Novel municipal sewage-associated bacterial genomes and their potential in source tracking

Little is known about the genomic diversity of raw municipal wastewater (sewage) microbial communities, including to what extent sewage-specific populations exist and how they can be used to improve source attribution and partitioning in sewage-contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) as inoculum in multiple controlled laboratory mesocosms to simulate sewage contamination events and followed these perturbed freshwater microbial communities with metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inoculum yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster under the well-aerated incubation conditions. Notably, a portion of these populations show decay patterns similar to common markers, Enterococcus and HF183. Comparisons against MAGs from different sources such as human and animal feces, revealed low cross-reactivity, indicating how genomic collections could be used to sensitively identify sewage contamination and partition signal among multiple sources. Overall, our results indicate the usefulness of metagenomic approaches for assessing sewage contamination in waterbodies and provides needed methodologies for doing so.

New Classification Method to Evaluate Pollution Levels of Sewage Contaminated Lakes

Monitoring water quality to minimize deterioration of a lake’s functionality is important, as several Indian lakes are exposed to sewage contamination. Public health laboratories, citizen scientists, and volunteers in developing nations often find it difficult to perform elaborate tests to monitor the water quality of freshwater systems. Developing a classification method to evaluate the pollution status of sewage-contaminated lakes using limited tests will expand environmental monitoring of freshwater systems and contribute valuable data to the regional and global repository. Four classes of lake pollution ranging from unpolluted (class 1) to mixed wastewater (class 4) were identified based on the distribution of data points in the K+ (potassium) versus COD (chemical oxygen demand) scatter chart. As pH, EC (electrical conductivity), turbidity, and DO (dissolved oxygen) are deteriorated by sewage contamination, these parameters were also incorporated in the proposed pollution classification table. Data of unpolluted and sewage polluted Indian lakes were employed to compile the limiting range of parameters in the proposed lake pollution classification. The five parameters (K+, pH, EC, DO, turbidity) required to categorize lake pollution (class 1 to 4) can be measured with equipment costing 800–1000 USD, while COD can be measured at 5 USD/sample in laboratories.

E. coli Is a Poor End-Product Criterion for Assessing the General Microbial Risk Posed From Consuming Norovirus Contaminated Shellfish

The fecal indicator organism (FIO) Escherichia coli is frequently used as a general indicator of sewage contamination and for evaluating the success of shellfish cleaning (depuration) processes. To evaluate the robustness of this approach, the accumulation, retention, and depuration of non-pathogenic E. coli, pathogenic E. coli O157:H7 and norovirus GII (NoV GII) RNA were evaluated using a combination of culture-based (E. coli) and molecular methods (E. coli, NoV GII) after exposure of mussels (Mytilus edulis) to water contaminated with human feces. We simulated water contamination after a point-source release from a combined sewer overflow (CSO) where untreated wastewater is released directly into the coastal zone. All three microbiological indicators accumulated rapidly in the mussels, reaching close to maximum concentration within 3 h of exposure, demonstrating that short CSO discharges pose an immediate threat to shellfish harvesting areas. Depuration (72 h) in clean water proved partially successful at removing both pathogenic and non-pathogenic E. coli from shellfish tissue, but failed to eradicate NoV GII RNA. We conclude that current EU standards for evaluating microbiological risk in shellfish are inadequate for protecting consumers against exposure to human norovirus GII found in polluted marine waters.

Statistical analysis of hydrochemistry and isotopic characterization of groundwater from the Parecis Basin

ABSTRACT Knowledge of mechanism controlling the hydrochemistry of groundwater are crucial requirement to understand the hydrochemical evolution and evaluate the water quality of subsurficial water resources. Thus, to understand the process governing the hydrochemistry variability and flow dynamics of the Parecis and Ronuro Aquifers, the use of statistical analysis and isotopic characterization were combined. In the correlation matrix it was found that the highest correlation coefficient was observed for HCO3-, Ca2+, Mg2+, Sr2+, SO42-, and F-, which suggested that these parameters are derived from the same source, most likely from rock–water interactions. Additionally, we noticed moderate to high correlation among NO3-, Cl-, Na+, K+, and Ba2+, which collectively are indicative of domestic sewage contamination. Finally, a principal component analysis (PCA) identified that the most variance in hydrochemistry from the evaluated samples was controlled by HCO3-, Ca2+ and Mg2+, which is associated with rock–water interaction. Regarding the 18O and 2H isotope values, it could be observed that the aquifer recharges were of meteoric origin and that the Ronuro Aquifer samples were more enriched than the PAS samples. This work reinforces the capability of multivariate statistics to discern the main process that controls the variability of groundwater hydrochemistry.