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Metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind" - specifically, the study of their small-molecule metabolite profiles[1] The metabolome represents the collection of all metabolites in a biological organism, which are the end products of its gene expression. 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 is to integrate proteomics, transcriptomics, and metabolomics information to give a more complete picture of living organisms.

The word metabonomics is also used, particularly in the context of drug toxicity assessment. There is some disagreement over the exact differences between 'metabolomics' and 'metabonomics'; in general, the term 'metabolomics' is more commonly used. However, the original distinction, which might have been forgotten, was that metaboNomics utilizes NMR as its analysis tool, while Metabolomics does not use NMR (and uses GC-MS).


Metabolic biochemists have arguably been 'doing metabolomics' for decades. It has been suggested that the concept of metabolomics is foreshadowed by Linus Pauling's work toward "orthomolecular medicine" and his hypotheses regarding the predictive capacity of chromatographic profiling of bodily fluids for detection and diagnosis of human disease. However, the common use of the term and the identification of metabolomics as a distinct scientific field is much more recent, with the earliest published references in the scientific literature dating from the late 1990s and early 2000s. Many of the bioanalytical methods used for metabolomics have been adapted (or in some cases simply adopted) from existing biochemical techniques, and thus there are not always clear distinctions between studies that are described as metabolomic and studies that are concerned with metabolism. However, metabolomic research has two characteristics: 1. Metabolites are profiled without bias towards a specific metabolite or group of metabolites 2. Relationships between the metabolites are characterized, currently mostly by multivariate methods.

Analytical technologies: separation methodsEdit

There are two issues to be addressed for metabolite analysis: 1. separation of the analytes, usually by chromatography. Electrophoresis, particularly capillary electrophoresis, is also used. 2. Detection of the analytes, following separation by chromatographic or other 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. (Some modern instruments allow '2D' chromatography, using a short polar column after the main analytical column, which increases the resolution still further.) Some large and polar metabolites cannot be analysed by GC.
  • High performance liquid chromatography (HPLC). Compared to GC, HPLC has lower chromatographic resolution, but it does have the advantage that a much wider range of analytes can potentially be measured.
  • Capillary electrophoresis (CE). So far, there are only a relatively small number of publications on use of CE for metabolite profiling. This will no doubt change, as there are a number of advantages of CE: it has a higher theoretical separation efficiency than HPLC, and is suitable for use with a wider range of metabolite classes than is GC. As for all electrophoretic techniques, it is most appropriate for charged analytes.

Analytical technologies: detection methodsEdit

  • Mass spectrometry (MS) is used to identify and to quantify metabolites after separation by GC, HPLC, or CE. GC-MS is the most 'natural' combination of the three, and was the first to be developed. In addition, mass spectral fingerprint libraries exist or can be developed that allow identification of a metabolite according to its fragmentation pattern. MS is both sensitive (although, particularly for HPLC-MS, sensitivity is more of an issue as it is affected by the charge on the metabolite, and can be subject to ion suppression artifacts) and can be very specific. There are also a number of studies which use MS as a stand-alone technology: the sample is infused directly into the mass spectrometer with no prior separation, and the MS serves to both separate and to detect metabolites.
  • Nuclear magnetic resonance (NMR) spectroscopy. NMR is the only detection technique which does not rely on separation of the analytes, and the sample can thus be recovered for further analyses. All kinds of small molecule metabolite can be measured simultaneously - NMR is close to being a universal detector. However, it also possesses one major disadvantage, which is that it is relatively insensitive compared to mass spectrometry-based techniques.
  • Other techniques. MS and NMR are by far the two leading technologies for metabolomics. Other methods of detection that have been used include electrochemical detection (coupled to HPLC) and radiolabel (when combined with thin-layer chromatography).

See: Dunn, W.B. and Ellis, D.I. (2005) Metabolomics: current analytical platforms and methodologies. Trends in Analytical Chemistry 24(4), 285-294. Ellis, D.I. and Goodacre, R. (2006) Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy. Analyst 131, 875-885. DOI:10.1039/b602376m

Key applicationsEdit

  • 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). In many cases, the observed changes can be related to specific syndromes, e.g. a specific lesion in liver or kidney. This is of particular relevance to pharmaceutical companies wanting to test the toxicity of potential drug candidates: if a compound can be eliminated before it reaches clinical trials on the grounds of adverse toxicity, it saves the enormous expense of the trials.
  • 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. Such advances are most likely to come from model organisms such as Saccharomyces cerevisiae and Arabidopsis thaliana.
  • Nutrigenomics is a generalised term which links genomics, transcriptomics, proteomics and metabolomics to human nutrition. In general a metabolome in a given body fluid is influenced by endogenous factors such as age, sex, body composition and genetics as well as underlying pathologies. The large bowel microflora are also a very significant potential confounder of metabolic profiles and could be classified as either an endogenous or exogenous factor. The main exogenous factors are diet and drugs. Diet can then be broken down to nutrients and non- nutrients. Metabolomics is one means to determine a biological endpoint, or metabolic fingerprint, which reflects the balance of all these forces on an individual's metabolism. Please consult the external link to NuGo below

External linksEdit

See alsoEdit


  1. ^  B. Daviss, "Growing pains for metabolomics," The Scientist, 19[8]:25-28, April 25, 2005.
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