Proteome

Proteome

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The proteome may be thought of as the realization of the information encoded in the genome. Quantifying the proteome is the domain of 2D-gel electrophoresis, tandem affinity purification, or other methods capable of accurately separating proteins or protein complexes, followed by the identification of proteins through mass-spectroscopy. The proteome is not merely a reflection of the organism's genes, it has its own levels of regulation among which differentially spliced isoforms and extensive post-translational modifications underly a variability that can not be directly inferred from genome sequences alone.

 

Introductory reading

Jones & Hubbard (2010) An introduction to proteome bioinformatics. Methods Mol Biol 604:1-5. (pmid: 20013360)

[ PubMed ] [ DOI ] This book is part of the Methods in Molecular Biology series, and provides a general overview of computational approaches used in proteome research. In this chapter, we give an overview of the scope of the book in terms of current proteomics experimental techniques and the reasons why computational approaches are needed. We then give a summary of each chapter, which together provide a picture of the state of the art in proteome bioinformatics research.

 

Contents

• Sample identification by fingerprinting
• Sample identification from MS/MS data
• relative vs. quantitative proteomics
• Proteome databases (PeptideAtlas, PRIDE)
• Transcriptome / Proteome correlation: codon usage or more?

   

Further reading and resources

Beltrao et al. (2007) Structures in systems biology. Curr Opin Struct Biol 17:378-84. (pmid: 17574836)

[ PubMed ] [ DOI ] Oil and water do not normally mix, and apparently structural biology and systems biology look like two different universes. It can be argued that structural biology could play a very important role in systems biology. Although at the final stage of understanding a signal transduction pathway, a cell, an organ or a living system, structures could be obviated, we need them to be able to reach that stage. Structures of macromolecules, especially molecular machines, could provide quantitative parameters, help to elucidate functional networks or enable rational designed perturbation experiments for reverse engineering. The role of structural biology in systems biology should be to provide enough understanding so that macromolecules can be translated into dots or even into equations devoid of atoms.

Matthiesen & Amorim (2010) Proteomics facing the combinatorial problem. Methods Mol Biol 593:175-86. (pmid: 19957150)

[ PubMed ] [ DOI ] A large number of scoring functions for ranking peptide matches to observed MS/MS spectra have been discussed in the literature. In contrast to scoring functions, search strategies have received less attention, and an accurate description of search algorithms is limited. Proteomics is becoming more and more commonly used in potential clinical applications; for such approaches to be successful, the combinatorial problems from amino acid modifications and somatic and heredity SAPs (single amino acid substitutions) need to be seriously considered. The modifications and SAPs are problematic since MS and MS/MS search algorithms are optimization processes, which means that if the correct match is not iterated through during the search, then the data will be matched incorrectly, resulting in serious downstream flaws. This chapter discusses several search algorithm strategies in more detail.

Jung (2010) Statistical methods for proteomics. Methods Mol Biol 620:497-507. (pmid: 20652518)

[ PubMed ] [ DOI ] During the last decade, analytical methods for the detection and quantification of proteins and peptides in biological samples have been considerably improved. It is therefore now possible to compare simultaneously the expression levels of hundreds or thousands of proteins in different types of tissue, for example, normal and cancerous, or in different cell lines. In this chapter, we illustrate statistical designs for such proteomics experiments as well as methods for the analysis of resulting data. In particular, we focus on the preprocessing and analysis of protein expression levels recorded by the use of either two-dimensional gel electrophoresis or mass spectrometry.