1: Development and evaluation of technologies for sample preparation, detection (label-based and label-free), and characterization of microbial, chemical, and biological contaminants of concern in foods that can be implemented for improved food safety and food defense. 1A. Spectroscopy-based identification of foodborne pathogens, toxins, and chemical contaminants. 1B. Antibody-based detection of foodborne pathogens and toxins. 1C. DNA - based detection of foodborne pathogens. 1D. Phage-based detection of foodborne pathogens. 1E. Cell-based detection of foodborne pathogens and toxins. 1F. Enabling technologies for pathogen detection. 2: Application of CFSE developed technologies either alone or in combination with existing methods to evaluate microbial populations and the microbial ecology of foods during production and processing. 2A. Expand the databases for BARDOT and HESPI techniques using pure cultures of known microorganisms (foodborne pathogens and indicator microorganisms) 2B. Apply BARDOT and HESPI techniques to analyze microbial populations in foods
The food supply must be protected from pathogens, toxins, and chemical contamination that cause disease or illness in humans. Detection technologies are a critical component for identifying and controlling the potentially harmful food contaminants. The overarching goal of the Center for Food Safety Engineering (CFSE), working in collaboration with USDA-ARS scientists, is to develop, validate, and implement new technologies and systematic approaches for improving food safety. We propose to develop a variety of timely, accurate, and cost-effective technologies for the pre-screening, detection, characterization, and classification of foodborne hazards. Our prototype pre-screening and detection technologies include hyperspectral light scattering, metal-enhanced plasma spectroscopy, phage-based detectors, cell-based assays, antibody- and DNA-probe inkjet-printed test strips, plasmonic ELISA, and enhanced lateral flow immunosensors. The accompanying algorithms and software for data processing, analysis, and interpretation of colorimetric, fluorometric, light-intensity, light-scattering, and spectroscopy-based assays, along with time-temperature tracking devices, will enable and enhance these technologies. These methods will detect Listeria monocytogenes, Shiga toxin-producing Escherichia coli (STEC), Campylobacter jejuni, and Salmonella enterica serovars, with demonstrated applications in meat, poultry, and produce, as well as detect toxins, metals, and chemicals of concern in foods. An experienced multidisciplinary team of investigators from Purdue University, the University of Illinois, and USDA will produce and evaluate operational technologies, and engage stakeholders and industry, in an integrated effort to validate and implement technologies for better detection of foodborne hazards along the food production continuum.
We are developing advanced technologies for sample handling and the detection of foodborne pathogens and toxins, and demonstrating their applications for meats, poultry, ready-to-eat (RTE) products, and produce. All of the individual projects continue to move forward with most of our milestones either fully or substantially met. Our elastic light scatter “BARDOT” (Bacterial Rapid Detection using Optical Scattering Technology) system uses light scattering techniques to differentiate and classify bacterial colonies grown on Petri-dishes. BARDOT analysis has successfully differentiated bacteria at genus, species, and serovar/serotype levels, with correct classification often above 90% for foodborne pathogens (Listeria monocytogenes, Salmonella, Shiga toxin-producing E. coli (STEC), Vibrio, Staphylococcus, and Bacillus species). The BARDOT systems use a single-wavelength red laser to interrogate the bacterial colonies to generate a scatter image, an enhanced version of the BARDOT technology (Hyperspectral Elastic Scatter Phenotyping Instrument, or HESPI) is being developed using a newly introduced supercontinuum laser. The HESPI system is capable of using 50-100 different laser lines to generate scatter images using multiple wavelengths of light, providing significantly more information for bacterial differentiation and identification. One of the critical issues in dealing with a wide range of wavelengths is that the imaging spot laterally translates due to diffraction phenomena from the laser filters. This year an optical relay system was designed and tested that can minimize this spot movement so that hyperspectral imaging from a single colony can be achieved within 40-100 ms. Efforts are ongoing to validate pathogen identification by BARDOT/HESPI in real-world samples, emphasizing leafy greens and poultry, by coupling laser scatter patterns with DNA sequence verification and macro- and micro-morphology of the colonies. Recent work has also demonstrated the feasibility of using a single culture system with BARDOT to simultaneously detect multiple different pathogens. An additional 1100 samples were collected from poultry farms in the past year and this yielded a collection of more than 800 isolates of Salmonella. These isolates are being confirmed via PCR and serotyping and will be used to enhance our optical scatter pattern libraries. Work is also ongoing to extend the use of BARDOT/HESPI to the characterization of entire microbial communities found on food samples. We have used our previous culture collection to construct BARDOT libraries that can classify most of the culturable naturally occurring bacterial genera from foods with 90% accuracy in mixed populations. Some genera generate scatter patterns that are so similar that it is difficult for BARDOT to distinguish them under these conditions and we are working with both HESPI and improvements to the software to see if we can develop methods to properly differentiate all of the genera. Characterization of the bacterial and fungal communities on lettuce using DNA sequencing methods is also ongoing. Culture-dependent methods were used to characterize the bacterial and fungal communities, and culture independent methods (next-generation DNA sequencing) are being optimized so that we can examine how these communities vary spatially and with differing growth conditions. Analysis of fungal communities has identified several types of yeast (Sporidiobolales) on the surface of lettuce that have also been reported from contrasting ecosystems, including marine, soil, polar ice, and many others. An analysis of niche preferences in Sporidiobolales shows they are ubiquitous on plant surfaces and in commercial crops and food products. The dominant yeast on the surface of lettuce is a new species (Sporobolomyces cf. roseus) that is ubiquitous on plant surfaces, but had not been previously isolated or characterized. We are currently collecting full assimilation profiles to fully characterize this species. We have created and started to populate an online fungal catalog that will eventually provide all data on the panmicrobiome of Romaine lettuce including numerous tools, spanning from classical to innovative (including molecular barcodes, scatter patterns, biochemical, and morphological) to expedite the identification of fungal colonies directly by food safety inspectors and members of the fresh produce industry. A better understanding of the ecology of the microorganisms that inhabit the surface of fresh produce will provide useful new approaches to increase product shelf-life and control human pathogens that exploit this environment. A “bi-phasic” DNA amplification assay system is also being developed. This involves the direct drying of food samples into a solid phase followed by the release of bacterial DNA into a liquid phase by thermal lysis of bacterial cells in the solid phase. This DNA can then be amplified and specific sequences detected in a loop mediated isothermal amplification (LAMP) reaction. The system has been shown to be capable of very sensitive detection in bacterial cultures (~1 cell in a 4 microliter sample). Further development of methods and testing of the system with environmental samples is in progress. The development of a metal enhanced plasma spectroscopy (MEPS) system was slowed this year to achieve the goal of having a more robust instrument in hand for the remaining development work. This system has now been used to demonstrate the detection of metals in a paper-based assay as well as detection of metals conjugated to antibody molecules. This has also been used to demonstrate the ability to detect E. coli O157:H7 in a paper-based assay and preliminary steps were achieved to demonstrate the ability to do multiplex assays using different metal ions. In addition, a Notice of Allowance was issued this year by the U.S. Patent and Trademark Office for a patent application (15/510,319) covering intellectual property related to the metal-antibody tagging and plasma-based detection technology. Several lateral flow immunochromatography assays (LFIA) and DNA-based aptamer approaches are in development. Work on magnetically focused lateral flow assays continued with real world samples including fruit juices and fresh produce. Detection limits of 50-100 cells per milliliter have been achieved. A cell phone-based sensor for reading the lateral flow assays has also been developed. Methods for optimized printing of DNA aptamers for use in detecting foodborne pathogens have also been developed and these assays can also be read with a sensor attached to a mobile phone. Detection limits of 100 cells/mL in ground beef enrichment cultures have also been achieved with this DNA-based system. Our plasmonic ELISA system (PES) has been tested for sensitivity and specificity when used with anti-Salmonella antibodies. All Salmonella enterica serovars including Typhimurium, Enteritidis, Choleraesuis and several others showed strong species-specific reaction while Listeria monocytogenes, Bacillus cereus, and Staphylococcus aureus did not show any reaction. Appropriate antibodies to adapt this technology to the detection of Listeria have been developed and are in the process of being tested. Both traditional and plasmonic ELISA have a limit of detection of about 10^8 cells/mL, however, PES yields a clear change in color which can be detected with naked eyes, while the color change in conventional ELISA is subtle and requires a spectrophotometer for quantification. We are now developing an In-Cell ELISA (ICE) for the detection of viable foodborne pathogenic bacteria. In ICE, instead of a capture antibody, which is used in conventional ELISA, a mammalian cells are used to capture the pathogenic bacteria. In ICE, the natural adhesion ability (achieved by using virulence factors) of a pathogen can be exploited for detection of the viable pathogenic organism from food. A secondary antibody and colorimetric detection is then used in a manner similar to conventional ELISA assays. Initial experiments have demonstrated the efficacy of ICE for detection of Listeria monocytogenes and Salmonella enterica. For monitoring the temperature of food products through distribution and retail, a high-resolution (1°C), low-powered, networked sensor for time-temperature monitoring was developed that can transmit measurements in real time to a base station. Modifications have been made that optimize data storage and transmission as well as providing a rigid housing for the sensor. These sensors have been tested in a real-world refrigerated environment and have provided temperature data for a period of more than two months. Work is continuing on battery-less sensors that can be inductively coupled to a receiving unit to provide a lower cost sensor. Experimentally determined bacterial growth curves in deli meats maintained under various temperature regimes will be used to model growth under a wide range of conditions. Integrating the TTM sensor data with the bacterial growth models could allow for real-time estimates of product shelf-life or potential increases food safety risks. A better understanding of the specificity of bacteriophage PhiV10 for E. coli O157:H7 was obtained by testing the phage on numerous strains of E. coli bearing serogroup O157 O-antigen and variable flagellar (H) antigens and other strains bearing the H7 flagellar antigen and various O antigens. The results demonstrate that PhiV10 requires both of these antigens to successfully infect, although it can bind to the bacterial cell if only the O157 antigen is present.
1. Cellphone-based technology for pathogen detection. Portability of new pathogen detection systems enables them to be used in a variety of critical real-world scenarios and smartphone-based detectors provide an easy access platform for portability. ARS-funded researchers at the Purdue University Center for Food Safety Engineering have developed a sensitive bioluminescence detector using a smartphone that was able to detect E. coli O157:H7 on spiked ground beef samples after 10-12 hours culture using a previously developed bacteriophage-based luminescent detection system. Purdue researchers also developed a smartphone-based imaging system for quantitative detection of pathogens via lateral flow immunoassays (akin to a home pregnancy test). Integration of existing foodborne pathogen detection systems with smartphone hardware and applications will provide a tremendous benefit to the food industry and food testing laboratories by increasing portability of testing methods and testing data. U.S. Patent Application (16/175752) has been submitted to cover the developed technology.
2. Nanoparticles for targeted bacterial killing. The presence of human pathogens in biofilms in foods and food production settings remains a major challenge for food safety. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, synthesized and assessed a novel functionalized gold nanoparticle (fGNP) that kills and prevents biofilm formation by the deadly foodborne pathogen Listeria monocytogenes. The fGNP is coated with a molecule that directs the nanoparticle to bind to L. monocytogenes and an antimicrobial molecule that kills the bacterium. In addition to providing an effective mechanism to killing L. monocytogenes, the fGNP provides a platform for the development of reagents to reduce or eliminate other foodborne pathogens on surfaces in food processing settings.
3. Simultaneous detection of three major pathogens from food samples using optical scattering technology. The detection of human pathogens in food remains a major challenge for the food industry. Application of novel, rapid technologies increases food safety while reducing costs. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, employed a laser light scattering technology (BARDOT) coupled with a multi-pathogen selective medium for concurrent detection of three major foodborne pathogens in a single assay. BARDOT was used to detect and distinguish Salmonella enterica, Shiga-toxin producing Escherichia coli (STEC) and Listeria monocytogenes from food based on colony scatter signature patterns. This innovative BARDOT multi-pathogen detection platform can reduce turn-around-time and economic burden on food industries by offering a label-free, non-invasive on-plate multi-pathogen screening technology to reduce microbial food safety and public health concerns.
4. A super-sensitive lateral flow immunosensor for rapid detection of pathogenic bacteria from foods. Rapid and inexpensive detection of human pathogens in food samples is critical to maintaining a safe food supply. ARS-funded scientists at the Purdue University Center for Food Safety Engineering in West Lafayette, Indiana, have developed an enhanced immunoassay that is about 1000-times more sensitive than current commercial tests. The ability to detect pathogens at this low level is due to the fact that we direct pathogens towards the signal generation region using a simple magnet integrated within the sensor. The entire procedure can be performed in under 45 minutes and the signal can be visualized by the naked eye. Tests have been developed for three foodborne pathogens: E. coli O157:H7, Salmonella, and Listeria monocytogenes. A provisional patent application has been filed (2019-IRUD-68420) related to magnetic focusing technology that leads to the dramatically improved sensitivity of this lateral flow assay.
5. Portable time-temperature monitors (TTMs) for food safety. Temperature is a critical control point to extend shelf-life and ensure safety of many foods. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, developed and deployed low-cost, portable time-temperature monitoring (TTM) sensors that provided continuous temperature data for over two months in a deli case of a commercial store. A smartphone-based application that interfaces with the TTM sensors for the acquisition, storage, and cloud-upload of measurements was also developed as part of this study. The interface is simple and allows simultaneous monitoring of multiple sensors with a single handheld device. Accurate TTM throughout food transport and storage would allow the modeling of bacterial growth in food products, which in turn could predict changes in shelf-life or risk of pathogen growth.
6. A large collection and characterization of bacterial strains associated with organic and conventional Romaine lettuce. Bacteria pathogenic to humans have been found at an increasing rate as contaminants in fresh produce. Reducing the frequency of illness associated with the consumption of fresh produce will require an understanding of both the events leading to contamination and how the human pathogens integrate into the native microbial communities. ARS-funded scientists at the Purdue University Center for Food Safety Engineering in West Lafayette, Indiana, have created a representative collection of 645 bacterial strains from organic and conventional romaine lettuce. The 9 most abundant types (representing about 77% of the romaine lettuce-associated culturable bacterial genera) were used to build image identification libraries using the light scattering bacterial identification technology called BEAM. Three BEAM identification libraries were tested using an additional 215 lettuce isolates; demonstrating an average error per class of less than 10%. These studies demonstrate the efficacy of the BEAM for identification of bacteria from food and environmental samples and the libraries developed will aid in the rapid characterization of the native bacterial community found on lettuce.
7. Comparison of Salmonella prevalence on conventional and no antibiotics ever (NAE) poultry farms. Salmonella is an important human foodborne pathogen often associated with poultry. With changing practices in the poultry industry, such as no antibiotics ever (NAE) on-farm production, it is important to determine the impact these changing practices have on Salmonella prevalence in poultry. ARS-funded researchers at the University of Georgia worked with poultry producers to test for the prevalence of Salmonella throughout the growth of broiler chickens on these different types of farms. Results from these samplings showed that there is a higher prevalence of Salmonella on the conventional farms than in NAE farms, suggesting that NAE poultry production does not pose an elevated risk of Salmonella prevalence.
8. A new bench top laser-based instrument for foodborne pathogen detection. Rapid and sensitive detection of human pathogens in food samples is a major challenge for food safety researchers. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, have developed a new laser-induced breakdown spectroscopy (LIBS) instrument and demonstrated that it can be used to detect metal-labeled antibodies in paper-based immunoassays, an assay platform commonly used for foodborne pathogen detection. These studies provide the basis for the use of this technology for the development of commercial food safety test kits. A Notice of Allowance was issued this year by the U.S. Patent and Trademark Office for a patent (application 15/510,319) covering intellectual property related to various aspects of this work.
9. Ink-jet printing of test strips for detection of E. coli O157:H7. It is known that the foodborne pathogen E. coli O157:H7 can cause severe disease and even death. Therefore, the detection of foodborne pathogens is crucial for global public health. The work performed by ARS-funded scientists at the Center for Food Safety Engineering, Purdue University, West Lafayette, Indiana, designed an inkjet printing-based, cost-efficient, reliable, and repeatable approach for the detection of foodborne bacterial pathogens in real food samples. Paper test strips that were printed with novel bio-inks containing DNA molecules (aptamers) that specifically bind to E. coli O157:H7 provided quantitative detection of the pathogenic bacteria from ground beef with an extremely low limit of detection (100 CFU/ml). This aptamer-based platform achieves highly sensitive and specific detection of E. coli O157:H7 using a cost-efficient and scalable printable bio-ink that has the potential to significantly reduce the price for rapid testing of foodborne pathogens.
10. Artificial intelligence for recognition of emerging foodborne pathogens. A major issue in any type of human disease prevention (including foodborne illness) is the ability to recognize new and emerging threats from a vast and complex sea of data. ARS-funded scientists at the Purdue University Center for Food Safety Engineering in West Lafayette, Indiana, have employed AI-enhanced data processing to enumerate classes of microorganisms and recognize the presence of new (i.e., previously unknown or emerging) types of microbes. The result demonstrates the tremendous capacity for machine learning technologies in the areas of biosurveillance; biothreat detection and agricultural biosafety. The developed software has applicability far exceeding the field of agriculture and food safety, and it could be potentially used for visualization and interaction with clinical samples processed using advanced genomic technologies.
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