Metabolomic is a newly emerging field of omics research concerns with the comprehensive characterization of small molecules (metabolites) in the biological system. It can provide an overview of the metabolic status and global biochemical events associated with cellular and biological systems, as such it can accurately depict both the steady-state and physiological state of cell or organism and their dynamic response to genetic, abiotic and biotic environmental modulation.
The terms metabolomics and metabonomics are often used interchangeably, the small distinction is that metabonomics is interested in a smaller set of metabolites, which have been changed as a result of stimuli, while metabolomics cover all the metabolome, so all the metabolites can be screened.
Fien had defined Metabolomics as “the quantitative measurement of the dynamic or time-related multi-parametric responses of the living systems to the pathophysiological stimuli or genetic modification “(1), it is has recently started to have a more important role in discovering biomarkers, physiological evaluation, drug safety measurements, diagnosis of human diseases, drug therapy monitoring, and characterization of genetically modified animal models (2, 3)
Metabonomics is typically performed on biofluids, such as serum, urine, saliva, and cerebrospinal fluid. In combination with (genomics which deals with gene identification, transcriptomics which indicates which gene is converted to transfer RNA (tRNA) and proteomics which indicates which RNA is translated to protein) together they would help researchers to understand the complete picture of the biological system and its response to any stimuli either disease or genetic modification etc… (4)
Metabolomics has also been traditionally used for analysis of plant metabolites, but plants have unique metabolites, which are present in higher organisms as xenobiotic.
The two key steps in metabonomics investigation are data collection of metabolite fingerprints (metabonome) and then data processing. These steps should be validated and calibrated.
An ideal analytical technique can be performed directly on the samples without troublesome pretreatment, high throughput screening covering as many classes of metabolites as rapidly as possible remaining unbiased with regard to the full set of metabolites, be robust, reproducible, sensitive and accurate (5).
Two major analytical techniques involved in metabolomics are nuclear magnetic resonance spectroscopy NMR, which has advantages of the high information content of
the resulting spectra, the relative stability of the NMR chemical shift, the ease of quantification and lack of any need to preselect the conditions employed. This contrasts with most chromatographic methods where the need to select columns and elution conditions may result in unintended bias in the analysis and potential for the retention time to drift making comparison between runs more difficult (6).
In comparison mass spectrometry MS, provides high sensitivity, high resolution, wide dynamic range, coverage of a wide diversity of chemical compounds, robustness and feasibility to elucidate the molecular weight and structure of unknown compounds and is more sensitive than the NMR (7),
In addition there is a wide range of additional techniques used in metabolomic analysis including FT-IR, gas chromatography coupled with MS, two dimensional GC-MS, liquid chromatography coupled with MS, and capillary electrophoresis coupled with MS but in the real life situation there is no technique that provides all the desired properties for ideal global metabolite profiling(5).
Some application of metabolomics in pharmaceutical chemistry:
1. Pharmaceutical research and development
The first reported rodent toxicity investigation of HPLC-MS based metabonomics method was by Plumb and co-workers where urine samples obtained in long term toxicity were studied using LC-ESI/TOF-MS and in the negative ion mode. PCA had shown a great difference between dose groups and the controls (8), several recent studies focused on the effects of nephrotoxins on the urinary metabolites profiles of rats that administered mercuric chloride, cyclosporin, gentamicin, and others.
Lafaye and co-workers used an LC/ESI-MS method to investigate the heavy metal exposure in rodents over a 3 month period, a significant difference in metabolite profile was observed between the different heavy metals and doses (9).
Acute and chronic doses of paracetamol were given to rats then the urine samples from the control and treatment were analyzed by NMR and UPLC coupled with QTOFMS both techniques had shown a number of metabolites such as hippurate, phenylalanine, phenyacetylglycine, pantothenate,pipecolinate, allantoin, indoxysulphuric acid, benzenediolsulphate, ferulic acid sulphate, gluconic acid, citrate, and 2-oxoglutarate which suggested mitochondrial damage(10).
2. Diseases biomarkers discovery
There are many examples in the literature of the use of metabolic profiling to aid human disease diagnosis including diabetes, Alzheimer’s disease, osteoarthritis, and
others. A recent study by Yan et al used the analysis of metabolites in human saliva using HPLC-MS as a diagnostic tool for oral squamous cell carcinoma, and oral leucoplakia. The proposed approach was low cost, efficient and noninvasive and it can be developed as a promising method for population-based screening of cancer and pre-cancers in the oral cavity (11).
1- J.K. Nicholson, J.C. Lindon, E. Holmes, Xenobiotica 29 (1999) 1181.
2- J.C. Lindon, E. Holmes, M.E. Bollard, E.G. Stanley, J.K. Nicholson,
Biomarkers 9 (2004) 1.
3- J.K. Nicholson, J. Connelly, J.C. Lindon, E. Holmes, Nat. Rev. Drug
Discov. 1 (2002) 153.
4- Lay JJO, Liyanage R, Borgmann S, et al., TrAC. Trends in Analytical Chemistry 2006; 25:1046–56.
6-Xin lu,xinjie zhao,Bai C,Zhao C, Lu G,Xu G,(2008), Journal of Chromatography B,866 (2008) 64–76
5-Georgios Theodoridis, Helen G. Gika, Ian D. Wilson, Trends in Analytical Chemistry, Vol. 27, No. 3, 2008
7-W.B. Dunn, D.I. Ellis, Trac-Trends Anal. Chem. 24 (2005) 285.
8-R.S. Plumb, C.L. Stumpf, M.V. Gorenstein, J.M. Castro-Perez, G.J. Dear,
M. Anthony, B.C. Sweatman, S.C. Connor, J.N. Haselden, Rapid Commun.
Mass Spectrom. 16 (2002) 1991
9-A. Lafaye, C. Junot, B. Ramounet-Le Gall, P. Fritsch, J.C. Tabet, E. Ezan,
Rapid Commun. Mass Spectrom. 17 (2003) 2541
10-Sun J, Schnackenberg LK, Holland RD, et al. J Chromatogr B 2008;871:328–40.
11-28-Shi-Kai Yan a,d, Ben-Juan Wei b,d, Zhong-Ying Lin a, Yun Yang a, Zeng-Tong Zhoub, Wei-Dong Zhang a, Oral Oncology (2008) 44, 477– 483