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

• Published in: Molecular plant Vol. 15; no. 1; pp. 189 - 202
• Main Authors: Yuan, Honglun, Cao, Guangping, Hou, Xiaodong, Huang, Menglan, Du, Pengmeng, Tan, Tingting, Zhang, Youjin, Zhou, Haihong, Liu, Xianqing, Liu, Ling, Jiangfang, Yiding, Li, Yufei, Liu, Zhenhuan, Fang, Chuanying, Zhao, Liqing, Fernie, Alisdair R., Luo, Jie
• Format: Journal Article
• Language: English
• Published: England Elsevier Inc 03.01.2022
• Subjects: Crops, Agricultural - metabolism; Fruit - metabolism; Gas Chromatography-Mass Spectrometry - methods; GC-MS; Metabolomics - methods; MS2T library; Plant Leaves - metabolism; plant volatilome; Reproducibility of Results; rice; Seeds - metabolism; tomato; Volatile Organic Compounds - metabolism; widely targeted volatilomics; GC-MS; plant volatilome; widely targeted volatilomics; tomato; rice; MS2T library
• ISSN: 1674-2052; 1752-9867
• DOI: 10.1016/j.molp.2021.09.003

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, 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. A widely targeted volatilomics method was developed based on a high-coverage MS2 spectral tag library, and “targeted spectra extraction” algorithm and regression models were developed to address spectral convolution and signal drift. Using the developed method, the authorsreveal that benzothiazole is a potential signal priming tomato plants and that the aromatic compounds 2-nonanone and 2-heptanone contribute to rice fragrance.