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用于食品微生物组分析的逐步宏基因组学:详细综述

Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review.

作者信息

Sadurski Jan, Polak-Berecka Magdalena, Staniszewski Adam, Waśko Adam

机构信息

Department of Biotechnology, Microbiology and Human Nutrition, Faculty of Food Science and Biotechnology, University of Life Sciences in Lublin, 20-704 Lublin, Poland.

出版信息

Foods. 2024 Jul 14;13(14):2216. doi: 10.3390/foods13142216.

Abstract

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.

摘要

这篇综述文章全面概述了目前在食品微生物组研究中使用宏基因组学工具的理解。它涵盖了食品微生物材料遗传分析技术的科学基础和实际应用,包括生物信息学分析和数据解释。文章中讨论的无需传统培养方法分析食品中微生物的方法称为食品宏基因组学。这种方法与其他组学技术,如营养基因组学、蛋白质组学、代谢组学和转录组学,共同构成了食品组学领域。食品宏基因组学通过利用食品组学数据库,能够快速、全面地检测细菌和潜在的代谢途径。尽管其有既定的科学基础和可用的生物信息学资源,但文章中概述的食品宏基因组学研究方法尚未在行业中广泛应用。作者认为,将下一代测序(NGS)与快速发展的数字技术,如人工智能(AI)、物联网(IoT)和大数据相结合,将有助于这种研究策略在食品工业微生物分析中的广泛采用。预计这种采用将在不久的将来提高食品安全和产品质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a51/11276190/4dbbbfaeadad/foods-13-02216-g001.jpg

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