Journal of Systems Biology & Proteome Research

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Perspective - Journal of Systems Biology & Proteome Research (2022) Volume 3, Issue 5

Protein turnover analysis in metabolic labeling studies

Alexander Donald *

Oncology Department, Antwerp University Hospital, Wilrijkstraat 10, Belgium

*Corresponding Author:
Alexander Donald
Oncology Department, Antwerp University Hospital, Wilrijkstraat 10, Belgium
E-mail: [email protected]

Received: 05-Sep -2022, Manuscript No. AASBPR-22-78352; Editor assigned: 06-Sep-2022, PreQC No. AASBPR-22-78352 (PQ); Reviewed: 20-Sep -2022, QC No. AASBPR-22-78352; Revised: 21-Sep -2022, Manuscript No. AASBPR-22-78352 (R); Published: 28-Sep -2022, DOI:10.35841/aacmt-3.5.124

Citation: Donald. A. Protein turnover analysis in metabolic labeling studies. J Syst Bio Proteome Res. 2022;3(5):124

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Abstract

The benefits of stable isotope labelling for proteomics have gradually come to light. However, a lot of stable isotope labelling techniques rely on labelling in vitro with intricate and occasionally pricey chemicals. The methodologies for labelling proteins in vivo through metabolic incorporation of labels into proteins are covered in this article. Although this method has several benefits and is particularly well adapted to single cells grown in culture (prokaryotic or eukaryotic), there are still a number of complicated elements that need to be controlled in order to conduct relevant studies. The metabolic instability of the precursor amino acid, insufficient labelling, and the impact of protein turnover on labelling kinetics are all confounding factors. If the proper safety measures are taken, all of these are manageable. This parameter's acquisition over a number of proteins enables comparisons between various tissues and the turnover profiling of cellular proteins. Muscle protein degrades on average at a far slower rate than liver or kidney, with the heart falling somewhere in the middle.

Introduction

New methods for analysing the study of gene expression at the protein level have been developed as a result of the rapidly expanding field of functional genomics, and proteomics in particular. There are several fresh and newly developed methods for the separation, analysis, and identification of proteins in the current literature. Mass spectrometric techniques that use gentle ionisation procedures and moderate to high resolution mass analyzers are almost solely used in proteome analysis to offer reliable mass determination, whether of a collection of proteolytic fragments or of the entire protein. It is premature to predict that protein microarrays would replace mass spectrometry for global proteomics, despite early evidence of their relevance for some areas of quantitative proteomics [1].

Protein microarrays, on the other hand, are likely to be concentrated on selective examination of a small number of analytes in, for instance, molecular diagnostics. High sensitivity, universal detection (in the context of proteomics), unparalleled molecular selectivity, and the opportunity for exact quantification are all advantages of mass spectrometry. Unit mass resolution across the usable mass range is more than adequately provided by the current generation of readily accessible mass spectrometers. It is now possible to create mass tagging techniques for the differential analysis of protein expression at this level of performance. In order to compare two biological states, a protein or signature peptide is marked with an isotopically labelled tag that comes in "light" and "heavy" varieties, and the analytes are mixed before analysis [2,3].

Comparative expression analysis is therefore made possible by mass spectrometric measurement of the heavy/light ratio, which is unaffected by factors like instrument response, sample quality, and so forth. To date, comparative proteomics, in which the insertion of a metabolic label is employed to identify one of the components in a pair-wise comparison, has received the majority of attention regarding stable isotope labelling in vivo. Although it may seem simple, this strategy has a number of presumptions that are not always rigorously evaluated. In order to use the heavy/light ratio as a direct indicator of the relative concentrations of the analyte in the two systems, it is first assumed that the proteins have been completely tagged with the stable isotope precursor [4,].

Second, it's frequently believed that the stable isotope label in the precursor amino acid is not differentially processed and does not show up in another amino acid. It's also important to note that some amino acids that are non-essential in intact mammals are necessary for cultured cells (possibly reflecting the roles of different cell types in biosynthesis of amino acids). For instance, although though it is produced in the urea cycle processes, arginine is frequently added to the culture medium. This is likely done to prevent the depletion of the arginine pool by protein synthesis, which would impair the performance of this crucial metabolic cycle. Additionally, because they are metabolically extremely labile, some amino acids are quickly deaminated or transaminated, producing carbon skeletons that can be oxidised or utilised in other biosynthetic pathways. This might lead to a rapid recycling of the label into different amino acid pools, which might alter the pattern of isotope incorporation into proteins and deplete the labelled precursor [5,].

conclusion

Although there has been a lot of interest in stable isotope labelling in vitro, labelling in vivo has only recently been thoroughly investigated in terms of its extent and applicability. There is growing expertise working with increasingly complicated systems, such entire animals, which is particularly suited to cells developed in culture. These investigations have established that in complex systems where comprehensive labelling is challenging, if not impossible to achieve, metabolic labelling may not be an option for comparative proteomics. Even in these systems, it is possible to track labelling rates, which makes it possible to study the dynamics of the proteome.

References

  1. Barry R, Soloviev M. . Quantitative protein profiling using antibody arrays . Proteomics. 2004;4(12):3717-26.
  2. Indexed at, Google Scholar, Cross Ref

  3. 2. Parker KC, Patterson D, Williamson B, et al .. Depth of proteome issues: a yeast isotope-coded affinity tag reagent study . MCP. 2004;3(7):625-59.
  4. Indexed at, Google Scholar, Cross Ref

  5. Yu LR, Conrads TP, Uo T, et al. Evaluation of the acid-cleavable isotope-coded affinity tag reagents: application to camptothecin-treated cortical neurons . J Proteome Res. 2004;3(3):469-77.
  6. Indexed at, Google Scholar, Cross Ref

  7. Thevis M, Ogorzalek Loo RR, Loo JA. In-gel derivatization of proteins for cysteine-specific cleavages and their analysis by mass spectrometry . J Proteome Res. 2003;2(2):163-72.
  8. Indexed at, Google Scholar, Cross Ref

  9. Blagoev B, Kratchmarova I, Ong SE, et al. A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling. Nat Biotechnol. 2003;21(3):315-8.
  10. Indexed at, Google Scholar, Cross Ref

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