Metabolomics Tools

Because of large variations in the chemical stmctures of metabolites, it is practically impossible to find a single analytical technique that can determine aU metabolites present in biological samples. Many metabolites are polar, nonvolatile, and do not have chromophore groups in their stracture, which makes them difficult to detect. Hence, the modem comprehensive analytical approach in metabolomics is based on use of various complementary anal34ical techniques to enable large numbers of metabolites to be detected and determined. 

A typical metabolomics workflow consist of three main phases sample pretreatment, analytical determination, and bioinformatics data calculation. 

Liquid-liquid extraction (LLE), solid phase extraction (SPE), and solid phase micro-extraction (SPME) are frequently applied for sample pretreatment. The type of extraction is highly related to the type of metabolites selected for determination. In previous metabolomics studies, extraction was focused on compounds of adequate stability that could be extracted together (carbohydrates, esters, amino acids, or organic acids). 

Metabolites are mostly extracted into aqueous or methanolic solutions. Subsequently, they are separated and analyzed as separate fractions, either aqueous or lipophilic. Here again, it should be emphasized that there is no single extraction 

Moreover, in terms of the large range of properties of analyzed metabolites, the extraction method is practically useless. Often, it can be replaced or preceded by a derivatization step, as is commonly performed for thiol compounds. These compounds are very unstable but application of an adequate derivatization step converts them into stable derivatives, allowing their determination. Unfortunately, in such a situation, many relevant metabolites are neglected because further analysis is focused only on those that have been subjected to chemical modification. 

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Xia, J., Wishart, D.S. MetPA a web-based metabolomics tool for pathway analysis and visualization. Bioinformaties 26, 2342-2344 (2010)... 

Oldiges, M., Lutz, S., Pflug, S. et al. (2007) Metabolomics current state and evolving methodologies and tools. 

The above bioinformatic tools provide methods of determining differences or similarities in datasets. The next step is to incorporate metabolomic data with other expression information, including mRNA and proteins, to infer gene function. To accomplish this, metabolomic data sets must be integrated and correlated in a global maimer with genetic and enzymatic data, pathways assembled into systems, and... 

Duran, A.L., Yang, J., Wang, L., and Sumner, L.W., Metabolomics spectral formatting alignment and conversion tools (MSFACTs), Bioinformatics, 19, 2283,2003. 

Thus, the value of metabolomics would currently appear to be greater as a research tool than as a universal tool to help assess the risks presented to humans or other organisms through the widespread cultivation of a plant with a changed NP composition. 

This example clearly shows that with further improvement in sensitivity, online cHPLC-NMR, in conjunction with cHPLC-MS, is likely to be used as the major tool for the successful treatment of problems encountered with genomics, proteomics and drug metabolomics. 

Currently, DSM uses biocatalysis, biotransformation, and fermentation technologies in addition to chemical methods to produce these specialties. To keep ahead of the competition and provide the best service to our customers, we use classical and/or advanced (gen)omics tools such as proteomics and metabolomics to make continuous improvements in the productivity and quality of our industrial workhorses. In the many cases where it is difficult - or impossible - to apply fermentation, we use (multi-step) biocatalysis to achieve our goal. Other in-house competences that are of growing relevance to the pharmaceutical area include the formu-... 

Foodomics involves the use of multiple tools to deal with its different applications. Thus, the use of omics tools (as e.g., transcriptomics, proteomics, or metabolomics) is a must in this new discipline. Although a detailed description on these tools is out of the scope of this chapter, some fundamental concepts on different omics techniques are provided below. 

Transcriptomic, proteomic, and/or metabolomic approaches have already been shown to be extremely useful to assess food safety and quality at every stage of production to ensure food safety for human consumption. They are also valuable tools to distinguish between similar food products and to detect food frauds (adulteration, origin, authenticity, etc.), food-borne pathogens, toxic species, food allergens, etc. 

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