Aims: The goal of this study was to develop and test the efficacy of a PCR assay for the environmental detection of the nifH gene of Methanobrevibacter smithii, a methanogen found in human faeces and sewage. Methods and Results: PCR primers for the nifH gene of M. smithii were designed, tested and used to detect the presence or absence of this organism in faecal and environmental samples. Specificity analysis showed that the Mnif primers amplified products only in M. smithii pure culture strains (100%), human faeces (29%), human sewage samples (93%) and sewage‐contaminated water samples (100%). No amplification was observed when primers were tested against 43 bacterial stock cultures, 204 animal faecal samples, 548 environmental bacterial isolates and water samples from a bovine waste lagoon and adjacent polluted creek. Sequencing of PCR products from sewers demonstrated that a 222‐bp product was the nifH gene of M. smithii. The minimal amount of total DNA required for the detection of M. smithii was 10 ng for human faeces, 10 ng for faecally contaminated water and 5 ng for sewage. Recreational water seeded with M. smithii established a lower detection limit of 13 cells ml−1. Conclusions: The Mnif assay developed during this investigation showed successful detection of M. smithii in individual human faecal samples, sewage and sewage‐contaminated water but not in uncontaminated marine water or bovine‐contaminated waters. The Mnif assay appears to be a potentially useful method to detect sewage‐polluted coastal waters. Significance and Impact of the Study: This study was the first to utilize methanogens as an indicator of sewage pollution. Mnif PCR detection of M. smithii was shown to be a rapid, inexpensive and reliable test for determining the presence or absence of sewage pollution in coastal recreational waters.
As part of a larger microbial source tracking (MST) study, several laboratories used library-based, phenotypic subtyping techniques to analyse fecal samples from known sources (human, sewage, cattle, dogs and gulls) and blinded water samples that were contaminated with the fecal sources. The methods used included antibiotic resistance analysis (ARA) of fecal streptococci, enterococci, fecal coliforms and E. coli; multiple antibiotic resistance (MAR) and Kirby-Bauer antibiotic susceptibility testing of E. coli; and carbon source utilization for fecal streptococci and E. coli. Libraries comprising phenotypic patterns of indicator bacteria isolated from known fecal sources were used to predict the sources of isolates from water samples that had been seeded with fecal material from the same sources as those used to create the libraries. The accuracy of fecal source identification in the water samples was assessed both with and without a cut-off termed the minimum detectable percentage (MDP). The libraries (approximately 300 isolates) were not large enough to avoid the artefact of source-independent grouping, but some important conclusions could still be drawn. Use of a MDP decreased the percentage of false-positive source identifications, and had little effect on the high percentage of true-positives in the most accurate libraries. In general, the methods were more prone to false-positive than to false-negative errors. The most accurate method, with a true-positive rate of 100% and a false-positive rate of 39% when analysed with a MDP, was ARA of fecal streptococci. The internal accuracy of the libraries did not correlate with the accuracy of source prediction in water samples, showing that one should not rely solely on parameters such as the average rate of correct classification of a library to indicate its predictive capabilities.
The methods comparison study described in accompanying manuscripts demonstrated the potential value of microbial source tracking (MST) techniques, but also identified a need for method refinement. This paper provides three classes of recommendations to improve MST technology: optimization, development and evaluation. Optimization recommendations focus on library-dependent methods and include improved selection of restriction enzymes or antibiotics, better definition of appropriate library size, selection of target species and choice of statistical pattern-matching algorithms. Methods development recommendations focus on identifying new genomic targets and quantification procedures for library-independent methods. Longer-term methods development recommendations include integration of microarrays and other direct pathogen detection technology with MST. Studies defining host specificity and population dynamics should aid selection of target species during methods development. Evaluation recommendations include enhancements that should be incorporated into future methods comparison studies, along with studies to assess the value of MST results for risk characterization.
The goal of this study was to evaluate methanogen diversity in animal hosts to develop a swine-specific archaeal molecular marker for fecal source tracking in surface waters. Phylogenetic analysis of swine mcrA sequences compared to mcrA sequences from the feces of five animals (cow, deer, sheep, horse, and chicken) and sewage showed four distinct swine clusters, with three swine-specific clades. From this analysis, six sequences were chosen for molecular marker development and initial testing. Only one mcrA sequence (P23-2) showed specificity for swine and therefore was used for environmental testing. PCR primers for the P23-2 clone mcrA sequence were developed and evaluated for swine specificity. The P23-2 primers amplified products in P23-2 plasmid DNA (100%), pig feces (84%), and swine waste lagoon surface water samples (100%) but did not amplify a product in 47 bacterial and archaeal stock cultures and 477 environmental bacterial isolates and sewage and water samples from a bovine waste lagoon and a polluted creek. Amplification was observed in only one sheep sample out of 260 human and nonswine animal fecal samples. Sequencing of PCR products from pig feces demonstrated 100% similarity to pig mcrA sequence from clone P23-2. The minimal amount of DNA required for the detection was 1 pg for P23-2 plasmid, 1 ng for pig feces, 50 ng for swine waste lagoon surface water, 1 ng for sow waste influent, and 10 ng for lagoon sludge samples. Lower detection limits of 10 ؊6 g of wet pig feces in 500 ml of phosphate-buffered saline and 10 ؊4 g of lagoon waste in estuarine water were established for the P23-2 marker. This study was the first to utilize methanogens for the development of a swine-specific fecal contamination marker.
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