https://www.mdpi.com/2079-6374/10/6/58/pdf

Application of Biosensors for Detection of Pathogenic Food Bacteria: A Review.

Campylobacter can enter a viable but non-culturable (VBNC) state to evade various stresses, and this state is undetectable using traditional microbiological culturing techniques. These VBNC bacterial cells retain metabolism and demonstrate pathogenic potential due to their ability to resuscitate under favorable conditions. Rapid and accurate determination of VBNC Campylobacter is critical to further understand the induction and resuscitation of the dormancy state of this microbe in the agri-food system. Here, we integrated propidium monoazide (PMA) with real-time polymerase chain reaction (qPCR) targeting the rpoB gene to detect and quantify Campylobacter jejuni in the VBNC state. First, we optimized the concentration of PMA (20 μM) that could significantly inhibit the amplification of dead cells by qPCR with no significant interference on the amplification of viable cell DNA. PMA-qPCR was highly specific to C. jejuni with a limit of detection (LOD) of 2.43 log CFU/ml in pure bacterial culture. A standard curve for C. jejuni cell concentrations was established with the correlation coefficient of 0.9999 at the linear range of 3.43 to 8.43 log CFU/ml. Induction of C. jejuni into the VBNC state by osmotic stress (i.e., 7% NaCl) was rapid ( 10% population). The LOD of PMA-qPCR for VBNC C. jejuni exogenously applied to chicken breasts was 3.12 log CFU/g. In conclusion, PMA-qPCR is a rapid, specific, and sensitive method for the detection and quantification of VBNC C. jejuni in poultry products. This technique can give insight into the prevalence of VBNC Campylobacter in the environment and agri-food production system.

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Detection and Quantification of Viable but Non-culturable Campylobacter jejuni.

To protect drinking water systems, a contamination warning system can use in-line sensors to indicate possible accidental and deliberate contamination. Currently, reporting of an incident occurs when data from a single station detects an anomaly. This paper proposes an approach for combining data from multiple stations to reduce false background alarms. By considering the location and time of individual detections as points resulting from a random space-time point process, Kulldorff’s scan test can find statistically significant clusters of detections. Using EPANET to simulate contaminant plumes of varying sizes moving through a water network with varying amounts of sensing nodes, it is shown that the scan test can detect significant clusters of events. Also, these significant clusters can reduce the false alarms resulting from background noise and the clusters can help indicate the time and source location of the contaminant. Fusion of monitoring station results within a moderately sized network show fal...

Distributed Sensor Fusion in Water Quality Event Detection

A method for detecting and characterizing outbreaks of infectious disease from clinical reports

This paper describes the problem of public health monitoring for waterborne disease outbreaks using disparate evidence from health surveillance data streams and environmental sensors. We present a combined monitoring approach along with examples from a recent project at the Johns Hopkins University Applied Physics Laboratory in collaboration with the U.S. Environmental Protection Agency. The project objective was to build a module for the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) to include water quality data with health indicator data for the early detection of waterborne disease outbreaks. The basic question in the fused surveillance application is 'What is the likelihood of the public health threat of interest given recent information from available sources of evidence?' For a scientific perspective, we formulate this question in terms of the estimation of positive predictive value customary in classical epidemiology, and we present a solution framework using Bayesian Networks (BN). An overview of the BN approach presents advantages, disadvantages, and required adaptations needed for a fused surveillance capability that is scalable and robust relative to the practical data environment. In the BN project, we built a top-level health/water-quality fusion BN informed by separate waterborne-disease-related networks for the detection of water contamination and human health effects. Elements of the art of developing networks appropriate to this environment are discussed with examples. Results of applying these networks to a simulated contamination scenario are presented.

An integrated approach for fusion of environmental and human health data for disease surveillance

In the event of an indoor release of an environmentally persistent microbial pathogen such as Bacillus anthracis, the potential for human exposure will be considered when remedial decisions are made. Microbial site characterization and clearance sampling data collected in the field might be used to estimate exposure. However, there are many challenges associated with estimating environmental concentrations of B. anthracis or other spore-forming organisms after such an event before being able to estimate exposure. These challenges include: (1) collecting environmental field samples that are adequate for the intended purpose, (2) conducting laboratory analyses and selecting the reporting format needed for the laboratory data, and (3) analyzing and interpreting the data using appropriate statistical techniques. This paper summarizes some key challenges faced in collecting, analyzing, and interpreting microbial field data from a contaminated site. Although the paper was written with considerations for B. anthracis contamination, it may also be applicable to other bacterial agents. It explores the implications and limitations of using field data for determining environmental concentrations both before and after decontamination. Several findings were of interest. First, to date, the only validated surface/sampling device combinations are swabs and sponge-sticks on stainless steel surfaces, thus limiting availability of quantitative analytical results which could be used for statistical analysis. Second, agreement needs to be reached with the analytical laboratory on the definition of the countable range and on reporting of data below the limit of quantitation. Finally, the distribution of the microbial field data and statistical methods needed for a particular data set could vary depending on these data that were collected, and guidance is needed on appropriate statistical software for handling microbial data. Further, research is needed to develop better methods to estimate human exposure from pathogens using environmental data collected from a field setting.

/pdf/considerations-for-estimating-microbial-environmental-data-5cfdagp4qn.pdf

Considerations for estimating microbial environmental data concentrations collected from a field setting.

The U.S. Environmental Protection Agency (EPA) strives to develop technologies and protocols to assist drinking water utilities in reducing the risks of potential terrorist attacks on our nation's infrastructure. Of particular interest are the development and feasibility testing of contamination warning systems that integrate existing public health surveillance and water quality measurements. In collaboration with the EPA, APL is developing a novel prototype warning system that employs sensor clustering and Bayesian Network analyses. These techniques address the challenges of synthesizing results from disparate data types with different data rates and complex environmental and operational responses into a warning system that can provide the user with a measure of the likelihood that data anomalies do or do not indicate a potential water-borne disease outbreak These critical challenges and how this novel approach and its components address them will be described.

Drinking Water Security and Public Health Disease Outbreak Surveillance

The Bio-response Operational Testing and Evaluation (BOTE) Project was a cross-government effort designed to operationally test and evaluate a response to a biological incident (release of Bacillus anthracis [Ba] spores, the causative agent for anthrax) from initial public health and law enforcement response through environmental remediation. The BOTE Project was designed to address site remediation after the release of a Ba simulant, Bacillus atrophaeus spp. globigii (Bg), within a facility, drawing upon recent advances in the biological sampling and decontamination areas. A key component of response to a biological contamination incident is the proper management of wastes and residues, which is woven throughout all response activities. Waste is generated throughout the response and includes items like sampling media packaging materials, discarded personal protective equipment, items removed from the facility either prior to or following decontamination, aqueous waste streams, and materials gener...

Cynthia Yund

Papers

An integrated approach for fusion of environmental and human health data for disease surveillance

Considerations for estimating microbial environmental data concentrations collected from a field setting.

Drinking Water Security and Public Health Disease Outbreak Surveillance

Analysis of waste management issues arising from a field study evaluating decontamination of a biological agent from a building.