Two major technologies are used for metabolomics analysis, i.e., NMR and MS. The two platforms have different limits and advantages deeply discussed elsewhere in the literature (Ellis et al., 2007; Pan and Raftery, 2007). The critical issue regarding SCs is the availability of biomaterial for analysis and the related sample volumes and concentrations. MS analysis is an obliged choice for the aforementioned limits, due to its higher sensitivity compared with NMR, but it does not imply that NMR analysis should be avoided. In fact, the two methods are very comparable and complementary with a highly different coverage. There are limited examples of concomitant use of both techniques in metabolomics, but the scientific community is recognizing more and more the need to complement the technical limits by coupling these two technologies online. Although this association will probably be the method of choice in the foreseeable future, the tools for this type of analysis, e.g., software and hardware handling both instruments online, and integrated data analysis, are still in their infancy or lacking. The most popular methodology in metabolomics is based on liquid chromatography coupled with MS. This is due to advances in material science and instrumental precision and sensitivity. In liquid chromatography, a major advancement was achieved by the introduction of core-shell particle technologies (Fekete et al., 2012). Compared with classical stationary phases, core-shell particles have lower mass-transfer dispersion, thus resulting in a lower height of theoretical plates and enhanced separation efficiency. As a result, this type of stationary phase allows for narrowing of the peak width, and as a consequence, increases the peak intensities (Martano et al., 2014). These characteristics are well exploited thanks to the development of chromatographic platforms that can handle high pressure (>1,000 bars) and are coupled to high resolution mass spectrometers that are able to sustain a scan rate in the millisecond ranges. Of particular interest, the ability to scale down the instrumental platform to nanoUHPLC coupled with nanoESI-MS gives the possibility to analyze the metabolome using a limited number of cells per sample (commonly between 100 and 500 cells), with high metabolic coverage. This methodology allows for further downscaling of sample investigation to single cell analysis, but this choice is not costless in term of metabolic coverage, separation and sample handling, as discussed later.
Do you have any questions about this protocol?
Post your question to gather feedback from the community. We will also invite the authors of this article to respond.