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中国精品科技期刊2020
杨荣,黄慧玲,谢李明,等. 基于非靶向代谢组学分析添加富含谷胱甘肽酵母衍生物对混菌发酵葡萄酒代谢物的影响[J]. 食品工业科技,2025,46(16):184−193. doi: 10.13386/j.issn1002-0306.2024090048.
引用本文: 杨荣,黄慧玲,谢李明,等. 基于非靶向代谢组学分析添加富含谷胱甘肽酵母衍生物对混菌发酵葡萄酒代谢物的影响[J]. 食品工业科技,2025,46(16):184−193. doi: 10.13386/j.issn1002-0306.2024090048.
YANG Rong, HUANG Huiling, XIE Liming, et al. Non-targeted Metabolomic Analysis of the Effect of g-IDY Addition on Metabolites in Mixed Fermentation Wine[J]. Science and Technology of Food Industry, 2025, 46(16): 184−193. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024090048.
Citation: YANG Rong, HUANG Huiling, XIE Liming, et al. Non-targeted Metabolomic Analysis of the Effect of g-IDY Addition on Metabolites in Mixed Fermentation Wine[J]. Science and Technology of Food Industry, 2025, 46(16): 184−193. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024090048.

基于非靶向代谢组学分析添加富含谷胱甘肽酵母衍生物对混菌发酵葡萄酒代谢物的影响

Non-targeted Metabolomic Analysis of the Effect of g-IDY Addition on Metabolites in Mixed Fermentation Wine

  • 摘要: 富含谷胱甘肽酵母衍生物(Glutathione-enriched inactive dry yeast,g-IDY)是一种替代SO2的酵母衍生物,为探究g-IDY对混菌(酿酒酵母、德尔布有孢圆酵母、酒酒球菌)发酵葡萄酒中代谢物及代谢途径的影响。本研究采用超高液相色谱-串联高分辨质谱(UHPLC-MS)联用非靶向代谢组学技术,通过多元统计学方法对三组葡萄酒(单菌发酵S组、混菌发酵TS0组、添加g-IDY混菌发酵TS60组)中的代谢物进行分析。结果表明,混菌发酵TS0组与单菌发酵S组(TS0 vs. S)在正、负离子模式下分别筛选出643种、293种差异代谢物;添加g-IDY混菌发酵TS60组与混菌发酵TS0组(TS60 vs. TS0)在正、负离子模式下分别筛选出153、57种差异代谢物。进一步选择log2(FC)绝对值≥1,VIP值>1,P<0.05的差异代谢物并通过KEGG数据库注释,发现在TS0 vs. S中有53种显著差异代谢物被注释到16条代谢通路,且混菌发酵能通过上调葡萄酒中L-谷氨酰胺、L-脯氨酸、L-组氨酸、色氨酸、L-赖氨酸和下调胞磷胆碱、乙酰胆碱等主要差异代谢物上调D-氨基酸代谢,组氨酸代谢,氨基酸生物合成和下调核苷酸代谢、嘌呤代谢等主要代谢通路。在TS60 vs. TS0中有18种显著差异代谢物被注释到8条代谢通路,且g-IDY能通过上调混菌发酵葡萄酒中精胺酸琥珀酸、4-氨基丁酸、D-氨基葡萄糖6-磷酸、L-谷氨酰胺和下调鸟嘌呤、脱氧鸟苷、腺嘌呤等主要差异代谢物来上调丙氨酸、天冬氨酸、谷氨酸代谢,组氨酸代谢以及下调甘油磷脂代谢,核苷酸代谢等主要代谢通路。通过深入分析葡萄酒中差异代谢物的变化与作用,发现g-IDY有利于混菌发酵葡萄酒中香气、风味的形成。

     

    Abstract: g-IDY was a yeast derivative that replaces SO2. In order to investigate the effects of g-IDY on metabolites and their metabolic pathways in wine fermented by mixed bacteria (Saccharomyces cerevisiae, Torulaspora delbrueckii CICC 33458, Oenococcus oeni CICC 33458). In this study, UHPLC-MS combined with non-targeted metabolomics technology was used to analyze the metabolites in three groups of wines (single fermentation S group, mixed fermentation TS0 group, mixed fermentation TS60 group with g-IDY) by multivariate statistical method. The study showed that 643 and 293 different metabolites were screened in positive and negative ion modes in TS0 group and S group. Similarly, in TS60 group and TS0 group, 153 and 57 different metabolites were screened in positive and negative ion modes. Subsequently, the differential metabolites with absolute value of log2(FC)≥1, VIP >1, P<0.05 were further selected and annotated by KEGG database. The study showed that 53 significantly different metabolites were annotated to 16 metabolic pathways in the TS0 and S groups. The mixed-bacteria fermentation was able to up-regulate D-amino acid metabolism, histidine metabolism, amino acid biosynthesis and down-regulate nucleotide metabolism, purine metabolism and other major metabolic pathways by up-regulating the major differential metabolites such as L-glutamine, L-proline, L-histidine, tryptophan, L-lysine and down-regulating cytosolic phosphatidylcholine, and acetylcholine in the wines. Similarly, in the TS60 and TS0 groups, 18 significantly different metabolites were annotated to 8 metabolic pathways. g-IDY was able to upregulate major differential metabolites such as spermidine succinate, 4-aminobutyric acid, D-glucosamine 6-phosphate, and L-glutamine and downregulate guanine, deoxyguanosine, and adenine in mixed-bacteria-fermented wines through upregulation of alanine, aspartate, and glutamate metabolism, histidine metabolism and down-regulate major metabolic pathways such as glycerophospholipid metabolism, and nucleotide metabolism. Through in-depth analysis of the changes and effects of differential metabolites in wines, the results showed that g-IDY was beneficial to the formation of aroma and flavor in mixed-bacteria fermented wine.

     

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