This review summarises and discusses the degree to which proteomics is contributing to medical care, providing examples and signspots for future directions. Why do genomic approaches provide a limited view of gene expression? Because of the multifactorial nature of many diseases, proteomics enables us to understand the molecular basis of disease, not only at the organism, whole‐cell or tissue levels, but also in subcellular structures, protein complexes and biological fluids. The application of proteomics in medicine is expected to have a major impact by providing an integrated view of individual disease processes. This review describes several proteomic platforms and examines the role of proteomics as a tool for clinical biomarker discovery, the identification of prognostic and earlier diagnostic markers, their use in monitoring the effects of drug treatments and eventually find more efficient and safer therapeutics for a wide range of pathologies.

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Protein expression was assessed in samples of Pseudoscleropodium purum cross-transplanted between one unpolluted (UNP) and two polluted (POLL) sites. Firstly, the level of expression (LE) of 17 proteins differed between native mosses from both types of sites, but differences were only maintained throughout the experiment for 5 of them. The LE of these five proteins changed over time in mosses transplanted from UNP to POLL and vice versa, becoming similar to that in autotransplants. However, these changes occurred slower than changes in the heavy metal concentrations measured in the same samples, and therefore they were not related to atmospheric pollution. Although the proteins identified were associated with moss metabolism, the expected growth reduction in samples autotransplanted within POLL (as a result of the down-regulation of photosynthesis-related proteins), did not occur. This supports the hypothesis that mosses growing in polluted areas adapt to heavy metal pollution and are able to reduce/overcome their toxic effects (i.e., reduced growth). Nevertheless, further specific research must be carried out to identify the proteins involved in this type of response, as lack of information on the bryophyte genome precludes us from reaching further conclusions.

Vibrio tapetis is the etiological agent of brown ring disease (BRD) in clams. Phenotypic, antigenic and genetic variability have been demonstrated, with three groups being established associated with host origin. In this work we analyze the variability of representative strains of these three groups, CECT 4600(T) and GR0202RD, isolated from Manila clam and carpet-shell clam, respectively, and HH6087, isolated from halibut, on the basis of the whole proteome analysis by 2D-PAGE and multilocus sequence analysis (MLSA). A quantitative analysis of the proteome match coefficient showed a similarity of 79% between the clam isolates, whereas fish isolate showed similarities lower than 70%. A preliminary mass spectrometry (MS) assay allowed the identification of 27 proteins including 50S ribosomal protein L9, riboflavin synthase β subunit, ribose-phosphate pyrophosphokinase and succinyl-CoA synthase α subunit. The MLSA approach gave similar results, showing a 99.4% similarity of the clam isolates, which was higher than that observed between the fish isolate and either clam strain (98.2%). The topology of the maximum parsimony tree, obtained from 2D-PAGE analysis, and the phylogenetic tree, constructed with the maximum likelihood algorithm from concatenated sequences of 16S rRNA gene and five housekeeping genes (atpA, pyrH, recA, rpoA and rpoD), was very similar, confirming the closer relationship between the two clam isolates.

Because of the multifactorial nature of many diseases, two-dimensional electrophoresis is a basic proteomics tool for its ability of simultaneously detecting post-and co-translational modifications, which cannot be predicted from genome sequences.This review describes the central role of proteomics tool, two-dimensional electrophoresis for clinical biomarker discovery, the identification of prognostic and diagnostic markers, their use in monitoring the effects of drug treatments and eventually finding more efficient and safer therapeutics for a wide range of pathologies.