Development of fluorescent in situ hybridisation for Cryptosporidium detection reveals zoonotic and anthrioponotic transmission of sporadic cryptosporidiosis in Sydney

Cryptosporidium, is the most common non-viral cause of diarrhea worldwide. Of the 5 described species that contribute to the majority of human infections, C. parvum is of major interest due to its zoonotic potential. A species-specific fluorescence in situ hybridisation probe was designed to the variable region in the small subunit of the 18S rRNA of C. parvum and labeled with Cy3. Probe specificity was validated against a panel of 7 other Cryptosporidium spp. before it was applied to 33 human faecal samples positive for cryptosporidiosis which were obtained during the period from 2006-2007. Results were compared to PCR-RFLP targeting the 18S rDNA. FISH results revealed that 19 of the 33 isolates analysed were identified as C. parvum. Correlation of PCR-RFLP and FISH was statistically significant (P < 0.05), resulting in a calculated correlation coefficient of 0.994. In this study, species identification by FISH and PCR-RFLP provided preliminary evidence to support both anthroponotic and zoonotic transmission of sporadic cases of cryptosporidiosis in the Sydney basin. In conclusion, FISH using a C. parvum-specific probe provided an alternative tool for accurate identification of zoonotic Cryptosporidium which will be applied in the future to both epidemiological and outbreak investigations

Meeting Report: Knowledge and Gaps in Developing Microbial Criteria for Inland Recreational Waters

The U.S. Environmental Protection Agency (EPA) has committed to issuing in 2012 new or revised criteria designed to protect the health of those who use surface waters for recreation. For this purpose, the U.S. EPA has been conducting epidemiologic studies to establish relationships between microbial measures of water quality and adverse health outcomes among swimmers. New methods for testing water quality that would provide same-day results will likely be elements of the new criteria. Although the epidemiologic studies upon which the criteria will be based were conducted at Great Lakes and marine beaches, the new water quality criteria may be extended to inland waters (IWs). Similarities and important differences between coastal waters (CWs) and IWs that should be considered when developing criteria for IWs were the focus of an expert workshop. Here, we summarize the state of knowledge and research needed to base IWs microbial criteria on sound science. Two key differences between CWs and IWs are the sources of indicator bacteria, which may modify the relationship between indicator microbes and health risk, and the relationship between indicators and pathogens, which also may vary within IWs. Monitoring using rapid molecular methods will require the standardization and simplification of analytical methods, as well as greater clarity about their interpretation. Research needs for the short term and longer term are described

Meeting Report: Application of Genotyping Methods to Assess Risks from Cryptosporidium in Watersheds

A workshop titled “Application of Genotyping Methods to Assess Pathogen Risks from Cryptosporidium in Drinking Water Catchments” was held at the International Water Association biennial conference, Marrakech, Morocco, 23 September 2004. The workshop presented and discussed the findings of an interlaboratory trial that compared methods for genotyping Cryptosporidium oocysts isolated from feces. The primary goal of the trial and workshop was to assess the utility of current Cryptosporidium genotyping methods for determining the public health significance of oocysts isolated from feces in potable-water–supply watersheds. An expert panel of 16 watershed managers, public health practitioners, and molecular parasitologists was assembled for the workshop. A subordinate goal of the workshop was to educate watershed management and public health practitioners. An open invitation was extended to all conference delegates to attend the workshop, which drew approximately 50 interested delegates. In this report we summarize the peer consensus emerging from the workshop. Recommendations on the use of current methods by watershed managers and public health practitioners were proposed. Importantly, all the methods that were reported in the trial were mutually supporting and found to be valuable and worthy of further utility and development. Where there were choices as to which method to apply, the small-subunit ribosomal RNA gene was considered to be the optimum genetic locus to target. The single-strand conformational polymorphism method was considered potentially the most valuable for discriminating to the subtype level and where a large number of samples were to be analyzed. A research agenda for protozoan geneticists was proposed to improve the utility of methods into the future. Standardization of methods and nomenclature was promoted

Reproducibility and Sensitivity of Thirty-Six Methods to Quantify the SARS-CoV-2 Genetic Signal in Raw Wastewater: Findings from an Interlaboratory Methods Evaluation in the U.S.

In response to COVID-19, the international water community rapidly developed methods to quantify the SARS-CoV-2 genetic signal in untreated wastewater. Wastewater surveillance using such methods has the potential to complement clinical testing in assessing community health. This interlaboratory assessment evaluated the reproducibility and sensitivity of 36 standard operating procedures (SOPs), divided into eight method groups based on sample concentration approach and whether solids were removed. Two raw wastewater samples were collected in August 2020, amended with a matrix spike (betacoronavirus OC43), and distributed to 32 laboratories across the U.S. Replicate samples analyzed in accordance with the project\u27s quality assurance plan showed high reproducibility across the 36 SOPs: 80% of the recoverycorrected results fell within a band of ±1.15 log10 genome copies per L with higher reproducibility observed within a single SOP (standard deviation of 0.13 log10). The inclusion of a solids removal step and the selection of a concentration method did not show a clear, systematic impact on the recovery-corrected results. Other methodological variations (e.g., pasteurization, primer set selection, and use of RT-qPCR or RT-dPCR platforms) generally resulted in small differences compared to other sources of variability. These findings suggest that a variety of methods are capable of producing reproducible results, though the same SOP or laboratory should be selected to track SARS-CoV-2 trends at a given facility. The methods showed a 7 log10 range of recovery efficiency and limit of detection highlighting the importance of recovery correction and the need to consider method sensitivity when selecting methods for wastewater surveillance

Deterministic model to quantify pathogen and faecal indicator loads in drinking water catchments.

Catchments are the first potential barrier to pathogen hazards in the water supply system. Reducing pathogen loads exported from catchments to drinking water reservoirs is thus an important priority in applying a risk-based approach to managing water supplies. Although predictive models are available to estimate sediment and nutrient loads, few models are available to predict either bacterial indicator or pathogen loads exported from catchments. This paper describes the application of a process-based mathematical model to predict pathogen (Cryptosporidium) and faecal indicator (E. coli) loads generated within and exported from the Sydney drinking water catchments. The model was derived from a conceptual model that identified key processes for microbial sources from animals, on-site systems and sewage treatment plants (STPs) and their subsequent transport within drinking water catchments (Ferguson et al. 2003). Inputs to the model include GIS land use and hydrologic data and catchment specific information. The model was initially applied to the Wingecarribee catchment in the Sydney drinking water catchment and a sensitivity analysis of the model was undertaken to determine components of the model that required further investigation (Ferguson et al. submitted). The model was then applied to all 27 individual catchments (and the 196 subcatchments) within the Sydney Catchment Authority (SCA) area of operations. The model predicts pathogen catchment budgets (PCB) and ranks the sub-catchments that generate the highest loads of pathogens and indicators (per km2), as well as the sub-catchments that export the greatest load of pathogens to the downstream storages. Ranking the sub-catchments enables quick identification of those areas that are generating the highest pathogen and indicator loads facilitating the implementation of control measures. The outputs from the model show that in dry weather the highest daily loads of Cryptosporidium were predicted to be generated in Kellys Creek and Mittagong Creek sub-catchments in the Wingecarribee catchment. These sub-catchments are heavily impacted by the effluent discharged from Bowral and Moss Vale STPs, respectively. However, in wet weather the wash off of faecal material into surface runoff predicts that large loads of Cryptosporidium are generated in sub-catchments dominated by improved pasture grazed by cattle. The slow decay of protozoan pathogens combined with their rapid transport in water during wet weather events results in a cumulative export of Cryptosporidium to downstream sub-catchments. For example, the PCB model predicts that Warragamba reservoir would receive 4 x 1011 Cryptosporidium oocysts following a 100 mm in 24 h rainfall event in the Sydney catchment. The model predicts that in dry weather approximately 1 x 1011 E. coli per day were generated in sub-catchments that contain improved pasture with agricultural livestock with additional inputs from sub-catchments receiving STP effluent. The rapid die-off and limited transport of this microorganism in dry weather results in fairly localized impacts. However in wet weather significant loads of faecal indicator bacteria are mobilised to the stream network and transported to downstream sub-catchments with Warragamba reservoir and the Lower Wollondilly predicted to receive up to 5.4 x 1015 E. coli following a 100 mm in 24 h rain event in the Sydney catchment. The pathogen and indicator wet weather export loads predicted by the PCB model can be used as input variables to the hydrodynamic reservoir model developed by Hipsey et al. (2005) thus enabling the estimation of the risk of their subsequent transport to the water storage offtake point in Warragamba Reservoir

Concentrations of Pathogens and Indicators in Animal Feces in the Sydney Watershed

A fecal analysis survey was undertaken to quantify animal inputs of pathogenic and indicator microorganisms in the temperate watersheds of Sydney, Australia. The feces from a range of domestic animals and wildlife were analyzed for the indicator bacteria fecal coliforms and Clostridium perfringens spores, the pathogenic protozoa Cryptosporidium and Giardia, and the enteric viruses adenovirus, enterovirus, and reovirus. Pathogen and fecal indicator concentrations were generally higher in domestic animal feces than in wildlife feces. Future studies to quantify potential pathogen risks in drinking-water watersheds should thus focus on quantifying pathogen loads from domestic animals and livestock rather than wildlife

Deterministic model of microbial sources, fate and transport: a quantitative tool for pathogen catchment budgeting

The most important priority for the management of Australian drinking water catchments is the control of pathogen loads delivered to raw water reservoirs and treatment plant intakes. A process-based mathematical model was developed to estimate pathogen catchment budgets (PCB) for Cryptosporidium, Giardia and E. coli loads generated within and exported from catchments. The model quantified key processes affecting the generation and transport of microorganisms from humans and animal excreta using land use and hydrologic data, and catchment specific information including point sources such as sewage treatment plants and on-site systems. The PCB model was applied in the Wingecarribee catchment, Sydney and used to predict and rank pathogen and indicator loads in dry weather, intermediate (<30 mm in 24 h) and large wet weather events (100mm in 24 h). Sensitivity analysis identified that pathogen excretion rates from animals and humans, and manure mobilisation rates were the most significant factors determining the output of the model. Comparison with water quality data indicated that predicted dry weather loads were generally within 1-2 log10 of the measured loads for Cryptosporidium and E. coli and within 1 log10 for Giardia. The model was subsequently used to predict and rank pathogen and indicator loads for the entire (16 000 km2) Sydney drinking water catchment

Development of a process-based model to predict pathogen budgets for the Sydney drinking water catchment

In drinking water catchments, reduction of pathogen loads delivered to reservoirs is an important priority for the management of raw source water quality. To assist with the evaluation of management options, a process-based mathematical model (pathogen catchment budgets - PCB) is developed to predict Cryptosporidium, Giardia and E. coli loads generated within and exported from drinking water catchments. The model quantifies the key processes affecting the generation and transport of microorganisms from humans and animals using land use and flow data, and catchment specific information including point sources such as sewage treatment plants and on-site systems. The resultant pathogen catchment budgets (PCB) can be used to prioritize the implementation of control measures for the reduction of pathogen risks to drinking water. The model is applied in the Wingecarribee catchment and used to rank those sub-catchments that would contribute the highest pathogen loads in dry weather, and in intermediate and large wet weather events. A sensitivity analysis of the model identifies that pathogen excretion rates from animals and humans, and manure mobilization rates are significant factors determining the output of the model and thus warrant further investigation