Cell-Based Biosensors for Rapid Pathogen Detection

1. Cell-Based Biosensors for Rapid Pathogen Detection Ivica Arsov, Ph.D.

2. Biosensor

3. Key Biosensor Components Transducer Electrochemical (clark electrode, ion sel. electrode, etc) Optical (absorbance, luminescence, fluorescence, etc) Piezoelectric (quartz crystals, surface acoustic wave device, etc) Calorimetric (thermometric) Analyte Bioreceptor Enzyme Microorganism Antibodies Chemoreceptors Tissue Organelles Nucleic acids Recording device

4. Cell-Based Biosensors • B cell lines were genetically engineered to express cytosolic aequorin, a calcium sensitive bioluminiscent protein from jellyfish, as well as membrane-bound antibodies specific for pathogens of interest (Rider et al., 2003) • Cross-linking of the antibodies with specific pathogens increases intracellular calcium concentrations within seconds, causing the aequorin to emit light. • This sensor was named CANARY (cellular analysis and notification of antigen risks and yields)

5. Cell-Based Biosensor Analytes Surface Immunoglobulin Data analysis Signaling cascade Ca++ Aequorin Luminometer

6. Excellent Speed, Sensitivity, and Specificity • The CANARY Cell-based sensor detected as few as 50 CFU of Y. pestis in a total assay time of 3 minutes. • The system was also tested in one food sample-E. coli O157:H7 in lettuce • 500 CFU/g of E. coli O157:H7 in lettuce was detected in less than 5 minutes, including the sample preparation. • 1000 CFU of B. anthracis spores

7. Cell-Based Biosensors • The CANARY system can be easily custom tailored to respond to specific strains. • It can distinguish pathogenic E. coli O157:H7 from nonpathogenic E. coli strains.

8. www.innovativebiosensors.com

9. Biosensor Based on Immobilized Indicator Cells • A B-lymphocyte cell line was encapsulated in a collagen gel matrix (Banerjee et al., 2007). • This assay measures alkaline phosphatase or lactate dehydrogenase released by cells infected with pathogens or exposed to different toxins. • The system was tested using different strains of Listeria, listeriolysin O, and enterotoxins from Bacillus species. Banerjee et al., Laboratory Investigation (2007) 1-11. Reproduced with permission.

10. Biosensor Based on Immobilized Indicator Cells • The assay provides quantitative and qualitative information • Very fast (1-6 hours) • Good sensitivity (MOI>10:1) • Portability-collagen entrapped cells remain viable in 48 well plates for 48 hours.

11. The cryo-SEM images of pathogen- or toxin-induced damage of Ped-2E9 cells in collagen gel matrix. FROM: A novel and simple cell-based detection system with a collagen-encapsulated B-lymphocyte cell line as a biosensor for rapid detection of pathogens and toxins (2007) Pratik Banerjee, Dominik Lenz, Joseph Paul Robinson, Jenna L Rickus and Arun K Bhunia Laboratory Investigation (2007) 1-11. Reproduced with permission

12. Future… • Only few biosensors were tested with food samples so far • At this point it may not be a cost-effective technology • Sample preparation plays a critical role

13. Future… • The main advantage of cell-based biosensors is that they provide information about the physiological effects of pathogens/toxins. • Capable of distinguishing between viable pathogenic strains from nonpathogenic ones or dead cells. • Sensitivity and specificity comparable to current methods. • Expected to have broad applications in food testing, animal health, biodefense, disease diagnosis etc.

18. Collaborative Study to evaluate a Total Bacteria Count Assay using Quantitative Real-Time PCR. Thomas L. Romick and Rafael C. Marfil. Industrial Microbial Testing and Grupo Sinergia Introduction A collaborative study was undertaken to demonstrate the precision and accuracy of a total bacteria count (TBC) assay developed to run with commercially available PCR reagents and a rapid thermocycling platform. The TBC assay can be completed within one hour. The TBC assay has many applications for enhanced HACCP applications. Purpose This study was designed to show how diverse laboratories can use the TBC assay in their labs for specific applications. Once a standard curve is constructed for a sample type, it can be used time again for quantifying unknown samples. Methods A collaborator kit was supplied to each lab with all the necessary reagents and consumables that were detailed on a chain of custody document. Collaborating laboratories were: Brigham Young University California Department of Public Health NASA Jet Propulsion Laboratory NASA Ames Research Center Nestle USA Quality Assurance Center North Carolina State University San Francisco Water Quality Division

19. Results Results from the 7 collaborative labs were analyzed using ANOVA and Signal to Noise ratio statistics (Taguchi Method) and showed excellent results for the standard curve and some variation in the unknown data. The β value indicated how close the average result was to the target and ranged from 0.87 to 1.07 (1.00 target). The signal to noise ratio (S/R) which includes the variance and β factor as the indicator ranged from 14.22 to 23.18 (20.00 target). Significance The overall conclusions are that all the labs performed well in constructing the standard curve and had some variance with the unknown samples. However, the results show that all collaborators successfully used the TBC assay to quantify bacterial load accurately within one hour. The TBC assay can be used for a rapid real-time measure of bacteria in many diverse applications and support HACCP for real-time statistical process control.