Navegando por Palavras-chave "Viral Evolution"
Agora exibindo 1 - 1 de 1
Resultados por página
Opções de Ordenação
- ItemSomente MetadadadosModelo Matemático E Computacional Para O Estudo De Evolução E Adaptação Viral Com Presença De Reservatório(Universidade Federal de São Paulo (UNIFESP), 2017-05-25) Gorzoni, Bruno Zanardo [UNIFESP]; Janini, Luiz Mario Ramos [UNIFESP]; Universidade Federal de São Paulo (UNIFESP)Abstract The theory of lethal mutagenesis predicts that RNA virus populations could become extinct by reduction of their mean replication capacity (mean number of progeny per infected cell), triggered by the elevation of detrimental mutation rates. However, there are RNA viruses, such as HIV-1, capable of escaping extinction, even after long ART (Antiretroviral Therapy) periods due to the presence of an integrated latent viral reservoir. We believe that the reservoir can play an important role in the evolution of viral populations, acting as an evolutionary strategy to delay its own extinction. We developed a mathematical model to emulate the reservoir by applying the concept of aging to particles integrated in cells with latent infection. By adding ages to particles, we sought to represent the latent reservoir containing resting cells harboring the integrated viral genome. We implemented the model as a user-friendly program, which is an upgrade from a previous published model by our group, which is capable of performing simulations and displaying the results in real time. In our results, we show that the emulated reservoir delays viral extinction in comparison to simulations performed without reservoir. We believe that there is a strong indication that the reservoir could even avoid complete extinction in certain adaptive scenarios helping the virus population to escape from the lethal mutagenesis. According to our simulations, the reservoir can act as a viral population memory retaining particles with greater replication capacity that have been lost from the replicating viral population. The reintroduction of highly replicative particles allows the population to survive for longer periods even in the presence of elevated mutation rates.