A Protocol to Compare Methods for Untargeted Metabolomics
There are thousands of published methods for profiling metabolites with liquid chromatography/mass spectrometry (LC/MS). While many have been evaluated and optimized for a small number of select metabolites, very few have been assessed on the basis of global metabolite coverage. Thus, when performing untargeted metabolomics, researchers often question which combination of extraction techniques, chromatographic separations, and mass spectrometers is best for global profiling. Method comparisons are complicated because thousands of LC/MS signals (so-called features) in a typical untargeted metabolomic experiment cannot be readily identified with current resources. It is therefore challenging to distinguish methods that increase signal number due to improved metabolite coverage from methods that increase signal number due to contamination and artifacts. Here, we present the credentialing protocol to remove the latter from untargeted metabolomic datasets without having to identify metabolite structures. This protocol can be used to compare or optimize methods pertaining to any step of the untargeted metabolomic workflow (e.g., extraction, chromatography, mass spectrometer, informatic software, etc.).
Key wordsUntargeted metabolomics Metabolite profiling Metabolism Credentialing Liquid chromatography Mass spectrometry
This work was supported by NIH grants R35ES028365 and R21CA191097 as well as support from the Pew Scholars Program in the Biomedical Sciences, the Edward Mallinckrodt, Jr., Foundation, and Agilent Technologies.