Standards requirements for systems biology approaches to health care: mitochondrial proteomics

A review of the standards needs of the mitochondrial proteomics communities is presented based on the presentations and discussions at National Institute of Standards and Technology (NIST) workshop, Systems Biology Approaches to Health Care: Mitochondrial Proteomics, held on September 17-18, 2002. The mitochondrial proteomics areas addressed for standards needs are model systems, methods and data. This review outlines the challenges in the field, proposes standards efforts that the community would like to see pursued to meet those challenges, and is followed by a summary and NIST's planned efforts to address these standards requirements.     

Introduction to proteomics: tools for the new biology

Towards revolutionary biomarkers, a considerable amount of research funds and time have been dedicated to proteomics. Although the discovery of novel biomarkers at the dawn of proteomics was a promising development, only a few identified biomarkers seemed to be beneficial for cancer patients. We may need to approach this issue differently, instead of only extending the conventional approaches that have been used historically. The study of biomarkers is essentially a study of diseases and the biochemistry relating to peptide, protein and post-translational modifications is only a tool. A problem-oriented approach should be needed in biomarker development. Clinician participation in the study of biomarkers will lead to realistic, practical and interesting biomarker candidates, which justify the time and expense involved in validation studies. Although discussion in this article is focused on cancer biomarkers, it can generally be applied to biomarker studies for other diseases.     

Protease proteomics: revealing protease in vivo functions using systems biology approaches

Proteases irreversibly modify proteins by cleaving their amide bonds and are implicated in virtually every important biological process such as immunity, development and tissue repair. Accordingly, it is easy to see that deregulated proteolysis is a pathognomic feature of many diseases. Most of the current information available on proteases was acquired using in vitro methods, which reveals molecular structure, enzyme kinetics and active-site specificity. However, considerably less is known about the relevant biological functions and combined roles of proteases in moulding the proteome. Although models using genetically modified animals are powerful, they are slow to develop, they can be difficult to interpret, and while useful, they remain only models of human disease. Therefore, to understand how proteases accomplish their tasks in organisms and how they participate in pathology, we need to elucidate the protease degradome-the repertoire of proteases expressed by a cell, a tissue or an organism at a particular time-their expression level, activation state, their biological substrates, also known as the substrate degradome-the repertoire of substrates for each protease-and the effect of the activity of each protease on the pathways of the system under study. Achieving this goal is challenging because several proteases might cleave the same protein, and proteases also form pathways and interact to form the protease web [Overall, C.M., Kleifeld, O., 2006. Tumour microenvironment - opinion: validating matrix metalloproteinases as drug targets and anti-targets for cancer therapy. Nat. Rev. Cancer 6 (3), 227-239]. Hence, the net proteolytic potential of the degradome at a particular time on a substrate and pathway must also be understood. Proteomics offers one of the few routes to the understanding of proteolysis in complex in vivo systems and especially in man where genetic manipulations are impossible. The aim of this chapter is to review methods and tools that allow researchers to study protease biological functions using proteomics and mass spectrometry. We describe methods to assess protease expression at the messenger RNA level using DNA microarrays and at the protein level using mass spectrometry-based proteomics. We also review methods to reveal and quantify the activity state of proteases and to identify their biological substrates. The information acquired using these high throughput, high content techniques can then be interpreted with different bioinformatics approaches to reveal the effects of proteolysis on the system under study. Systems biology of the protease web-degradomics in the broadest sense-promises to reveal the functions of proteases in homeostasis and in disease states. This will indicate which proteases participate in defined pathologies and will help targeting specific proteases for disease treatments.     

From proteomics toward systems biology: integration of different types of proteomics data into network models

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.     

From correlation to causation: analysis of metabolomics data using systems biology approaches

Introduction

Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

Objectives

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

Methods

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

Results

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

Conclusions

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

     

Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery

Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.     

Shotgun proteomics of bacterial pathogens: advances,challenges and clinical implications

Mass spectrometry-based proteomics is increasingly used in analysis of bacterial pathogens. Simple experimental set-ups based on high accuracy mass spectrometry and powerful biochemical and bioinformatics tools are capable of reliably quantifying levels of several thousand bacterial proteins in a single experiment, reaching the analytical capacity to completely map whole proteomes. Here the authors present the state-of-the-art in bacterial pathogen proteomics and discuss challenges that the field is facing, especially in analysis of low abundant, modified proteins from organisms that are difficult to culture. Constant improvements in speed and sensitivity of mass spectrometers, as well as in bioinformatic and biochemical workflows will soon allow for comprehensive analysis of regulatory mechanisms of pathogenicity and enable routine application of proteomics in the clinical setting.     

From bacterial genomics to metagenomics: concept,tools and recent advances

In the last 20 years, the applications of genomics tools have completely transformed the field of microbial research. This has primarily happened due to revolution in sequencing technologies that have become available today. This review therefore, first describes the discoveries, upgradation and automation of sequencing techniques in a chronological order, followed by a brief discussion on microbial genomics. Some of the recently sequenced bacterial genomes are described to explain how complete genome data is now being used to derive interesting findings. Apart from the genomics of individual microbes, the study of unculturable microbiota from different environments is increasingly gaining importance. The second section is thus dedicated to the concept of metagenomics describing environmental DNA isolation, metagenomic library construction and screening methods to look for novel and potentially important genes, enzymes and biomolecules. It also deals with the pioneering studies in the area of metagenomics that are offering new insights into the previously unappreciated microbial world. The authors have contributed equally to the work     

From systems biology to systems biomedicine

Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine.     

Simple chemical tools to expand the range of proteomics applications

Proteomics is an expanding technology with potential applications in many research fields. Even though many research groups do not have direct access to its main analytical technique, mass spectrometry, they can interact with proteomics core facilities to incorporate this technology into their projects. Protein identification is the analysis most frequently performed in core facilities and is, probably, the most robust procedure. Here we discuss a few chemical reactions that are easily implemented within the conventional protein identification workflow. Chemical modification of proteins with N-hydroxysuccinimide esters, 4-sulfophenyl isothiocyanate, O-methylisourea or through β-elimination/Michael addition can be easily performed in any laboratory. The reactions are quite specific with almost no side reactions. These chemical tools increase considerably the number of applications and have been applied to characterize protein-protein interactions, to determine the N-terminal residues of proteins, to identify proteins with non-sequenced genomes or to locate phosphorylated and O-glycosylated.     

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Proteomics approaches to the systems biology of cardiovascular diseases

Proteins play a central role in a systems view of biologic processes. This review provides an overview of proteomics from a systems perspective. We survey the key tools and methodologies used, present examples of how these are currently being used in the systems biology context, and discuss future directions.     

Software for systems biology: from tools to integrated platforms

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.