Literature DB >> 14595820

Approaches for the quantification of protein concentration ratios.

Bernd Moritz1, Helmut E Meyer.   

Abstract

The function of a protein is modulated by its abundance and its degree of specific post-translational modifications such as phosphorylation, glycosylation or truncation. Consequently, changes of protein concentration and the extent of their post-translational modifications has a great influence on the activity of intracellular substrate degradation processes, on the activity of intracellular biosynthetic pathways, on the cell cycle or on the function of a single cell in a whole organism. Defects in this area lead to diseases like cancer or neurodegeneration. Therefore, it is a challenge to quantify changes within the proteome in the diseased state or between developmental stages and to use the results obtained for the maximization of product yields in biotechnology or for the development of new drug targets to fight against diseases. In order to determine the intracellular concentration of a protein it is necessary to spike the cell sample with the same protein in a pure form. If the concentration changes of many proteins have to be determined, it takes a long time to obtain all these proteins in a pure form. Therefore, most approaches in this field are restricted to the determination of protein abundance ratios between two states such as diseased or healthy tissues. In this case the proteins in the sample of state A function as an internal standard for the proteins in the sample of state B and vice versa. The most common techniques in this field are the comparison of two-dimensional gel spot intensities after staining or the integration of mass spectrometric peak intensities after stable isotope labelling with (13)C, (15)N, (18)O or deuterium. The results, advantages and drawbacks of these approaches are discussed. Stable isotope labelling in combination with mass spectrometry is more accurate than the comparison of spot intensities and has the potential for the investigation of highly complex tissue samples.

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Year:  2003        PMID: 14595820     DOI: 10.1002/pmic.200300581

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  5 in total

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4.  MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides.

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5.  Plant cell wall proteomics: the leadership of Arabidopsis thaliana.

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  5 in total

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