WTV2.0: A high-coverage plant volatilomics method with a comprehensive selective ion monitoring acquisition mode

Volatilomics is essential for understanding the biological functions and fragrance contributions of plant volatiles. However, the annotation coverage of current untargeted and widely-targeted methods has been limited by low sensitivity and/or low acquisition coverage. Here, we introduce WTV 2.0. It enables the construction of a high-coverage library containing 2111 plant volatiles; the development of a comprehensive-selective ion monitoring (cSIM) acquisition method that contains the fewest but sufficient ions for most plant volatiles, including the selection of characteristic qualitative ions with minimal ions number for each compound and the optimized segmentation of acquisition method; and finally, the automatic qualitative and semi-quantitative analysis of cSIM data. Furthermore, the library and acquisition method can be self-expanded by incorporating compounds not present in the library, utilizing the obtained cSIM data. WTV 2.0 increased the median signal-to-noise ratio by 7.6-fold compared to the untargeted method, doubled the annotation coverage compared to the untargeted and WTV 1.0 methods in tomato fruit, and leading to the discovery of menthofuran as a novel flavor compound in passion fruit. WTV 2.0 is a Python library with a user-friendly interface, and is applicable to volatiles and primary metabolites profiling in any species.