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A review of the literature published in 2008 is presented on topics related to occurrence and detection of fecal indicators and pathogens. This review is divided into three major sections: occurrence, persistence, and transport of fecal indicators and pathogens, detection methods, and microbial source tracking. The first section is subdivided into persistence and transport of fecal indicators, microbiological quality of recreational beaches, occurrence of fecal indicator and pathogens in shellfish, alternative fecal indicators, and fecal indicators and pathogens in groundwater, watersheds, and wetlands. The second section describes the studies related to endpoint PCR and reverse transcription PCR, real-time PCR and real-time reverse transcription PCR, loop mediated isothermal amplification, microarrays, immunoassay-based detection schemes, labelindependent detection schemes, and sample concentration. The third section covers genotypic and phenotypic microbial source tracking methods. [ABSTRACT FROM AUTHOR]

The article focuses on the issues with environmental occurrence and transport of fecal indicators and pathogens, method's development and application for their detection as well as the source that tracks for their detection. It is being noted that the fecal indicator bacteria (FIB) are bacteria that are commensal in animal intestines, which are shed by feces. Accordingly, their presence in the ecosystem is assumed to indicate that there is a presence of fecal matter and therefore the potential presence of pathogens of intestinal origin. Hence, the author implies that interpretation of the detection of conventional FIB in the environment is sometimes straightforward, though not all the time.

Pathogen detection tools with high reliability are needed for various applications, including food and water safety and clinical diagnostics. In this study, we designed and validated an in situ-synthesized biochip for detection of 12 microbial pathogens, including a suite of pathogens relevant to water safety. To enhance the reliability of presence/absence calls, probes were designed for multiple virulence and marker genes (VMGs) of each pathogen, and each VMG was targeted by an average of 17 probes. Hybridization of the biochip with amplicon mixtures demonstrated that 95% of the initially designed probes behaved as predicted in terms of positive/negative signals. The probes were further validated using DNA obtained from three different types of water samples and spiked with pathogen genomic DNA at decreasing relative abundance. Excellent specificity for making presence/absence calls was observed by using a cutoff of 0.5 for the positive fraction (i.e., the fraction of probes yielding a positive signal for a given VMG). A split multiplex PCR design for simultaneous amplification of the VMGs resulted in a detection limit of between 0.1 and 0.01% relative abundance, depending on the type of pathogen and the VMG. Thermodynamic analysis of the hybridization patterns obtained with DNA from the different water samples demonstrated that probes with a hybridization Gibbs free energy of approximately -19.3 kcal/mol provided the best trade-off between sensitivity and specificity. The developed biochip may be used to detect the described bacterial pathogens in water samples when parallel and specific detection is required. [ABSTRACT FROM AUTHOR]

Virulence factor activity relationships (VFAR) is a predictive approach proposed by the National Research Council's Committee on Drinking Water Contaminants (Washington, D.C.) to classify and rank waterborne pathogens. It is based on the presumption that health threats of waterborne pathogens can be predicted from descriptors at different levels of cellular organization. This paper summarizes challenges that need to be addressed while developing VFAR, with a focus on genomics, such as genomic variability among related pathogens and the need to incorporate genetic descriptors for persistence and host susceptibility. Three key components of VFAR development and validation are also presented, including (1) compilation of a comprehensive VFAR database, (2) development of predictive mathematical models relating descriptors to health effects and other microbial responses, and (3) high-throughput molecular monitoring of drinking water supplies and sources. Bayesian approach and on-chip polymerase chain reaction are discussed as examples of mathematical models and molecular monitoring. [ABSTRACT FROM AUTHOR]

Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (CT) equation was developed to calculate the number of starting copies based on an experimental CT The empirical equation was developed with Sybr green detection in nanoliter-volume QPCR chambers (OpenArray) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R² = 0.816) was observed between the predicted and experimental CTs based on the organism's genome size, guanine and cytosine (GC) content, amplicon length, and stability of the primer's 3′ end. The performance of the predictive CT equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, the primer success rate was dependent on the GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive CT equation are expected to reduce the extent of the validation necessary when developing QPCR arrays for a large number of pathogens or other targets. [ABSTRACT FROM AUTHOR]

Dangling ends and surface-proximal tails of gene targets influence probe-target duplex formation and affect the signal intensity of probes on diagnostic microarrays. This phenomenon was evaluated using an oligonucleotide microarray containing 18-mer probes corresponding to the 16S rRNA genes of 10 waterborne pathogens and a number of synthetic and PCR-amplified gene targets. Signal intensities for Klenow/random primer-labeled 16S rRNA gene targets were dissimilar from those for 45-mer synthetic targets for nearly 73% of the probes tested. Klenow/random primer-labeled targets resulted in an interaction with a complex mixture of 16S rRNA genes (used as the background) 3.7 times higher than the interaction of 45-mer targets with the same mixture. A 7-base-long dangling end sequence with perfect homology to another single-stranded background DNA sequence was sufficient to produce a cross-hybridization signal that was as strong as the signal obtained by the probe-target duplex itself. Gibbs free energy between the target and a well-defined background was found to be a better indicator of hybridization signal intensity than the sequence or length of the dangling end alone. The dangling end (Gibbs free energy of -7.6 kcal/mol) was found to be significantly more prone to target-background interaction than the surface-proximal tail (Gibbs free energy of -64.5 kcal/mol). This study underlines the need for careful target preparation and evaluation of signal intensities for diagnostic arrays using 16S rRNA and other gene targets due to the potential for target interaction with a complex background. [ABSTRACT FROM AUTHOR]