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中国精品科技期刊2020
汤涵岚,杨阳,刘晓彤,等. 基于宏基因组-宏转录组-宏蛋白组的大曲微生物组学研究进展J. 食品工业科技,2026,47(8):1−11. doi: 10.13386/j.issn1002-0306.2025040324.
引用本文: 汤涵岚,杨阳,刘晓彤,等. 基于宏基因组-宏转录组-宏蛋白组的大曲微生物组学研究进展J. 食品工业科技,2026,47(8):1−11. doi: 10.13386/j.issn1002-0306.2025040324.
TANG Hanlan, YANG Yang, LIU Xiaotong, et al. Advances in Daqu microbiome research based on metagenomics-metatranscriptomics-metaproteomicsJ. Science and Technology of Food Industry, 2026, 47(8): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2025040324.
Citation: TANG Hanlan, YANG Yang, LIU Xiaotong, et al. Advances in Daqu microbiome research based on metagenomics-metatranscriptomics-metaproteomicsJ. Science and Technology of Food Industry, 2026, 47(8): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2025040324.

基于宏基因组-宏转录组-宏蛋白组的大曲微生物组学研究进展

Advances in Daqu microbiome research based on metagenomics-metatranscriptomics-metaproteomics

  • 摘要: 本文综述了近年来应用宏基因组、宏转录组及宏蛋白组等组学技术解析大曲微生物群落的结构与功能的研究进展。在群落组成上,大曲蕴藏着大量未培养微生物资源,核心菌群以 AspergillusBacillusLactobacillus 等为主;在群落功能上,研究明确了关键代谢酶(如酯合成酶)的微生物来源,阐明了菌群在原料降解与风味形成中的协同作用;在驱动因子上,组学分析证实了温度等环境因子通过调控微生物的转录与蛋白表达活性,从而影响发酵进程。未来,该领域研究应注重多组学与培养组学、代谢组学及计算模型的整合,构建从基因到产物、从预测到调控的系统研究框架,以推动大曲发酵由经验控制向精准设计与性能预测的范式转变,进一步深化对大曲发酵原理的理解并提升生产过程的可控性。

     

    Abstract: This review summarizes recent research progress in applying omics technologies, including metagenomics, metatranscriptomics and metaproteomics, to analyze the structure and function of the microbial community in Daqu. In terms of community composition, Daqu harbors a vast reservoir of uncultured microbial resources, with core taxa predominantly consisting of Aspergillus, Bacillus, and Lactobacillus. Regarding community function, studies have identified the microbial origins of key metabolic enzymes, such as ester synthases, and elucidated the synergistic role of the microbiota in raw material degradation and flavor formation. With respect to driving factors, omics analyses have confirmed that environmental factors, such as temperature, influence the fermentation process by regulating microbial transcriptional and protein expression activities. Future research in this field should focus on integrating multi-omics approaches with culturomics, metabolomics, and computational modeling to establish a systematic framework spanning from genes to products and from prediction to regulation. This will facilitate a paradigm shift in Daqu fermentation from empirical control to precision design and performance prediction, thereby deepening the understanding of the principles of Daqu fermentation and enhancing the controllability of the production process.

     

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