The INCA-Pathogens model: An application to the Loimijoki River basin in Finland

Effects of temperature and light exposure on the decay characteristics of fecal indicators, norovirus, and Legionella in mesocosms simulating subarctic river water

Knowledge of the decay characteristics of health-related microbes in surface waters is important for modeling the transportation of waterborne pathogens and for assessing their public health risks. Although water temperature and light exposure are major factors determining the decay characteristics of enteric microbes in surface waters, such effects have not been well studied in subarctic surface waters. This study comprehensively evaluated the effect of temperature and light on the decay characteristics of health-related microbes [Escherichia coli, enterococci, microbial source tracking markers (GenBac3 & HF183 assays), coliphages (F-specific and somatic), noroviruses GII and Legionella spp.] under simulated subarctic river water conditions. The experiments were conducted in four different laboratory settings (4 °C/dark, 15 °C/dark, 15 °C/light, and 22 °C/light). The T90 values (time required for a 90 % reduction in the population of a target) of all targets were higher under cold and dark (2.6-51.3 days depending upon targets) than under warm and light conditions (0.6-3.5 days). Under 4 °C/dark (simulated winter) water conditions, F-specific coliphages had 27.2 times higher, and coliform bacteria had 3.3 times higher T90 value than under 22 °C/light (simulated summer) water conditions. Bacterial molecular markers also displayed high variation in T90 values, with the greatest difference between 4 °C/dark and 22 °C/light recorded for HF183 DNA (20.6 times) and the lowest difference for EC23S857 RNA (6.6 times). E. coli, intestinal enterococci, and somatic coliphages were relatively more sensitive to light than water temperature, but F-specific coliphages, norovirus, and all bacterial rDNA and rRNA markers were relatively more sensitive to temperature than light exposure. Due to the slow microbial decay in winter under subarctic conditions, the microbial quality of river water might remain low for a long time after a sewage spill. This increased risk associated with fecal pollution during winter may deserve more attention, especially when river waters are used for drinking water production.

The Use of Ribosomal RNA as a Microbial Source Tracking Target Highlights the Assay Host-Specificity Requirement in Water Quality Assessments

For microbial source tracking (MST), the 16S ribosomal RNA genes (rDNA) of host-specific bacteria and mitochondrial DNA (mtDNA) of animal species, known to cause fecal contamination of water, have been commonly used as molecular targets. However, low levels of contamination might remain undetected by using these DNA-based qPCR assays. The high copy numbers of ribosomal RNA (rRNA) could offer a solution for such applications of MST. This study compared the performance of eight MST assays: GenBac3 (general Bacteroidales), HF183 (human), BacCan (dog), Rum-2-Bac (ruminant), Pig-2-Bac (swine), Gull4 (gull), GFD, and Av4143 (birds) between rRNA-based and rDNA-based approaches. Three mtDNA-based approaches were tested: DogND5, SheepCytB, and HorseCytB. A total of 151 animal fecal samples and eight municipal sewage samples from four regions of Finland were collected for the marker evaluation. The usability of these markers was tested by using a total of 95 surface water samples with an unknown pollution load. Overall, the performance (specificity, sensitivity, and accuracy) of mtDNA-based assays was excellent (95–100%), but these markers were very seldom detected from the tested surface water samples. The rRNA template increased the sensitivity of assays in comparison to the rDNA template. All rRNA-based assays (except Av4143) had more than 80% sensitivity. In contrast, only half (HF183, Rum-2-Bac, Pig-2-Bac, and Gull4) of rDNA-based assays reached this value. For markers targeted to bird feces, the use of the rRNA-based assay increased or at least did not change the performance. Regarding specificity, all the assays had >95% specificity with a DNA template, except the BacCan assay (71%). While using the RNA template for the assays, HF183 and BacCan exhibited only a low level of specificity (54 and 55%, respectively). Further, the HF183 assay amplified from multiple non-targeted animal fecal samples with the RNA template and the marker showed cross-amplification with the DNA template as well. This study recommends using the rRNA-based approach for MST assays targeting bird fecal contamination. In the case of mammal-specific MST assays, the use of the rRNA template increases the sensitivity but may reduce the specificity and accuracy of the assay. The finding of increased sensitivity calls for a further need to develop better rRNA-based approaches to reach the required assay performance.

The impact of socio-economic development and climate change on E. coli loads and concentrations in Kabul River, Pakistan

Microbial pollution is a major problem worldwide. High concentrations of Escherichia coli have been found in Kabul River in Pakistan. E. coli concentrations vary under different socio-economic conditions, such as population and livestock densities, urbanisation, sanitation and treatment of wastewater and manure, and climate-change aspects, such as floods and droughts. In this paper, we assess potential future E. coli loads and concentrations in the Kabul River using the Soil and Water Assessment Tool with scenarios that are based on the most recent Shared Socio-economic Pathways and Representative Concentration Pathways (SSPs and RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC). Scenario_1 considers moderate population and livestock density growth, planned urbanisation and strongly improved wastewater and manure treatment (based on SSP1, "Sustainability"), and moderate climate change (RCP4.5, moderate greenhouse gas (GHG) emissions). Scenario_2 considers strong population and livestock density growth, moderate urbanisation, slightly improved wastewater treatment, no manure treatment (based on SSP3, "Regional rivalry") and strong climate change (RCP8.5, high GHG emissions). Simulated E. coli responses to Scenario_2 suggest a mid-century increase in loads by 111% and a late century increase of 201% compared to baseline loads. Similarly, simulated E. coli loads are reduced by 60% for the mid-century and 78% for the late century compared to the baseline loads. When additional treatment is simulated in Scenario_1, the loads are reduced even further by 94%, 92% and 99.3% compared to the baseline concentrations when additional tertiary treatment, manure treatment or both have been applied respectively. This study is one of the first to apply combined socio-economic development and climate change scenario analysis with an E. coli concentration model to better understand how these concentrations may change in the future. The scenario analysis shows that reducing E. coli concentrations in Pakistan's rivers is possible, but requires strongly improved waste water treatment and manure management measures.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r_s=0.88; p<0.01) than the Wyre (r_s=-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool.