Rubiola Selene, Macori Guerrino, Civera Tiziana, Fanning Séamus, Mitchell Molly, Chiesa Francesco
Department of Veterinary Sciences, University of Turin, Grugliasco, Italy.
University College Dublin-Centre for Food Safety, School of Public Health, Physiotherapy & Sports Science, Dublin, Ireland.
Foodborne Pathog Dis. 2022 Jul;19(7):495-504. doi: 10.1089/fpd.2022.0027.
Since the number of studies of the microbial communities related to food and food-associated matrices almost completely reliant on next-generation sequencing techniques is rising, evaluations of these high-throughput methods are critical. Currently, the two most used sequencing methods to profile the microbiota of complex samples, including food and food-related matrices, are the 16S ribosomal RNA (rRNA) metabarcoding and the whole metagenome sequencing (WMS), both of which are powerful tools for the monitoring of foodborne pathogens and the investigation of the microbiome. Herein, the microbial profiles of 20 bulk tank milk filters from different dairy farms were investigated using both the full-length 16S (FL-16S) rRNA metabarcoding, a third-generation sequencing method whose application in food and food-related matrices is yet in its infancy, and the WMS, to evaluate the correlation and the reliability of these two methods to explore the microbiome of food-related matrices. Metabarcoding and metagenomic data were generated on a MinION platform (Oxford Nanopore Technologies) and on a Illumina NovaSeq 6000 platform, respectively. Our findings support the greater resolution of WMS in terms of both increased detection of bacterial taxa and enhanced detection of diversity; in contrast, FL-16S rRNA metabarcoding has proven to be a promising, less expensive, and more practical tool to profile most abundant taxa. The significant correlation of the two technologies both in terms of taxa diversity and richness, together with the similar profiles defined for both highly abundant taxa and core microbiomes, including , and genera, highlights the possible application of both methods for different purposes. This study allowed the first comparison of FL-16S rRNA sequencing and WMS to investigate the microbial composition of a food-related matrix, pointing out the advantageous use of FL-16S rRNA to identify dominant microorganisms and the superior power of WMS for the taxonomic detection of low abundant microorganisms and to perform functional analysis of the microbial communities.
由于几乎完全依赖下一代测序技术的与食品及食品相关基质有关的微生物群落研究数量不断增加，对这些高通量方法进行评估至关重要。目前，用于分析包括食品和食品相关基质在内的复杂样品中微生物群的两种最常用测序方法是16S核糖体RNA（rRNA）元条形码测序和全宏基因组测序（WMS），这两种方法都是监测食源性病原体和研究微生物组的有力工具。在此，使用全长16S（FL-16S）rRNA元条形码测序（一种第三代测序方法，其在食品和食品相关基质中的应用尚处于起步阶段）和WMS对来自不同奶牛场的20个大容量储奶罐过滤器的微生物概况进行了研究，以评估这两种方法在探索食品相关基质微生物组方面的相关性和可靠性。元条形码测序和宏基因组数据分别在MinION平台（牛津纳米孔技术公司）和Illumina NovaSeq 6000平台上生成。我们的研究结果表明，WMS在增加细菌分类群检测和提高多样性检测方面具有更高的分辨率；相比之下，FL-16S rRNA元条形码测序已被证明是一种有前景、成本较低且更实用的工具，可用于分析最丰富的分类群。这两种技术在分类群多样性和丰富度方面具有显著相关性，同时为包括 、 和 属在内的高丰度分类群和核心微生物组定义了相似的概况，这突出了这两种方法在不同目的下的可能应用。这项研究首次比较了FL-16S rRNA测序和WMS来研究食品相关基质的微生物组成，指出了FL-16S rRNA在识别优势微生物方面的优势用途以及WMS在低丰度微生物分类检测和微生物群落功能分析方面的卓越能力。
