Foods (Dec 2024)
Integrated Transcriptomic and Metabolomic Analyses Reveal Changes in Aroma- and Taste-Related Substances During the Withering Process of Black Tea
Abstract
Withering is one of the major processing steps critical for the quality of black tea. In this study, we investigated the mechanisms underlying the physicochemical changes in metabolites and gene expression during the withering process of black tea using metabolomic and transcriptomic approaches, respectively. Based on gas chromatography/mass spectrometry non-targeted metabolomic approaches (GC-MS) and ultra-high performance liquid chromatograph–tandem mass spectrometry (UHPLC-MS/MS), a total of 76 volatile compounds and 160 non-volatile compounds were identified from tea leaves, respectively. RNA-seq analysis revealed that the number of differentially expressed genes (DEGs) for the comparative combination of withering time (i.e., W4h, W6h, W8h, W10h, and W12h) compared with CK (i.e., fresh leaves) were 3634, 2906, 4127, 5736, and 7650, respectively. The core genes in starch metabolism, namely alpha-amylase (AMY) and beta-amylase (BAM), were upregulated as withering time increased. AMY and BAM contributed to the decomposition of starch to increase the soluble sugars. The content of tea leaf alcohols and aldehydes, which are the vital contributors for greenish aroma, gradually decreased as withering time increased due to the downregulation of associated genes while the compounds related to sweet and fruity characteristics increased due to the upregulated expression of related genes. Most DEGs involved in amino acids were significantly upregulated, leading to the increase in free amino acids content. However, DEGs involved in catechins metabolism were generally downregulated during withering, and resulted in a reduction in catechins content and the accumulation of theaflavins. The same trend was observed in alpha-linolenic acid metabolism-related genes that were downregulated and enhanced the reduction in grassy aroma in black tea. The weighted gene co-expression network analysis (WGCNA) of DEGs showed that one module can be associated with more components and one component can be regulated by various modules. Our findings provide new insights into the quality formation of black tea during the withering process.
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