Zika virus (ZIKV) is an emerging arbovirus of the Flaviviridae family. Although ZIKV infection is typically mild and self-limiting in healthy adults, infection has been associated with neurological symptoms such as Guillain-Barré syndrome, and a causal link has been established between fetal microcephaly and ZIKV infection during pregnancy. These risks, and the magnitude of the ongoing ZIKV pandemic, have created an urgent need for the development of animal models to study the immune response to ZIKV infection. Previous animal models have primarily focused on pathogenesis in immunocompromised mice. In this study, we provide a model of ZIKV infection in wild-type immunocompetent C57BL/6 mice, and have provided an analysis of the immune response to infection. We evaluated the activation of several innate immune cell types, and studied the kinetics, phenotype, and functionality of T cell responses to ZIKV infection. Our results demonstrate that ZIKV infection is mild in wild-type immunocompetent C57BL/6 mice, resulting in minimal morbidity. Our data establish that at the peak of the adaptive response, antigen-experienced CD4+ T cells polarize to a Th1 phenotype, and antigen-experienced CD8+ T cells exhibit an activated effector phenotype, producing both effector cytokines and cytolytic molecules. Furthermore, we have identified a novel ZIKV CD8+ T cell epitope in the envelope protein that is recognized by the majority of responding cells. Our model provides an important reference point that will help dissect the impact of polymorphisms in the circulating ZIKV strains on the immune response and ZIKV pathogenesis. In addition, the identification of a ZIKV epitope will allow for the design of tetramers to study epitope-specific T cell responses, and will have important implications for the design and development of ZIKV vaccine strategies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322871 | PMC |
http://dx.doi.org/10.1371/journal.ppat.1006184 | DOI Listing |
Virology
December 2024
The Centre for Infection and Immunity Studies, School of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, 518107, China. Electronic address:
The knowledge on the life cycle of flaviviruses is still incomplete, and no direct-acting antivirals against their infections are clinically available. Herein, by screening via a Zika virus (ZIKV) replicon assay, we found that the N-terminus of NS2A exhibited great tolerance to the insertions of different split fluorescent proteins (split-FPs). Furthermore, both ZIKV and dengue virus encoding a split-FP-tagged NS2A propagated efficiently, and the split-FP-tagged ZIKVs had good genetic stability.
View Article and Find Full Text PDFPediatr Res
January 2025
Center for Genetic Medicine, Children's National Research Institute, Washington, DC, USA.
Background: Prenatally transmitted viruses can cause severe damage to the developing brain. There is unexplained variability in prenatal brain injury and postnatal neurodevelopmental outcomes, suggesting disease modifiers. Of note, prenatal Zika infection can cause a spectrum of neurodevelopmental disorders, including congenital Zika syndrome.
View Article and Find Full Text PDFJ Virol
December 2024
1Division of Gastroenterology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Flaviviruses utilize the cellular endoplasmic reticulum (ER) for all aspects of their lifecycle. Genome replication and other viral activities take place in structures called replication organelles (ROs), which are invaginations induced in the ER membrane. Among the required elements for RO formation is the biogenesis of viral nonstructural proteins NS4A and NS4B.
View Article and Find Full Text PDFVirol Sin
December 2024
Department of Medical Laboratory Science, University of Maiduguri, College of Medical Sciences, P.M.B. 1069, Maiduguri, Nigeria. Electronic address:
Sci Rep
December 2024
Public Health and community medicine Department, Theodor Bilharz Research Institute, Helwan University, Cairo, Egypt.
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forecast outbreaks of Dengue, Chikungunya, and Zika, utilizing a comprehensive dataset comprising climate and socioeconomic data. Spanning the years 2007 to 2017, the dataset includes 1716 instances characterized by 27 distinct features.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!