Global In-Silico Performance Assessment of the CDC Zika Trioplex Detection System

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Abstract

Arboviruses, transmitted by arthropod vectors such as mosquitoes and ticks, represent a significant public health challenge due to their association with high mortality rates and the absence of vaccines or effective treatments. Dengue, Zika, and Chikungunya viruses (DENV, ZIKV, and CHIKV) are of particular concern, often co-circulating and causing outbreaks worldwide. The development of molecular detection tools has been crucial for improving diagnostic accuracy and facilitating early outbreak management. However, many detection tools, including the widely adopted CDC Trioplex RT-PCR assay, have not undergone comprehensive evaluation against global viral sequence diversity. This assay simultaneously detects DENV, ZIKV, and CHIKV, yet its performance across emerging viral strains, particularly in regions like West Africa, remains underexplored. We conducted an in-silico analysis of the CDC Trioplex assay’s primers and probes against a global dataset of ZIKV strains. Phylogenetic analysis revealed notable differences between the African and Asian ZIKV genotypes. Further, mismatch analyses demonstrated that the CDC Trioplex primers and probes exhibit varying degrees of mismatches across different ZIKV strains, particularly of African genotypes. These mismatches, especially in key primer and probe regions, can significantly impact PCR efficiency, potentially leading to diagnostic failures. Our findings underscore the need for ongoing surveillance of circulating viral strains and the importance of validating diagnostic assays like the CDC Trioplex in diverse geographic regions. Further experimental research is necessary to determine the practical implications of these mismatches for ZIKV detection accuracy, especially in regions with diverse viral strains such as West Africa.

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