7.22C: Metabolomics

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Learning Objectives

Review metabolomics

Metabolomics is the scientific study of chemical processes involving metabolites. The metabolome represents the collection of all metabolites, which are the end products of cellular processes, in a biological cell, tissue, organ, or organism. Thus, while mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to give a more complete picture of living organisms.

History and Development

The idea that biological fluids reflect the health of an individual has existed for a long time. 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. GC-MS is a method that combines the features of gas-liquid chromatography and mass spectrometry to identify different substances within a test sample. 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 tissue 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.

Figure: **Gas Chromatography–mass spectrometry**: Gas chromatography–mass spectrometry (GC-MS) is a method that combines the features of gas-liquid chromatography and mass spectrometry to identify different substances within a test sample.

In 2005, the first metabolomics web database for characterizing human metabolites, METLIN, was developed in the Siuzdak laboratory at The Scripps Research Institute. METLIN contained over 10,000 metabolites and tandem mass spectral data. On January 23, 2007, the Human Metabolome Project, led by Dr. 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.

As late as mid-2010, metabolomics was still considered an “emerging field”. Further, it was noted that further progress in the field was in large part the result of addressing otherwise “irresolvable technical challenges” through technical evolution of mass spectrometry instrumentation. The word was coined in analogy with transcriptomics and proteomics. Like the transcriptome and the proteome, the metabolome is dynamic, changing from second to second. Although the metabolome can be defined readily enough, it is not currently possible to analyse the entire range of metabolites by a single analytical method.

Metabolites are the intermediates and products of metabolism. Within the context of metabolomics, a metabolite is usually defined as any molecule less than 1 kDa in size. However, there are exceptions to this, depending on the sample and detection method. Macromolecules such as lipoproteins and albumin are reliably detected in NMR-based metabolomics studies of blood plasma. In plant-based metabolomics, it is common to refer to “primary metabolites,” which are directly involved in growth, development and reproduction, and “secondary metabolites,” which are indirectly involved in growth, development and reproduction. In contrast, in human-based metabolomics it is more common to describe metabolites as being either endogenous (produced by the host organism) or exogenous. The metabolome forms a large network of metabolic reactions, where outputs from one enzymatic chemical reaction are inputs to other chemical reactions. Such systems have been described as hypercycles.

Separation methods: Gas chromatography, especially when interfaced with mass spectrometry (GC-MS), is one of the most widely used and powerful methods. It offers very high chromatographic resolution, but requires chemical derivatization for many biomolecules: only volatile chemicals can be analysed without derivatization.

Detection methods: Mass spectrometry (MS) is used to identify and to quantify metabolites after separation. Surface-based mass analysis has seen a resurgence in the past decade, with new MS technologies focused on increasing sensitivity, minimizing background, and reducing sample preparation.

Statistical methods: The data generated in metabolomics usually consist of measurements performed on subjects under various conditions. These measurements may be digitized spectra, or a list of metabolite levels. In its simplest form this generates a matrix with rows corresponding to subjects and columns corresponding to metabolite levels.

Key applications

Toxicity assessment/toxicology. Metabolic profiling, especially of urine or blood plasma samples, can be used to detect the physiological changes caused by toxic insult of a chemical or mixture of chemicals. This is of particular relevance to pharmaceutical companies wanting to test the toxicity of potential drug candidates.
Functional genomics. Metabolomics can be an excellent tool for determining the phenotype caused by a genetic manipulation, such as gene deletion or insertion. Sometimes this can be a sufficient goal in itself—for instance, to detect any phenotypic changes in a genetically-modified plant intended for human or animal consumption. More exciting is the prospect of predicting the function of unknown genes by comparison with the metabolic perturbations caused by deletion/insertion of known genes.

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