Objective 1: Development and evaluation of innovative sensor technologies for the detection and characterization of biological, chemical, and physical contaminants of concern in foods that can be implemented for improved food safety and/or assessment of food integrity and adulteration. Sub-objective 1A: Lysogenic phage-based detection of Shiga toxin producing E. coli and Salmonella serovars. 1.A. Aim 1 Development of luminescent/colorimetric phage for detection of Salmonella serovars. (Applegate) 1.A. Aim 2 Generate, validate, and transfer a field-portable and lab based luminescent phage-based method for quantitative detection of Shiga-toxin producing E. coli (STEC). (Applegate) Sub-objective 1B: Cell phone-based technologies for pathogen detection. 1.B. Aim 1 Electrochemical and mass-based methods for smartphone-based instrumentation. (Bae, Robinson, Rajwa) 1.B. Aim 2 Enhancing the cell phone-linked bioluminescence and lateral flow assay technology for food safety applications. (Bae, Applegate, Deering, Robinson, Rajwa) Sub-objective 1C: Portable laser-induced breakdown spectroscopy system for on-field multiplexed detection of pathogens. 1.C. Aim 1 Design of LIBS-compatible immunoassays. (Robinson, Bae, Rajwa) 1.C. Aim 2 Design and prototyping of portable LIBS-based system. (Robinson, Bae, Rajwa) 1.C. Aim 3 Development and implementation of data acquisition and management software. (Robinson, Bae, Rajwa) Sub-objective 1D: Multiplexed detection platform technologies for food safety threats 1.D. Aim 1 Design of a multiplex/multi-replicate dual modality detection platform for whole-cell foodborne pathogens. (Stanciu, Deering, Chiu, Allebach) 1.D. Aim 2 Design and fabricate a portable multiplexed paper-based platform for quantifying live Shiga toxin-producing E. coli strains in the field. (Verma, Stanciu, Chiu, Allebach) Sub-objective 1E: Development of a novel yeast biosensor for continuous real-time monitoring of produce safety. 1.E. Aim 1 Develop a transformation system for Sporobolomyces lactuca nom. prov. and identify transcripts that are differentially expressed in the presence of E. coli. (Aime, Solomon, Pruitt) 1.E. Aim 2 Development and testing of S. lactuca nom. prov. as a living biosensor. (Solomon, Aime, Pruitt) Sub-objective 1F: Development of a handheld LIBS unit, assays, and analysis tools for use in label-free food fingerprinting and tracing to improve food defense and combat food adulteration, contamination, and fraud. 1.F. Aim 1 Expansion and re-design of the benchtop LIBS instrument and associated measurement procedures to accommodate a variety of agricultural samples. (Rajwa, Robinson, Bae) 1.F. Aim 2 Design and feasibility study of a portable LIBS-based food fingerprinting platform. (Rajwa, Robinson, Bae) 1.F. Aim 3 Development of machine learning tools for LIBS food fingerprinting and classification. (Rajwa, Robinson, Bae)
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.
The Center for Food Safety Engineering (CFSE) continues to develop novel methods for the detection of biological, chemical, and physical contaminants in food that could pose food safety threats. Despite the continuing impact of COVID-19, most of our projects were able to continue to move forward and achieve their 12-month milestones. Our work on the use of bacteriophage as a sensitive detection tool has expanded to include a phage that can be used for the detection of Salmonella. During the past year we have examined the host specificity of different isolates of phage P22 in an attempt to identify one that can infect many (or all) Salmonella serovars, while still providing specificity by not infecting other bacteria outside the genus Salmonella. Most isolates tested had a narrow host range, but by screening phage at high densities it was possible to identify presumptive mutants that were capable of infecting a much broader range of Salmonella serovars. Work has also continued on the development of tools to allow the easy construction of phage capable of being used in colorimetric or luminescent assays once a phage(s) with the appropriate specificity of infection has been identified. The CFSE also continues work to develop new and improve existing cell phone-based detection technologies. Work is ongoing on two new types of sensors – one that uses mass-based detection (a quartz crystal microbalance) and another that is based on electrochemistry. A bench top model of the microbalance has been successfully tested in the detection of Salmonella. The design of the electrochemical sensor is complete and a prototype is being constructed. Both are ultimately planned to interface with commonly available smart phones to provide portable detection. Work also continues on improving the utility of our existing cell phone-based lateral flow assay detector. A new method has been developed to optically read the concentrations of bacteria detected directly from the lateral flow test strips. Work to develop an assay system based on laser-induced breakdown spectroscopy (LIBS) has focused on transferring the system we have developed to work as a paper-based assay. This has involved testing a variety of assay components that work well in paper including testing antibodies conjugated to gold particles. We have worked with 1 cm square paper that can be placed into 3D printed holders to provide a level of automation for multiple samples. We have also designed a liquid transfer paper device for direct LIBS evaluation by changing the flow characteristics to improve the speed of flow of paper assays. We are also working to move our LIBS assay system to a portable instrument. This process has been accelerated by acquisition of a commercial hand held device (rather than developing our own from scratch), but use of this device will require modification of the software to work with our assays. We have modified the hardware to work with our assays and are working on modifying the software to work specifically with our assays. Work also continued on two microfluidic paper-based systems to detect bacterial pathogens in a multiplexed assay. The first system is aptamer-based and utilizes a custom designed aptamer coated particle that provides high sensitivity and reduces false signals. Several aptamers have been tested and optimized for detection of Escherichia coli (E.coli) O157:H7 and Salmonella Typhimurium in solution. These aptamers have subsequently been incorporated into a colorimetric paper-based assay coupled with an image analysis algorithm that produces linear results over a wide range of bacterial concentrations and a limit of detection in the range of 102 to 103 cells/ml. Aptamers are currently being tested that will extend the range of the sensors to include Listeria monocytogenes and Campylobacter jejuni. The second system is designed to use loop-mediated isothermal amplification (LAMP) to specifically detect Shiga toxin-producing E. coli (STEC) strains. Primers have been designed and tested for three specific target genes (stx1, stx2, eae) as well as the rfbE gene to help with detection of E. coli O157 strains. Each primer set has been shown to amplify its target in approximately 15 minutes using a genomic DNA template in solution. These primers are being tested to determine the limit of detection, their ability to distinguish between live and dead bacteria, and to adapt them to providing a colorimetric response in the paper-based assay. A new project at the CFSE involves the development of a yeast species (Sporobolomyces lactuca) that occurs laterally on lettuce leaves into a biosensor that could detect and report the presence of bacterial pathogens. Preliminary work was performed to characterize this newly described species and to determine how commonly it could be detected in environmental and lettuce samples. To facilitate the bioengineering of this species our work has moved on in two directions. First we have completed a draft genome sequence that has been assembled and is in the process of being annotated. Experiments to define the transcriptome to help with the annotation are underway. The second approach is to develop a transformation system for this species. Different transformation methods (Agrobacterium-mediated, electroporation, and chemical) are being tested to determine the most efficient method to introduce DNA into the yeast. Experiments have been conducted that demonstrate that both hygromycin resistance and URA3 will work as selectable markers in this species. In addition, the URA3 gene has been isolated and introduced into Agrobacterium to be used as a test bed for that transformation system. The CFSE has also initiated a project to adapt LIBS technology into a handheld device that can be used for “food fingerprinting” to detect either adulteration or food fraud. We have collaborated with a commercial manufacturer of handheld LIBS units to evaluate what modifications of their production units would produce an optimal unit for food fingerprinting. This collaboration has substantially shortened the time required for design and hardware prototyping and allowed us to spend more effort focused on testing and validation. To achieve the desired end result we have also examined several spectral data classification algorithms to allow us to build a system that would allow both classification and measurement of spectral attributes (chemical species), which help distinguish across classes. Work also continues on low cost, miniaturized temperature monitoring sensors that can be used to continuously monitor storage conditions of perishable items. The new design uses a receiver unit that can monitor multiple individual package mounted sensors over a range of 10 cm, with a future goal being to extend the range of the unit. The selected frequencies and signal modulation techniques allow the tags to be simplified, making them more suitable for low-cost fabrication. Data collected by the unit can be subsequently transmitted via Bluetooth (or another low energy transmission protocol) to a wireless receiver device such as a smartphone or tablet. Following on from work to develop and test wet biofilms we have developed a protocol for the generation of dry biofilms with sufficient bacterial populations to test sanitizers using standard EPA protocols. These methods are being expanded to include foodborne pathogens including Salmonella enterica and Listeria monocytogenes, as well as the opportunistic pathogen Pseudomonas aeruginosa. These are pathogens of concern in low-moisture food processing environments, which have been associated with many recent outbreaks (e.g., peanut butter, chocolate, and infant powder). We are also testing these in vitro models against dry sanitation methods of microfiber and alcohol-based sanitizers to evaluate their efficacies and refine effectiveness of dry sanitation practices.
1. Creating multiplexed assays for portable instruments. Field use is important for many pathogen detection situations and this requires the design and operation of both special assays as well as portable hardware. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, have redesigned assays so that they can be performed in the field without the need for expensive, complex laboratory devices or reagents. It has been possible to produce low-cost paper-based assays that are read using laser-induced breakdown spectroscopy (LIBS) using a bench top system. This system provides a rapid, low-cost method that can detect multiple pathogens from the same sample simultaneously and would be of utility to food safety testing labs found in industry, academia, or regulatory agencies.
2. Paper-based microfluidic device for the simultaneous detection of Escherichia coli (E. coli) O157:H7 and Salmonella (S.) Typhimurium. Foodborne pathogens are major public health concerns worldwide. Paper-based microfluidic devices are portable, user-friendly, and cost-effective for the detection of foodborne pathogens. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, have developed a novel paper-based single input channel microfluidic device that can simultaneously detect E. coli O157:H7 and Salmonella Typhimurium and provides cell concentration information through the use of an image analysis algorithm. The colorimetric sensor detects whole-cell bacteria rapidly, lessening the overall time required when compared to traditional detection methods. Moreover, the limit of detection for E. coli O157:H7 (103) and S. Typhimurium (102) was comparable or superior to other paper-based bacterial detection devices. This technology provides a rapid, low-cost detection method that could easily be deployed anywhere with a need for food safety testing.
3. A portable system to detect food fraud and adulteration. The development of machine learning tools and chemometrics for food-fraud detection and classification requires extensive testing that employs realistic challenges in terms of food product variety. To this end, ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, employed benchtop and portable instruments to evaluate food authenticity using a spectroscopic method call LIBS (laser-induce breakdown spectroscopy). designed a set of realistic tests employing a wide variety of food products. The portable instrument was developed for application to foods in collaboration with a well-established manufacturer of LIBS-bases testers used for metal analysis. We tested LIBS food-fraud detection ability for hard cheeses (continuing and extending our previous work) and coffee beans (both used as examples of solid food products). In addition, we evaluated powdered samples (various spices) and two liquid products (olive oil and balsamic vinegar). The gathered data allowed us to establish a robust machine learning data analysis pipeline capable of utilizing LIBS spectra from all the evaluated goods in the context of fraud detection. This instrument provides portable food adulteration and fraudulent food detection capabilities that can be easily moved to any remote location where it is required.
4. Wireless, high-resolution, time-temperature measurement by low-cost tags. Continuous temperature monitoring is essential for safety assessment of ready-to-eat foods. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, have designed a high-resolution and high-sensitivity sensor system. The system leverages wireless measurement technologies to monitor individual products through low-cost tags attached to their packaging. The tag structure is optimized for fabrication with low-cost techniques such as screen and ink-jet printing, to facilitate integration into the food packaging. Implementation of this system to tag the packaging of perishable food items would allow them to be continuously monitored for temperature abuse and allow potentially damaged or dangerous items to be removed from retail food outlets.
5. Developing rapid in vitro dry surface biofilm models of pathogens to improve sanitation and disinfection interventions. While cleaning and sanitation/disinfection interventions target removal of “visible” dirt and viable cells, there is a knowledge gap about “dry” surface biofilms that can easily persist in food and healthcare environments resulting in foodborne illnesses and medical infections. ARS-funded scientists at the Center for Food Safety Engineering in West Lafayette, Indiana, developed a rapid in vitro dry biofilm model of Pseudomonas aeruginosa and Staphylococcus aureus on glass coupons using a CDC biofilm reactor. Models were tested against different classes of disinfectants. Currently, these models are expanded to include major foodborne pathogens such as Salmonella Typhimurium and Listeria monocytogenes to study the behavior of these bacteria in environments in the form of dry biofilms and tested against dry sanitation methods such as microfiber and alcohol-based sanitizers. These results will help refine sanitation and/or disinfection control measures to prevent pathogen transmission within food and healthcare environments. They also provide a new validation model to consider for detection assays and technologies.
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Min, H.J., Mina, H.A., Deering, A.J., Bae, E. 2021. Development of a smartphone-based lateral-flow imaging system using machine-learning classifiers for detection of Salmonella spp. Journal of Microbiological Methods. https://doi.org/10.1016/j.mimet.2021.106288.