Comparative Analysis of Quantitative Mass Spectrometric Methods for Subcellular Proteomics
Autor: | David E. Sleat, Haiyan Zheng, Colin J. Germain, Peter Lobel, Marielle Boonen, Caifeng Zhao, Michel Jadot, Dirk F. Moore, Abla Tannous |
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Rok vydání: | 2020 |
Předmět: |
Ions
Proteomics 0301 basic medicine Proteome 030102 biochemistry & molecular biology Chemistry General Chemistry Fractionation Computational biology Mass spectrometry Tandem mass tag Biochemistry Protein subcellular localization prediction Article Mass Spectrometry Rats 03 medical and health sciences Isobaric labeling 030104 developmental biology Animals Data-independent acquisition |
Zdroj: | J Proteome Res |
ISSN: | 1535-3907 1535-3893 |
DOI: | 10.1021/acs.jproteome.9b00862 |
Popis: | Knowledge of intracellular location can provide important insights into the function of proteins and their respective organelles, and there is interest in combining classical subcellular fractionation with quantitative mass spectrometry to create global cellular maps. To evaluate mass spectrometric approaches specifically for this application, we analyzed rat liver differential centrifugation and Nycodenz density gradient subcellular fractions by tandem mass tag (TMT) isobaric labeling with reporter ion measurement at the MS2 and MS3 level and with two different label-free peak integration approaches, MS1 and data independent acquisition (DIA). TMT-MS2 provided the greatest proteome coverage, but ratio compression from contaminating background ions resulted in a narrower accurate dynamic range compared to TMT-MS3, MS1, and DIA, which were similar. Using a protein clustering approach to evaluate data quality by assignment of reference proteins to their correct compartments, all methods performed well, with isobaric labeling approaches providing the highest quality localization. Finally, TMT-MS2 gave the lowest percentage of missing quantifiable data when analyzing orthogonal fractionation methods containing overlapping proteomes. In summary, despite inaccuracies resulting from ratio compression, data obtained by TMT-MS2 assigned protein localization as well as other methods but achieved the highest proteome coverage with the lowest proportion of missing values. |
Databáze: | OpenAIRE |
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