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

Abstract

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 metabolomics is commonly used to assess plant volatiles, it suffers from high spectral convolution, low detection sensitivity, limited annotated metabolites and relatively poor reproducibility. Herein, we report a widely-targeted volatilomics (WTV) method: using "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 the sensitivity; and using regression models to adjust for signal drift. The newly developed method was used to profile the volatilome of the rice grain. Compared with the untargeted method, the developed method has higher sensitivity, with for example the signal noise ratio of guaicol being increased from 4.1 to 18.8; high annotation coverage, with the number of annotated volatiles being increased from 43 to 132; better reproducibility, in quality control samples, number of volatiles with relative standard deviation value below 30.0% increased from 14 to 92 after normalization. We also studied the metabolic responses of tomato to environmental stimuli, and profiling the volatilome of different rice accessions. Our work indicates that benzothiazole is a potential airborne signal to prime tomato plants for enhanced defense. This method additionally identified 2-nonanone and 2-heptanone as novel aromatic compounds contributing to rice fragrance. These case studies lead us to believe that this widely-targeted volatilomics method is more efficient than those currently used and will thus considerably promote plant volatilomics studies.