This study evaluated and compared molecular methods (Whole Genome Sequencing-WGS, MinION, and RT-qPCR) for the detection of arboviruses Dengue (DENV), Chikungunya (CHIKV), and Zika (ZIKV) in 63 hospital and municipal wastewater samples collected from July 2022 to May 2023 in the region of Belo Horizonte, Brazil. Detection rates varied substantially across the methods (WGS, MinION, and RT-qPCR). DENV was identified in 24% (15/63) of samples using a hybrid capture method of WGS and MinION sequencing and in 66.6% (20/30) using only WGS but was not detected using the CDC Trioplex RT-PCR Assay Kit or ZDC (IBMP). CHIKV was detected in 19.0% (12/63) of the samples by WGS and MinION and in 85.7% (12/14) using only MinION sequencing. Using the RT-qPCR kit to detect CHIKV yielded a rate of 4.7% (3/63) in false positives. ZIKV was found in only one sample (1/63) by WGS, while RT-qPCR yielded a high false positive rate (65.1%, 41/63). These findings highlight the operational advantage of these methods (WGS and MinION) for enhancing early-warning surveillance where standard RT-qPCR might underperform in low-prevalence settings. This is the first study that has compared these methods to detect and genetically characterize DENV, CHICK, and ZIKV in wastewater in Brazil and has indicated that hospital wastewater can be used as a sentinel system for arbovirus surveillance. The relative effectiveness of genomic wastewater surveillance for arboviruses was demonstrated, and it was found that diagnostic RT-qPCR kits used for clinical samples were not directly suitable for environmental surveillance. The feasibility of arbovirus wastewater surveillance as an epidemiological tool was demonstrated, although absolute quantifications were not performed.

Uncovering DENV, CHIKV, and ZIKV in Urban Wastewater in Brazil Through Genomic and Molecular Screening

Giovanetti M.;
2025-01-01

Abstract

This study evaluated and compared molecular methods (Whole Genome Sequencing-WGS, MinION, and RT-qPCR) for the detection of arboviruses Dengue (DENV), Chikungunya (CHIKV), and Zika (ZIKV) in 63 hospital and municipal wastewater samples collected from July 2022 to May 2023 in the region of Belo Horizonte, Brazil. Detection rates varied substantially across the methods (WGS, MinION, and RT-qPCR). DENV was identified in 24% (15/63) of samples using a hybrid capture method of WGS and MinION sequencing and in 66.6% (20/30) using only WGS but was not detected using the CDC Trioplex RT-PCR Assay Kit or ZDC (IBMP). CHIKV was detected in 19.0% (12/63) of the samples by WGS and MinION and in 85.7% (12/14) using only MinION sequencing. Using the RT-qPCR kit to detect CHIKV yielded a rate of 4.7% (3/63) in false positives. ZIKV was found in only one sample (1/63) by WGS, while RT-qPCR yielded a high false positive rate (65.1%, 41/63). These findings highlight the operational advantage of these methods (WGS and MinION) for enhancing early-warning surveillance where standard RT-qPCR might underperform in low-prevalence settings. This is the first study that has compared these methods to detect and genetically characterize DENV, CHICK, and ZIKV in wastewater in Brazil and has indicated that hospital wastewater can be used as a sentinel system for arbovirus surveillance. The relative effectiveness of genomic wastewater surveillance for arboviruses was demonstrated, and it was found that diagnostic RT-qPCR kits used for clinical samples were not directly suitable for environmental surveillance. The feasibility of arbovirus wastewater surveillance as an epidemiological tool was demonstrated, although absolute quantifications were not performed.
2025
arbovirus; genomic surveillance; molecular screening; public health laboratories; RT-qPCR diagnostic kit; wastewater surveillance
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/90904
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