Simulação computacional e análise de um modelo de recombinação retroviral
Retroviruses cause major diseases in humans, such as Acquired Human Immunodeficiency Syndrome (AIDS), caused by HIV-1, which accounts for 2.1 million new cases in 2015 alone, and T-cell lymphoma, caused by HTLV-1. One of the hallmarks of retroviruses is the high frequency of genetic recombination du...
| Autor: | |
|---|---|
| Formato: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Brasil |
| Recursos: | Universidade Federal de São Paulo (UNIFESP) |
| Repositorio: | Repositório Institucional da UNIFESP |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.unifesp.br:11600/50657 |
| Acesso em linha: | https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=5026522 https://repositorio.unifesp.br/handle/11600/50657 |
| Access Level: | acceso abierto |
| Palavra-chave: | Viral evolution Computational simulation Viral recombination Retroviruses Quasispecies Evolução viral Simulação computacional Recombinação viral |
| Resumo: | Retroviruses cause major diseases in humans, such as Acquired Human Immunodeficiency Syndrome (AIDS), caused by HIV-1, which accounts for 2.1 million new cases in 2015 alone, and T-cell lymphoma, caused by HTLV-1. One of the hallmarks of retroviruses is the high frequency of genetic recombination during replication, associated with a high mutational rate, considered one of the highest in nature. These characteristics contribute to the generation of expressive genetic diversity in the viral population, strongly impacting its virulence, facilitating evasion from detection by the immune system, increasing resistance to antiviral treatment, hindering diagnosis, and the development of effective vaccines. With the purpose of guiding experimental studies and investigating scenarios that cannot yet be approached experimentally, in addition to providing support to elaborate new scientific predictions, we propose, in this work, a model to study mutational rates and genetic recombination in retroviruses. Custom software for the model was also developed. It performs computational simulations and analysis to understand how mutational rates and genetic recombination affect the evolution of the retrovirus population, in the host organism, during four stages of infection: recovery time, mutation-selection equilibrium, extinction threshold, and lethal mutagenesis. |
|---|