Literature DB >> 19757418

Advances in protein turnover analysis at the global level and biological insights.

Qingbo Li1.   

Abstract

The concept of a dynamic state of body constituents, a precursor of the modern term of proteome dynamics, was conceived over a century ago. But, not until recently can we examine the dynamics of individual "constituents" for example, proteins at a truly global level. The path of advancement in our understanding of protein turnover at the global level is marked by the introduction of some key technological innovations. These methods include the isotopic tracer technique in the 1930s, the two-dimensional gel electrophoresis technique in the 1970s, the sector mass spectrometer that could analyze isotopomers of peptides in the early 1990s, the 2D gel/MALDI-TOF proteomics technology in the late 1990s, the booming liquid chromatography/mass spectrometry proteomics technology in this decade, and the recently emerging protein-tagging approaches that offer single-cell resolution for protein turnover measurements. The long-standing inquiry raised in the 1950s about the existence of a dynamic state in different organisms at different physiological conditions can now be answered with an individual "constituent" resolution on a truly global scale. Now it appears that protein degradation is not necessarily an end to the protein function. Rather, it can be the start of a new function because protein degradation clears the way for the action of other proteins. Protein turnover participates in a multi-layer complex regulatory network and shares equal importance with gene transcription and protein translation. The advances in technologies for protein turnover analysis and the improved understanding of the biological role of protein turnover will likely help to solve some long-standing biomedical problems such as the tuberculosis disease that at the present day still affects one-third of the world population. 2009 Wiley Periodicals, Inc.

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Year:  2010        PMID: 19757418     DOI: 10.1002/mas.20261

Source DB:  PubMed          Journal:  Mass Spectrom Rev        ISSN: 0277-7037            Impact factor:   10.946


  9 in total

1.  Acid stress response of a mycobacterial proteome: insight from a gene ontology analysis.

Authors:  Bryan Ap Roxas; Qingbo Li
Journal:  Int J Clin Exp Med       Date:  2009-11-10

2.  Degradation of protein translation machinery by amino acid starvation-induced macroautophagy.

Authors:  Christine Gretzmeier; Sven Eiselein; Gregory R Johnson; Rudolf Engelke; Heike Nowag; Mostafa Zarei; Victoria Küttner; Andrea C Becker; Kristoffer T G Rigbolt; Maria Høyer-Hansen; Jens S Andersen; Christian Münz; Robert F Murphy; Jörn Dengjel
Journal:  Autophagy       Date:  2017-04-28       Impact factor: 16.016

3.  Determining degradation and synthesis rates of arabidopsis proteins using the kinetics of progressive 15N labeling of two-dimensional gel-separated protein spots.

Authors:  Lei Li; Clark J Nelson; Cory Solheim; James Whelan; A Harvey Millar
Journal:  Mol Cell Proteomics       Date:  2012-01-03       Impact factor: 5.911

4.  Measuring the dynamics of E. coli ribosome biogenesis using pulse-labeling and quantitative mass spectrometry.

Authors:  Stephen S Chen; Edit Sperling; Josh M Silverman; Joseph H Davis; James R Williamson
Journal:  Mol Biosyst       Date:  2012-10-30

Review 5.  Mechanisms of protein balance in skeletal muscle.

Authors:  T G Anthony
Journal:  Domest Anim Endocrinol       Date:  2016-07       Impact factor: 2.290

6.  Gaussian Process Modeling of Protein Turnover.

Authors:  Mahbubur Rahman; Stephen F Previs; Takhar Kasumov; Rovshan G Sadygov
Journal:  J Proteome Res       Date:  2016-06-09       Impact factor: 4.466

7.  Elements of the cellular metabolic structure.

Authors:  Ildefonso M De la Fuente
Journal:  Front Mol Biosci       Date:  2015-04-28

8.  Degradation Parameters from Pulse-Chase Experiments.

Authors:  Celine Sin; Davide Chiarugi; Angelo Valleriani
Journal:  PLoS One       Date:  2016-05-16       Impact factor: 3.240

Review 9.  Protein turnover in mycobacterial proteomics.

Authors:  Prahlad K Rao; Qingbo Li
Journal:  Molecules       Date:  2009-08-28       Impact factor: 4.411

  9 in total

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