Interactive proteomics: what lies ahead?

Mass spectrometry for proteomics-based investigation

Within the past years, we have witnessed a great improvement in mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify proteins but also to identify the protein's posttranslational modifications (PTMs), protein isoforms, protein truncation, protein-protein interaction (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in scientific and clinical settings in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Applications of Mass Spectrometry in Proteomics

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

Mitochondrial proteomics--a tool for the study of metabolic disorders

Mitochondria are important for a number of life and death processes, such as energy production, creation of reactive oxygen species, and elicitation of stress responses. These responses range from induction of protein quality control and antioxidant systems to mitochondria elimination and cell death. Mitochondrial dysfunctions are involved in pathologies associated with many diseases, for example metabolic disorders, diabetes, cancers, cardiovascular and neurodegenerative diseases as well as obesity and aging. Mitochondrial proteomics can be a powerful tool in the study of these diseases, especially since it can cover mitochondrial proteins from several metabolic pathways, such as the citric acid cycle, fatty acid oxidation, and respiratory chain, as well as protein networks involved in stress responses. The mitochondrial proteome can consist of more than 1,000 different proteins. However, it is difficult to define the precise number, since mitochondria are dynamic and difficult to purify, and because an unknown number of proteins possess dual or multiple localization, depending on cell type and physiological conditions. This review describes several quantitative studies of proteins from mitochondria isolated by centrifugation, separated by various methods (e.g., electrophoresis and nanoLC), and analyzed by advanced mass spectrometry. We illustrate the methods by showing that multiple pathways and networks are affected in cells from patients carrying gene variations affecting a mitochondrial protein. The study of cultured skin fibroblasts from patients with ethylmalonic aciduria associated with variations in the genes coding for short-chain acyl-CoA dehydrogenase (SCAD) or ETHE1 are two of the examples. The possibility of obtaining mitochondrial proteomics data from whole cell proteomics studies is also exemplified by the involvement of liver mitochondria in metabolic syndrome.

Investigation of membrane protein interactions using the split-ubiquitin membrane yeast two-hybrid system

Proteins are generally organized into molecular complexes, in which multiple interaction partners collaborate to carry out cellular processes. Thus, techniques to map protein-protein interactions have become pivotal for biological studies of as yet uncharacterized proteins. Investigation of interaction partners of membrane proteins is of special interest, as they play a major role in cellular processes and are often directly linked to human diseases. Owing to their hydrophobic nature, however, it has proven difficult to study their interaction partners. To circumvent this problem, a yeast-based genetic technology for the in vivo detection of membrane protein interactions, the split-ubiquitin membrane yeast two-hybrid (MYTH) system, has been developed. MYTH allows for detection of both stable and transient interactions and can be applied to large- and small-scale screens. It uses the split-ubiquitin approach, in which the reconstitution of two ubiquitin halves is mediated by a specific protein-protein interaction. Briefly, the bait membrane protein is fused to the C-terminal half of ubiquitin and an artificial transcription factor. The mutated N-terminal moiety of ubiquitin is fused to the prey protein. Upon interaction of bait and prey proteins, ubiquitin is reconstituted and further recognized by ubiquitin-specific proteases, which subsequently cleave off the transcription factor, thus resulting in reporter gene activation. To date, MYTH has been successfully applied to study interactions of membrane proteins from various organisms and has only recently been adapted for the identification of interaction partners of mammalian receptor tyrosine kinases.

Photoactivable peptides for identifying enzyme-substrate and protein-protein interactions

Photoactivated cross-linking of peptides to proteins is a useful strategy for identifying enzyme-substrate and protein-protein interactions in cell lysates as demonstrated by studies on the human hypoxia inducible factor system.

Encoding the states of interacting proteins to facilitate biological pathways reconstruction

Background

In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruction of biological pathways.

Results

We propose a logical model of PPI that takes into account the "state" of proteins before and after the interaction. This information is necessary for proper reconstruction of the pathway.

Conclusions

The adoption of the proposed model, which can be easily integrated into existing machine-readable formats used to store the PPI data, would facilitate the automatic or semi-automated reconstruction of biological pathways.

Reviewers

This article was reviewed by Dr. Wen-Yu Chung (nominated by Kateryna Makova), Dr. Carl Herrmann (nominated by Dr. Purificación López-García) and Dr. Arcady Mushegian.

Rapid interactome profiling by massive sequencing

We have developed a high-throughput protein expression and interaction analysis platform that combines cDNA phage display library selection and massive gene sequencing using the 454 platform. A phage display library of open reading frame (ORF) fragments was created from mRNA derived from different tissues. This was used to study the interaction network of the enzyme transglutaminase 2 (TG2), a multifunctional enzyme involved in the regulation of cell growth, differentiation and apoptosis, associated with many different pathologies. After two rounds of panning with TG2 we assayed the frequency of ORFs within the selected phage population using 454 sequencing. Ranking and analysis of more than 120 000 sequences allowed us to identify several potential interactors, which were subsequently confirmed in functional assays. Within the identified clones, three had been previously described as interacting proteins (fibronectin, SMOC1 and GSTO2), while all the others were new. When compared with standard systems, such as microtiter enzyme-linked immunosorbant assay, the method described here is dramatically faster and yields far more information about the interaction under study, allowing better characterization of complex systems. For example, in the case of fibronectin, it was possible to identify the specific domains involved in the interaction.

Array MAPPIT: high-throughput interactome analysis in mammalian cells

Physical interactions between proteins play a key role in probably every cellular process. Efforts to chart the protein interaction networks are ongoing in a number of model organisms using a diversity of approaches. The resulting genome-wide interaction maps will provide a scaffold for further detailed functional analysis. We developed MAPPIT, a mammalian two-hybrid approach that allows identification and analysis of mammalian protein-protein interactions in their native environment. Here, we introduce an efficient MAPPIT assay that permits high-throughput screening of arrayed collections of proteins and complements a previously published cDNA library screening approach. We validated both methods in screens for interaction partners of the Cullin-based E3 ubiquitin ligase subunits SKP1 and Elongin C. In addition to a number of known interactors, novel SKP1 and Elongin C binding proteins were identified. The array assay is an important addition to the MAPPIT suite of technologies that is expected to significantly increase its utility as a toolbox to screen for novel interactors of proteins or small molecules.

Literature-curated protein interaction datasets

High quality datasets are needed to understand how global and local properties of protein-protein interaction, or “interactome”, networks relate to biological mechanisms, and to guide research on individual proteins. Evaluations of existing curation of protein interaction experiments reported in the literature find that curation can be error prone and possibly of lower quality than commonly assumed.

Knowledgebase for addiction-related genes: is it possible an extrapolation to rational multi-target drug design?

In recent years the single-probe-single-target approach in drug design has started to be smoothly replaced by the single-probe-multiple-target (or multi-target) one, where a single drug is able to tackle different, but disease-related targets in a selective manner. However, the design of multi-target drugs has been hindered by a lack of a systematic network of disease-related common pathways. The recent development of the knowledgebase of addiction-related genes (KARG) has provided important hints on how to rationally design multi-target probes by connecting experimental techniques with available network models. In this perspective, the use of KARG as a template to build knowledgebases of disease-related genes for the rational multi-target drug design is suggested. Moreover, it is proposed that building knowledgebases of disease-related genes will become a necessary and ubiquitous tool in the rational design of multi-target drugs.

Cellular membranes and lipid-binding domains as attractive targets for drug development

Interdisciplinary research focused on biological membranes has revealed them as signaling and trafficking platforms for processes fundamental to life. Biomembranes harbor receptors, ion channels, lipid domains, lipid signals, and scaffolding complexes, which function to maintain cellular growth, metabolism, and homeostasis. Moreover, abnormalities in lipid metabolism attributed to genetic changes among other causes are often associated with diseases such as cancer, arthritis and diabetes. Thus, there is a need to comprehensively understand molecular events occurring within and on membranes as a means of grasping disease etiology and identifying viable targets for drug development. A rapidly expanding field in the last decade has centered on understanding membrane recruitment of peripheral proteins. This class of proteins reversibly interacts with specific lipids in a spatial and temporal fashion in crucial biological processes. Typically, recruitment of peripheral proteins to the different cellular sites is mediated by one or more modular lipid-binding domains through specific lipid recognition. Structural, computational, and experimental studies of these lipid-binding domains have demonstrated how they specifically recognize their cognate lipids and achieve subcellular localization. However, the mechanisms by which these modular domains and their host proteins are recruited to and interact with various cell membranes often vary drastically due to differences in lipid affinity, specificity, penetration as well as protein-protein and intramolecular interactions. As there is still a paucity of predictive data for peripheral protein function, these enzymes are often rigorously studied to characterize their lipid-dependent properties. This review summarizes recent progress in our understanding of how peripheral proteins are recruited to biomembranes and highlights avenues to exploit in drug development targeted at cellular membranes and/or lipid-binding proteins.

Resolving the network of cell signaling pathways using the evolving yeast two-hybrid system

In 1983, while investigators had identified a few human proteins as important regulators of specific biological outcomes, how these proteins acted in the cell was essentially unknown in almost all cases. Twenty-five years later, our knowledge of the mechanistic basis of protein action has been transformed by our increasingly detailed understanding of protein-protein interactions, which have allowed us to define cellular machines. The advent of the yeast two-hybrid (Y2H) system in 1989 marked a milestone in the field of proteomics. Exploiting the modular nature of transcription factors, the Y2H system allows facile measurement of the activation of reporter genes based on interactions between two chimeric or "hybrid" proteins of interest. After a decade of service as a leading platform for individual investigators to use in exploring the interaction properties of interesting target proteins, the Y2H system has increasingly been applied in high-throughput applications intended to map genome-scale protein-protein interactions for model organisms and humans. Although some significant technical limitations apply, Y2H has made a great contribution to our general understanding of the topology of cellular signaling networks.