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，造成156亿美元的健康相关费用。该项目将创建细菌测试技术（即，传感器），具有成本效益，快速，易于使用，以确保在食品加工设施中的广泛使用。这些传感器的工作原理和外观很像家用血糖检测设备，允许用户从几乎任何表面（包括设备和地漏）采集的拭子样本中检测病原体。 将开发多个传感器并连接到互联网，以便在中央位置同时收集和分析测量结果。因此，污染的爆发将被迅速识别和精确定位，以便在受污染的食品进入市场之前采取适当的纠正措施。 外展活动将包括在妇女探索工程夏令营的传感器和指导学生的动手展览。在加工设施中的食源性病原体检测很少进行，因为成本（每次测试8 -10美元），时间（24-48小时的结果），和低灵敏度（约100 CFU/mL的检测限，通常需要样品预富集）与当前的实验室检测技术。因此，在被污染的食品到达消费者之前，病原体污染的来源没有被及时地确定。低成本、快速（几分钟）和高灵敏度（5 CFU/mL检测限）的可现场部署的食源性病原体生物传感器是非常理想的，但目前还不存在。拟议工作的目标是开发有效的现场部署的生物传感器，用于食品加工设施中的沙门氏菌，这些食品加工设施对食品污染构成高风险（例如，设备、工作表面）。多个生物传感器将在食品加工设施中创建和使用，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）模式，传感器网络将能够同时监测病原体和卫生功效，以便采取适当的行动。预计拟议的生物传感器将表现出与当前基于实验室的沙门氏菌检测方法相当（如果不是更好的话）的灵敏度。 该项目的具体目标是：目标1：开发基于石墨烯的微流体生物传感器系统;目标2：生物功能化和评估生物传感器系统用于食源性病原体检测;目标3：通过物联网范式评估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体系统使用喷墨打印和快速激光脉冲退火来创建具有高电导率、可调疏水性和纳米结构形态的石墨烯表面，其可以协同操作以高灵敏度检测沙门氏菌，而不需要预富集技术。石墨烯电极将用具有类似于单克隆抗体的结合亲和力的适体进行生物功能化。将在存在其他潜在干扰物（例如，其他革兰氏阴性菌）。生物传感器将被优化以消除假阳性和假阴性。如果适体的灵敏度或选择性不够，则将使用单克隆抗体（例如抗沙门氏菌）。TAMU，ISU和AES Controls（行业合作者）的小规模食品加工设施将用于帮助验证食品加工环境中的传感器系统。此外，ISU的虚拟现实应用中心（联合PI是联合主任）将直接参与开发这个自组织网络。外联活动：开发互动展览，展示纳米级和微米级图案如何诱导疏水性，为代表性不足的少数民族学生提供基于物联网的学习模块，生物传感器设计和食源性病原体检测的实践演示，并指导妇女探索工程（WEE）夏令营的年轻女性。

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.