Genetic diversity and development of a rapid molecular detection method for protozoan parasites in raw and treated wastewater

Abstract

Protozoan parasites can cause a wide range of diseases in both humans and animals. Despite this, little is known about their genetic diversity in the environment, particularly in wastewater. Current methods of detecting protozoan parasites are time-consuming and expensive, limiting our ability to monitor potential risks associated with their discharge into the environment. Consequently, this study aimed to determine the genetic diversity of protozoan parasites in wastewater treatment plants and to develop a rapid and affordable technique for their detection and quantification from environmental samples. Shotgun metagenomics and 18S rRNA gene sequencing were employed to assess the diversity of protozoan parasites in influent (untreated) and effluent (treated) wastewater samples collected from different geographical locations within South Africa. Furthermore, rapid fluorescent and colorimetric loop-mediated isothermal amplification (LAMP) methods were developed for their detection from different environmental matrices. The LAMP methods were then compared with the established methods, including quantitative PCR and digital PCR for their sensitivity and feasibility. Additionally, the study has also evaluated oocyst concentration and DNA extraction methods to maximize oocyst recovery from wastewater samples resulting in a recovery rate of 64.1%. Using 18SrRNA analysis, it was found that protozoan diversity (Shannon index, P-value=0.003) and taxonomic composition (PERMANOVA, P-value=0.02) were significantly associated with WWTP location and treatment stage (P-value=0.003). An abundant number of free-living, parasitic, and potentially pathogenic protists was observed in the untreated wastewater samples, including Alveolates (Apicomplexa and Ciliophora), Excavata (Discoba and Parasalia), and Amoebozoa (Entamoeba and Acanthamoeba). In contrast, treated wastewater samples were found to be dominated by fungi and algae. In a subset of samples (n=3), shotgun metagenomics analyses revealed the presence of protozoa of public health importance, including Cryptosporidium spp. All untreated wastewater samples studied were found to contain Entamoeba hystolitica, Blastocystis hominis, Naegleria gruberi, Toxoplasma gondii, Cyclospora cayetanensis, and Giardia intestinalis. The functional pathways associated with pathogenic protozoa were classified into thiamine diphosphate biosynthesis III, Heme biosynthesis, methyl erythritol phosphate (MEP), Methylerythritol 4-phosphate pathway, and pentose phosphate pathway. The optimized LAMP methods (colorimetric and fluorescent) successfully detected Cryptosporidium parvum (GP60 gene) and the Cryptosporidium genus (SAM gene) from environmental samples with 100% specificity. Both methods demonstrated a high sensitivity, with the same limit of detection (LOD) of 1.1 copies of C. parvum per 25 µl reaction (0.02 ng/µl). A comparison of LAMP, ddPCR, and qPCR revealed that ddPCR had the highest sensitivity, with a limit of detection (LOD) of 1 copy/reaction and 100% true positives followed by fluorescent LAMP with a LOD of 1.1 copies and 75% true positives, while qPCR was the least sensitive with a LOD of 14 copies and 100% true positives. All three methods showed good linearity (> R2 =0.9) over a wide dynamic range of C. parvum concentrations. The study further revealed that fLAMP is the most affordable ($12.46/sample), followed by qPCR ($28.19/sample), and ddPCR ($67.29/sample). Using the optimized protocol, C. parvum and Cryptosporidium spp. were detected in 50–85% (n = 60) of environmental samples (treated and untreated wastewater, sludge, and surface water) in comparison to 58–98% (n = 60) detected by ddPCR. Additionally, these findings suggest that LAMP can be an effective and affordable method for monitoring protozoan parasites in the environment. The findings of this study provided valuable insights into the genetic diversity of protozoan parasites in wastewater, which is crucial for advancing our understanding of disease epidemiology, evolution, and ecology. Furthermore, the findings of this study have important implications for monitoring pathogens in wastewater, especially in countries with limited resources for monitoring and managing waterborne diseases.