COLLABORATIVE RESEARCH: Disposable All-Graphene Microfluidic Biosensor System for Real-Time Foodborne Pathogen Detection in Food Processing Facilities

仅在美国，食品中发现的致病细菌每年就导致4800万人患病，与健康相关的成本高达156亿美元。该项目将创造具有成本效益、快速和易于使用的细菌检测技术(即传感器)，以确保在食品加工设施中广泛使用。这些传感器的工作和外观都很像家用血糖检测设备，用户可以从几乎任何表面的拭子样本中检测病原体，包括设备和地面排水沟。将开发多个传感器并将其连接到互联网，以便可以在中央位置同时收集和分析测量数据。因此，污染突破将被迅速识别和准确定位，以便在受污染的食品进入市场之前采取适当的纠正措施。推广活动将包括在女性探索工程夏令营中进行传感器动手展览和指导学生。由于目前实验室测试技术的成本(每次测试8-10美元)、时间(24-48小时)和低灵敏度(通常需要样品预浓缩的~100 CFU/毫升检测限度)，在处理设施中很少进行食源性病原体检测。因此，在被污染的食品到达消费者手中之前，不能及时确定病原体污染的来源。现场可部署的食源性病原体生物传感器具有低成本、快速(几分钟)和高灵敏度(检测下限为5CFU/毫升)，是非常理想的，但目前还不存在。拟议工作的目标是为食品加工设施中对食品污染(如设备、工作表面)构成高风险的沙门氏菌开发有效的现场可部署生物传感器。多个生物传感器将被创建并在食品加工设施中使用，而测量的数据将通过互联网传输到中央位置。通过物联网(IoT)范式，传感器网络将能够同时监测病原体和卫生效果，以便实施适当的行动。建议的生物传感器有望表现出与目前基于实验室的沙门氏菌检测方法相当的灵敏度，如果不是更好的话。该项目的具体目标是：目标1：开发基于石墨烯的微流控生物传感器系统；目标2：生物功能化和评估用于食源性病原体检测的生物传感器系统；目标3：通过物联网范例评估来自食品加工设施内多个生物传感器的数据。基于石墨烯的生物传感器和相应的微流控系统使用喷墨打印和快速激光脉冲退火来创建具有高导电性、可调疏水性和纳米结构形貌的石墨烯表面，可以协同操作以高灵敏度检测沙门氏菌，而不需要预浓缩技术。石墨烯电极将用适体进行生物功能化，适体具有类似于单抗的结合亲和力。将在缓冲液、鸡汤、屠体衬里和拭子样本中存在其他潜在干扰物(例如，其他革兰氏阴性细菌)的情况下，评估适体对目标沙门氏菌菌株的选择性。生物传感器将进行优化，以消除假阳性和假阴性。如果适配子不够敏感或选择性，将使用单抗(如抗沙门氏菌)。TAMU、ISU和AES Controls(行业协作者)的小规模食品加工设施将用于在食品加工环境中帮助验证传感器系统。此外，ISU的虚拟现实应用中心(Co-Pi是联席主任)将直接致力于开发这个特别网络。外联活动：开发一个互动展览，展示纳米和微型图案如何导致疏水性，为代表不足的少数族裔学生提供物联网学习模块，关于生物传感器设计和食源性病原体检测的动手演示，以及在妇女探索工程夏令营指导年轻女性。

Disease-causing bacteria found in food causes 48 million illnesses and $15.6 billion in health-related costs annually in the U.S. alone. This project will create bacteria testing technology (i.e., sensors) that are cost-effective, rapid, and easy-to-use to ensure wide use in food processing facilities. The sensors will work and look much like a home blood sugar test device that will permit users to test for pathogens from swab samples taken from virtually any surface including equipment and floor drains. Multiple sensors will be developed and connected to the internet so that measurements can be collected and analyzed simultaneously at a central location. Contamination breakouts will therefore be quickly identified and pinpointed so that appropriate corrective measures can be taken prior to the contaminated food reaches the market. Outreach activities will include hands-on exhibit on sensors and mentoring students in Women Explore Engineering Summer Camp.Foodborne pathogen detection in processing facilities is infrequently performed because of the cost ($8-10 per test), time (24-48 h for results), and low sensitivity (~100 CFU/mL detection limits that usually require sample pre-enrichment) associated with current laboratory test techniques. Thus, the sources of pathogen contamination are not determined in a timely fashion prior to the contaminated food reaching the consumer. Field deployable foodborne pathogen biosensors that are low-cost, rapid (a few minutes), and highly sensitive ( 5 CFU/mL detection limits) are highly desirable, but currently do not exist. The objective of the proposed work is to develop effective field deployable biosensors for Salmonella in food processing facility that pose high risk for food contamination (e.g., equipment, work surfaces). Multiple biosensors will be created and used within a food processing facility, while the measured data will be streamed to a central location via the internet. Through the Internet of Things (IoT) paradigm the sensor network will enable simultaneous monitoring of pathogens and sanitation efficacy so that appropriate action can be implemented. The proposed biosensor is expected to exhibit a sensitivity comparable to, if not better than, current laboratory-based Salmonella detection methods. The project specific aims are: Aim 1: Develop a graphene-based microfluidic biosensor system; Aim 2: Biofunctionalize and evaluate the biosensor system for foodborne pathogen detection; Aim 3: Evaluate data from multiple biosensors within a food processing facility via an IoT paradigm. The graphene-based biosensor and corresponding microfluidics system uses inkjet printing and rapid laser-pulse annealing to create graphene surfaces with high electrical conductivity, tunable hydrophobicity, and nanostructured morphologies that can operate synergistically to detect Salmonella with a high sensitivity and without the need for pre-enrichment techniques. The graphene electrodes will be biofunctionalized with aptamers that have binding affinities similar to monoclonal antibodies. The aptamers selectivity to the targeted Salmonella strains will be evaluated within the presence of other potential interferents (e.g., other gram-negative bacteria) in buffer, chicken broth, carcass rinsate, and swab samples. The biosensor will be optimized to negate false positives and false negatives. If the aptamers are not sufficiently sensitive or selective than monoclonal antibodies (e.g. Anti-Salmonella) will be used instead. Small-scale food processing facilities at TAMU, ISU, and AES Controls (industry collaborator) will be used to help validate the sensor system in a food processing setting. Also, the Virtual Reality Applications Center at ISU (Co-PI is the co-director) will directly work in developing this ad-hoc network. Outreach activities the development of an interactive exhibit that displays how nanoscale and microscale patterning induces hydrophobicity, IoT-based learning modules for underrepresented minority students, hands-on demonstrations on biosensor design and foodborne pathogen detection and mentoring young women in the Women Explore Engineering (WEE) summer camp.