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Updated: Jul 27, 2026

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters
Published on: March 9, 2016
Microbial indicators and molecular markers used to differentiate the source of faecal pollution in the Bogotá River
Andrea C Sánchez-Alfonso1, Camilo Venegas1, Hugo Díez1
1Department of Microbiology, Pontifical Xavierian University, Carrera 7 No. 43 - 82, Bogotá, Colombia.
Abstract:
Intestinal pathogenic microorganisms are introduced into the water by means of faecal contamination, thus creating a threat to public health and to the environment. Detecting these contaminants has been difficult due to such an analysis being costly and time-intensive; as an alternative, microbiological indicators have been used for this purpose, although they cannot differentiate between human or animal sources of contamination because these indicators are part of the digestive tracts of both. To identify the sources of faecal pollution, the use of chemical, microbiological and molecular markers has been proposed. Currently available markers present some geographical specificity. The aim of this study was to select microbial and molecular markers that could be used to differentiate the sources of faecal pollution in the Bogotá River and to use them as tools for the evaluation and identification of the origin of discharges and for quality control of the water. In addition to existing microbial source markers, a phage host strain (PZ8) that differentiates porcine contamination was isolated from porcine intestinal content. The strain was identified biochemically and genotypically as Bacteroides. The use of this strain as a microbial source tracking indicator was evaluated in bovine and porcine slaughterhouse wastewaters, raw municipal wastewaters and the Bogotá River. The results obtained indicate that the selected microbial and molecular markers enable the determination of the source of faecal contamination in the Bogotá River by using different algorithms to develop prediction models.
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