Hellenic Agricultural Organization "DEMETER", Institute of Technology of Agricultural Products, Department of Dairy Research, Ethnikis Antistaseos 3, 45221, Ioannina, Greece.
University of Turin, Department of Agricultural, Forest and Food Sciences, Laboratory of Food Microbiology, Largo P. Braccini 2, 10095, Grugliasco, Turin, Italy.
Food Microbiol. 2018 Dec;76:279-286. doi: 10.1016/j.fm.2018.05.009. Epub 2018 May 24.
The recent advances in molecular biology, such as the advent of next-generation sequencing (NGS) platforms, have paved the way to new exciting tools which rapidly transform food microbiology. Nowadays, NGS methods such as 16S rDNA/rRNA metagenomics or amplicon sequencing are used for the taxonomic profiling of the food microbial communities. Although 16S rDNA/rRNA NGS-based microbial data are not suited for the investigation of the functional potential of the identified operational taxonomic units as compared to shotgun metagenomics, advances in the bioinformatics discipline allow now the performance of such studies. In this paper, a bioinformatics workflow is described integrating predictive metagenomics profiling with specific application to food microbiology data. Bioinformatics tools pertinent to each sub-module of the pipeline are suggested as well. The published 16S rDNA/rRNA amplicon data originated from an Italian Grana-type cheese, using an NGS platform, was employed to demonstrate the predictive metagenomics profiling approach. The pipeline identified the microbial community and the changes that occurred in the microbial profile during manufacture of the food product studied (taxonomic profiling). The workflow also indicated significant changes in the functional profiling of the community. The tool may help to investigate the functional potential, alterations, and interactions of a microbial community. The proposed workflow may also find an application in the investigation of the ecology of foodborne pathogens encountered in various food products.
近年来，分子生物学领域的进展，如高通量测序（NGS）平台的出现，为快速转化食品微生物学提供了新的令人兴奋的工具。如今，16S rDNA/rRNA 宏基因组学或扩增子测序等 NGS 方法被用于食品微生物群落的分类分析。虽然与宏基因组学相比，基于 16S rDNA/rRNA 的 NGS 微生物数据不适合研究鉴定的操作分类单位的功能潜力，但生物信息学领域的进展现在允许进行此类研究。本文描述了一种生物信息学工作流程，该流程将预测宏基因组分析与特定的食品微生物学数据应用相结合。还提出了与该管道的每个子模块相关的生物信息学工具。使用 NGS 平台从意大利格拉纳干酪中获得的已发表的 16S rDNA/rRNA 扩增子数据被用于演示预测宏基因组分析方法。该流程确定了微生物群落以及在研究的食品生产过程中微生物谱发生的变化（分类分析）。该工作流程还表明，群落的功能分析也发生了显著变化。该工具可用于研究微生物群落的功能潜力、变化和相互作用。该工作流程还可能在调查各种食品中遇到的食源性致病菌的生态学方面找到应用。
