Location: Characterization and Interventions for Foodborne Pathogens
2021 Annual Report
Objectives
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)
Approach
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.
Progress Report
This is a newly approved OSQR NP108 project. Please see final annual report 8072-42000-077-00D for further information.
Accomplishments
Review Publications
Ren, W., Cabush, A., Irudayaraj, J. 2020. Checkpoint enrichment for sensitive detection of target bacteria from large volume of food matrices. Analytica Chimica Acta. 1127:114-121.
Ryan A, V.E., Bailey, T.W., Lin, D., Vemulapalli, T., Cooper, B., Cox, A., Bhunia, A. 2021. Listeria adhesion protein-expressing bioengineered probiotics prevent fetoplacental transmission of Listeria monocytogenes in a pregnant guinea pig model pig model Valerie E. Ryan a, Taylor. Microbial Pathogenesis. doi.org/10.1016/j.micpath.2021.104752. https://doi.org/10.1016/j.micpath.2021.104752.
Ren, W., Ahmad, S., Irudayaraj, J. 2021. 16S rRNA monitoring point-of-care magnetic focus lateral flow sensor. 6:11095-11102. https://doi.org/10.1021/acsomega.1c01307.
Bai, X., Liu, D., Xu, L., Tenguria, S., Drolia, R., Gallina, N.L., Cox, A.D., Koo, O., Bhunia, A.K. 2021. Biofilm-isolated Listeria monocytogenes exhibits reduced systemic dissemination at the early (12–24 h) stage of infection. npj Biofilms and Microbiomes. Available online:npj Biofilms and Microbiomes (2021) 7:18. https://doi.org/10.1038/s41522-021-00189-5.
