Page Banner

United States Department of Agriculture

Agricultural Research Service

Research Project: INTEGRATED BIOSENSOR-BASED PROCESSES FOR MULTIPATHOGENIC ANALYTE DETECTION
2011 Annual Report


1a.Objectives (from AD-416)
The ultimate goal of this project is to develop rapid, specific, and sensitive biosensor-based assays for diverse pathogenic bacteria which can be widely adopted in applications ranging from simple field tests to high speed, high throughput laboratory screening assays. To meet this goal, several objectives will be pursued: 1) Develop specific, high affinity biorecognition reagents for food-borne pathogens and toxins. 2) Develop rapid and effective means to separate and concentrate targeted pathogens without carryover of background organisms. 3) Develop integrated assay systems based on multiple target biosensor platforms.


1b.Approach (from AD-416)
The primary objective of the proposed research is to develop biosensor processes that are capable of detecting multiple pathogens of food safety and food security concern. We plan to concentrate our research on a few selected pathogens: E. coli O157:H7, Listeria monocytogenes, Salmonella and Yersinia spp. Collaborative arrangements have been made for evaluation of the developed methods with virulent strains. Methods will generally be developed with culture media as the sample matrix, and then extended to food samples containing the target pathogen. The efficacy of developed methods will be primarily tested in ground beef, ready-to-eat meats and liquid eggs. Modification of the plan to include other pathogens and foods will be determined by ARS needs. To facilitate the progress of planned research, we will seek useful advice and/or input from our colleagues in other Research Units at the Eastern Regional Research Center (ERRC).


3.Progress Report
Traditional methods for the detection of foodborne pathogens involve the growth of microorganisms in selective culture media followed by microbiological and biochemical characterization of putative pathogenic isolates, which can take days to weeks to complete. Furthermore, these methods are designed to detect a single pathogen. This project is aimed at developing rapid methods for the detection of very low numbers of pathogens in food and the development of methods to detect multiple pathogens simultaneously. Progress has been made on several lines of research: (1) Thorough computational and experimental analysis of sampling requirements to ensure detection of bacterial pathogens present at very low cell concentrations (i.e., approaching 1 cell per sample). Previous work confirmed that counting methods (e.g., counting bacterial colonies on Petri-plates) would require 30 sample replicates in order to accurately estimate the number of cells in dilute samples. Recent studies employed another common method for enumerating bacteria, the most-probable number (MPN) method. The studies revealed that, by the MPN method, very low numbers of cells could be enumerated by either bacterial growth or the polymerase chain reaction (PCR) using only 8 replicates per dilution; (2) PCR and other DNA-based detection methods require efficient methods for extraction of purified DNA from bacteria. In another line of research, numerous commercially available reagents were examined to develop an optimized DNA extraction protocol for rapid PCR assays for detection of pathogens from filter-concentrated food homogenates. By using a non-inhibitory extraction reagent (i.e., a reagent that provides a purified DNA sample, free of other cellular components that inhibit the PCR assay), the entire DNA extract can by assayed, increasing sensitivity by up to 100 fold; (3) Additional progress was made on an antibody-based method with the potential for the detection of numerous pathogens and associated toxins (antibody microarray). In this method, capture antibodies are spotted onto a surface, and the captured pathogens or toxins are detected using a second, fluorescently labeled antibody. We previously developed such an antibody microarray and demonstrated the capability to detect E. coli O157:H7, Salmonella, and the Shiga-toxin (a protein toxin produced by E. coli O157:H7). This year, progress has been made in optimizing the assay and demonstrating that less expensive materials and reagents can be used without reducing the efficacy of the method; (4) In collaboration with other ARS scientists, studies revealed the antibacterial properties and mechanism of action of zinc oxide nanoparticles against the important foodborne pathogen, Campylobacter jejuni; (5) An additional study with an international collaborator examined molecular methods to characterize and categorize strains of Staphylococcus aureus, another pathogen associated with foodborne infections. These studies revealed that the most common method used to characterize bacterial strains for tracking foodborne infections may not be the best method for characterizing strains of Staphylococcus aureus.


4.Accomplishments
1. Antibody-based method for high-throughput screening of foods for harmful foodborne bacteria. Since traditional microbiological methods are slow (time frame in days), rapid methods (minutes to hours) are needed for the detection of harmful bacteria (pathogens) in foods. Furthermore, it is particularly advantageous if the method can detect multiple pathogens and/or toxins, as well as be applied in a high-throughput (simultaneous testing of multiple samples) manner. Antibody microarray, a technique that uses biological recognition molecules (i.e., antibodies that specifically bind to bacteria or toxins) printed as hundreds of tiny arrayed dots, can be used for such screening. Antibody microarrays for the simultaneous detection of E. coli O157:H7 and E. coli Shiga toxin 1 were constructed by ARS researchers at Wyndmoor, PA, in 96-well plates, allowing the high throughput processing of up to 96 samples per plate. Upon optimization, the method was able to detect in concentration of 580,000 cells or 110 nanogram toxin per milliliter, respectively, in a total assay time of 75 min. The assay cost was greatly reduced through the use of relatively inexpensive polystyrene plastic 96-well plates and elimination of the need for chemical modification (biotinylation) of antibodies prior to spotting. This method, which can be readily applied for the detection of additional pathogens, may be applied by regulatory agencies and food producers for the screening of foods for harmful contaminants.

2. Toward the enumeration of low levels (1-2 cells per pound) of bacterial contamination. The variability associated with a genetic marker-based most probable number (MPN) analysis of foods, which is being developed by ARS researchers at Wyndmoor, PA, is large. We seek to know if this variability is associated with the innate statistics of random sampling or some physical aspect of the assay in development. To this end, we mathematically modeled the purely statistical part of the errors of random sampling associated with binomial (presence of bacteria in the sampled volume either there or not) observations in order to estimate the number of repeats per dilution are necessary for reasonable accuracy. Our results indicated that six to eight 4 mL samplings per dilution (no more than 3 dilutions total) are nominally required to estimate a sample population containing 1-2 cells per pound of food. Rather than increasing the number of observations per dilution, and thereupon increase costs, we now know that certain physical aspects of our assay should be tweaked in order to improve reproducibility.

3. Geneotypes and toxin gene content of Staphylococcus aureus. The ability to determine the source of foodborne outbreaks caused by various pathogenic bacteria is dependent upon one of many forms of molecular typing. In order to determine which method is best for Staphylococcus aureus typing, several common methods were investigated by ARS researchers at Wyndmoor, PA against over 100 S. aureus strains. We found that the sequence analysis of 18 different enterotoxin genes provided the best discrimination between all the tested strains and could be reasonably applied during a S. aureus outbreak in order to track down the specific food source of the contamination in question.

4. Nanoparticles kill Campylobacter. The antimicrobial activity and molecular basis of zinc oxide nanoparticles (ZNP) were investigated against Campylobacter jejuni, an important foodborne pathogen and a common cause of bacterial gastroenteritis worldwide. ARS researchers at Wyndmoor, PA found that C. jejuni was extremely sensitive to ZNP (8-16 fold more so than Salmonella or E. coli) which prevented it from growing via cell death. Results indicate that the mechanism for ZNP action is likely due to the induction of oxidative stress. The rapid and lethal effect of low concentrations of ZNP on Campylobacter implies a potential use in certain food systems. Also, the molecular basis of ZNP action could lead to the development of more powerful, but less toxic, antimicrobial nanoparticles for food safety applications.


Review Publications
Irwin, P.L., Martin, J., Nguyen, L.T., He, Y., Gehring, A.G., Chen, C. 2010. Antimicrobial activity of spherical silver nanoparticles prepared using a biocompatible macromolecular capping agent: evidence for induction of a greatly prolonged bacterial lag phase. Journal of Nanobiotechnology (Biomed Central Open Access). 34:1-12.

Chen, C., Strobaugh Jr, T.P., Lindsey, R.L., Frye, J.G., Uhlich, G.A. 2011. Sequence analysis of a group of low molecular-weight plasmids carrying multiple IS903 elements flanking a kanamycin resistance aph gene in Salmonella enterica serovars. Plasmid Journal. 65:246-252.

Xie, Y., He, Y., Irwin, P.L., Jin, Z.T., Shi, X. 2011. Antibacterial activity and mechanism of action of zinc oxide nanoparticles against Campylobacter jejuni. Applied and Environmental Microbiology. 77:2325-2331.

Gehring, A.G., Tu, S. 2011. High-throughput biosensors for multiplexed foodborne pathogen detection. Annual Review of Analytical Chemistry. DOI: 10.1146/annurev-anchem-061010-114010.

Last Modified: 11/24/2014
Footer Content Back to Top of Page