Abstract

IntroductionSchistosomiasis (Bilharzia), a neglected tropical disease caused by Schistosoma parasites, afflicts over 240 million people globally, disproportionately impacting Sub-Saharan Africa. Current diagnostic tests, despite their utility, suffer from limitations like low sensitivity. Polymerase chain reaction (PCR) and quantitative real-time PCR (qPCR) remain the most common and sensitive nucleic acid amplification tests. Still, the sensitivity of nucleic acid amplification tests is significantly affected by the copy number of amplification targets, resulting in underestimation of true Schistosoma infections, especially in low transmission settings. Additionally, lengthy qPCR run times pose challenges when dealing with large sample volumes and limited resources. In this study, the identical multi-repeat sequences (IMRS) were used as a novel approach to enhance the sensitivity of nucleic acid-based Bilharzia diagnosis.MethodsTo identify novel genomic repeat regions, we utilized the IMRS algorithm, with modifications to enable larger target region (100-200bp) identification instead of smaller sequences (18-30bp). These regions enabled customised primer-probe design to suit requirements for qPCR assay. To lower the qPCR amplification times, the assay was conducted using fast cycling condition. Regression analysis, and qPCR data visualization was conducted using Python programming.ResultsUsing Schistosoma mansoni and S. haematobium, we found that IMRS-based qPCR, employing genus-specific primers and TaqMan probes, offers exceptional analytical sensitivity, detecting as little as a single genome copy per microliter within 36 minutes.DiscussionThe lowest concentration of DNA detected using IMRS-based PCR and qPCR represented tenfold improvement over conventional PCR. As part of further development, there is a need to compare IMRS-based qPCR against other qPCR methods for Schistosoma spp. Nonetheless, IMRS-based diagnostics promise a significant advancement in bilharzia diagnosis, particularly in low-transmission settings, potentially facilitating more effective control and treatment strategies.

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