Transcriptional Response to Tick-Borne Flavivirus Infection in Neurons, Astrocytes and Microglia In Vivo and In Vitro
Issued Date
2024-08-01
Resource Type
eISSN
19994915
Scopus ID
2-s2.0-85202478166
Journal Title
Viruses
Volume
16
Issue
8
Rights Holder(s)
SCOPUS
Bibliographic Citation
Viruses Vol.16 No.8 (2024)
Suggested Citation
Rosendal E., Lindqvist R., Chotiwan N., Henriksson J., Överby A.K. Transcriptional Response to Tick-Borne Flavivirus Infection in Neurons, Astrocytes and Microglia In Vivo and In Vitro. Viruses Vol.16 No.8 (2024). doi:10.3390/v16081327 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100937
Title
Transcriptional Response to Tick-Borne Flavivirus Infection in Neurons, Astrocytes and Microglia In Vivo and In Vitro
Author's Affiliation
Corresponding Author(s)
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Abstract
Tick-borne encephalitis virus (TBEV) is a neurotropic member of the genus Orthoflavivirus (former Flavivirus) and is of significant health concern in Europe and Asia. TBEV pathogenesis may occur directly via virus-induced damage to neurons or through immunopathology due to excessive inflammation. While primary cells isolated from the host can be used to study the immune response to TBEV, it is still unclear how well these reflect the immune response elicited in vivo. Here, we compared the transcriptional response to TBEV and the less pathogenic tick-borne flavivirus, Langat virus (LGTV), in primary monocultures of neurons, astrocytes and microglia in vitro, with the transcriptional response in vivo captured by single-nuclei RNA sequencing (snRNA-seq) of a whole mouse cortex. We detected similar transcriptional changes induced by both LGTV and TBEV infection in vitro, with the lower response to LGTV likely resulting from slower viral kinetics. Gene set enrichment analysis showed a stronger transcriptional response in vivo than in vitro for astrocytes and microglia, with a limited overlap mainly dominated by interferon signaling. Together, this adds to our understanding of neurotropic flavivirus pathogenesis and the strengths and limitations of available model systems.