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:
Progress was made on both objectives and several sub-objectives, all of which fall under National Program 108, Food Safety, contributing to Component 1: Food Contaminants and Problem Statement 1.C Technologies for the Detection and Characterization of Microbial Contaminants of the 2011-2015 Strategic Action Plan. To prevent outbreaks of foodborne illness, food regulatory agencies and the food industry need rapid, sensitive, and specific methods to check for the presence of harmful bacteria (pathogens) in food. Our approach to develop such methods involves novel bioseparation technology to separate and concentrate pathogens from foods (a 1000-fold concentration of cells in less than 30 minute) and various methods to detect and quantify foodborne pathogens. Two prototype filtration instruments were built this year. The filtration device was used to separate and concentrate bacteria from water and foods and, when coupled to polymerase chain reaction (PCR) analysis, pathogen detection was completed within 6 hours. A variety of platforms for detection of the concentrated pathogens were studied. A novel method was developed to rapidly heat sub-nanoliter droplets on the biochips, to facilitate ultra-rapid (< 10 min) PCR assays. In addition, developments in loop mediated isothermal amplification enabled multiplexed screening of virulence genes of L. monocytogenes, E. coli, and Salmonella on the chip. 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. Major hardware and software updates supported the development of a portable instrument, and a prototype was delivered to USDA for further testing and application development. The BARDOT technology was augmented with different optical methods (Raman spectroscopy and a multispectral interrogation) and preliminary analyses of E.coli and Listeria are underway. Efforts are ongoing to validate pathogen identification by BARDOT in real world produce samples through DNA sequence verification. A third system employs an E. coli O157:H7-specific phage that was genetically engineered to cause the target bacteria to produce a bright yellow color if infected. This year methods were developed to encapsulate the phage into a pill format using commercially available polymers to enhance shelf-life and facilitate their addition to selective enrichments. Efforts are ongoing to expand the reporter phage specificity to other Shiga toxin-producing E. coli. Also, methods employing fluorescent immunoassays in combination with magnetic concentration enabled rapid (2 hours) and sensitive (5 CFU/mL) detection of E. coli O157:H7, Salmonella, and L. monocytogenes. Finally, as part of larger study, DNA fingerprinting of over 800 L. monocytogenes isolates from retail delis representing diverse geographic regions was completed.
1. Portable method for identifying harmful bacteria from food. Rapid detection of harmful bacteria in food is necessary to prevent foodborne illness and safeguard public health. The BARDOT sensor technology is easy to use and allows for rapid identification of bacteria. Developed by ARS-funded researchers at Purdue University’s Center for Food Safety Engineering (CFSE) in West Lafayette, Indiana, BARDOT involves shining a laser light through the bacterial colony on a plate and collecting images of the light that passes through. The resulting pictures of these colonies contain descriptive characteristics which can be used to identify bacteria by comparing the resulting image with a library of previously collected images. We report here the development of a portable BARDOT instrument by CFSE scientists and the delivery of an instrument to a USDA laboratory. The new instrument is able to identify known pathogenic bacteria, including pathogenic E.coli, Salmonella, and Listeria monocytogenes. The pathogen identification capabilities coupled with the portability of this new BARDOT instrument has tremendous potential for improving the response to foodborne illness outbreaks because the method can travel to the source thereby reducing the time to detection.
2. Detection of foodborne pathogens using nanobiosensors. Consumption of foods contaminated with pathogenic bacteria is a major public health concern. A key challenge in food safety is to rapidly screen foods to determine the presence of pathogens so that appropriate intervention protocols can be pursued as needed. Nanobiosensors have advantages over traditional microbiological and standard-scale biosensors for pathogen detection because of their low cost and potential for testing multiple samples simultaneously. ARS-funded researchers in collaboration with Purdue University’s Center for Food Safety Engineering at West Lafayette, Indiana, have developed a nanobiosensor for simultaneous detection of several pathogens using a method for specific detection of pathogen DNA. Unlike traditional DNA amplification which involves numerous temperature changes, the developed nanobiosensor is simplified because it uses a DNA amplification method that occurs at one temperature. Using these biochip sensors, scientists were able to rapidly and simultaneously detect L. monocytogenes, E. coli O157:H7, and Salmonella. Another nanobiosensor is based on a fluorescent nanoparticle strategy. In this sensor, nanoparticle magnetic beads are modified to bind specific pathogenic bacteria, and upon binding of the target pathogen to the beads, a fluorescent signal is generated that is easily detectable by common laboratory equipment. This nanoparticle magnetic bead method detected low numbers of E. coli O157:H7, Salmonlla Typhimurium, and L. monocytogenes in less than 2 hours. These nanobiosensors could be used for fast, portable, and inexpensive on-site testing of foodborne pathogen contamination and could therefore be used to reduce the public health impact of foodborne pathogens.
3. Identification of Listeria monocytogenes in retail delis. Listeria monocytogenes is one of the deadliest foodborne pathogens in the United States and an estimated 83% of listeriosis cases result from consumption of deli meats that are cross-contaminated at retail. Nevertheless, very few studies have investigated L. monocytogenes transmission, prevalence, and persistence in retail delis. To determine if the same L. monocytogenes strain was being recovered routinely from a deli (evidence of persistence) or if L. monocytogenes was transient in the deli environment, ARS-funded researchers at Purdue University’s Center for Food Safety Engineering at West Lafayette, Indiana, characterized over 800 strains of L. monocytogenes collected from 30 retail delis in three states. DNA fingerprinting of the revealed significant similarities between the strains and led to the conclusion that over 40% of the delis studied had evidence of persistent L. monocytogenes contamination. The substantial genetic similarity between the isolates suggests that a small number of highly related L. monocytogenes types are responsible for retail deli contamination. This study concludes that: (i) some retail delis have an increased likelihood of prevalent and persistent L. monocytogenes contamination, (ii) there is a need to develop feasible and practical approaches to control L. monocytogenes in these environments, and (iii) control of L. monocytogenes in retail delis will likely lead to a decrease in listeriosis cases in the United States.
4. Rapid concentration and detection of pathogens from vegetable wash water. Outbreaks of illness linked to consumption of leafy greens are an increasing concern, and from an industry perspective it would be ideal to avoid the high costs associated with issuing a recall. Sampling of large volumes of vegetable wash water to detect pathogens, that may be present in low numbers, is a major obstacle. New methods to recover and concentrate foodborne pathogens from large sample volumes would facilitate rapid detection 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 and E.coli O157:H7 from commercial vegetable wash water. The developed system is a rapid (2 hours), automated operation from cell concentration and recovery to cleaning steps (ie, “hands off’ operation), which minimizes the risk of cross-contamination, reduces labor intensity, and results in high recovery rates (75-80%) for the target pathogen. These concentrated samples can be analyzed by conventional or emerging pathogen detection techniques. For example, the concentration method used in conjunction with conventional microbiological plating techniques allowed detection of Salmonella and E.coli O157:H7 in about 24 hours or, in conjunction with DNA-based detection methods (real-time PCR), could 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 will facilitate more sensitive and timely testing of large volumes of vegetable wash water and reduce the likelihood of distributing contaminated products.
5. Reduced time to detect Salmonella in peanut butter. Salmonella is an important cause of human illness in the United States. Following an outbreak of Salmonella infections linked to peanut butter in 20 states in 2012, in which over half of ill persons were children, ARS-funded researchers at Purdue University’s Center for Food Safety Engineering at West Lafayette, Indiana, improved the detection of Salmonella in peanut butter using the BARDOT bacterial identification system they developed. The method includes a brief culture enrichment prior to BARDOT-based detection of Salmonella. The BARDOT technique was able to detect Salmonella in peanut butter within 24 hours with an accuracy of 98%. This is comparable to the current USDA-FSIS method, which requires about 72 hours. This reduced time to detect Salmonella could improve the response time to foodborne illness outbreaks, as well as better facilitate analyses to prevent the distribution of contaminated foods.
6. Understanding microbial populations on fresh produce. Food safety outbreaks linked to consumption of leafy greens are an increasing concern. Produce is often consumed raw, and, while many sanitizers are highly effective on the majority of produce, they fail to effectively kill harmful and/or spoilage microorganisms on some leafy greens. To date, most studies of bacterial populations on vegetables report only population reductions following sanitation treatments but provide no information concerning which bacteria are present. ARS-funded researchers at Purdue University’s Center for Food Safety Engineering at West Lafayette, Indiana, established and optimized experimental protocols to reliably isolate and identify both total populations of bacteria as well as specific harmful bacteria from leafy green vegetables by DNA sequencing methods. Application of the developed methods revealed the bacterial communities associated with fresh produce are complex and variable. Although most of the communities examined are dominated by just two kinds of bacteria, several hundred types of bacteria are present in smaller numbers. The bacterial communities observed on spinach and lettuce are markedly different from one another, and they change in different ways following sanitization and/or cold storage. The results of these studies can be used to develop more targeted approaches for the sanitation of leafy green vegetables.