Identification and sub-typing of food-born bacteria from animal feed ingredients, animal feed & pet foods samples using Matrix-Assisted Laser Desorption & Ionization Time-of-Flight Mass Spectrometry.

FDA CVM VET-LRN 计划 (U18) 拨款提案 适用于 FOA # PA-13-244、CFDA 93、103 项目概要/摘要 该项目将使用基质辅助激光解吸电离飞行时间质量 用于鉴定人类食源性病原体的光谱测定法 (MALDI-TOF MS)，包括 沙门氏菌、大肠杆菌、弯曲杆菌、单核细胞增生李斯特氏菌、产气荚膜梭菌、 动物饲料成分、宠物食品和动物饲料中的金黄色葡萄球菌。第一年 该项目的重点是使用 MALDI 对沙门氏菌进行鉴定和分型 飞行时间女士。同样的方法将用于以下四个领域的其他食源性病原体 年。宠物食品/动物饲料的沙门氏菌污染已导致人类疾病爆发 沙门氏菌病。然而，动物饲料成分、动物饲料和宠物零食的污染 食物还没有被系统地研究过。常规培养是“金标准”方法 用于隔离和识别。这种方法是劳动密集型、昂贵且耗时的， 在受污染动物分发之前没有及时提供信息 食物矩阵。因此，快速可靠的识别和分型的替代方法 迫切需要沙门氏菌来提高动物饲料供应的安全性和完整性， 这反过来又会限制人类感染。在此应用中，我们建议开发方法 使用 MALDI-TOF MS 快速、特异性地鉴定和分型沙门氏菌 在动物饲料基质的初步培养板上生长。微生物鉴定使用 该技术基于直接从细胞或获得的光谱模式的比较 使用模式识别算法根据参考光谱进行细胞提取。这项技术是 目前以商业平台的形式提供，并且有相当多的研究 已生成证明其在沙门氏菌鉴定和分型方面的实用性。 我们已成功利用该技术来鉴定粪便和粪便中的沙门氏菌。 动物组织样本。然而，人们对 MALDI-TOF 的使用缺乏了解。 MS 用于鉴定宠物食品和动物饲料基质中的细菌分离株。拟议的 研究将通过以下三个具体目标来解决这些问题： 具体目标 1：来自各种动物的食源性细菌分离株的鉴定和分型 使用 MALDI-TOF MS 使用新颖的库分析食品基质。 具体目标 2：直接从生长的菌落中鉴定食源性细菌并进行分型 在来自动物饲料和食品基质的各种培养基上。 具体目标 3：向其他 Vet-LIRN 转移和培训这种新方法 实验室。 该项目的成功完成将扩大该技术目前的应用范围 将粪便和动物组织样本添加到动物饲料基质中，以提高饲料的安全性和完整性 美国动物饲料供应。此外，该研究还经过多实验室协作验证 该方法将提高 Vet-LIRN 实验室的能力和容量，以便为 CVM 提供服务 应对动物食品污染事件时需要快速周转时间。

FDA CVM VET-LRN PROGRAM (U18) GRANT PROPOSAL FOR FOA # PA-13-244, CFDA 93, 103 Project Summary/Abstract This project will use Matrix-Assisted Laser Desorption Ionization Time-of-Flight mass spectrometry (MALDI-TOF MS) for identification of human foodborne pathogens, including Salmonella, E. coli, Campylobacter species, Listeria monocytogenes, Clostridium perfringens, and Staphylococcus aureus in animal feed ingredients, pet foods and animal feed. The first year of the project will focus on identification and subtyping of Salmonella bacteria using MALDI- TOF MS. The same approach will be used for other foodborne pathogens in the following four years. Salmonella contamination of pet foods/animal feeds has resulted in outbreaks of human Salmonellosis. However, contamination of animal feed ingredients, animal feed, and pet treats and foods have not been systematically studied. Routine culture is the "gold standard" method for isolation and identification. This method is labor intensive, expensive, and time consuming, which does not provide timely information before the distribution of the contaminated animal food matrices. Therefore, alternative methods for rapid and reliable identification and subtyping of Salmonella bacteria are urgently needed to improve safety and integrity of animal feed supply, which in turn will limit human infections. In this application we propose to develop methods using MALDI-TOF MS for rapid and specific identification and typing of Salmonella bacteria grown on preliminary culture plates from animal feed matrices. Microbial identification using this technology is based on the comparison of spectral patterns obtained directly from cells or cell extracts against reference spectra using a pattern recognition algorithm. This technology is currently available in the form of commercial platforms, and a considerable amount of studies have been generated demonstrating its utility for identification and typing of Salmonella bacteria. We have successfully used this technology for identification of Salmonella bacteria in fecal and animal tissue samples. There is, however, a lack of knowledge regarding the use of MALDI-TOF MS for identification of bacterial isolates from pet food and animal feed matrices. The proposed study will address these issues by the following three specific aims: Specific aim 1: Identification and subtyping of foodborne bacterial isolates from various animal food matrices using MALDI-TOF MS using a novel library. Specific aim 2: Identification and subtyping of foodborne bacteria directly from colonies grown on various culture media from animal feed and food matrices. Specific aim 3: Transferring and training of this new methodology to other Vet-LIRN laboratories. Successful completion of this project will expand the current application of this technology from fecal and animal tissue samples to animal feed matrices to improve the safety and integrity of the US animal feed supply. In addition, the multi-laboratory collaboration validation of this methodology will increase Vet-LIRN laboratory capability and capacity in order to serve CVM's need for rapid turnaround times when responding to animal food contamination events.