PROCESSING TECHNOLOGY
Advances in rapid pathogen detection

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By Guest Contributor on 1/13/2014

Recent recalls and outbreaks caused by foodborne pathogens are bringing great impact to personal lives, business and national economies. According to the Centers for Disease Control and Prevention (CDC), about 48 million of us, approximately one in six people, get sick; 128,000 are hospitalized; and 3,000 die of foodborne diseases from eating contaminated food each year in the United States.
To safeguard our food supplies, rapid pathogen detection and identification is critical to detect the presence of pathogens in food products and along the production chain, which is essential for determining intervention and control strategies. In addition, the outbreaks and their causes can be quickly identified so consumers and industry of concerns can be alerted to prevent more illness.
Furthermore, microbiologists often face a “needle-in-a-haystack” challenge to detect small numbers of food-borne pathogens in large numbers of harmless background microflora in a complex sample matrix.
Three major detection methods
Intensive efforts have been made to reduce the assay times and improve the assay sensitivity for pathogen identification. There are three major groups of food borne pathogen detection methods: culturing based detection, antibody-based detection (immunoassay), and nucleic acid based detection (PCR).
Conventional microbiological methods for determining the cell counts of bacteria employ selective culture, biochemical, and serological characterization. Although these methods achieve sensitive and selective bacterial detection, they are labor-intensive and time-consuming as it takes 2–3 days for initial results, and up to 7–10 days for confirmation. Spectroscopic technologies such as mass spectroscopy, IR and Raman spectroscopies have been used to identify individual colony on culture plates with promising results presented. However, it still requires the lengthy incubation steps for colony formation.
The immunoassays utilize the specific recognition of antibody towards the target antigen in the presence of other organisms and interfering food components. Traditional enzyme linked immuosorbent assay (ELISA) methods can detect down to 1 x 105 cells/ml but multiple lengthy incubation and washing steps are required. A large number of biosensor transducers have been developed to minimize the incubation and washing steps.
There are three groups of transducers including optical (SPR, interferometer), electrochemical (impedance, amperometry) and mass (piezoelectric, magnetoelastic) based biosensors. For label-free immuoassays on biosensors (no need for bioreceptors labeling, washing and incubation steps), the bindings between the antibody (immobilized on the surface of the transducer) and pathogen are converted to a measurable optical or electrical signal based on the signal transduction platform.
The pathogen measurement is real-time so the assay time can be greatly reduced down to minutes. However, the detection limits of biosensors were reported to be in the range of 105-107 bacterial cells/ml. In order to be attractive, biosensors first need to show that they are capable of reaching at least the same detection levels as traditional techniques (between 10 and 100 cfu/ml).
Polymerase chain reaction (PCR) based methods have revolutionized the detection technology for foodborne pathogens. It can reach a sensitivity limit of less than 1 cfu/ml Salmonella typhimurium per PCR reaction. However, PCR is more susceptible to contamination, and requires a high level of laboratory skill to avoid carryover when used for different samples. In addition, PCR cannot distinguish between viable and dead bacteria. This is the major disadvantage of PCR based pathogen detection in food.
Although ethidium monoazide and propidium monoazide have been used to specifically permeate dead bacteria and irreversibly attach covalently to the DNA, thereby preventing its amplification, the degree of deactivation is limited to the presence of no more than 103 dead cells in the PCR. Reverse transcriptase PCR (RT-PCR) was adapted to detect the less environmentally stable messenger RNA (mRNA) in bacteria so live cells detection can be achieved. However, costs, complexities, and other technical issues have made neither a routine diagnostic
Other advances
Fluorescence microscopes and flow cytometers have also been used to distinguish the viable cells from dead cells. They use a fluorescent dye exclusion method for cell viability measurement. Typical viability dyes are excluded by viable cells but can penetrate damaged cell membranes of dead cells and emit fluorescence upon binding to nucleic acid structures inside these cells. However, usage of fluorescence dyes with bacteria is not simple.
Due to large interspecies variation staining and measurement protocols have to be developed separately for every bacterial species to ensure qualitative and quantitative high level results. In addition, some cells are still structurally intact, e.g., after being killed with UV light and antibiotics. Some cells with injured cell membranes can be repaired and remain viable. Therefore, assays based on the cell membrane integrity might not be accurate to differentiate live cells from the dead population.
Recent discovery that Raman scattering can be enhanced on the order of 1014 when taking place in the close vicinity of metal surfaces and nanostructures due to coupling to surface plasmons has made single bacteria identification possible. The combination of high level of molecular structural information of a vibrational spectroscopy with ultrasensitive detection limits makes SERS a promising method in biosensing.
Whole-organism fingerprinting obtained from SERS spectra has identified bacteria to the strain level and provided the ability to distinguish between viable and nonviable cells. However, typical SERS detection schemes use offline measurements on bulky microscope setups with discrete optical elements at high costs. In addition, bacteria samples need to be washed and purified to remove the background interference (such as buffer saline and growth media) before SERS measurements. Furthermore, SERS signals can be irreproducible due to the irregularities in the metal SERS substrates and the variations in experimental conditions.
Conclusion
Rapid foodborne pathogen detection in food matrix remains a challenging task. Beyond the requirement to distinguish the viable pathogens from dead cells, the detection sensitivity and specificity are also challenged by the presence of low number pathogen cells in complicated food matrix.
Until those hurdles are solved, the conventional cultural based method will remain the gold standard for foodborne pathogen detection.
 
– Jie Xu, research scientist with the Georgia Tech Research Institute