Literature DB >> 25301408

Kinetics of precursor labeling in stable isotope labeling in cell cultures (SILAC) experiments.

Tian Zhang1, John C Price, Eslam Nouri-Nigjeh, Jun Li, Marc K Hellerstein, Jun Qu, Sina Ghaemmaghami.   

Abstract

Recent advances in mass spectrometry have enabled proteome-wide analyses of cellular protein turnover. These studies have been greatly propelled by the development of stable isotope labeling in cell cultures (SILAC), a set of standardized protocols, reagents aimed at quantifying the incorporation of (15)N/(13)C labeled amino acids into proteins. In dynamic SILAC experiments, the degree of isotope incorporation in proteins is measured over time and used to determine turnover kinetics. However, the kinetics of isotope incorporation in proteins can potentially be influenced not only by their intracellular turnover but also by amino acid uptake, recycling and aminoacyl-tRNA synthesis. To assess the influence of these processes in dynamic SILAC experiments, we have measured the kinetics of isotopic enrichment within intracellular free amino acid and aminoacyl-tRNA precursor pools in dividing and division-arrested neuroblastoma cells following the introduction of extracellular (15)N labeled amino acids. We show that the total flux of extracellular amino acids into cells greatly exceeds that of intracellular amino acid recycling and synthesis. Furthermore, in comparison to internal sources, external amino acids are preferentially utilized as substrates for aminoacyl-tRNA precursors for protein synthesis. As a result, in dynamic SILAC experiments conducted in culture, the aminoacyl-tRNA precursor pool is near completely labeled in a few hours and protein turnover is the limiting factor in establishing the labeling kinetics of most proteins.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25301408     DOI: 10.1021/ac503067a

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

1.  Poisson Model To Generate Isotope Distribution for Biomolecules.

Authors:  Rovshan G Sadygov
Journal:  J Proteome Res       Date:  2017-12-19       Impact factor: 4.466

Review 2.  Recent advances in quantitative and chemical proteomics for autophagy studies.

Authors:  Yin-Kwan Wong; Jianbin Zhang; Zi-Chun Hua; Qingsong Lin; Han-Ming Shen; Jigang Wang
Journal:  Autophagy       Date:  2017-08-18       Impact factor: 16.016

3.  Proteome-wide modulation of degradation dynamics in response to growth arrest.

Authors:  Tian Zhang; Clara Wolfe; Andrew Pierle; Kevin A Welle; Jennifer R Hryhorenko; Sina Ghaemmaghami
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-13       Impact factor: 11.205

4.  Global analysis of protein degradation in prion infected cells.

Authors:  Charles R Hutti; Kevin A Welle; Jennifer R Hryhorenko; Sina Ghaemmaghami
Journal:  Sci Rep       Date:  2020-07-01       Impact factor: 4.379

5.  JNK modifies neuronal metabolism to promote proteostasis and longevity.

Authors:  Lifen Wang; Sonnet S Davis; Martin Borch Jensen; Imilce A Rodriguez-Fernandez; Cagsar Apaydin; Gabor Juhasz; Bradford W Gibson; Birgit Schilling; Arvind Ramanathan; Sina Ghaemmaghami; Heinrich Jasper
Journal:  Aging Cell       Date:  2019-02-27       Impact factor: 9.304

6.  Global Analysis of Cellular Protein Flux Quantifies the Selectivity of Basal Autophagy.

Authors:  Tian Zhang; Shichen Shen; Jun Qu; Sina Ghaemmaghami
Journal:  Cell Rep       Date:  2016-03-03       Impact factor: 9.423

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.