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多组学时代食品和药品中的真菌次生代谢产物。

Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.

机构信息

Laboratory of Enzymology and Recombinant DNA Technology, Department of Microbiology, Maharshi Dayanand University, Rohtak, 124001, Haryana, India.

出版信息

Appl Microbiol Biotechnol. 2022 May;106(9-10):3465-3488. doi: 10.1007/s00253-022-11945-8. Epub 2022 May 12.

DOI:10.1007/s00253-022-11945-8
PMID:35546367
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9095418/
Abstract

Fungi produce several bioactive metabolites, pigments, dyes, antioxidants, polysaccharides, and industrial enzymes. Fungal products are also the primary sources of functional food and nutrition, and their pharmacological products are used for healthy aging. Their molecular properties are validated through the use of recent high-throughput genomic, transcriptomic, and metabolomic tools and techniques. Together, these updated multi-omic tools have been used to study fungal metabolites structure and their mode of action on biological and cellular processes. Diverse groups of fungi produce different proteins and secondary metabolites, which possess tremendous biotechnological and pharmaceutical applications. Furthermore, its use and acceptability can be accelerated by adopting multi-omics, bioinformatics, and machine learning tools that generate a huge amount of molecular data. The integration of artificial intelligence and machine learning tools in the era of omics and big data has opened up a new outlook in both basic and applied researches in the area of nutraceuticals and functional food and nutrition. KEY POINTS: • Multi-omic tool helps in the identification of novel fungal metabolites • Intra-omic data from genomics to bioinformatics • Novel metabolites and application in human health.

摘要

真菌产生多种生物活性代谢物、色素、染料、抗氧化剂、多糖和工业酶。真菌产品也是功能性食品和营养的主要来源,其药理产品用于健康老龄化。它们的分子特性通过使用最近的高通量基因组、转录组和代谢组学工具和技术得到验证。这些更新的多组学工具一起用于研究真菌代谢物的结构及其对生物和细胞过程的作用模式。不同类群的真菌产生不同的蛋白质和次生代谢物,具有巨大的生物技术和制药应用潜力。此外,通过采用多组学、生物信息学和机器学习工具来加速其使用和可接受性,这些工具会生成大量分子数据。人工智能和机器学习工具在组学和大数据时代的结合,为营养保健品和功能性食品和营养领域的基础和应用研究开辟了新的前景。

关键点

  • 多组学工具有助于鉴定新型真菌代谢物

  • 从基因组学到生物信息学的组内数据

  • 新型代谢物及其在人类健康中的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/efc12e32598f/253_2022_11945_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/07a830e5fe50/253_2022_11945_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/2b72e7abb7c1/253_2022_11945_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/0f6ef20b5668/253_2022_11945_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/efc12e32598f/253_2022_11945_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/07a830e5fe50/253_2022_11945_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/2b72e7abb7c1/253_2022_11945_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/0f6ef20b5668/253_2022_11945_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efa/9095418/efc12e32598f/253_2022_11945_Fig4_HTML.jpg

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