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Global kinetic analysis of proteolysis via quantitative targeted proteomics.

ABSTRACT: Mass spectrometry-based proteomics is a powerful tool for identifying hundreds to thousands of posttranslational modifications in complex mixtures. However, it remains enormously challenging to simultaneously assess the intrinsic catalytic efficiencies (k(cat)/K(M)) of these modifications in the context of their natural interactors. Such fundamental enzymological constants are key to determining substrate specificity and for establishing the timing and importance of cellular signaling. Here, we report the use of selected reaction monitoring (SRM) for tracking proteolysis induced by human apoptotic caspases-3, -7, -8, and -9 in lysates and living cells. By following the appearance of the cleaved peptides in lysate as a function of time, we were able to determine hundreds of catalytic efficiencies in parallel. Remarkably, we find the rates of substrate hydrolysis for individual caspases vary greater than 500-fold indicating a sequential process. Moreover, the rank-order of substrate cutting is similar in apoptotic cells, suggesting that cellular structures do not dramatically alter substrate accessibility. Comparisons of extrinsic (TRAIL) and intrinsic (staurosporine) inducers of apoptosis revealed similar substrate profiles, suggesting the final proteolytic demolitions proceed by similarly ordered plans. Certain biological processes were rapidly targeted by the caspases, including multiple components of the endocyotic pathway and miRNA processing machinery. We believe this massively parallel and quantitative label-free approach to obtaining basic enzymological constants will facilitate the study of proteolysis and other posttranslational modifications in complex mixtures.

SUBMITTER: Agard NJ

PROVIDER: S-EPMC3277568 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Global kinetic analysis of proteolysis via quantitative targeted proteomics.

Agard Nicholas J NJ Mahrus Sami S Trinidad Jonathan C JC Lynn Aenoch A Burlingame Alma L AL Wells James A JA

Proceedings of the National Academy of Sciences of the United States of America 20120123 6

Mass spectrometry-based proteomics is a powerful tool for identifying hundreds to thousands of posttranslational modifications in complex mixtures. However, it remains enormously challenging to simultaneously assess the intrinsic catalytic efficiencies (k(cat)/K(M)) of these modifications in the context of their natural interactors. Such fundamental enzymological constants are key to determining substrate specificity and for establishing the timing and importance of cellular signaling. Here, we ...[more]

PMID: 22308409

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Project description:Quantitative proteomics strategies - which are playing important roles in the expanding field of plant molecular systems biology - are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) - referred to as TDA/DDA - to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy.

Dataset Information

Global kinetic analysis of proteolysis via quantitative targeted proteomics.

Publications

Global kinetic analysis of proteolysis via quantitative targeted proteomics.

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