A Novel Integrated Method for Large-Scale Detection, Identification, and Quantification of Widely Targeted Metabolites： Application in the Study of Rice Metabolomics

Liquid chromatography-mass spectrometry （LC-MS）-based metabolomics has been facilitated by the con- struction of MSz spectral tag （MS2T） library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. In this report, a novel strategy called step- wise multiple ion monitoring-enhanced product ions （stepwise MIM-EPI） was developed to construct the MS2T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698 （almost） non- redundant metabolites with MS2 spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2T library and other available multiple reaction monitoring （MRM） information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation of the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid （ABA） with metabolites such as serotonin derivative（s）, polyamine conjugates under drought stress, but also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.

Development of a widely targeted volatilomics method for profiling volatilomes in plants

Volatile organic compounds play essential roles in plant environment interactions as well as determining the fragrance of plants.Although gas chromatography-mass spectrometry-based untargeted metabolo-mics is commonly used to assess plant volatiles,it suffers from high spectral convolution,low detection sensitivity,a limited number of annotated metabolites,and relatively poor reproducibility.Here,we report a widely targeted volatilomics(WTV)method that involves using a“targeted spectra extraction”algorithm to address spectral convolution,constructing a high-coverage MS2 spectral tag library to expand volatile annotation,adapting a multiple reaction monitoring mode to improve sensitivity,and using regression models to adjust for signal drift.The newly developed method was used to profile the volatilome of rice grains.Compared with the untargeted method,the newly developed WTV method shows higher sensitivity(for example,the signal-to-noise ratio of guaicol increased from 4.1 to 18.8),high annotation coverage(the number of annotated volatiles increased from 43 to 132),and better reproducibility(the number of volatiles in quality control samples with relative standard deviation value below 30.0%increased from 14 to 92 after normalization).Using the WTV method,we studied the metabolic responses of tomato to environmental stimuli and profiled the volatilomes of different rice accessions.The results identified benzothiazole as a potential airborne signal priming tomato plants for enhanced defense and 2-nonanone and 2-heptanone as novel aromatic compounds contributing to rice fragrance.These case studies suggest that the widely targeted volatilomics method is more efficient than those currently used and may considerably promote plant volatilomics studies.