Metabolomics is important to investigate regulation and function of metabolic networks. Current metabolomics methods have either long measurement times or they are not quantitative. Scientists at the Max Planck Institute for Terrestrial Microbiology have now developed a new method to quantify metabolites in hundreds of microbial cell extracts per day. The analytical targets are metabolites of central carbon metabolism and biosynthetic pathways. The technological advancement opens the possibility for quantitative large-scale investigations of metabolic networks and will also be useful to optimally engineer microorganisms in the biotech industry.
Metabolomics aims to comprehensively quantify small molecules in a cell. Such data is important for biotechnological applications, because accumulated metabolites, for instance, can indicate bottlenecks in engineered pathways to produce pharmaceuticals or fine chemicals. For basic biological research metabolomics provides a quantitative picture about function of naturally evolved metabolic networks. For example, how do intracellular metabolite concentrations compare with kinetic parameters of enzymes, and to which extend do they change after perturbations? Now, the research group of Hannes Link has optimized conditions for liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) to overcome the long measurement time of current methods. To cover as many metabolites as possible they tested the method for all polar metabolites such as amino acids, nucleotides, cofactors and compounds in central metabolism, and were able to detect more than 200 of these in extracts of the bacterial work horse Escherichia coli. As an ultimate “stress test”, single metabolite standards were mixed with samples from cells. In these analyses it was confirmed that the method is highly selective. The novel LC-MS/MS method will allow researchers to rapidly probe the metabolites of interest under many conditions and in many strains.
Guder J.C. et al. (2017) Time-Optimized Isotope Ratio LC-MS/MS for High-Throughput Quantification of Primary Metabolites. Analytical Chemistry, 10.1021/acs.analchem.6b03731