A Portable, On-site Food Pathogen Detector for Agriculture and Food Systems

NON-TECHNICAL SUMMARY: In order to ensure agriculture and food safety, as well as to enhance our anti-bioterrorism (including anti-agroterrorism) ability, a rapid, sensitive and specific detection system must be developed. More importantly, this system must be able to detect multiple pathogens simultaneously (termed as "multiplexed") as opposed to detecting one pathogen at a time. But most importantly, this system must be portable so that it can be deployed in the field or point of interest. Furthermore, it must be operable by minimally trained, non-skilled workers. At the moment, such a system does not exist. The current detection and diagnosis of bacterial pathogens requires a pre-knowledge of the correlation between the presence of bacteria and their appearance and/or clinical symptoms. This is time consuming, laborious, and easily misleading. In the case of food inspection and safety, there are few symptoms, and the detection is thus usually limited to a few common bacteria. Currently employed detection systems include a variety of molecular, cellular and immunological approaches. Most of these systems are laboratory based requiring non-portable equipment (e.g., a bulk thermo cycling machine, a floor-standing machine called flow cytometer, a microscope, etc. all of them need at least 120 volt house power supplies; some even need 220 volts). In addition, most current detection systems target one pathogen at a time, severely limiting the response time and capacity in the case of outbreak caused either naturally or deliberately. Thus a portable detection system that can detect multiple targets simultaneously is urgently needed. An effective portable detector usually includes three components: 1) sample collection and processing; 2) labeling and encoding, and 3) decoding and detection. This proposed research will address the third aspect of a pathogen detection system: decoding and detection. Previously the PI's group has developed a novel, DNA-based nanobarcode labeling system (the second aspect) that can be used to detect multiple pathogens simultaneously. The nanobarcode system is a platform technology that can be decoded and detected by any fluorescent-based equipment. The proposed research will expand our DNA nanobarcode achievements and build a portable detection device that will be able to detect multiple pathogens with high accuracy, low cost, and fast speed. Most importantly, it uses 9 volt batteries and eliminates the need for large pieces of equipment, making it usable at the point of interest including dairy farms, food manufactures, and livestock production facilities. This device will also have a very strong commercial potential. In essence the proposed device will be much like a UPC barcode scanner but with a compact, all-in-one format. In addition to build a portable device, the proposed research also has far reaching significance by employing nanotechnology in agricultural and food systems. Such integration of nanotechnology with agriculture and food systems has been lagged behind. <P>

APPROACH: We will adapt a modular approach to carry out the proposed research. In particular, we will divide the proposed portable device into the following five modules: 1) a sample module that includes micro wells and microfluidic channels; 2) a UV-light source that is battery-powered; 3) an optical magnification that will be fabricated in-house; 4) an approach that will produce two spectral images (see below); and 5) a digital camera coupled with a laptop computer that will be graphically interfaced with end users with our in-house-built, MatLab-coded software. The basic procedures of decoding the DNA nanobarcodes are as follows. Samples will first be processed by removing excess liquids, debris, etc. Pathogens will then be captured onto a microbead that has been pre-labeled with a specific probe (DNA probe, or RNA probe, or Antibody probe), and the beads will be incubated with our nanobarcodes. To decode the beads, they will pulse-flow over a transparent microfabricated Poly(dimethylsiloxane) (PDMS) sample chip. The size of the wells is designed such that only 1 bead can fit into 1 well. When flow is stopped, a portable LED (UV source) will be developed to excite the fluorescence barcodes on the beads. Spectral characteristics at each of the wells will be detected. Two images will then be collected to match the emission output from equal amounts of fluorescent materials. Spectral filters and neutral density filters will be used to match intensity. It is also possible to produce a single image with multiple spectral images. In this case, there would not be a need to switch filters between images. The resolution of the camera will depend on the number of wells processed at a single time and the technique used to generate multiple images. Using MatLab, GUI (graphic user interface) will be coded to assign pseudo-colors to each ratio of the fluorescent color; thus untrained end-users can easily identify specific species by unique colors (rather than ratios). The proposed methods are truly interdisciplinary integrating molecular biology, nanotechnology, DNA engineering, and biosensing together for agriculture and food systems. During the implementation, the proposed research will be jointly designed with an extended research and extension community including people in the state diagnostic labs and relevant industries. In particular, co-PI Prof. Daniel Aneshansley will provide his expertise in electronic design and imaging processing. Together, we will also collaborate with Dr. Yung Fu Chang, Director of New York State Diagnostic Laboratory and Professor in the Department of Population Medicine and Diagnostic Sciences in the College of Veterinary Medicine at Cornell University. Prof. Chang will provide real samples from cattle feces as well as positive controls for detections. Prof. Chang and the PI (Luo) have established close collaborations in multiple fronts including veterinary diagnostic and drug delivery, evidenced by one joint paper that has been submitted. We are confident that our methods are well positioned to generate expected results.