In general, metabolomics refers to metabolite profiling or the differential study of the metabolome between experimental and control groups when challenged with an external stimulus such as a drug treatment, a biochemical or environmental stress, or pathologies such as mutant/resistance-bred organisms. The stimulus could also be non-biological, such as food processing; as a consequence, metabolomics has huge potential across several application areas, including food and nutrition.
Mass spectrometry-based metabolomics
Because metabolomics aims to comprehensively identify and measure a large number of compounds in complex mixtures, its goals are a challenge for standard analytical chemistry. As a result, mass spectrometry has emerged as an alternative to NMR-based metabolomics, offers high selectivity and sensitivity, and has the potential to assess metabolites in both a qualitative and quantitative manner.
For scientists without specialized training in the field of mass spectrometry, using this approach can feel daunting. There are four fundamental areas one must master in order to be successful in metabolomics:
- Experimental design . Separating the biological study into multiple analytical experiments and ensuring quality control for accuracy and precision of results are both paramount to successful experimental design.
- Sample preparation  is a must when using mass spectrometry-based techniques. There are multiple techniques based on sample type, and there are entire methods for extracting specific classes of metabolites.
- Analytical procedures. Small molecule compounds are chemically and structurally diverse, so the mass spectrometer must be combined with a separation technique to reduce sample complexity prior to MS analysis. Depending on the separation technique, specific metabolite classes may be discriminated against and not appear at their normal abundance.
- Data analysis. Huge amounts of complex raw data must be analyzed in a stringent manner to remove experimental artifacts. To accomplish this task, stringent statistical tools and software are required for accurate compound identification and quantitation.
Selecting the analytical technique