Dynamic changes of differential metabolites and key metabolic pathways of Gastrodia elata Blume during fermentation

ABSTRACT

The fermentation of Gastrodia elata Blume (GEB) is an extremely complex process, and abundant metabolites are produced, which have a great influence on the quality and flavor. The non-targeted metabolomics method was used to analyze the comprehensive changes of differential metabolites and key metabolic pathways in the fermentation process of GEB. After fermented for 60 d, carbohydrate, organic acid, peptide, and nucleic acid metabolites were 79.77%, 12.91%, 4.39% and 2.79%, respectively. Compared with unfermented GEB, the carbohydrates decreased obviously, while organic acid, peptide and nucleic acid metabolites increased. A total of 32 metabolites were identified as the differential metabolites (VIP>1 and P < .05). Subsequently, metabolic pathways of differential metabolites were analyzed and 14 key metabolic pathways were found, among which methyl butyrate metabolic pathway, TCA cycle, alanine, aspartic acid and glutamate metabolism had greater influences on the GEB fermentation. Finally, the metabolic pathways network was constructed preliminarily. This work could be helpful to understand the differential metabolites and establish a preliminary foundation for further elucidation of the flavor formation mechanism during GEB fermentation.

KEYWORDS:

• Gastrodia elata Blume
• fermentation
• metabolomics
• metabolites

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was financially supported by the State Key Laboratory of Functions and Applications of Medicinal Plant, Guizhou Medical University (No. FAMP201907K), Science and Technology Department of Guizhou Province (QKHRCPT[2017]5101), Food And Pharmaceutical Resources Health Products Development and Achievement Transformation Innovation Ability Improvement Platform Construction Project of Guizhou Province (QKHFQ[2020]4013); the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 20KJB550013), and the Research Projects of Xuzhou University of Technology (No. XKY2019226). Authors’ Contributions Yu Wang and Ling Lin contributed equally to this work.