Comparison of Chikungunya Virus-Induced Disease Progression and Pathogenesis in Type-I Interferon Receptor-Deficient Mice (A129) and Two Wild-Type (129Sv/Ev and C57BL/6) Mouse Strains

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus causing a debilitating febrile illness with rheumatic disease symptoms of arthralgia and arthritis. Since its spread outside of Africa in 2005, it continues to cause outbreaks and disseminates into new territories. Intervention strategies are urgently required, including vaccination and antiviral approaches. To test efficacy, the use of small animal models is required. Two mouse strains, A129, with a deficiency in their type-I interferon (IFN) receptor, and C57BL/6 are widely used. A direct comparison of these strains alongside the wild-type parental strain of the A129 mice, 129Sv/Ev, was undertaken to assess clinical disease progression, viral loads in key tissues, histological changes and levels of sera biomarkers. Our results confirm the severe disease course in A129 mice which was not observed in the parental 129Sv/Ev strain. Of the two wild-type strains, viral loads were higher in 129Sv/Ev mice compared to C57BL/6 counterparts. Our results have established these models and parameters for the future testing of vaccines and antiviral approaches.

Authors

Institutions

Publication Details

Journal
Viruses
Published
2024-09-27
DOI
https://doi.org/10.3390/v16101534
Citations
1
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
0.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparison of Chikungunya Virus-Induced Disease Progression and Pathogenesis in Type-I Interferon Receptor-Deficient Mice (A129) and Two Wild-Type (129Sv/Ev and C57BL/6) Mouse Strains

Susan Fotheringham, Neil Almond, Victoria Graham, Emma Kennedy et al.
1 citations
Viruses
Mosquito-borne diseases and control
0.54
article

Comparison of Chikungunya Virus-Induced Disease Progression and Pathogenesis in Type-I Interferon Receptor-Deficient Mice (A129) and Two Wild-Type (129Sv/Ev and C57BL/6) Mouse Strains

Susan Fotheringham, Neil Almond, Victoria Graham, Emma Kennedy, Emma Rayner, Sarah Kempster, Stuart Dowall, Linda Easterbrook, Stephen Findlay‐Wilson, Lucy Flett
article en
1 citations

Abstract

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus causing a debilitating febrile illness with rheumatic disease symptoms of arthralgia and arthritis. Since its spread outside of Africa in 2005, it continues to cause outbreaks and disseminates into new territories. Intervention strategies are urgently required, including vaccination and antiviral approaches. To test efficacy, the use of small animal models is required. Two mouse strains, A129, with a deficiency in their type-I interferon (IFN) receptor, and C57BL/6 are widely used. A direct comparison of these strains alongside the wild-type parental strain of the A129 mice, 129Sv/Ev, was undertaken to assess clinical disease progression, viral loads in key tissues, histological changes and levels of sera biomarkers. Our results confirm the severe disease course in A129 mice which was not observed in the parental 129Sv/Ev strain. Of the two wild-type strains, viral loads were higher in 129Sv/Ev mice compared to C57BL/6 counterparts. Our results have established these models and parameters for the future testing of vaccines and antiviral approaches.

VirusesVol. 16(10)
UK Health Security Agency (GB), National Institute for Biological Standards and Control (GB)
Innovate UK
Good health and well-being
Openalex Percentile: Top 28%
Mosquito-borne diseases and control
0.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.