Proteomics turns functional

Highlights

• Proteomics generates new functional hypotheses by systems biology.

• Proteomics emergent properties are defined by pathway and network analyses.

• Interactomics data provides a snapshot of specific condition complexes.

• Terminomics reveals new functional outcomes of proteolysis.

Abstract

Proteomics is acquiring a pivotal role in the comprehensive understanding of human biology. Biochemical processes involved in complex diseases, such as neurodegenerative diseases, diabetes and cancer, can be identified by combining proteomics analysis and bioinformatics tools. In the last ten years, the main output of differential proteomics investigations evolved from long lists of proteins to the generation of new hypotheses and their functional verification. The Journal of Proteomics participated to this progress, reporting more and more biologically-oriented papers with functional interpretation of proteomics data. This change in the field was due to both technological development and novel strategies in exploiting the deep characterization of proteomes. In this review, we explore several approaches that allow proteomics to turn functional. In particular, systems biology tools for data analysis are now routinely used to interpret results, thus defining the biological meaning of differentially abundant proteins. Moreover, by considering the importance of protein-protein interactions and the composition of macromolecular complexes, interactomics is complementing the information given by differential quantitative proteomics. Eventually, terminomics is unveiling new functions for cleaved proteoforms, by analyzing the effect of proteolysis globally.

Significance

Proteomics is rapidly evolving not only technologically but also strategically. The correct interpretation of proteomics data can reveal new functions of proteins in several biological backgrounds. Systems biology tools allow researchers to formulate new hypotheses to be further functionally tested. Interactomics is shedding new light on protein complexes truly involved in biochemical pathways and how their alteration can lead to dysfunctionality (in disease pathogenesis, for example). Terminomics is revealing the function of new discovered proteoforms and attributing a novel role to proteolysis. This review would provide the biologist important insights into current applications of several proteomic approaches that could offer new strategies to investigate biological systems.

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.