Rivers are often challenged by fecal contaminations. The barrier effect of sediments against fecal bacteria was investigated through the use of a microbial source tracking (MST) toolbox, and by Next Generation Sequencing (NGS) of V5-V6 16S rRNA gene (rrs) sequences. Non-metric multi-dimensional scaling analysis of V5-V6 16S rRNA gene sequences differentiated bacteriomes according to their compartment of origin i.e., surface water against benthic and hyporheic sediments. Classification of these reads showed the most prevalent operating taxonomic units (OTU) to be allocated to Flavobacterium and Aquabacterium. Relative numbers of Gaiella, Haliangium, and Thermoleophilum OTU matched the observed differentiation of bacteriomes according to river compartments. OTU patterns were found impacted by combined sewer overflows (CSO) through an observed increase in diversity from the sewer to the hyporheic sediments. These changes appeared driven by direct transfers of bacterial contaminants from wastewaters but also by organic inputs favoring previously undetectable bacterial groups among sediments. These NGS datasets appeared more sensitive at tracking community changes than MST markers. The human-specific MST marker HF183 was strictly detected among CSO-impacted surface waters and not river bed sediments. The ruminant-specific DNA marker was more broadly distributed but intense bovine pollution was required to detect transfers from surface water to benthic and hyporheic sediments. Some OTU showed distribution patterns in line with these MST datasets such as those allocated to the Aeromonas, Acinetobacter, and Pseudomonas. Fecal indicators (Escherichia coli and total thermotolerant coliforms) were detected all over the river course but their concentrations were not correlated with MST ones. Overall, MST and NGS datasets suggested a poor colonization of river sediments by bovine and sewer bacterial contaminants. No environmental outbreak of these bacterial contaminants was detected.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.