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 achieved using current untargeted and widely targeted volatomics (WTV) methods has been limited by low sensitivity and/or low acquisition coverage. Here, we introduce WTV 2.0, which enabled the construction of a high-coverage library containing 2111 plant volatiles, and report the development of a comprehensive selective ion monitoring (cSIM) acquisition method, including the selection of characteristic qualitative ions with the minimal ion number for each compound and an optimized segmentation method, that can acquire the smallest but sufficient number of ions for most plant volatiles, as well as the automatic qualitative and semi-quantitative analysis of cSIM data. Importantly, the library and acquisition method we developed can be self-expanded by incorporating compounds not present in the library, utilizing the obtained cSIM data. We showed that WTV 2.0 increases the median signal-to-noise ratio by 7.6-fold compared with the untargeted method, doubled the annotation coverage compared with the untargeted and WTV 1.0 methods in tomato fruit, and led 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 profiling of volatiles and primary metabolites in any species.

Widely Targeted Volatilomics and Metabolomics Analysis Reveal the Metabolic Composition and Diversity of Zingiberaceae Plants.

Zingiberaceae plants are widely used in the food and pharmaceutical industries; however, research on the chemical composition and interspecific differences in the metabolome and volatilome of Zingiberaceae plants is still limited. In this study, seven species of Zingiberaceae plants were selected, including Curcuma longa L., Zingiber officinale Rosc., Alpinia officinarum Hance, Alpinia tonkinensis Gagnep, Amomum tsaoko Crevost et Lemarie, Alpinia hainanensis K. Schum. and Amomum villosum Lour. Myristica fragrans Houtt. was also selected due to its flavor being similar to that of the Zingiberaceae plant. The metabolome and volatilome of selected plants were profiled by widely targeted approaches; 542 volatiles and 738 non-volatile metabolites were detected, and ß-myrcene, α-phellandrene and α-cadinene were detected in all the selected plants, while chamigren, thymol, perilla, acetocinnamone and cis-α-bisabolene were exclusively detected in certain Zingiberaceae plants. Differential analysis showed that some terpenoids, such as cadalene, cadalene-1,3,5-triene, cadalene-1,3,8-triene and (E)-ß-farnesene, and some lipids, including palmitic acid, linoleic acid and oleic acid were amongst the most varied compounds in Zingiberaceae plants. In conclusion, this study provided comprehensive metabolome and volatilome profiles for Zingiberaceae plants and revealed the metabolic differences between these plants. The results of this study could be used as a guide for the nutrition and flavor improvement of Zingiberaceae plants.

Identification of Key Aromatic Compounds in Basil (Ocimum L.) Using Sensory Evaluation, Metabolomics and Volatilomics Analysis.

Basil (Ocimum L.) is widely used as a flavor ingredient, however research on basil flavor is limited. In the current study, nine basil species were selected, including Ocimum basilicum L.var. pilosum (Willd.) Benth., Ocimum sanctum, Ocimum basilicum cinnamon, Ocimum gratissimum var. suave, Ocimum tashiroi, Ocimum basilicum, Ocimum americanum, Ocimum basilicum ct linalool, and Ocimum basilicum var. basilicum, and their fragrance and flavor characteristics were assessed by sensory evaluation. The results indicated that Ocimum basilicum var. basilicum and Ocimum gratissimum var. suave have a strong clove smell and exhibited a piquant taste. Metabolomics and volatilomics analyses measured 100 nonvolatile metabolites and 134 volatiles. Differential analysis showed that eugenol, γ-terpinene, germacrene D and malic acid were among the most varied metabolites in basil species. Combined with sensory evaluation results, correlation analysis revealed that ß-pinene and γ-cadinene contributed to the piquant smell, while eugenol and germacrene D contributed to the clove smell, and malic acid and L-(−)-arabitol contributed to the sweet flavor in basil. This study provided comprehensive flavor chemistry profiles of basil species and could be used as a guide for basil flavor improvement. The better understanding of objective sensory attributes and chemical composition of fresh basil could introduce the improved cultivars with preponderant traits, which is also in accordance with the various demands of breeders and growers, food producers, and consumers.

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 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.