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Zika Virus Infectious Cell Culture System and the In Vitro Prophylactic Effect of Interferons
Published on: August 23, 2016
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Temperate Conditions Limit Zika Virus Genome Replication.
Blanka Tesla1, Jenna S Powers1, Yvonne Barnes1
1Department of Infectious Diseases, University of Georgiagrid.213876.9, Athens, Georgia, USA.
Journal of Virology
|April 25, 2022
Summary
Cool temperatures inhibit Zika virus genome replication in mosquito cells, impacting transmission. This finding is crucial for predicting arboviral disease spread and developing control strategies.
Area of Science:
- Virology
- Vector-borne diseases
- Epidemiology
Background:
- Zika virus (ZIKV) causes severe birth defects and neuroimmunological disorders.
- Temperature significantly influences vector-borne disease transmission by affecting mosquito vectors and viruses.
- Previous studies showed ZIKV transmission decreases at cooler temperatures.
Purpose of the Study:
- To investigate the mechanisms behind temperature-induced changes in ZIKV transmission.
- To determine how temperature affects ZIKV replication steps in mosquito cells.
- To differentiate temperature effects on Asian and African ZIKV lineages.
Main Methods:
- ZIKV replication steps were analyzed in C6/36 mosquito cells at optimal (28°C) and cool (20°C) temperatures.
- Virus entry, translation, and genome replication were assessed.
- The impact of temperature shifts on replication complex formation was evaluated.
Main Results:
- Cool temperatures (20°C) did not affect ZIKV entry or translation.
- Genome replication was impaired at 20°C, evidenced by reduced double-stranded RNA intermediates.
- If replication complexes formed at 28°C, late replication steps were completed efficiently upon shifting to 20°C.
- The Asian ZIKV lineage showed restricted replication at 20°C, while the African lineage was less affected.
Conclusions:
- Cool temperatures decrease ZIKV genome replication efficiency in mosquito cells.
- Temperature-dependent replication is a key factor in ZIKV transmission dynamics.
- Understanding these mechanisms aids in predicting arboviral disease seasonality and developing control strategies.

