ms ms
- data analysis
- electronic health record
- solid phase extraction
- randomized controlled trial
- high resolution mass spectrometry
- big data
- liquid chromatography tandem mass spectrometry
- bioinformatics analysis
- computed tomography
- magnetic resonance
- magnetic resonance imaging
- genome wide
- clinical practice
- multidrug resistant
- machine learning
- drug induced
- gram negative
- deep learning
- contrast enhanced