Modelagem matemática e computacional do gargalo de transmissão durante o estabelecimento da infecção pelo HIV

• Ano de defesa: 2019
• Autor(a) principal: Furuyama, Taima Naomi [UNIFESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Paulo (UNIFESP)
• Palavras-chave em Português: HIV; Transmission Bottlenecks; Transmitted Founder Virus; Computational Biology Theoretical Models; Gargalos De Transmissão Viral; Biologia Computacional; Modelos Teóricos; Partícula Viral Fundadora Transmissora
• Link de acesso: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=7708109; https://repositorio.unifesp.br/handle/11600/59622

Objective: To develop a computational tool that simulates the initial moments of HIV infection in a single host and the viral inoculum development in several hosts. Considering viral rep lication as the most i mpor tant factor, and from a phenotypical analysis, it will be possible to evaluate the viral transmission events and the establishment of the transmitted infections Methods: An in silico model was developed to analyze the t ransmissio n moment and the viral par ticles quality, under a phenotypical approach . The model assigns a quality factor to viral particles, the replication class. This class determines how many viral particles an initial particle can generate, as a progeny, after a re plication cycle. The p roge ny can suffer interferences, like the occurrence of deleterious effects (caused by deleterious mutations, for example) on the viral particles. The probabilities of occurrence for deleterious, neutral or beneficial effect s characte rize the stochastic na ture of the phenotypical model, altering the progeny distribution on the replication classes during viral replication cycles. After the formation and distribution o f viral progenies inside a host, a genetic transmission bott leneck is then generated. This b ottl eneck is represented by an algorithm responsible for simulating the transmission of viral particles to a new host. In this work, it was defined that only 5 vira l particles would be transmitted to a new host, as the genet ic transmi ssion bottleneck. Resu lts: Eight different scenarios were simulated, each one being simulated a thousand times, so that a statistically robust data set could be obtained, resulting in 8 thousand simulations in total. Each scenery simulated 101 pa tients bei ng infected in a linea r ch ain sequence, and each patient had 45 cycles of viral replication, the equivalent to about 100 days of viral evolution. The results show that the higher the fre quency of early transmissions (less cycles of viral replicat ion), the greater the chance of a pe rsistent infection over time. In cases of late transmissions, the viral particles cannot maintain the epidemic. The infections do occur, but the viral inoculum, carrying effects from the suffered mutations, is not capabl e of promo ting a lasting infecti on i n a new host. Therefore, chances of new, successful infections, are lower over transmissions among host that in their late moments of transmission. Conclusion: The HIV transmission moment is a key factor in maintaining t he epidemi c. The model proposed here shows that transmission occurred in the first ~10 days of infection presents higher probabilities of promoting an infection with better transmitter founder vir al particles.