Identification of Plasmodium DNA sequences from anopheline samples in the rural settlement of Santa Luzia, Cruzeiro do Sul county, Acre state, Brazil

Abstract

INTRODUCTION: Female anopheline mosquitoes can be naturally infected by one or more species of Plasmodium and, through their bite, transmit this parasite, which results in malaria in humans. The transmission dynamics depend on several factors, including the vector species, and therefore differ from region to region. Landscapes impacted by deforestation and collections of shaded, low-flow, and clean water, which are commonly found in the Brazilian Amazon, are the preferred habitats for malaria vectors. In most endemic regions, infections by Plasmodium vivax and Plasmodium falciparum are the main causes of malaria, varying geographically in proportion depending on the susceptibility of the specific population. The primary malaria vector in Brazil, along with other vectors that can transmit the disease, is Anopheles darlingi, which has a wide distribution throughout the Amazon Basin. Despite considerable progress in the elimination, control, and understanding of malaria in South America, the disease continues to be a significant public health issue in Brazil.OBJECTIVE: To identify Plasmodium DNA sequences in samples of anophelines from the rural settlement of Santa Luzia, in the municipality of Cruzeiro do Sul, Acre, Brazil.METHODS: The project will be conducted in the Santa Luzia Settlement, in the municipality of Cruzeiro do Sul, Acre. Anophelines will be collected and identified both morphologically and molecularly. Individual samples of identified anophelines will be processed for genomic DNA extraction using a non-destructive nucleic acid extraction technique. Following this, the detection and identification of Plasmodium species will be performed using conventional PCR and real-time PCR assays with fluorescein-labeled probes and cytb markers. Accumulated deforestation and forest cover will be estimated using Landsat satellite images (Landsat 1-8) according to a protocol developed by the group. The method involves supervised classification of the landscape composition into distinct classes: water collection on the ground, native dense ombrophilous forest, secondary vegetation, exposed soil and pasture, and urban soil with buildings and pavement. Accumulated deforestation will be measured as the inverse of native forest cover over time and can range from 0% (completely preserved) to 100% (completely degraded). A generalized linear Poisson regression model will be used to test the hypothesis of an association between deforestation time and the occurrence of natural infection in mosquitoes. This same model will be used to estimate the risk of transmission as a function of accumulated deforestation.EXPECTED RESULTS: From the data collected in this research, we intend to contribute to the promotion and creation of public policies for planning and controlling malaria in Brazil and conserving the Amazon rainforest.