Metabolomics

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule intermediates and products of metabolism. Specifically, metabolomics is the 'systematic study of the unique chemical fingerprints that specific cellular processes leave behind', the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct 'functional readout of the physiological state' of an organism. One of the challenges of systems biology and functional genomics is to integrate genomics, transcriptomic, proteomic, and metabolomic information to provide a better understanding of cellular biology. Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule intermediates and products of metabolism. Specifically, metabolomics is the 'systematic study of the unique chemical fingerprints that specific cellular processes leave behind', the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct 'functional readout of the physiological state' of an organism. One of the challenges of systems biology and functional genomics is to integrate genomics, transcriptomic, proteomic, and metabolomic information to provide a better understanding of cellular biology. The beginning of metabolomics traces back to 2000-1500 B.C. At this time, Ancient Chinese doctors used ants for the evaluation of urine of patients to detect whether the urine contained high levels of glucose, and hence detect diabetes. In the Middle Ages, 'urine charts' were used to link the colours, tastes and smells of urine to various medical conditions, which are metabolic in origin. In 300 B.C., the ancient Greeks first use body fluids (called humor at the time) to predict disease, which shows the early steps towards metabolomics. Later in 131 A.D., Galen developed a system of pathology that combined the humoral theories of Hippocrates with the Pythagorean theory. Galen's theory was unchallenged and remained standard until the 17th century. The concept that individuals might have a 'metabolic profile' that could be reflected in the makeup of their biological fluids was introduced by Roger Williams in the late 1940s, who used paper chromatography to suggest characteristic metabolic patterns in urine and saliva were associated with diseases such as schizophrenia. However, it was only through technological advancements in the 1960s and 1970s that it became feasible to quantitatively (as opposed to qualitatively) measure metabolic profiles. The term 'metabolic profile' was introduced by Horning, et al. in 1971 after they demonstrated that gas chromatography-mass spectrometry (GC-MS) could be used to measure compounds present in human urine and tissue extracts. The Horning group, along with that of Linus Pauling and Arthur B. Robinson led the development of GC-MS methods to monitor the metabolites present in urine through the 1970s. Concurrently, NMR spectroscopy, which was discovered in the 1940s, was also undergoing rapid advances. In 1974, Seeley et al. demonstrated the utility of using NMR to detect metabolites in unmodified biological samples. This first study on muscle highlighted the value of NMR in that it was determined that 90% of cellular ATP is complexed with magnesium. As sensitivity has improved with the evolution of higher magnetic field strengths and magic angle spinning, NMR continues to be a leading analytical tool to investigate metabolism. Recent efforts to utilize NMR for metabolomics have been largely driven by the laboratory of Jeremy K. Nicholson at Birkbeck College, University of London and later at Imperial College London. In 1984, Nicholson showed 1H NMR spectroscopy could potentially be used to diagnose diabetes mellitus, and later pioneered the application of pattern recognition methods to NMR spectroscopic data. In 1995 liquid chromatography mass spectrometry metabolomics experiments were performed by Gary Siuzdak while working with Richard Lerner (then president of The Scripps Research Institute) and Benjamin Cravatt, to analyze the cerebral spinal fluid from sleep deprived animals. One molecule of particular interest, oleamide, was observed and later shown to have sleep inducing properties. This work is one of the earliest such experiments combining liquid chromatography and mass spectrometry in metabolomics. In 2005, the first metabolomics tandem mass spectrometry database, METLIN, for characterizing human metabolites was developed in the Siuzdak laboratory at The Scripps Research Institute. METLIN has since grown and as of July 1st 2019, METLIN contains over 450,000 metabolites and other chemical entities, each compound having experimental tandem mass spectrometry data generated from molecular standards at multiple collision energies and in positive and negative ionization modes. METLIN is the largest repository of tandem mass spectrometry data of its kind. In 2005, the Siuzdak lab was engaged in identifying metabolites associated with sepsis and in an effort to address the issue of statistically identifying the most relevant dysregulated metabolites across hundreds of LC/MS datasets, the first algorithm was developed to allow for the nonlinear alignment of mass spectrometry metabolomics data. Called XCMS, where the 'X' constitutes any chromatographic technology, it has since (2012) been developed as an online tool and as of 2019 (with METLIN) has over 30,000 registered users. On 23 January 2007, the Human Metabolome Project, led by David Wishart of the University of Alberta, Canada, completed the first draft of the human metabolome, consisting of a database of approximately 2500 metabolites, 1200 drugs and 3500 food components. Similar projects have been underway in several plant species, most notably Medicago truncatula and Arabidopsis thaliana for several years. As late as mid-2010, metabolomics was still considered an 'emerging field'. Further, it was noted that further progress in the field depended in large part, through addressing otherwise 'irresolvable technical challenges', by technical evolution of mass spectrometry instrumentation.