Condicionantes ambientais da infecção de carrapatos Amblyomma spp. (Acari: Ixodidae) por Rickettsia spp. (Rickettsiales: Rickettsiae)

• Ano de defesa: 2014
• Autor(a) principal: Gomes, Gabriel Guimarães
• Orientador(a): Siqueira, Cláudio Lísias Mafra de
• Banca de defesa: Lima, Gumercindo Souza , Fietto, Luciano Gomes , Sperber, Carlos Frankl , Galvão, Márcio Antonio Moreira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Bioquímica Agrícola
• Departamento: Bioquímica e Biologia molecular de plantas; Bioquímica e Biologia molecular animal
• País: BR
• Palavras-chave em Português: Carrapatos; Amblyomma; Rickettsia; Bactéria - Condições ambientais - Transmissão de doença; Doenças infecciosas
• Palavras-chave em Inglês: Ticks; Amblyomma; Rickettsia; Bacteria - Environmental conditions - Disease transmission; Infectious diseases
• Área do conhecimento CNPq: CNPQ::CIENCIAS BIOLOGICAS::BIOFISICA::BIOFISICA MOLECULAR
• Link de acesso: http://locus.ufv.br/handle/123456789/2473

Pathogens transmitted mainly by ticks their invertebrate hosts, bacteria of the genus Rickettsia may cause highly lethal diseases in humans and animals. Seeking to clarify why some ticks of the genus Amblyomma are infected with Rickettsia and not others, evaluated the environmental constraints of this infection. We tested the hypothesis that infection correlates by monthly climatic drivers (temperature and humidity) and host availability, and that the environmental drivers of this infection differed among host stages. We performed monthly samplings, along ne year, in 15 sites, at least 50m distant from each other, within an area of 1Km2. Ticks were subdivided in three stages: larvae, nymphs and adults, so that we had 540 samples, 180 per host stage. Each sample with ticks submitted to Real Time Polymerase Chain Reaction (PCR), so as to detect infection by Rickettsia. To evaluate the environmental drivers of infection, we run binary logistic analyses, using infection as response variable. We adjusted linear regressions, using Generalized Linear Mixed Models (GLMM), with binomial distribution and random intercepts. Temporal auto- correlation was handled by including sampling sequence (month) as repeated measures in the models. Significance of explanatory terms was evaluated by deletion, beginning from the complete model, without interaction terms. We adjusted different models for each host stage. To describe the seasonal variation in host abundance, we used semi-parametric regressions, with number of individuals as response variable, adjusting Generalized Additive Models (GAM) with Poisson distribution. Host larvae infection decreased with temperature (&#967;2 = 10,5; P = 0,001), while nymph (&#967;2 = 5,3; P = 0,02) and adult (&#967;2 = 5,4; P = 0,02) infection increased with temperature. Humidity and host abundance did not affect infection (&#967;2 < 2,6; P > 0,1). While host larvae abundance was highest in winter (June to August), and decreased in summer (November to February), nymphs were most abundant in spring (September to October). We did not detect seasonality in host adults. Combining the findings, we found the occurrence of negative correlation of infection with larvae of organisms of the genus Rickettsia, with decreases in temperature coincided with the maximum abundance of hosts. The increase of nymph and adult infection with temperature coincides with the maximum abundance of these hosts in warmer periods. Both patterns suggest a Strong synchronicity between the pathogen s virulence with the host s population dynamics.