Metabolic profiles of dystrophin and utrophin expression in mouse models of Duchenne muscular dystrophy

Biomarkers in Duchenne Muscular Dystrophy

PURPOSE OF REVIEW

This review highlights the key studies investigating various types of biomarkers in Duchenne muscular dystrophy (DMD).

RECENT FINDINGS

Several proteomic and metabolomic studies have been undertaken in both human DMD patients and animal models of DMD that have identified potential biomarkers in DMD. Although there have been a number of proteomic and metabolomic studies that have identified various potential biomarkers in DMD, more definitive studies still need to be undertaken in DMD patients to firmly correlate these biomarkers with diagnosis, disease progression, and monitoring the effects of novel treatment strategies being developed.

Complementary NAD+ replacement strategies fail to functionally protect dystrophin-deficient muscle

BACKGROUND

Duchenne muscular dystrophy (DMD) is a progressive muscle wasting disorder stemming from a loss of functional dystrophin. Current therapeutic options for DMD are limited, as small molecule modalities remain largely unable to decrease the incidence or mitigate the consequences of repetitive mechanical insults to the muscle during eccentric contractions (ECCs).

METHODS

Using a metabolomics-based approach, we observed distinct and transient molecular phenotypes in muscles of dystrophin-deficient MDX mice subjected to ECCs. Among the most chronically depleted metabolites was nicotinamide adenine dinucleotide (NAD), an essential metabolic cofactor suggested to protect muscle from structural and metabolic degeneration over time. We tested whether the MDX muscle NAD pool can be expanded for therapeutic benefit using two complementary small molecule strategies: provision of a biosynthetic precursor, nicotinamide riboside, or specific inhibition of the NAD-degrading ADP-ribosyl cyclase, CD38.

RESULTS

Administering a novel, potent, and orally available CD38 antagonist to MDX mice successfully reverted a majority of the muscle metabolome toward the wildtype state, with a pronounced impact on intermediates of the pentose phosphate pathway, while supplementing nicotinamide riboside did not significantly affect the molecular phenotype of the muscle. However, neither strategy sustainably increased the bulk tissue NAD pool, lessened muscle damage markers, nor improved maximal hindlimb strength following repeated rounds of eccentric challenge and recovery.

CONCLUSIONS

In the absence of dystrophin, eccentric injury contributes to chronic intramuscular NAD depletion with broad pleiotropic effects on the molecular phenotype of the tissue. These molecular consequences can be more effectively overcome by inhibiting the enzymatic activity of CD38 than by supplementing nicotinamide riboside. However, we found no evidence that either small molecule strategy is sufficient to restore muscle contractile function or confer protection from eccentric injury, undermining the modulation of NAD metabolism as a therapeutic approach for DMD.

Metabolomics Analysis of Skeletal Muscles from FKRP-Deficient Mice Indicates Improvement After Gene Replacement Therapy

Muscular dystrophy-dystroglycanopathies comprise a heterogeneous and complex group of disorders caused by loss-of-function mutations in a multitude of genes that disrupt the glycobiology of α-dystroglycan, thereby affecting its ability to function as a receptor for extracellular matrix proteins. Of the various genes involved, FKRP codes for a protein that plays a critical role in the maturation of a novel glycan found only on α-dystroglycan. Yet despite knowing the genetic cause of FKRP-related dystroglycanopathies, the molecular pathogenesis of disease and metabolic response to therapeutic intervention has not been fully elucidated. To address these challenges, we utilized mass spectrometry-based metabolomics to generate comprehensive metabolite profiles of skeletal muscle across diseased, treated, and normal states. Notably, FKRP-deficient mice elicit diverse metabolic abnormalities in biomarkers of extracellular matrix remodeling and/or aging, pentoses/pentitols, glycolytic intermediates, and lipid metabolism. More importantly, the restoration of FKRP protein activity following AAV-mediated gene therapy induced a substantial correction of these metabolic impairments. While interconnections of the affected molecular mechanisms remain unclear, our datasets support the notion that global metabolic profiling can be valuable for determining the involvement of previously unsuspected regulatory or pathological pathways as well as identifying potential targets for drug discovery and diagnostics.

Age-dependent changes in metabolite profile and lipid saturation in dystrophic mice

Duchenne Muscular Dystrophy (DMD) is a fatal X-linked genetic disorder. In DMD, the absence of the dystrophin protein causes decreased sarcolemmal integrity resulting in progressive replacement of muscle with fibrofatty tissue. The effects of lacking dystrophin on muscle and systemic metabolism are still unclear. Therefore, to determine the impact of the absence of dystrophin on metabolism, we investigated the metabolic and lipid profile at two different, well-defined stages of muscle damage and stabilization in mdx mice. We measured NMR-detectable metabolite and lipid profiles in the serum and muscles of mdx mice at 6 and 24 weeks of age. Metabolites were determined in muscle in vivo using ¹ H MRI/MRS, in isolated muscles using ¹ H-HR-MAS NMR, and in serum using high resolution ¹ H/¹³ C NMR. Dystrophic mice were found to have a unique lipid saturation profile compared with control mice, revealing an age-related metabolic change. In the 6-week-old mdx mice, serum lipids were increased and the degree of lipid saturation changed between 6 and 24 weeks. The serum taurine-creatine ratio increased over the life span of mdx, but not in control mice. Furthermore, the saturation index of lipids increased in the serum but decreased in the tissue over time. Finally, we demonstrated associations between MRI-T₂ , a strong indicator of inflammation/edema, with tissue and serum lipid profiles. These results indicate the complex temporal changes of metabolites in the tissue and serum during repetitive bouts of muscle damage and regeneration that occur in dystrophic muscle.

Circulating Biomarkers for Duchenne Muscular Dystrophy

Duchenne muscular dystrophy is the most common form of muscular dystrophy. Genetic and biochemical research over the years has characterized the cause, pathophysiology and development of the disease providing several potential therapeutic targets and/or biomarkers. High throughput - omic technologies have provided a comprehensive understanding of the changes occurring in dystrophic muscles. Murine and canine animal models have been a valuable source to profile muscles and body fluids, thus providing candidate biomarkers that can be evaluated in patients. This review will illustrate known circulating biomarkers that could track disease progression and response to therapy in patients affected by Duchenne muscular dystrophy. We present an overview of the transcriptomic, proteomic, metabolomics and lipidomic biomarkers described in literature. We show how studies in muscle tissue have led to the identification of serum and urine biomarkers and we highlight the importance of evaluating biomarkers as possible surrogate endpoints to facilitate regulatory processes for new medicinal products.

Metabolomics of ApcMin/+ mice genetically susceptible to intestinal cancer

Background

To determine how diets high in saturated fat could increase polyp formation in the mouse model of intestinal neoplasia, Apc^Min/+, we conducted large-scale metabolome analysis and association study of colon and small intestine polyp formation from plasma and liver samples of Apc^Min/+ vs. wild-type littermates, kept on low vs. high-fat diet. Label-free mass spectrometry was used to quantify untargeted plasma and acyl-CoA liver compounds, respectively. Differences in contrasts of interest were analyzed statistically by unsupervised and supervised modeling approaches, namely Principal Component Analysis and Linear Model of analysis of variance. Correlation between plasma metabolite concentrations and polyp numbers was analyzed with a zero-inflated Generalized Linear Model.

Results

Plasma metabolome in parallel to promotion of tumor development comprises a clearly distinct profile in Apc^Min/+ mice vs. wild type littermates, which is further altered by high-fat diet. Further, functional metabolomics pathway and network analyses in Apc^Min/+ mice on high-fat diet revealed associations between polyp formation and plasma metabolic compounds including those involved in amino-acids metabolism as well as nicotinamide and hippuric acid metabolic pathways. Finally, we also show changes in liver acyl-CoA profiles, which may result from a combination of Apc^Min/+-mediated tumor progression and high fat diet. The biological significance of these findings is discussed in the context of intestinal cancer progression.

Conclusions

These studies show that high-throughput metabolomics combined with appropriate statistical modeling and large scale functional approaches can be used to monitor and infer changes and interactions in the metabolome and genome of the host under controlled experimental conditions. Further these studies demonstrate the impact of diet on metabolic pathways and its relation to intestinal cancer progression. Based on our results, metabolic signatures and metabolic pathways of polyposis and intestinal carcinoma have been identified, which may serve as useful targets for the development of therapeutic interventions.

Modeling inflammatory bowel disease: the zebrafish as a way forward

The zebrafish has proved to be an informative model of vertebrate development and, more recently, an emerging model of human disease. The realization of the full potential of the zebrafish as a disease model lies in two interdependent areas. The first is an appreciation that the often overlooked strength of this species lies in allowing the design of experiments that address the interplay of genetics and the environment in a manipulable manner. The second is in the application and further development of gene targeting approaches. These twin features will be addressed in this review in the context of modeling inflammatory bowel disease.

Taurine detected using high-resolution magic angle spinning (1)H nuclear magnetic resonance: A potential indicator of early myocardial infarction

Magnetic resonance spectroscopy (MRS) is a unique non-invasive method for detecting cardiac metabolic changes. However, MRS in cardiac diagnosis is limited due to insensitivity and low efficiency. Taurine (Tau) is the most abundant free amino acid in the myocardium. We hypothesized that Tau levels may indicate myocardial ischemia and early infarction. Sprague-Dawley rats were divided into seven groups according to different time points during the course of myocardial ischemia, which was induced by left anterior descending coronary artery ligation. Infarcted myocardial tissue was obtained for high-resolution magic angle spinning (1)H nuclear magnetic resonance (NMR) analysis. Results were validated via high-performance liquid chromatography. The Tau levels in the ischemic myocardial tissue were reduced significantly within 5 min compared with those in the control group (relative ratio from 20.27±6.48 to 8.81±0.04, P<0.05) and were maintained for 6 h post-ischemia. Tau levels declined more markedly (56.5%) than creatine levels (48.5%) at 5 min after ligation. This suggests that Tau may have potential as an indicator in the early detection of myocardial ischemia by (1)H MRS.

Metabolomics as a tool for cardiac research

Metabolomics represents a paradigm shift in metabolic research, away from approaches that focus on a limited number of enzymatic reactions or single pathways, to approaches that attempt to capture the complexity of metabolic networks. Additionally, the high-throughput nature of metabolomics makes it ideal to perform biomarker screens for diseases or follow drug efficacy. In this Review, we explore the role of metabolomics in gaining mechanistic insight into cardiac disease processes, and in the search for novel biomarkers. High-resolution NMR spectroscopy and mass spectrometry are both highly discriminatory for a range of pathological processes affecting the heart, including cardiac ischemia, myocardial infarction, and heart failure. We also discuss the position of metabolomics in the range of functional-genomic approaches, being complementary to proteomic and transcriptomic studies, and having subdivisions such as lipidomics (the study of intact lipid species). In addition to techniques that monitor changes in the total sizes of pools of metabolites in the heart and biofluids, the role of stable-isotope methods for monitoring fluxes through pathways is examined. The use of these novel functional-genomic tools to study metabolism provides a unique insight into cardiac disease progression.

From cancer metabolism to new biomarkers and drug targets

Great interest is presently given to the analysis of metabolic changes that take place specifically in cancer cells. In this review we summarize the alterations in glycolysis, glutamine utilization, fatty acid synthesis and mitochondrial function that have been reported to occur in cancer cells and in human tumors. We then propose considering cancer as a system-level disease and argue how two hallmarks of cancer, enhanced cell proliferation and evasion from apoptosis, may be evaluated as system-level properties, and how this perspective is going to modify drug discovery. Given the relevance of the analysis of metabolism both for studies on the molecular basis of cancer cell phenotype and for clinical applications, the more relevant technologies for this purpose, from metabolome and metabolic flux analysis in cells by Nuclear Magnetic Resonance and Mass Spectrometry technologies to positron emission tomography on patients, are analyzed. The perspectives offered by specific changes in metabolism for a new drug discovery strategy for cancer are discussed and a survey of the industrial activity already going on in the field is reported.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

Applications of metabolomics and proteomics to the mdx mouse model of Duchenne muscular dystrophy: lessons from downstream of the transcriptome

Functional genomic studies are dominated by transcriptomic approaches, in part reflecting the vast amount of information that can be obtained, the ability to amplify mRNA and the availability of commercially standardized functional genomic DNA microarrays and related techniques. This can be contrasted with proteomics, metabolomics and metabolic flux analysis (fluxomics), which have all been much slower in development, despite these techniques each providing a unique viewpoint of what is happening in the overall biological system. Here, we give an overview of developments in these fields 'downstream' of the transcriptome by considering the characterization of one particular, but widely used, mouse model of human disease. The mdx mouse is a model of Duchenne muscular dystrophy (DMD) and has been widely used to understand the progressive skeletal muscle wasting that accompanies DMD, and more recently the associated cardiomyopathy, as well as to unravel the roles of the other isoforms of dystrophin, such as those found in the brain. Studies using proteomics, metabolomics and fluxomics have characterized perturbations in calcium homeostasis in dystrophic skeletal muscle, provided an understanding of the role of dystrophin in skeletal muscle regeneration, and defined the changes in substrate energy metabolism in the working heart. More importantly, they all point to perturbations in proteins, metabolites and metabolic fluxes reflecting mitochondrial energetic alterations, even in the early stage of the dystrophic pathology. Philosophically, these studies also illustrate an important lesson relevant to both functional genomics and the mouse phenotyping in that the knowledge generated has advanced our understanding of cell biology and physiological organization as much as it has advanced our understanding of the disease.

Technology insight: metabonomics in gastroenterology-basic principles and potential clinical applications

Metabonomics-the study of metabolic changes in an integrated biologic system-is an emerging field. This discipline joins the other 'omics' (genomics, transcriptomics and proteomics) to give rise to a comprehensive, systems-biology approach to the evaluation of holistic in vivo function. Metabonomics, especially when based on nuclear magnetic resonance spectroscopy, has the potential to identify biomarkers and prognostic factors, enhance clinical diagnosis, and expand hypothesis generation. As a consequence, the use of metabonomics has been extensively explored in the past decade, and applied successfully to the study of human diseases, toxicology, microbes, nutrition, and plant biology. This Review introduces the basic principles of nuclear magnetic resonance spectroscopy and commonly used tools for multivariate data analysis, before considering the applications and future potential of metabonomics in basic and clinical research, with emphasis on applications in the field of gastroenterology.

A combined metabolomic and proteomic investigation of the effects of a failure to express dystrophin in the mouse heart

Muscle degeneration in the heart of 1-9 month-old mdx mice (a model for Duchenne muscular dystrophy) has been monitored using metabolomic and proteomic approaches. In both data sets, a pronounced aging trend was detected in control and mdx mice, and this trend was separate from the disease process. In addition, the characteristic increase in taurine associated with dystrophic tissue is correlated with proteins associated with oxidative phosphorylation and mitochondrial metabolism.

From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics

Mass spectrometry (MS) is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research. Its utility derives from its wide dynamic range, reproducible quantitative analysis, and the ability to analyze biofluids with extreme molecular complexity. The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites. In this review, we will discuss the techniques involved in this exciting area and the current and future applications of this field.

Metabolomics as a functional genomic tool for understanding lipid dysfunction in diabetes, obesity and related disorders

With the rise of systems biology, a number of approaches have been developed to globally profile a tier of organization in a cell, tissue or organism. Metabolomics is an approach that attempts to profile all the metabolites in a biological matrix. One of the major challenges of this approach, as with other 'omic' technologies, is that the metabolome is context-dependent and will vary with pathology, developmental stage and environmental factors. Thus, the possibility of globally profiling the metabolome of an organism is a genuine analytical challenge, as by definition this must also take into consideration all relevant factors that influence metabolism. Despite these challenges, the approach has already been applied to understand the metabolism in a range of animal models, and has more recently started to be projected into the clinical situation. In this review, the technologies currently being used in metabolomics will be assessed prior to examining their use to study diseases related to the metabolic syndrome, including Type II diabetes, obesity, cardiovascular disease and fatty liver disease.

Understanding mouse models of disease through metabolomics

Metabolomics is widely applicable to a number of fields including toxicology, plant metabolism and functional genomics. In the area of functional genomics, a number of studies have demonstrated the potential of this approach, which combines high-throughput metabolite profiling with computer-assisted pattern recognition approaches. In this review, recent applications of metabolomics to understanding mouse models of disease are considered. This includes studies on the impact of mouse strain on disease models, as well as metabolic profiling of cardiovascular, metabolic and neurodegenerative diseases. This versatile tool is set to increase in popularity as functional genomic approaches produce more mouse models for phenotyping.

The application of NMR-based metabonomics in neurological disorders

Advances in postgenomic technologies have radically changed the information output from complex biological systems, generating vast amounts of high complexity data that can be interpreted by means of chemometric and bioinformatic methods to achieve disease diagnosis and prognosis. High-resolution nuclear magnetic resonance (NMR) spectroscopy of biofluids such as plasma, cerebrospinal fluid (CSF), and urine can generate robust, interpretable metabolic fingerprints that contain latent information relating to physiological or pathological status. This technology has been successfully applied to both preclinical and clinical studies of neurodegenerative diseases such as Huntington's disease, muscular dystrophy, and cerebellar ataxia. An extension of this technology, (1)H magic-angle-spinning (HRMAS) NMR spectroscopy, can be used to generate metabolic information on small intact tissue samples, providing a metabolic link between metabolic profiling of biofluids and histology. In this review we provide a summary of high-resolution NMR studies in neurodegenerative disease and explore the potential of metabonomics in evaluating disease progression with respect to therapeutic intervention.

The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics

The measurement of metabolite profiles that are interpreted to yield biomarkers using multivariate data analysis is now a well-established approach for gaining an improved understanding of the impact of genetic modifications, toxicological and therapeutic interventions, and exposure to stimuli (e.g., noxious agents, stressors, nutrients) on the network of transcripts, proteins, and metabolites present in cells, tissues, or whole organisms. This has been termed metabonomics. In this study, multivariate analysis of (1)H nuclear magnetic resonance (NMR) spectra of metabolite profiles of urine and plasma from 150 healthy humans revealed that in young people and/or individuals with low body mass indexes, females had higher rates of lipid biosynthesis than did males, whereas males had higher rates of protein turnover than did females. With increasing age, overall lipid biosynthesis decreased in females, whereas metabolism increasingly favored lipid synthesis over protein turnover in males. By relating the derived metabonomic data to known metabolic pathways and published biochemical data, it appears that females synthesize relatively more lipoproteins and unsaturated lipids than do males. Furthermore, the changes in lipid biosynthesis and urinary citrate excretion in females showed a positive correlation. Estrogen most likely plays an essential role in the regulation of, and communication between, protein and lipid biosynthesis by controlling pH in mitochondria and the cytoplasm and hence the observed altered citrate levels.

Magnetic resonance imaging for detection and analysis of mouse phenotypes

With the enormous and growing number of experimental and genetic mouse models of human disease, there is a need for efficient means of characterizing abnormalities in mouse anatomy and physiology. Adaptation of magnetic resonance imaging (MRI) to the scale of the mouse promises to address this challenge and make major contributions to biomedical research by non-invasive assessment in the mouse. MRI is already emerging as an enabling technology providing informative and meaningful measures in a range of mouse models. In this review, recent progress in both in vivo and post mortem imaging is reported. Challenges unique to mouse MRI are also identified. In particular, the needs for high-throughput imaging and comparative anatomical analyses in large biological studies are described and current efforts at handling these issues are presented.

A Functional Analysis of Mouse Models of Cardiac Disease through Metabolic Profiling

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. Tools are needed for assessing the phenotypes of the many mouse models that are now being generated, where genes have been "knocked out," "knocked in," or mutated, so that gene expression can be understood in its biological context. Metabolic profiling of cardiac tissue through high resolution NMR spectroscopy in conjunction with multivariate statistics has been used to classify mouse models of cardiac disease. The data sets included metabolic profiles from mouse models of Duchenne muscular dystrophy, two models of cardiac arrhythmia, and one of cardiac hypertrophy. The metabolic profiles demonstrate that the strain background is an important component of the global metabolic phenotype of a mouse, providing insight into how a given gene deletion may result in very different responses in diverse populations. Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease. Thus, this approach is a rapid method of phenotyping mouse models of disease.

The potential of metabonomics in drug safety and toxicology

Metabonomics (or metabolomics) defines a global profile of the metabolites in a cell, tissue or organism using either (1)H NMR spectroscopy or mass spectrometry in conjunction with statistical pattern recognition. Unlike other functional genomic tools, it is high-throughput and cheap on a per sample basis, providing a rapid screen for large scale drug toxicity testing and screening of large populations. However, for its widespread use in toxicology there is an urgent need for biomarker databases.:

Metabolic profiles to define the genome: can we hear the phenotypes?

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified by the description of the silent phenotype in genetic manipulations of yeast. High-resolution proton nuclear magnetic resonance ((1)H NMR) spectroscopy provides an ideal mechanism for the profiling of metabolites within biofluids, tissue extracts or, with recent advances, intact tissues. These metabolic datasets can be readily mined using a range of pattern recognition techniques, including hierarchical cluster analysis, principal components analysis, partial least squares and neural networks, with the combined approach being termed metabolomics. This review describes the application of NMR-based metabolomics or metabonomics to genetic and chemical interventions in a number of different species, demonstrating the versatility of such an approach, as well as suggesting how it may be integrated with other "omic" technologies.

Advancing drug discovery through systems biology

Pharmaceutical companies are facing an urgent need to both increase their lead compound and clinical candidate portfolios and satisfy market demands for continued innovation and revenue growth. Here, we outline an emerging approach that attempts to facilitate and alleviate many of the current drug discovery issues and problems. This is, in part, achieved through the systematic integration of technologies, which results in a superior output of data and information, thereby enhancing our understanding of biological function, chemico-biological interactions and, ultimately, drug discovery. Systems biology is one new discipline that is positioned to significantly impact this process.