Trypanosoma cruzi Immune Response Modulation Decreases Microbiota in Rhodnius prolixus Gut and Is Crucial for Parasite Survival and Development

Trypanosoma cruzi in order to complete its development in the digestive tract of Rhodnius prolixus needs to overcome the immune reactions and microbiota trypanolytic activity of the gut. We demonstrate that in R. prolixus following infection with epimastigotes of Trypanosoma cruzi clone Dm28c and, in comparison with uninfected control insects, the midgut contained (i) fewer bacteria, (ii) higher parasite numbers, and (iii) reduced nitrite and nitrate production and increased phenoloxidase and antibacterial activities. In addition, in insects pre-treated with antibiotic and then infected with Dm28c, there were also reduced bacteria numbers and a higher parasite load compared with insects solely infected with parasites. Furthermore, and in contrast to insects infected with Dm28c, infection with T. cruzi Y strain resulted in a slight decreased numbers of gut bacteria but not sufficient to mediate a successful parasite infection. We conclude that infection of R. prolixus with the T. cruzi Dm28c clone modifies the host gut immune responses to decrease the microbiota population and these changes are crucial for the parasite development in the insect gut

Modeling Disease Vector Occurrence when Detection Is Imperfect: Infestation of Amazonian Palm Trees by Triatomine Bugs at Three Spatial Scales

Blood-sucking bugs of the genus Rhodnius are major vectors of Chagas disease. Control and surveillance of Chagas disease transmission critically depend on ascertaining whether households and nearby ecotopes (such as palm trees) are infested by these vectors. However, no bug detection technique works perfectly. Because more sensitive methods are more costly, vector searches face a trade-off between technical prowess and sample size. We compromise by using relatively inexpensive sampling techniques that can be applied multiple times to a large number of palms. With these replicated results, we estimate the probability of failing to detect bugs in a palm that is actually infested. We incorporate this information into our analyses to derive an unbiased estimate of palm infestation, and find it to be about 50% – twice the observed proportion of infested palms. We are then able to model the effects of regional, landscape, and local environmental variables on palm infestation. Individual palm attributes contribute overwhelmingly more than landscape or regional covariates to explaining infestation, suggesting that palm tree management can help mitigate risk locally. Our results illustrate how explicitly accounting for vector, pathogen, or host detection failures can substantially improve epidemiological parameter estimation when perfect detection techniques are unavailable