Datasets related to "Genomic diversity analysis enables development of pan-Dengue Toehold RNA sensors"

Abstract of the research described in the manuscriptThe Dengue virus (DENV) like many other RNA viruses exhibits high genome sequence diversity. This poses a challenge to nucleic acid-based diagnostics, rendering them inefficient at detecting the diverse DENV strains circulating in a population. In this study, we address this challenge by developing a Toehold sensor assay that despite significant genomic diversity is able to detect ~99.4% of all strains of DENV. To this end, our custom workflow first identifies relatively conserved short stretches (36-nt) within all DENV genomes, which could potentially serve as triggers that activate Toehold RNA sensors. We then add a crucial step of mismatch-tolerance that allows related triggers with high sequence diversity and multiple mismatches in the sensor binding region to be efficiently sensed by the same sensor. Deploying in vitro transcription translation assays, we show that the designed sensors were able to efficiently sense target RNA triggers from all the four DENV serotypes. These data demonstrate that multiple Toehold RNA sensors were able to tolerate limited mismatches in the target RNA sequences without compromising response. The sensitivity of the Toehold sensor assay is often increased by inclusion of an isothermal RNA amplification step. We show by employing multiple primer sets that diverse trigger RNAs from all four serotypes of the dengue virus can be successfully amplified and subsequently detected by the same sensor. Together, this approach has resulted in a pan-dengue Toehold sensor assay, which presents a powerful nucleic acid detection platform to detect viruses with high sequence diversity.