Qualitative and Quantitative Shotgun Proteomics Data Analysis from Data-Dependent Acquisition Mass Spectrometry

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 2259; p. 297
• Main Author: Meyer, Jesse G
• Format: Journal Article
• Language: English
• Published: United States 2021
• Subjects: Animals; Chromatography, Liquid - methods; Gene Ontology; Humans; Molecular Sequence Annotation; Peptide Fragments - analysis; Proteins - analysis; Proteome - analysis; Proteomics - methods; Software; Tandem Mass Spectrometry - methods; Pathway analysis; Data-dependent acquisition; Peptides; Quantification; Proteomics; Gene ontology analysis; Mass spectrometry
• ISSN: 1940-6029
• DOI: 10.1007/978-1-0716-1178-4_19

Shotgun proteomics is the inferential analysis of proteoforms using peptide proxies produced by enzyme-catalyzed hydrolysis of entire proteomes. Such peptides are usually identified by nanoflow liquid chromatography coupled to tandem mass spectrometry analysis (nLC-MS/MS). Traditionally, MS/MS analysis is performed in data-dependent acquisition (DDA) mode, which usually produces a pattern of fragment masses unique to a single peptide's fragmentation. Here, I describe a statistically rigorous qualitative and quantitative computational analysis for shotgun proteomics DDA analysis using free open-source software tools. MS/MS data are used to identify peptides, and the area of peptide mass/charge over chromatographic elution is used to quantify peptides. All peptides that uniquely map to a protein sequence predicted from the genome are combined into a single protein quantity, which can then be compared across experimental conditions. Statistically significant protein changes can be summarized using gene ontology or pathway term enrichment analysis.