Exploring the molecular basis of SARS-CoV-2 infection in preclinical neural models

• Grant number: 20/10282-7
• Support type: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): September 01, 2020
• Effective date (End): June 30, 2021
• Field of knowledge: Biological Sciences - Biochemistry - Chemistry of Macromolecules
• Principal researcher: Daniel Martins-de-Souza
• Grantee: Andre Saraiva Leao Marcelo Antunes
• Home Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 20/04746-0 - Understanding the molecular bases and the role of risk factors associated to SARS-CoV-2 infection in preclinical models, AP.R

Abstract

There is still little understanding of the molecular mechanisms of SARS-CoV-2 infection, especially in the Central Nervous System (CNS). This makes it difficult to halt the rapid spread of the virus, which has taken on pandemic dimensions, leading many countries, including Brazil, to declare a state of public calamity. There is evidence that SARS-CoV2 is hosted not only in the respiratory tract but that it can also infect the CNS, induce neurological changes and symptoms, such as headache, nausea and vomiting. In early 2003, samples from SARS-CoV-infected patients demonstrated the presence of viral particles in the brain, mainly in neurons. The presence of SARS-CoV was also observed in the brain of infected animal preclinical models, and the number of positive samples for SARS-CoV increased during the course of infection with prevalence in the hippocampus. In this project we will investigate, at the protein and metabolite level, the influence of SARS-CoV-2 on human in vitro models. We will generate neurons and astrocytes derived from neural stem cells. These cells, infected, uninfected and eventually treated with potential anti-viral drugs, will have their proteomes and metabolomes investigated by large-scale mass spectrometry. We hope to unveil biochemical pathways and potential therapeutic targets associated with SARS-CoV-2 infection, which will serve as a basis for new treatments. The data generated here may compose a framework of information about the mode of infection by Coronaviruses. (AU)