1a. Objectives (from AD-416):
1: Develop and integrate operational technologies to rapidly and effectively concentrate viable target cells from food matrices in a self-validating system into an automated instrument. 1A: Integrate technology platforms that we have developed and individually tested into a usable technology for detecting L. monocytogenes in less than 8 h (time-to-result). 1B: Integrate technology platforms, currently being developed in our laboratory, into a usable technology for detecting Salmonella . 1C: Integrate technology platforms into a usable technology for detecting STEC. 2: Develop, evaluate, and adopt novel technologies for rapid detection, identification, and quantification of viable and non-viable target microorganisms. Research areas to be addressed include microfluidic biochips, optical light scattering technology, bacteriophage sensors, and Raman spectroscopy. 2A: Microfabricate and characterize microfluidic biochips that will direct, concentrate, and quantify living microorganisms using micro- and nano-scale electrical, mechanical, and optical methodologies. 2B: Develop light scattering technologies for rapid and high throughput detection and identification of pathogenic bacteria based on unique scattering signatures generated by concentrated colonies. 2C: Develop bacteriophages carrying reporter genes for the detection of E. coli O157:H7 and other foodborne pathogenic bacteria. 2D: Develop a highly sensitive enhanced Raman spectrosensor for field-deployable and routine benchtop in-lab identification of foodborne pathogens.
1b. Approach (from AD-416):
Our approach will be to carry out our objectives using 2 important steps. The first step will be to develop and integrate operational technologies to rapidly and effectively concentrate viable target cells from food matrices in a self-validating system into an automated instrument. When carried out effectively, this step will enable different types of detection platforms to be more effective and accurate. The next step is to develop, evaluate, and adopt novel technologies for rapid detection, identification, and quantification of viable and non-viable target microorganisms. Research areas to be addressed include microfluidic biochips, optical light scattering technology, bacteriophage sensors, and Raman spectroscopy. An experienced multidisciplinary team of investigators from Purdue University, University of Illinois, and the USDA will engage manufacturers of commercial, off-the-shelf components to construct instruments, and the food processing industry or regulatory agencies to test them. This integrated effort will produce operational technologies that can be used to better detect and quantify microbial hazards in food.
3. Progress Report:
Our approach involves development of a bioseparation technology to separate and concentrate pathogenic microorganisms from food matrixes, as well as effective methods for the detection and quantification of foodborne pathogens. The bioseparation technology concentrates cells directly via a sequential filtration process, achieving a 1000-fold concentration of cells in less than 30 minutes. The filtration system was improved this year by optimizing sanitation procedures and software, such that a ‘hands-off’ operation cycle from cell concentration and recovery to cleaning steps can be completed within 2 hours. The filtration device was used successfully to separate and concentrate pathogens from complex foods and coupled to quantitative polymerase chain reaction (qPCR) analysis for detection of very low levels of Salmonella in chicken rinse water within 7 hours. A wide variety of platforms appropriate for detection of the concentrated pathogens were also studied. One detection method uses a microfluidic biochip to further concentrate bacteria, grow and break-open the bacteria, and detect specific pathogens using PCR. This year developments in field effect transistors (FETs) for single cell lysis and localized heating on the biochip were important steps to release and denature DNA from the bacteria cells as a precursor to PCR. Electrical detection of PCR products as an essential part of monitoring the reaction’s progress was also accomplished. A second system called “BARDOT” (Bacterial Rapid Detection using Optical Scattering Technology) uses light scattering techniques to differentiate and classify bacterial colonies grown on Petri-dishes. The database of scattering images from different pathogens continued to be expanded to include a wider variety of microorganisms, including molds, yeasts, and spoilage bacteria in addition to pathogenic bacteria, as well as more types of growth media. BARDOT was able to differentiate and classify 32 different types of Salmonella and seven common types of pathogenic Shiga-toxin producing E. coli. To reduce total detection time from food samples, detection of micro-colonies was optimized. BARDOT could differentiate micro-colonies of Salmonella, E. coli, and Listeria after only 8-12 h of growth on agar plates. Furthermore, BARDOT was equipped with multiple wavelength lasers to improve discriminatory power of scatter signatures and to detect microorganisms that are difficult to detect. A third system is a phage-based detection of E. coli O157:H7. Phage are bacterial viruses that infect specific bacteria. Genetic engineering tools were developed to manipulate the bacterial E. coli O157:H7 phage to produce a phage which causes the target bacteria to glow (luminesce) if infected. Initial experiments detected 1-5 cells in less than 12 hours using observable luminescence. Finally, methods employing Raman (infrared light) spectroscopy were improved this year by developing Raman probes and magnetic nanoparticles that are able to target pathogens and enhance Raman signals such that key pathogens (E. coli O157:H7, Salmonella and L. monocytogenes) could be detected at very low concentration.
1. Rapid recovery, concentration, and detection of Salmonella from chicken extracts. Despite a recent decline in some bacterial foodborne illnesses, foodborne infections caused by the most common strains of Salmonella have not declined in 15 years. New methods to recover and concentrate foodborne pathogens from complex food matrices would greatly facilitate the rapid detection of Salmonella and other foodbonre pathogens leading to a reduction in the distribution of contaminated foods and the prevention of outbreaks of foodborne illness. ARS-funded researchers at Purdue University’s Center for Food Safety Engineering in West Lafayette, Indiana identified ultra and micro-filtration methods for the rapid concentration and recovery of Salmonella from chicken. The concentration method has been used in conjunction with microbiological plating technique for detection of Salmonella in about 24 hours or with DNA-based detection methods (real-time PCR) that can be completed in about 7 hours. The combined approach of concentrating the microorganisms and then testing the concentrated samples for the presence of food pathogens using PCR based techniques will contribute to food safety by increasing identification specificity of the target organism.
2. Nanotechnology for bacterial detection. Nanobiosensors offer advantages over traditional microbiological and standard-scale biosensors for pathogen detection because of their low cost, label-free detection, and potential for massive parallelization. ARS-funded researchers in collaboration with Purdue University’s Center for Food Safety Engineering in West Lafayette, Indiana have made significant advances toward the development of nanobiosensors for nucleic acid-based detection of pathogens. The scientists developed a method to position tiny droplets on an array of individual silicon microwave heaters, allowing precise control the temperature of droplets-in-air and subsequently perform biochemical reactions like DNA melting.
3. Identification of unknown foodborne pathogens. Rapid detection of bacterial foodborne pathogens is necessary to prevent foodborne illness and safeguard public health. The optical light scattering sensor, BARDOT, is a noninvasive label-free detection system which allows identification of bacterial colonies in real-time. Developed by ARS-funded researchers at Purdue University’s Center for Food Safety Engineering in West Lafayette, Indiana, BARDOT involves shining a laser light through the bacterial colony and collecting images of the light that passes through. The images collected contain descriptive characteristics of bacterial colonies, which can be used to identify bacteria by comparing the resulting light scattering image with a library of previously collected images. This method has tremendous potential for properly classifying foodborne pathogens; even emergent pathogens such as the previously unknown type of E. coli that recently caused a serious foodborne outbreak in Europe.