Research / Metabolite Identification
Project 1: Construction of an Ultrahigh Pressure Liquid Chromatography-Tandem Mass Spectral Library of Plant Natural Products and Comparative Spectral Analyses
A plant natural product tandem mass spectral library has been constructed using authentic standards and purified compounds. Currently, the library contains 1734 tandem mass spectra for 289 compounds, with the majority (76%) of the compounds being plant phenolics such as flavonoids, isoflavonoids, and phenylpropanoids. Tandem mass spectra and chromatographic retention data were acquired on a triple quadrupole mass spectrometer coupled to an ultrahigh pressure liquid chromatograph using six different collision energies (10–60 eV). The library is freely available for nonprofit, academic use at download/libraries page.
Relevant scientific article(s) published by our team:
Zhentian Lei, Li Jing, Feng Qiu, Hua Zhang, David V. Huhman, Zhiqin Zhou, Lloyd W. Sumner. Construction of a UHPLC‐Tandem Mass Spectral Library of Plant Natural Products and Comparative Spectral Analyses. Analytical Chemistry, 2015, 87, 7373‐7381; doi: 10.1021/acs.analchem.5b01559
Project 2: Development of PlantMAT Software for Predicting the Specialized Metabolic Potential of a System and for Large-Scale Metabolite Identifications
Custom software entitled Plant Metabolite Annotation Toolbox (PlantMAT) has been developed to address the number one grand challenge in metabolomics, which is the large-scale and confident identification of metabolites. PlantMAT uses informed phytochemical knowledge for the prediction of plant natural products such as saponins and glycosylated flavonoids through combinatorial enumeration of aglycone, glycosyl, and acyl subunits. PlantMAT allows users to operate an automated and streamlined workflow for metabolite annotation from a user-friendly interface within Microsoft Excel, a familiar, easily accessed program for chemists and biologists. The software is freely available for nonprofit, academic use at download/software page.
Relevant scientific article(s) published by our team:
Feng Qiu, Dennis D. Fine, Daniel J. Wherritt, Zhentian Lei, Lloyd W. Sumner. PlantMAT: A Metabolomics Tool for Predicting the Metabolic Potential of a System and for Large‐scale Metabolite Identifications. Analytical Chemistry, 2016, 88, 11373-11383; doi: 10.1021/acs.analchem.6b00906