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Mol Plant

Title:		Development of a widely targeted volatilomics method for profiling volatilomes in plants
Author(s):		Yuan H; Cao G; Hou X; Huang M; Du P; Tan T; Zhang Y; Zhou H; Liu X; Liu L; Jiangfang Y; Li Y; Liu Z; Fang C; Zhao L; Fernie AR; Luo J;
Address:		"College of Tropical Crops, Hainan University, Haikou 570288, China; Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China. College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, China. National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China. Department of Molecular Physiology, Max-Planck-Institute of Molecular Plant Physiology, Am Muhlenberg 1, 14476 Potsdam-Golm, Germany. College of Tropical Crops, Hainan University, Haikou 570288, China; Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China; National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China. Electronic address: jie.luo@hainanu.edu.cn"
Journal Title:		Mol Plant
Year:		2022
Volume:		20210910
Issue:		1
Page Number:		189 - 202
DOI:		10.1016/j.molp.2021.09.003
ISSN/ISBN:		1752-9867 (Electronic) 1674-2052 (Linking)
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, 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 MS(2) 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"
Keywords:		"Crops, Agricultural/*metabolism Fruit/*metabolism Gas Chromatography-Mass Spectrometry/*methods Metabolomics/*methods Plant Leaves/*metabolism Reproducibility of Results Seeds/*metabolism Volatile Organic Compounds/*metabolism Gc-ms MS2T library plant vol;"
Notes:		"MedlineYuan, 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 eng Comparative Study Research Support, Non-U.S. Gov't England 2021/09/13 Mol Plant. 2022 Jan 3; 15(1):189-202. doi: 10.1016/j.molp.2021.09.003. Epub 2021 Sep 10"