This project aims to develop new methods that can be used by the water industry and its regulators to remove/limit these constraints.

Developing rapid and specific diagnostics for the detection and genotyping of Cryptosporidium species and Giardia assemblages in drinking water

Current Cryptosporidium and Giardia detection methodologies in raw/drinking water used by water utility companies rely on the detection of oocysts/cysts microscopically, which is very subjective, labour-intensive and time-consuming. Identification of oocysts by microscopy requires high levels of expertise but operators can only work microscopically for 4 hours per day for health and safety reasons. An additional drawback is that oocyst/cyst identification is only to the genus level, while there are many Cryptosporidium and Giardia species and assemblages that are not infectious to humans.

We are developing and validating quantitative DNA detection methods (qPCR technologies) for the detection and enumeration of Cryptosporidium oocysts or Giardia cysts that could replace the need for microscopy. These are “catch-all” qPCRs that detect and enumerate all Cryptosporidium and Giardia species and provide equivalent results to microscopy but will be less labour-intensive and allow for multiple samples to be processed at the same time. This technology can distinguish between human-infectious and non-infectious Cryptosporidium and Giardia species/genotypes, which would give a direct indication of risk to human health faster than the current approach. A further advantage of the qPCRs is that they only amplify DNA from oocysts that have not been inactivated (killed) by UV, as UV treatment will degrade the parasite’s DNA. Therefore, the qPCRs could also provide evidence when UV treatment has failed, which cannot be achieved by microscopy. The proposed qPCRs not only provide time savings, but they will also provide additional information on human infectivity and viability of parasites compared to the current methodologies currently used.

Developing a technique to extract Toxoplasma gondii oocysts from drinking water

Detection methods for Toxoplasma in water are underdeveloped compared to other protozoan parasites and rely on a combination of molecular assays, microscopy, and bioassays. Currently, Scottish Water tests all its water supplies for Cryptosporidium spp. but there is no requirement to test for Toxoplasma. Previous work demonstrated that 9% of water samples (including finished water) from different public water supply plants in Scotland were positive for Toxoplasma DNA, highlighting the potential importance of this transmission route.

In a follow-up study, one Toxoplasma oocyst was detected by microscopy in a final water sample; however, this was likely an underestimate of positive samples due to the difficulty in detecting oocysts in turbid water samples. The Drinking Water Quality Regulator have highlighted their requirement for a specific and sensitive technique for detecting Toxoplasma in water samples. Therefore, we aim to develop an immunomagnetic separation (IMS) technique using a suitable monoclonal antibody specific to the outer wall of Toxoplasma oocysts. Initially, a panel of antibodies is being tested for their ability and efficiency to capture Toxoplasma oocysts and their ability to dissociate from the antibody/capture bead complex so that samples can be used for downstream microscopy or DNA extraction (qPCR, genotyping and assessing viability). Secondly, the IMS is being tested using spiked water samples ranging in turbidity to assess oocyst recovery rates and thus the suitability of the technique for detecting oocysts in drinking water as well as catchments. The development of a sensitive and specific technique for detecting Toxoplasma oocysts in water allows water industries, not only in Scotland but worldwide, to assess the risk of toxoplasmosis from water.

Developing digital image analysis methods for the detection and quantitation of protozoal oocysts/cysts

Currently, water utility companies use fluorescent microscopy to detect Cryptosporidium oocysts and Giardia cysts in raw and drinking water. This methodology is subjective, labour-intensive and time-consuming. In addition, the identification of oocysts by microscopy requires high levels of expertise but operators can only work for 4 hours per day due to health and safety guidance. Image processing algorithms have been developed that can automatically identify and quantify eggs from parasitic worms affecting humans in wastewater samples. We are using a similar approach to develop an algorithm that can identify oocysts/cysts from Cryptosporidium, Toxoplasma and Giardia in water samples. If successful, this automated image analysis algorithm has the potential to reduce the time required for the identification of parasite oocysts/cysts. In addition, the number of oocysts/cysts can be accurately counted, which would allow the infectious load to be accurately estimated. This algorithm for automated detection and quantitation of protozoal oocysts can inform the assessment of the risk of protozoan parasites within catchments and drinking water for the water industry and regulators.