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      Current Status of Marker Genes of Bacteroides and Related Taxa for Identifying Sewage Pollution in Environmental Waters

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      MDPI AG

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          Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data

          Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.
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            Development of Bacteroides 16S rRNA gene TaqMan-based real-time PCR assays for estimation of total, human, and bovine fecal pollution in water.

            Bacteroides species are promising indicators for differentiating livestock and human fecal contamination in water because of their high concentration in feces and potential host specificity. In this study, a real-time PCR assay was designed to target Bacteroides species (AllBac) present in human, cattle, and equine feces. Direct PCR amplification (without DNA extraction) using the AllBac assay was tested on feces diluted in water. Fecal concentrations and threshold cycle were linearly correlated, indicating that the AllBac assay can be used to estimate the total amount of fecal contamination in water. Real-time PCR assays were also designed for bovine-associated (BoBac) and human-associated (HuBac) Bacteroides 16S rRNA genes. Assay specificities were tested using human, bovine, swine, canine, and equine fecal samples. The BoBac assay was specific for bovine fecal samples (100% true-positive identification; 0% false-positive identification). The HuBac assay had a 100% true-positive identification, but it also had a 32% false-positive rate with potential for cross-amplification with swine feces. The assays were tested using creek water samples from three different watersheds. Creek water did not inhibit PCR, and results from the AllBac assay were correlated with those from Escherichia coli concentrations (r2= 0.85). The percentage of feces attributable to bovine and human sources was determined for each sample by comparing the values obtained from the BoBac and HuBac assays with that from the AllBac assay. These results suggest that real-time PCR assays without DNA extraction can be used to quantify fecal concentrations and provide preliminary fecal source identification in watersheds.
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              Validity of the indicator organism paradigm for pathogen reduction in reclaimed water and public health protection.

              The validity of using indicator organisms (total and fecal coliforms, enterococci, Clostridium perfringens, and F-specific coliphages) to predict the presence or absence of pathogens (infectious enteric viruses, Cryptosporidium, and Giardia) was tested at six wastewater reclamation facilities. Multiple samplings conducted at each facility over a 1-year period. Larger sample volumes for indicators (0.2 to 0.4 liters) and pathogens (30 to 100 liters) resulted in more sensitive detection limits than are typical of routine monitoring. Microorganisms were detected in disinfected effluent samples at the following frequencies: total coliforms, 63%; fecal coliforms, 27%; enterococci, 27%; C. perfringens, 61%; F-specific coliphages, approximately 40%; and enteric viruses, 31%. Cryptosporidium oocysts and Giardia cysts were detected in 70% and 80%, respectively, of reclaimed water samples. Viable Cryptosporidium, based on cell culture infectivity assays, was detected in 20% of the reclaimed water samples. No strong correlation was found for any indicator-pathogen combination. When data for all indicators were tested using discriminant analysis, the presence/absence patterns for Giardia cysts, Cryptosporidium oocysts, infectious Cryptosporidium, and infectious enteric viruses were predicted for over 71% of disinfected effluents. The failure of measurements of single indicator organism to correlate with pathogens suggests that public health is not adequately protected by simple monitoring schemes based on detection of a single indicator, particularly at the detection limits routinely employed. Monitoring a suite of indicator organisms in reclaimed effluent is more likely to be predictive of the presence of certain pathogens, and a need for additional pathogen monitoring in reclaimed water in order to protect public health is suggested by this study.
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                Author and article information

                Journal
                WATEGH
                Water
                Water
                MDPI AG
                2073-4441
                June 2016
                May 31 2016
                : 8
                : 6
                : 231
                Article
                10.3390/w8060231
                97bd7abb-6921-4854-a3bf-e16d03f96bae
                © 2016

                https://creativecommons.org/licenses/by/4.0/

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