Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining

Metagenomic evaluation of bacteria in drinking water using full-length 16S rRNA amplicons

Escherichia coli and total coliforms are important tools for identifying potential faecal contamination in drinking water. However, metagenomics offers a powerful approach for delving deeper into a bacterial community when E. coli or total coliforms are detected. Metagenomics can identify microbes native to water systems, track community changes and potential pathogens introduced by contamination events, and evaluate the effectiveness of treatment processes. Here, we demonstrate how the dual application of traditional monitoring practices and metagenomics can improve monitoring and surveillance for water resource management. The robustness of long-read metagenomics across replicates is demonstrated by the effect and interaction between manganese filters and bacterial communities, as well as the impact of chlorination after coliform detection. These examples reveal how metagenomics can identify the complex bacterial communities in the distribution system and the source waters used to supply drinking water treatment plants (DWTPs). The knowledge gained increases confidence in identified causes and mitigations of potential contamination events. By exploring bacterial communities, we can gain additional insights into the impact of faecal contamination events and treatment processes. This insight enables more precise remediation actions and enhances confidence in communicating health risks to drinking water operators and the public.

Current status of microbial source tracking applications in constructed wetlands serving as nature-based solutions for water management and wastewater treatment

Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

CrAss-Like Phages: From Discovery in Human Fecal Metagenome to Application as a Microbial Source Tracking Marker

CrAss-like phages are a diverse group of bacteriophages genetically similar to the prototypical crAssphage (p-crAssphage), which was discovered in the human gut microbiome through a metagenomics approach. It was identified as a ubiquitous and highly abundant bacteriophage group in the gut microbiome. Initial co-occurrence analysis postulated Bacteroides spp. as the prospective bacterial host. Subsequent studies have confirmed multiple host species under Phylum Bacteroidetes and some Firmicutes. Detection of crAss-like phages in sewage-contaminated environmental water and robust correlation with enteric viruses and bacteria has culminated in their adoption as a microbial source tracking (MST) marker. Polymerase chain reaction (PCR) and real-time PCR assays have been developed utilizing the conserved genes in the p-crAssphage genome to detect human fecal contamination of different water sources, with high specificity. Numerous investigations have examined the implications of crAss-like phages in diverse disease conditions, including ulcerative colitis, obesity and metabolic syndrome, autism spectrum disorders, rheumatoid arthritis, atopic eczema, and other autoimmune disorders. These studies have unveiled associations between certain diseases and diminished abundance and diversity of crAss-like phages. This review offers insights into the diverse aspects of research on crAss-like phages, including their discovery, genomic characteristics, structure, taxonomy, isolation, molecular detection, application as an MST marker, and role as a gut microbiome modulator with consequential health implications.

Integrating fecal pollution markers and fluorescence analysis for water quality assessment of urban river

Human fecal contamination in urban rivers poses significant health risks, but their potential connections with other substances like dissolved organic matter (DOM) remain underexplored. In this study, five fecal pollution markers related to fecal Bacteroides or human fecal contamination (AllBac, HF183, BacH, Hum2, and Hum163) and DOM along an urban river were analyzed using quantitative polymerase chain reaction (qPCR) and three-dimensional excitation-emission (3D EEM) fluorescence spectrometry. All five markers were detected with average absolute abundance ranging from 2.51 to 6.28 lg gene copies/100 mL, showing a progressive increase along the river (R2 = 0.29-0.92, p < 0.05). Parallel factor analysis identified three dominant DOM components (humic acid-like, fulvic acid-like, and protein-like), with strong positive correlations between protein-like components and all fecal markers (R2 = 0.59-0.66, p < 0.001). Both fecal and DOM distributions consistently showed significant differences between upstream and downstream areas (p < 0.001), suggesting their complementary assessment. While DOM was more sensitive to environmental variables such as rainfall, rubber dam, and tidal dynamic, the combination of fecal pollution markers and 3D EEM analysis allowed a more comprehensive assessment of contamination levels, mitigating potential biases caused by the influence of multiple factors on a single method. Furthermore, due to the strong correlation between protein-like and fecal markers in the DOM, 3D EEM can be used as a pre-detection means for qPCR detection, reducing testing time and costs.