用于食品微生物组分析的逐步式元基因组学:详细回顾

Foods Pub Date : 2024-07-14 DOI:10.3390/foods13142216
Jan Sadurski, M. Polak-Berecka, Adam Staniszewski, A. Waśko
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摘要

这篇综述文章全面概述了目前对在食品微生物组研究中使用元基因组工具的理解。文章涉及食品微生物材料基因分析技术的科学基础和实际应用,包括生物信息分析和数据解读。文章中讨论的不用传统培养方法分析食品中微生物的方法被称为食品元基因组学。这种方法与营养基因组学、蛋白质组学、代谢组学和转录组学等其他全息技术共同构成了食品组学领域。食品元基因组学可以利用食品组数据库对细菌和潜在的代谢途径进行快速、彻底的检查。尽管食品元基因组学的科学基础已经确立,生物信息学资源也已可用,但文章中概述的食品元基因组学研究方法尚未在工业中广泛应用。作者认为,下一代测序(NGS)与人工智能(AI)、物联网(IoT)和大数据等快速发展的数字技术相结合,将促进这一研究策略在食品行业微生物分析中的广泛应用。在不久的将来,这种应用有望提高食品安全和产品质量。
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Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review
This review article offers a comprehensive overview of the current understanding of using metagenomic tools in food microbiome research. It covers the scientific foundation and practical application of genetic analysis techniques for microbial material from food, including bioinformatic analysis and data interpretation. The method discussed in the article for analyzing microorganisms in food without traditional culture methods is known as food metagenomics. This approach, along with other omics technologies such as nutrigenomics, proteomics, metabolomics, and transcriptomics, collectively forms the field of foodomics. Food metagenomics allows swift and thorough examination of bacteria and potential metabolic pathways by utilizing foodomic databases. Despite its established scientific basis and available bioinformatics resources, the research approach of food metagenomics outlined in the article is not yet widely implemented in industry. The authors believe that the integration of next-generation sequencing (NGS) with rapidly advancing digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data will facilitate the widespread adoption of this research strategy in microbial analysis for the food industry. This adoption is expected to enhance food safety and product quality in the near future.
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