Literature DB >> 15801735

Determination of fractional synthesis rates of mouse hepatic proteins via metabolic 13C-labeling, MALDI-TOF MS and analysis of relative isotopologue abundances using average masses.

Josef A Vogt1, Christian Hunzinger, Klaus Schroer, Kerstin Hölzer, Anke Bauer, André Schrattenholz, Michael A Cahill, Simone Schillo, Gerhard Schwall, Werner Stegmann, Gerd Albuszies.   

Abstract

Proteins of a liver extract taken from a metabolically (13)C-labeled mouse were separated by 2D-PAGE and identified after tryptic digestion by MALDI-TOF MS peptide mass fingerprinting. (13)C-Labeling of proteins was achieved by an infusion of U-(13)C-glucose, which is metabolized to labeled nonessential amino acids. The labeling was analyzed using the relative isotopologue abundances of the measured isotope pattern of tryptic peptides and quantified by their increase in the average molecular mass (DeltaAVM). Fractional synthesis rates (FSR) of proteins were determined from corresponding peptides using measured DeltaAVM values as well as DeltaAVM values deduced from tRNA-precursor amino acid labeling, which in turn was derived from proteins showing high (13)C enrichments. The 8-h FSR values of 43 proteins were determined to range from 0 +/- 0.6 to 95 +/- 1%/8 h, with typical errors given as SEM values, which depend on the number of peptides of a specific protein usable for calculation. The method demonstrates that FSR values as an indicator for protein turnover in the liver proteome can be estimated within narrow error margins, providing baseline values from which treatment-dependent deviations could be detected with high statistical certainty.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15801735     DOI: 10.1021/ac048722m

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


  8 in total

Review 1.  Proteome dynamics: revisiting turnover with a global perspective.

Authors:  Amy J Claydon; Robert Beynon
Journal:  Mol Cell Proteomics       Date:  2012-11-02       Impact factor: 5.911

Review 2.  Mitochondrial protein turnover: methods to measure turnover rates on a large scale.

Authors:  X'avia C Y Chan; Caitlin M Black; Amanda J Lin; Peipei Ping; Edward Lau
Journal:  J Mol Cell Cardiol       Date:  2014-11-11       Impact factor: 5.000

3.  Measuring protein synthesis using metabolic ²H labeling, high-resolution mass spectrometry, and an algorithm.

Authors:  Takhar Kasumov; Serguey Ilchenko; Ling Li; Nadia Rachdaoui; Rovshan G Sadygov; Belinda Willard; Arthur J McCullough; Stephen Previs
Journal:  Anal Biochem       Date:  2011-01-20       Impact factor: 3.365

4.  Quantitative proteomics: measuring protein synthesis using 15N amino acid labeling in pancreatic cancer cells.

Authors:  Yingchun Zhao; Wai-Nang Paul Lee; Shu Lim; Vay Liang Go; Jing Xiao; Rui Cao; Hengwei Zhang; Robert Roy Recker; Gary Guishan Xiao
Journal:  Anal Chem       Date:  2009-01-15       Impact factor: 6.986

Review 5.  Quantitative proteomics and biomarker discovery in human cancer.

Authors:  Yingchun Zhao; Wai-Nang Paul Lee; Gary Guishan Xiao
Journal:  Expert Rev Proteomics       Date:  2009-04       Impact factor: 3.940

6.  A mass spectrometry workflow for measuring protein turnover rates in vivo.

Authors:  Mihai Alevra; Sunit Mandad; Till Ischebeck; Henning Urlaub; Silvio O Rizzoli; Eugenio F Fornasiero
Journal:  Nat Protoc       Date:  2019-11-04       Impact factor: 13.491

7.  SILAM for quantitative proteomics of liver Akt1/PKBα after burn injury.

Authors:  X-M Lu; R G Tompkins; A J Fischman
Journal:  Int J Mol Med       Date:  2011-12-14       Impact factor: 4.101

8.  Proteome Dynamics: Tissue Variation in the Kinetics of Proteostasis in Intact Animals.

Authors:  Dean E Hammond; Amy J Claydon; Deborah M Simpson; Dominic Edward; Paula Stockley; Jane L Hurst; Robert J Beynon
Journal:  Mol Cell Proteomics       Date:  2016-02-01       Impact factor: 5.911

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.