An autonomous metabolomic workflow combining mass spectrometry analysis with 
tandem mass spectrometry data acquisition was designed to allow for simultaneous 
data processing and metabolite characterization. Although previously tandem mass 
spectrometry data have been generated on the fly, the experiments described 
herein combine this technology with the bioinformatic resources of XCMS and 
METLIN. As a result of this unique integration, we can analyze large profiling 
datasets and simultaneously obtain structural identifications. Validation of the 
workflow on bacterial samples allowed the profiling on the order of a thousand 
metabolite features with simultaneous tandem mass spectra data acquisition. The 
tandem mass spectrometry data acquisition enabled automatic search and matching 
against the METLIN tandem mass spectrometry database, shortening the current 
workflow from days to hours. Overall, the autonomous approach to untargeted 
metabolomics provides an efficient means of metabolomic profiling, and will 
ultimately allow the more rapid integration of comparative analyses, metabolite 
identification, and data analysis at a systems biology level.