Jinnyoung Choi (Agilent Technologies Korea)

Jinnyoung Choi (Agilent Technologies Korea)

Cate Simmermaker (Agilent Technologies)

Karen E. Yannell (Agilent Technologies)

Sierra D. Durham (Agilent Technologies)

Common workflows for untargeted metabolomics by HRMS utilize multiple acquisition types. Data dependent acquisition provides rich fragment information important for identification and iterative injections give deeper metabolite identification utilizing exclusion lists. MS1 affords sensitive and comprehensive surveys of individual samples. This combination workflow gives analysts a wealth of information for observing changes in known metabolites, while also identifying metabolites or other analytes less frequently present in biologically curated metabolomic libraries. However, this heavy data load can create a barrier for some investigators. Herein is novel software that combines complex analysis into a streamlined workflow, untangling the interpretation of multiple data file types and giving researchers clear and confident interpretation of metabolomic alterations.

All data was acquired on the Revident LC/Q-TOF. Key performance elements of the Revident are a new detector, giving better mass accuracies even at saturation, as well as an increased dynamic range compared to previous instrument generations. In combination with the temperature-inert flight tube, contributing extended duration of mass stability, the overall mass accuracy has improved. These features enable Revident LC/Q-TOF to be principal hardware for untargeted metabolomic analysis.