Molecular barcode of foodborne disease precursors to improve biosanitizer performance - Phase II

用于提高生物消毒剂性能的食源性疾病前体分子条形码 - 第二阶段

• 批准号: 508707-2017
• 负责人: Constant, Philippe
• 金额: $ 0.73万
• 依托单位: Institut national de la recherche scientifique
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639696
• 关键词: Molecular; barcode; foodborne; disease; precursors

Increasing global population, globalization, and new living standards have considerably changed the foodmarket. Food is transported over long distances, stored and processed before being distributed to consumers,resulting in the emergence of food safety issues. Food diagnostic currently relies on the detection of modelpathogens and quantification of microbial load. Very few attempts have been made to develop more holisticdiagnostic tools, providing early signal of food susceptibility to pathogens, based on the abiotic and bioticfeatures of food matrices. In a previous NSERC-Engage grant, our team demonstrated that microbialassemblages associated with chia seeds are organized and could provide early signal of contamination risk byallochthonous Enterobacteriaceae. Here we propose a second phase to that previous project to characterize themicrobiome of hemp seeds imported from different countries. Fresh seeds and conditioned seedsdecontaminated using a proprietary process developed by Agri-Neo Inc. will be sampled and analyzed. Using acombination of co-occurrence network analyses, we seek to identify keystone microbial species that facilitateor impede occupation of hemp ecological niche by potential foodborne pathogens. The identification ofantagonist and synergetic species will lead to the development of a genetic barcode indicator to evaluate foodsusceptibility to pathogens. This strategy could revolutionize conditioning food process treatments and qualitycontrol, while helping to determine the commercial values of imported food destined to public markets, lowerthe loss of contaminated food products and the incidence of recall warnings.

全球人口增长、全球化和新的生活水平大大改变了食品市场。食品经过长途运输、储存和加工后，再分发给消费者，导致食品安全问题的出现。食品诊断目前依赖于模式病原体的检测和微生物负荷的量化。很少有人尝试开发更全面的诊断工具，根据食物基质的非生物和生物特征提供食物对病原体易感性的早期信号。在之前的NSERC-Engage资助中，我们的团队证明了与奇亚籽相关的微生物组合是有组织的，可以提供外来肠杆菌科污染风险的早期信号。在这里，我们提出了先前项目的第二阶段，以表征从不同国家进口的大麻种子的微生物组。使用Agri-Neo公司开发的专有工艺净化的新鲜种子和条件种子将被取样和分析。利用共现网络分析的结合，我们试图确定促进或阻碍潜在食源性病原体占领大麻生态位的关键微生物物种。拮抗和协同物种的鉴定将有助于开发一种遗传条形码指标来评估食物对病原体的易感性。这一策略可以彻底改变食品加工处理和质量控制，同时有助于确定运往公共市场的进口食品的商业价值，降低受污染食品的损失和召回警告的发生率。