Coastal waters can experience elevated levels of fecal contamination as a result of human populations, unsupported infrastructure, and terrestrial watershed drainage. Pathogens can be conveyed to waterways from human and non-human (e.g., wildlife, livestock, domesticated animals) sources, posing health risks through contaminated fisheries and recreational waters. Microbial source tracking
seeks to identify fecal contamination, and different approaches vary in capability and effort. There is a need for reliable and efficient methods to improve understanding of fecal sources for land use and waterway management. Molecular methods (e.g., environmental DNA, quantitative PCR) can identify DNA-based viral and bacterial communities as well as quantify Bacteroides (a dominant group of fecal bacteria that enables source identification due to high host specificity). This study aims to identify fecal sources to the Mississippi-Alabama coast using a novel multi-species approach. Water samples were collected monthly for one year from 13 sites that represent potential fecal inputs to Alabama's coast. Total DNA was extracted and metagenomes sequenced on an Illumina NovaSeq platform with 6X coverage to capture the rare biosphere. An aliquot was reserved for qPCR that targeted multiple species (fowl, pig and feral hog, human, cow, dog, general Bacteroides). Bacteria associated with feces were prevalent in Mobile Bay, Alabama year-round, with human-associated as the predominant source, followed episodically by pig-associated feces. Overall, greater concentrations of Bacteroides were found in the summer months, and north Mobile Bay had higher average concentrations than the south bay.
Coupled with an eDNA metabarcoding approach, species and trophic relationships not captured by qPCR methods can be identified (such as free-living or algal-associated Bacteroides) as well as potential pathogenicity. To enhance monitoring and management efforts, we are developing an eDNA Toolkit training workshop to provide partners guidance on implementing advanced source tracking methods.