Proteomics turns functional
Graphical abstract
Introduction
Complex biological events usually involve the interplay of genes, transcripts, proteins, metabolites and lipids. Thus, the development of omics methodologies (genomics, proteomics, transcriptomics, metabolomics and lipidomics) can unravel new domains in the complexity of biological systems. In particular, the understanding of complex diseases (such as cancer or neurodegenerative diseases) takes advantage of these approaches, to identify the numerous genetic, epigenetic and environmental factors involved. Even more meaningful would be a global approach of integrated omics, where potentially all molecular factors (e.g., proteins, genes, transcripts) will be simultaneously measured over time in cells, networks of cells or whole organisms.
High-throughput proteomics approaches are used to quantify proteins, to localize and identify post-translational modifications and to study protein–protein interactions (PPI), specifically related to particular physiological or pathological conditions. In the past twenty years, proteomics approaches have evolved from the technological point of view and moved from the mere identification of proteins to their quantification and finally to post-translational modifications characterization [1,2]. These technological improvements aided the proteome depiction to turn functional. Indeed, proteomics started to have a pivotal role in the study of biological systems (Fig. 1) and became a tool for the identification of disease-related proteins. In this frame, the goal of differential proteomics studies profoundly changed. Initially, they were designed to generate long lists of differentially abundant proteins to be validated by an independent technique, such as Western blot. Nowadays, proteomics projects are hypothesis-generating and focused on a functional interpretation of results. Consequently, the Human Proteome Organization (HUPO) finalities also evolved. The aim of the chromosome-centric Human Proteome Project (C-HPP) was the identification and characterization of at least one protein product of the 20,300 human protein-coding genes, together with related post-translational modifications, single amino acid polymorphisms and splice variant isoforms [3]. Conversely, the Biology and Disease-driven Human Proteome Project (B/D-HPP) now aims at describing the molecular basis of physiological and pathological processes, by identifying the driver proteins involved.
The Journal of Proteomics witnessed this functional evolution, reporting papers more and more focused on the biological meaning of proteomics results. Technological advancements lead to a deeper characterization of proteomes. Therefore, more complete datasets are interpreted to highlight the emergent properties of the biomedical problem examined. Moreover, verification steps of more recent papers do not simply confirm the role of every single protein but aim at unveiling the biochemical pathways underlying biological processes.
In the present review, we will explore how proteomics turned functional in studying biochemical processes involved in disease pathogenesis, with a focus on systems biology tools for data analysis and on the development of specific proteomics branches, such as interactomics and terminomics.
Section snippets
Differential quantitative proteomics followed by systems biology unveils the biochemical pathways perturbed by diseases
Differential quantitative proteomics refers to the analysis of two or more groups of samples by globally and quantitatively comparing their proteomes. Mass spectrometry (MS) has become the method of choice in quantitative proteomics approaches, due to its unique ability to measure changes in complex protein mixtures [4]. Protein quantification was initially obtained by data dependent acquisition (DDA) methods, where only the most intense precursor ions eluting at a given time point in a
Interactomics contributes to the dynamic view of cellular functions
The quantitative proteomics approach unveils qualitative and quantitative changes of a specific proteome, though it does not give back any information about protein complexes in biological samples. Instead of analyzing proteins as single entities, the study of the interactome is essential to get a more dynamic and complete picture of cellular functions [31]. Indeed, interactomics approaches are essential to study the assembly of specific protein complexes and to highlight interaction changes
Positional proteomics reveals the functional effects of proteolysis
An underexplored aspect of the human proteome is the proteolytic processing of proteins, which gives rise to different proteoforms, sometimes with new functions. Degradomics is an expanding field in proteomics, whose aim is a comprehensive characterization of all proteases in a specific biological system, together with their protein targets. Over the past decade, a consistent amount of data regarding proteases was collected by degradomics studies. Unfortunately, protease substrates with
Conclusions
In conclusion, proteomics moved from being an isolated field to an integrated tool for biologists, both for the generation of new hypotheses and for the explanation of biological functions. New strategies to analyse and interpret proteomics data are influencing all the workflow of proteomics studies, from the study design to the verification step. In this last case, for example, it is not the identity of each single protein to be proved but the real involvement of a cellular pathway in a given
Acknowledgments
C.M. is grateful to Italian Proteomics Association (ItPA) and to European Proteomics Association (EuPA) for the continuous support with travel grants during her PhD program. We gratefully acknowledge Prof. Maria Monti for her kind help in the revision of the interactomics section.
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