Metabolites play crucial biological roles; methods are needed for their study.

The genome, the transcriptome, and the proteome have gotten the lion's share of attention in the recent past. To truly understand biological mechanisms, however, researchers must also consider lipids, glycans, and the compendium of the thousands of small molecules (both endogenous and exogenous)—referred to as the metabolome—that serve as the substrates and products of biochemical reactions and play crucial roles in biological regulation.

There are many technical challenges when it comes to the untargeted discovery and quantification of small molecules. Given the diverse chemistries of metabolites, no single analysis method offers a 'one-size-fits-all' solution. The metabolome is also subject to very rapid changes, making it hard to accurately capture biological timepoints of interest.

Mass spectrometry is a highly sensitive technology that can potentially be used for broad analysis of metabolites in a biological sample. However, a major challenge remains: the identification of metabolites from a mass spectrum. Current public mass spectral libraries of chemical structures represent just a fraction of the expected diversity of metabolites across kingdoms. The field is in need of better computational tools for spectral identification, statistical validation of results, data management, and biological interpretation. And while it is common in other omics fields to make raw data publicly available, this culture shift has not yet happened in metabolomics, despite the availability of several resources where researchers can archive their data. Data sharing would spur the development of novel data analysis algorithms and help build spectral libraries, benefitting the field as a whole.

Metabolomics is an essential component of systems biology, and studies of metabolism abound in fields ranging from agriculture to the study of human disease. We look forward to seeing future user-friendly methodological developments that will drive this technique forward and help it become an integral part of a biologist's toolbox.