Development of experimental protocols and traceable spectral for rapid identification of foodborne pathogens by infrared imaging spectroscopy

麦吉尔大学食品科学和农业化学系的研究人员与加拿大瓦里安公司建立了合作伙伴关系，共同开发快速、自动识别食源性细菌的新技术。食源性疾病仍然非常常见，根据加拿大公共卫生署的数据，每年有超过40%的加拿大人口受到影响。从公共卫生的角度来看，这些疾病不仅会构成严重的健康风险，主要是对年幼者、体弱者和老年人，而且还会给医疗保健系统带来沉重的负担，占用越来越稀缺的资源，而这些资源本来可以用于其他健康问题。从经济角度来看，食源性疾病是生产力损失的主要原因，在加拿大，相关费用加上医疗费用估计每年达到13亿美元。各种各样的细菌是导致很大比例食源性疾病的原因，对公共卫生机构和食品工业来说，获得快速、具有成本效益的方法来识别这些细菌物种都很重要。在本CRD项目中，将开发一种基于红外成像光谱对细菌“指纹”的新识别技术。将建立一个数据库或“光谱库”，其中包含大约200种常见食源性细菌菌株的红外光谱指纹，并将开发数据分析算法，以便通过将其光谱指纹与数据库中的指纹进行匹配来识别从食物中分离出来的细菌。此外，将建立标准化的实验方案，红外图像采集、处理和解释将实现自动化，以便这项技术可以在微生物分析实验室中常规使用。该综合系统将由加拿大卫生部地区（魁北克）实验室的研究人员进行评估。这个为期三年的项目的成功完成，将为负责食品安全的人员提供一个快速鉴定食源性细菌的新而有力的工具。

A partnership between researchers in the Department of Food Science and Agricultural Chemistry of McGill University and Varian Canada Inc. has been formed to develop new technology for the rapid, automated identification of foodborne bacteria. Foodborne illnesses remain very common occurrences, with more than 40% of the Canadian population being afflicted each year according to the Public Health Agency of Canada. From a public health perspective, such illnesses not only can constitute a serious health risk, primarily for the very young, the infirm, and the elderly, but also represent a substantial burden on the healthcare system, taking up increasingly scarce resources that could otherwise be applied toward other health concerns. In economic terms, foodborne illnesses are a leading cause of lost productivity, and the associated costs combined with medical expenses have been estimated to reach $1.3 billion/yr in Canada. Various species of bacteria are responsible for a large proportion of foodborne illnesses, and the availability of rapid, cost-effective methods to identify these species is important to both public health agencies and the food industry. In this CRD project, a new identification technology based on the use of infrared imaging spectroscopy to "fingerprint" bacteria will be developed. A database or "spectral library" containing the infrared spectral fingerprints of approximately 200 strains of common foodborne bacteria will be created, and data analysis algorithms will be developed to allow for identification of bacteria isolated from food by matching of their spectral fingerprints against those in the database. In addition, a standardized experimental protocol will be established, and infrared image acquisition, processing, and interpretation will be automated so that this technique can be routinely employed in microbiological analysis laboratories. The integrated system will be evaluated by researchers at Health Canada's regional (Quebec) laboratory. The successful completion of this three-year project will provide those responsible for food safety with a new and powerful tool for the rapid identification of foodborne bacteria.