Zika virus infection in a non-neural cell host promotes differential expression of proteins associated with neurological conditions

The Zika Virus (ZIKV) is a Flavivirus that caused a recent outbreak worldwide resulting in different neurological outcomes that are still poorly characterized and understood. Concerning this issue, in vitro and in vivo models are being applied to improve the molecular understanding of ZIKV infection. In this work, applying shotgun proteomics we revealed the differential ZIKV infection proteome in Vero cells, a non-neural cell model. A dramatic change resulting from infection was found including the differential expression of several proteins previously associated with brain diseases. The molecular alterations caused by this pathogen were further characterized through bioinformatics such as Gene Ontology and protein-protein interaction network of resulting differential proteome. Our findings identified molecular markers that were differentially expressed during ZIKV infection and had been previously linked to neurological conditions and infections caused by ZIKV and/or SARS-CoV-2. The results presented in this article highlight molecular markers associated with neurological dysfunctions, demonstrating that ZIKV infection can dysregulate neural-specific genes, even in non-neural cells.

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Publication Details

Journal
Anais da Academia Brasileira de Ciências
Published
2025-01-01
DOI
https://doi.org/10.1590/0001-3765202520240849
Citations
2
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
3.76

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article

Zika virus infection in a non-neural cell host promotes differential expression of proteins associated with neurological conditions

Lucélia Santi, Aline Martins Faustino, Yohana Porto Calegari-Alves, Ana Paula Muterle Varela et al.
2 citations
Anais da Academia Brasileira de Ciências
Mosquito-borne diseases and control
3.76
article

Zika virus infection in a non-neural cell host promotes differential expression of proteins associated with neurological conditions

Lucélia Santi, Aline Martins Faustino, Yohana Porto Calegari-Alves, Ana Paula Muterle Varela, Ana Luiza Marques, Paulo Michel Roehe, Patrícia Sesterheim, Emanuela Fernanda Tureta Cagnini, Rafael Lopes da Rosa, Walter O. Beys‐da‐Silva, Larissa Daniele Bobermin, Alexandre Rosa Campos, André Quincozes‐Santos, Diogo O. Souza, Markus Berger Oliveira, Ramón Díaz, Jorge Almeida Guimarães, JÚLIA F. SANT’ANA
article en
2 citations

Abstract

The Zika Virus (ZIKV) is a Flavivirus that caused a recent outbreak worldwide resulting in different neurological outcomes that are still poorly characterized and understood. Concerning this issue, in vitro and in vivo models are being applied to improve the molecular understanding of ZIKV infection. In this work, applying shotgun proteomics we revealed the differential ZIKV infection proteome in Vero cells, a non-neural cell model. A dramatic change resulting from infection was found including the differential expression of several proteins previously associated with brain diseases. The molecular alterations caused by this pathogen were further characterized through bioinformatics such as Gene Ontology and protein-protein interaction network of resulting differential proteome. Our findings identified molecular markers that were differentially expressed during ZIKV infection and had been previously linked to neurological conditions and infections caused by ZIKV and/or SARS-CoV-2. The results presented in this article highlight molecular markers associated with neurological dysfunctions, demonstrating that ZIKV infection can dysregulate neural-specific genes, even in non-neural cells.

Anais da Academia Brasileira de CiênciasVol. 97(suppl 2)
Universidade Federal do Rio Grande do Sul (BR), Sanford Burnham Prebys Medical Discovery Institute (US), Discovery Institute (US), Hospital de Clínicas de Porto Alegre (BR), Fundação Universitária de Cardiologia (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Good health and well-being
Openalex Percentile: Top 8%
Mosquito-borne diseases and control
3.76
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