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. 2009 Dec 8:2009:239204.
doi: 10.4061/2009/239204.

Proteomics: challenges, techniques and possibilities to overcome biological sample complexity

Kondethimmanahalli Chandramouli  1 , Pei-Yuan Qian
Affiliations

Proteomics: challenges, techniques and possibilities to overcome biological sample complexity

Kondethimmanahalli Chandramouli et al. Hum Genomics Proteomics. .

Abstract

Proteomics is the large-scale study of the structure and function of proteins in complex biological sample. Such an approach has the potential value to understand the complex nature of the organism. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of proteome. Advances in protein fractionation and labeling techniques have improved protein identification to include the least abundant proteins. In addition, proteomics has been complemented by the analysis of posttranslational modifications and techniques for the quantitative comparison of different proteomes. However, the major limitation of proteomic investigations remains the complexity of biological structures and physiological processes, rendering the path of exploration paved with various difficulties and pitfalls. The quantity of data that is acquired with new techniques places new challenges on data processing and analysis. This article provides a brief overview of currently available proteomic techniques and their applications, followed by detailed description of advantages and technical challenges. Some solutions to circumvent technical difficulties are proposed.

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Figures

Figure 1
Figure 1
An overview of proteomic strategies.
Figure 2
Figure 2
2DE-DIGE subproteome profile of marine organism, Bryozoan Bugula neritina after IEF fractionation (pI 4.6–5.4) (a) Cy3 labeled swimming larvae, (b) Cy5 labeled settled larvae (c) Cy2 pooled internal standard.
Figure 3
Figure 3
iTRAQ work flow. Adapted from Bill Simon and Toni Slabas, Proteomics Facility, School of Biological and Biomedical Sciences, University of Durham, UK.
Figure 4
Figure 4
Applications of functional protein microarrays and tissue array.
Figure 5
Figure 5
Schematic representation of the different modules constituting a data analysis pipeline. RT: retention time; z: charge state; Int: signal intensity; Seq: peptide amino acid sequence; Prot: protein accession number and sequence; DB: database; Std: standard; MM: molecular mass. Adapted from: Bruno Domon and Ruedi Aebersold, Molecular & Cellular Proteomics 5:1921–1926, 2006.
Figure 6
Figure 6
Workflow for protein identification in cases where only little sequence information is available for the organism under investigation.
See this image and copyright information in PMC

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