Synergistic Application of Molecular Markers and Community-Based Microbial Source Tracking Methods for Identification of Fecal Pollution in River Water During Dry and Wet Seasons

Abstract

It is important to track fecal sources from humans and animals that negatively influence the water quality of rural rivers and human health. In this study, microbial source tracking (MST) methods using molecular markers and the community-based FEAST (fast expectation–maximization microbial source tracking) program were synergistically applied to distinguish the fecal contributions of multiple sources in a rural river located in Beijing, China. The performance of eight markers were evaluated using 133 fecal samples based on real-time quantitative (qPCR) technique. Among them, six markers, including universal (BacUni), human-associated (HF183-1 and BacH), swine-associated (Pig-2-Bac), ruminant-associated (Rum-2-Bac), and avian-associated (AV4143) markers, performed well in the study. A total of 96 water samples from the river and outfalls showed a coordinated composition of fecal pollution, which revealed that outfall water might be a potential input of the Fsq River. In the FEAST program, bacterial 16S rRNA genes of 58 fecal and 12 water samples were sequenced to build the “source” library and “sink,” respectively. The relative contribution (<4.01% of sequence reads) of each source (i.e., human, swine, bovine, or sheep) was calculated based on simultaneous screening of the operational taxonomic units (OTUs) of sources and sinks, which indicated that community-based MST methods could be promising tools for identifying fecal sources from a more comprehensive perspective. Results of the qPCR assays indicated that fecal contamination from human was dominant during dry weather and that fecal sources from swine and ruminant were more prevalent in samples during the wet season than in those during the dry season, which were consistent with the findings predicted by the FEAST program using a very small sample size. Information from the study could be valuable for the development of improved regulation policies to reduce the levels of fecal contamination in rural rivers.

A comprehensive database of human and livestock fecal microbiome for community-wide microbial source tracking: a case study in South Korea

“…Traditional MST methods have limitations in distinguishing different host species from contamination sources. In this study, the fecal microbiomes were distinguishable by different host groups, as reported in many other studies [39,40]. The machine learning models constructed in this study showed nearly 100% accuracy in predicting host groups based on fecal microbial community structures.…”

Wastewater microorganisms impact microbial diversity and important ecological functions of stream periphyton

“…The proportion of each sink community that did not match the signature of the sources included in our analysis was assigned to unknown sources. Such analysis is used to identify potential contamination of the sinks by other unidentified microbial sources (Liang et al, 2021;Shenhav et al, 2019). In our study, ultra-filtration did not only lead to an increase of the relative proportion of stream communities in periphyton, but also to an increased proportion of these unknown sources.…”

Have genetic targets for faecal pollution diagnostics and source tracking revolutionized water quality analysis yet?

“…The authors used cutting edge data handling methods, including statistical methods to account for the large proportion of nondetects, and an estimation of spatial and temporal variations of same-host contribution using ratios between given Bacteroidales MST markers and a general Bacteroidales marker (Bambic et al 2015 ). Separating the sample set into dry and wet periods allowed Liang et al ( 2021 ) to reveal differing pollution pathways. The results of MST markers agreed with those from 16S AmpSeq and the FEAST algorithm: humans were the main pollution source in the dry season, and ruminant and swine were the main pollution sources in the wet season at this river site near Beijing, China.…”