Adam Rosebrock: “One of the biggest cultural and training challenges in metabolomics is realizing that we don’t have a comprehensive database of what exists in the cell. There is no metabolic equivalent of a genome, which greatly increases the work required to move from raw instrument output to biological interpretation. In my work, we’re simultaneously trying to measure known compounds and keep our eyes open for new, previously unexpected metabolites.
Metabolomic mass spectral data are often much more ambiguous than genomic or proteomic results, even with high resolution instruments and MS/MS analysis. For example, in my work on polar central carbon compounds, we have many hexose and pentose sugars and their cognate mono- and bis-phosphates. Isomeric compounds with identical exact masses and similar MS–MS fragmentation patterns often have very different biological roles. Efficient and consistent chromatographic separation is often at least as, if not more, important than what’s happening in the mass spectrometer.”
Dajana Vuckovic: “For NMR, the greatest challenge is the low sensitivity. For MS, there are several challenges that are often overlooked in addition to metabolite identification, where great progress has been made over the past few years Many MS novices often ignore matrix effects in the context of untargeted studies. However, ionization suppression and/or enhancement can play a critical role in the biological conclusions we make about our metabolomics data: we can miss huge concentration changes due to severe suppression of a given metabolite and we can misinterpret changes in signal intensity as biological changes in the concentration of that metabolite. As a community, we need to address this challenge consistently and in every single study.
The second challenge is the instability of MS signals over long periods of time. This limits the number of samples we can run in a single batch, and poses difficulties when combining data acquired in different batches. Metabolomics, by its very complexity, requires a large number of study samples both for discovery and validation of our findings. Thus, we need additional ways to deal with instrument variability and signal stability. Advances in this area should go hand in hand with advances in sensitivity. Perhaps emerging technologies, such as triboelectric nanogenerators, which ionize molecules using friction in a controlled fashion, can be explored in the future to address some of these shortcomings.
A third challenge is separation of isomers, and I hope to see additional advances in IMS and other technologies that help us deal with isomer complexity. The fourth important challenge is miniaturization. I would like to see incorporation of innovative technologies such as nanowells, microfluidics etc., to help us analyze very small biological samples much more effectively.”
Ian Wilson: “In the case of NMR spectroscopy the most often quoted limitation is sensitivity, but in my view this is more than compensated for by its virtues. For MS, including LC–MS etc., there are problems with ion suppression, variable and compound dependent sensitivity, poor repeatability and robustness, all of which can be minimized with appropriate care and control, and indeed these limitations have not stopped MS from providing some very good data.”
Fengguo Xu: “In my opinion, the major technical challenges existing in metabolomics include: Absolute quantification with a broad metabolite coverage, the identification of unknown metabolites, standardization of data pre-process procedure and biological function elucidation of differential metabolites.”
