Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine, Veterinaerplatz 1, 1210, Vienna, Austria.
Austrian Competence Centre for Feed and Food Quality, Safety and Innovation FFoQSI GmbH, Technopark 1C, 3430, Tulln, Austria.
NPJ Biofilms Microbiomes. 2020 Jul 10;6(1):26. doi: 10.1038/s41522-020-0136-z.
Microbial food spoilage is responsible for a considerable amount of waste and can cause food-borne diseases in humans, particularly in immunocompromised individuals and children. Therefore, preventing microbial food spoilage is a major concern for health authorities, regulators, consumers, and the food industry. However, the contamination of food products is difficult to control because there are several potential sources during production, processing, storage, distribution, and consumption, where microorganisms come in contact with the product. Here, we use high-throughput full-length 16S rRNA gene sequencing to provide insights into bacterial community structure throughout a pork-processing plant. Specifically, we investigated what proportion of bacteria on meat are presumptively not animal-associated and are therefore transferred during cutting via personnel, equipment, machines, or the slaughter environment. We then created a facility-specific transmission map of bacterial flow, which predicted previously unknown sources of bacterial contamination. This allowed us to pinpoint specific taxa to particular environmental sources and provide the facility with essential information for targeted disinfection. For example, Moraxella spp., a prominent meat spoilage organism, which was one of the most abundant amplicon sequence variants (ASVs) detected on the meat, was most likely transferred from the gloves of employees, a railing at the classification step, and the polishing tunnel whips. Our results suggest that high-throughput full-length 16S rRNA gene sequencing has great potential in food monitoring applications.
微生物引起的食物腐败会造成大量浪费,并且可能导致人类食源性疾病,尤其是在免疫功能低下的个体和儿童中。因此,预防微生物引起的食物腐败是卫生当局、监管机构、消费者和食品工业的主要关注点。然而,由于在生产、加工、储存、配送和消费过程中存在多个潜在的污染源,食品产品的污染很难控制,微生物会接触到产品。在这里,我们使用高通量全长 16S rRNA 基因测序技术,深入了解猪肉加工厂的细菌群落结构。具体来说,我们研究了在切割过程中,有多少假定与动物无关的细菌通过人员、设备、机器或屠宰环境转移到肉上。然后,我们创建了一个特定于设施的细菌流动传输图,该图预测了以前未知的细菌污染来源。这使我们能够将特定的分类单元与特定的环境来源联系起来,并为设施提供有针对性消毒的必要信息。例如,莫拉氏菌(Moraxella spp.)是一种重要的肉类腐败生物,也是在肉上检测到的最丰富的扩增子序列变异(ASV)之一,很可能是从员工的手套、分类步骤的栏杆和抛光隧道鞭子上转移过来的。我们的结果表明,高通量全长 16S rRNA 基因测序在食品监测应用中具有巨大的潜力。