Current Pharmaceutical Biotechnology - Volume 12, Issue 7, 2011

It is my great pleasure to present this issue of Current Pharmaceutical Biotechnology covering the area of metabolomics and specifically how this area of research currently is transitioning from the lab bench to the patient bedside. The term “metabolome” was coined by Professor Stephen Oliver in 1998 in relation to the “transcriptome” and “proteome” terminology. According to this definition, the “metabolome” is essentially the entire complement of small endogenous/exogenous molecules in a cell, tissue or whole organism at any given time. Metabolomics therefore becomes the experimental discipline dealing with the measurement of the “metabolome” and numerous more exact definitions of metabolomics have been proposed. To some extent, small endogenous molecules are the ultimate manifestation of the genes. Profiling small molecules therefore reveals aspects of gene activity as well as protein activity. The notion to measure concentration profiles of small molecules in order to gain insight into human physiology and pathology has been around for a very long time. With the advent of commercial gas chromatography coupled to mass spectrometry (GC-MS) in the mid 1960's some real analytical power was brought into this game and publications on the topic of “metabolite profiling” started to appear. In the 1980's nuclear magnetic resonance spectroscopy (NMR) added more strength to the field. Liquid chromatography coupled to mass spectrometry (LC-MS) paired with some serious developments in data analysis tools such as the chromatography alignment software XCMS developed in Professor Gary Siuzdak's lab at The Scripps Research Institute, have made it possible to produce very comprehensive quantitative profiles of the metabolome. Another significant contribution particularly towards human metabolomics is the Human Metabolome Project headed by Professor David Wishart at University of Alberta. This project includes the Human Metabolome Database that which contains information about over 7900 metabolites found in the human body. The advancements within the filed of metabolite profiling and metabolomics over the last two decades have been made possible through developments in analytical hardware and software. Small endogenous molecules play an instrumental role as biomarkers daily in clinics world wide today. Diseases like diabetes is constantly monitored via measurement of glucose and thousands of new born babies are screened daily for inborn errors of metabolism. Hopefully can today's metabolomics research result in novel discoveries of shifts in small molecule concentrations that can be associated with for example a disease state or drug efficacy and potentially can these shifts acts as guides towards new drug targets. The great contributions to this issue of Current Pharmaceutical Biotechnology is covering some of the cutting edge work in metabolomics and provides examples of how metabolomics today is moving into the hospitals and the patient bed sides. Donald Chace and Alan Spitzer at Pediatrix Medical Group, Florida, USA presents an excellent review of how tandem mass spectrometry (MS/MS) has been employed over the last 20 years for screening of inherited metabolic disease in newborns. They discuss lessons learned, and how these experiences can be used to further develop the filed of multiplexed MS/MS assays in newborn screening applications. M. Anas Kamleh, Konstantina Spagou and Elizabeth J. Want at Imperial College, London, UK have written a very exciting review article about technologies used for metabolomics and the role of metabolomics within disease diagnosis, toxicology and personalized healthcare. Mattias Eliasson, Stefan Rannar and Johan Trygg at Umea University, Umea, Sweden discusses some of the recent and most cited data processing methods and presents and overview over the metabolomics data processing pipeline. Michael A. Zulyniak and David M. Mutch at University of Guelph, Guelph, Canada have written an in depth review that on the topic of metabolomics and nutritional health. It highlights the importance and benefit of identifying biomarkers that accurately reflect changes in nutrient intake and metabolism as well as molecular pathways by which nutrients affect health and disease. N.W. Lutz, P.J. Cozzone at Centre de Resonance Magnetique Biologique et Medicale, Universite Aix-Marseille, France have written a review article on the topic of NMR metabolomics of Cerebrospinal fluid (CSF) for variety of neurological diseases and particularly multiple sclerosis. They dissect currently existing results discuss the potential and limitations of this approach......

The use of tandem mass spectrometry (MS/MS) for screening of inherited metabolic disease in newborns has afforded many unique opportunities in the understanding of the benefits early their early detection, diagnosis and treatment. From the standpoint of the laboratory and modern analytical methods, the use of MS based analysis demonstrated that a multiple metabolite-multiple disease screen-one method approach expanded screening significantly. MS/MS and newborn screening has served as a model of one type of approach in preventative health care that has shown proven benefits. It has been nearly 20 years since the introduction of MS/MS analysis of dried blood spots from newborns. There have been many lessons learned in both the analytical approach as well as follow-up at the bedside. These lessons can be applied to future applications of MS/MS in newborn screening as well as other areas of metabolism and metabolic profiles such as that from acquired disease, environmental disease and other factors such as nutrition and age. The use of a highly specific, sensitive and multiplex platform such as MS/MS will continue to grow and experience in the newborn screening application will insure this outcome.

Metabolic profiling employs a combination of sophisticated analytical tools to obtain global “untargeted” metabolic profiles from tissues, cells or biofluids. The resulting complex multivariate data are then modeled statistically to reveal differences between classes (e.g. dosed vs. control) and identify discriminatory metabolites. Metabolic profiling has a wide range of applications, encompassing nutrition, disease diagnosis, epidemiology and toxicology, providing insights into altered biological pathways and offering fresh mechanistic perspectives. Further, the untargeted nature of metabolic profiling can allow for new biomarkers of disease or toxic effect to be uncovered. In this review, key metabolic profiling technologies will be introduced and data analysis approaches described briefly. The role of metabolic profiling in disease diagnosis, toxicology and personalized healthcare will be discussed.

In metabolomics studies there is a clear increase of data. This indicates the necessity of both having a battery of suitable analysis methods and validation procedures able to handle large amounts of data. In this review, an overview of the metabolomics data processing pipeline is presented. A selection of recently developed and most cited data processing methods is discussed. In addition, commonly used chemometric and machine learning analysis methods as well as validation approaches are described.

Comprehensive analytical technologies are rapidly becoming a cornerstone of modern nutritional sciences. Two of these technologies, mass spectrometry (MS) and nuclear magnetic resonance (NMR), have proven highly informative for the global analysis of metabolites, commonly referred to as metabolomics. Metabolomics provides a powerful approach to study small molecules in order to better understand the implications and subtle perturbations in metabolism triggered by nutrients. By studying how dietary molecules can modulate the metabolome, researchers have begun to elucidate the molecular pathways by which nutrients affect health and disease, expand the current state of knowledge regarding how inter-individual variability contributes to differences in nutrient metabolism, and develop novel avenues of research for nutritional sciences. Although metabolomics has been more commonly used to study disease states, its use in the nutritional sciences is gaining momentum. The current review is written for the clinical researcher wishing to incorporate metabolomics into dietary intervention studies. This review will highlight the importance and benefit of identifying biomarkers that accurately reflect changes in nutrient intake and metabolism, and present numerous issues that can introduce variability into a dataset and confound a study's biological interpretation, including sample population demographics, the biological specimen selected, diurnal variation, collection methods, and sample storage parameters. Considering these important areas at the experimental design stage will ensure that metabolomics provides a comprehensive and accurate assessment of the molecular impact of a dietary intervention.

Cerebrospinal fluid (CSF) is being analyzed for the diagnosis of a variety of neurological diseases. Among the methods employed, metabolomics and proteomics are increasingly gaining popularity. At present, sensitivity and, in particular, specificity are limited in CSF metabolomics by nuclear magnetic resonance (NMR) spectroscopy. Nonetheless, progress is being made by studying more and more well-defined and homogeneous patient cohorts. This review starts off with a brief overview of classical CSF analysis in multiple sclerosis (MS), followed by a description of NMR spectroscopy in general metabolic CSF analysis. The subsequent sections focus on metabolomic profiling of CSF by NMR spectroscopy in MS and other neurological disorders. Currently existing results are reviewed and compared, and the potential and limits of this approach are discussed. In addition, several methodological questions are addressed, and the prospects for future developments are briefly outlined.

Oxylipins (e.g. eicosanoids) are endogenous signaling molecules that are formed from fatty acids by mono- or dioxygenase-catalyzed oxygenation and have been shown to play an important role in pathophysiological processes in the lung. These lipid mediators have been extensively for their role in inflammation in a broad swathe of respiratory diseases including asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis and extrinsic allergic alveolitis. Traditional efforts have employed analytical methods (e.g. radio- and enzyme-immunoassay techniques) capable of measuring a limited number of compounds simultaneously. The advent of the omics technologies is changing this approach and methods are being developed for the quantification of small molecules (i.e. metabolomics) as well as lipid-focused efforts (i.e. lipidomics). This review examines in detail the breadth of oxylipins and their biological activity in the respiratory system. In addition, the state-of-the-art methodology in profiling of oxylipins via mass spectrometry is summarized including sample work-up and data processing. These methods will greatly increase our ability to probe oxylipin biology and examine for cross-talk between biological pathways as well as specific compartments in the body. These new data will increase our insight into disease processes and have great potential to identify new biomarkers for disease diagnosis as well as novel therapeutic targets.

Metabolomics is only truly unbiased if the whole metabolome is captured. Current metabolomics technologies capture only a part of the metabolome and therefore produce inherently biased results. Important factors that introduce such bias into a metabolomic analysis may include but are not limited to, timing of sample collection, the sample collection procedure, sample processing, stabilization, stability and storage, extraction procedures, dilution of sample, type and number of analytical methods used, preferences of analytical assays for metabolites with certain physico-chemical properties, ion suppression (LC-MS), derivatization (GC-MS), sensitivity of the assay, range of reliable response and the ability to allow at least for semi-quantitative comparison. Consideration of the many computational, chemometric and biostatistical steps required to link changes in metabolite patterns to metabolic pathways and the additional bias and risks that these steps entail, brings up the question of whether or not screening for changes in known metabolic pathways using a set of validated, quantitative multiplexing LC-MS assays (targeted pathway screening, TAPAS) would be a more robust and reliable approach. Instead of non-selectively screening for changes in metabolite patterns, TAPAS screens for changes in metabolic pathways. Since such assays are designed for specific groups of metabolites, TAPAS can cover a larger number of metabolic pathways including metabolites of a wide variety of physicochemical properties and concentration ranges and thus, although based on a suite of targeted assays, TAPAS may ultimately be a less biased strategy than current nontargeted metabolomics technologies.

Hundreds of volatile organic compounds (VOCs) are released from human body fluids. Some of them are produced by endogenous metabolic processes in and on the body, and others are derived from the environment. Expressions of some endogenous VOCs can be affected by pathophysiological changes, and several disease-specific volatile biomarkers have been identified and used as diagnostic aids. Monitoring volatile disease markers is attractive since the procedure can be performed in a noninvasive manner with little or no exposure to biohazardous body fluids. Although many VOCs have been claimed as potential biomarkers, only a few compounds have been consistently demonstrated and approved for clinical applications. This is mainly because (1) many of the putative markers are present in the environment as well as in the body and their levels in the environment are often higher than those in the body, (2) there are a large individual variation in the concentrations of biomarkers within diseased and/or healthy subjects, and (3) the origin and biosynthetic pathway of the claimed biomarkers have been frequently neglected. Unfortunately, these aspects have often been ignored in many studies. Here, we review a number of publications that have identified volatile disease biomarkers in breath, argue that many of these have not demonstrated to actually underlie the differences in volatile profiles between diseased patients and healthy subjects, speculate on the reasons for this lack of success, and suggest potential approaches that may provide a better chance of identifying disease biomarkers.

Metabolomics and metabolic flux analysis (MFA) are powerful tools in the arsenal of methodologies of systems biology. Currently, metabolomics techniques are applied routinely for biomarker determination. However, standard metabolomics techniques only provide static information about absolute or relative metabolite amounts. The application of stable-isotope tracers has opened up a new dimension to metabolomics by providing dynamic information of intracellular fluxes and, by extension, enzyme activities. In the first part of the manuscript we review experimental and computational technologies applicable for metabolomics analyses. In the second part we present current technologies based on the use of stable isotopes and their applications to the analysis of cellular metabolism. Beginning with the determination of mass isotopomer distributions (MIDs), we review technologies for metabolic flux analysis (MFA) and conclude with the presentation of a new methodology for the non-targeted analysis of stable-isotope labeled metabolomics data.