4.3 Article

Proteome dynamics from heavy water metabolic labeling and peptide tandem mass spectrometry

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Publisher

ELSEVIER
DOI: 10.1016/j.ijms.2019.116194

Keywords

In vivo protein turnover; Heavy water metabolic labeling; Protein half-life; Fragment ion quantification from deuterium labeled peptides

Funding

  1. National Institute of General Medical Sciences of the National Institutes of Health [R01GM112044]
  2. Gulf Coast Consortia, on the NLM Training Program in Biomedical Informatics and Data Science [T15LM007093]
  3. UTMB High School Summer Biomedical Research Program

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Protein homeostasis (proteostasis) is a result of a dynamic equilibrium between protein synthesis and degradation. It is important for healthy cell/organ functioning and is often associated with diseases such as neurodegenerative diseases and non-Alcoholic Fatty Liver disease. Heavy water metabolic labeling, combined with liquid-chromatography and mass spectrometry (LC-MS), is a powerful approach to study proteostasis in vivo in high throughput. Traditionally, intact peptide signals are used to estimate stable isotope incorporation in time-course experiments. The time-course of label incorporation is used to extract protein decay rate constant (DRC). Intact peptide signals, computed from integration in chromatographic time and mass-to-charge ratio (m/z) domains, usually, provide an accurate estimate of label incorporation. However, sample complexity (co-elution), limited dynamic range, and low signal-to-noise ratio (S/N) may adversely interfere with the peptide signals. These artifacts complicate the DRC estimations by distorting peak shape in chromatographic time and m/z domains. Fragment ions, on the other hand, are less prone to these artifacts and are potentially well suited in aiding DRC estimations. Here, we show that the label incorporation encoded into the isotope distributions of fragment ions reflect the isotope enrichment during the metabolic labeling with heavy water. We explore the label incorporation statistics for devising practical approaches for DRC estimations. Published by Elsevier B.V.

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