Comparative assessment of the bacterial communities associated with Anopheles darlingi immature stages and their breeding sites in the Brazilian Amazon.
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Mosquera KD, Nilsson LKJ, de Oliveira MR, Rocha EM, Marinotti O, Håkansson S, Tadei WP, de Souza AQL, Terenius O
Parasit Vectors 16 (1) 156 [2023-05-01; online 2023-05-01]
The neotropical anopheline mosquito Anopheles darlingi is a major malaria vector in the Americas. Studies on mosquito-associated microbiota have shown that symbiotic bacteria play a major role in host biology. Mosquitoes acquire and transmit microorganisms over their life cycle. Specifically, the microbiota of immature forms is largely acquired from their aquatic environment. Therefore, our study aimed to describe the microbial communities associated with An. darlingi immature forms and their breeding sites in the Coari municipality, Brazilian Amazon. Larvae, pupae, and breeding water were collected in two different geographical locations. Samples were submitted for DNA extraction and high-throughput 16S rRNA gene sequencing was conducted. Microbial ecology analyses were performed to explore and compare the bacterial profiles of An. darlingi and their aquatic habitats. We found lower richness and diversity in An. darlingi microbiota than in water samples, which suggests that larvae are colonized by a subset of the bacterial community present in their breeding sites. Moreover, the bacterial community composition of the immature mosquitoes and their breeding water differed according to their collection sites, i.e., the microbiota associated with An. darlingi reflected that in the aquatic habitats where they developed. The three most abundant bacterial classes across the An. darlingi samples were Betaproteobacteria, Clostridia, and Gammaproteobacteria, while across the water samples they were Gammaproteobacteria, Bacilli, and Alphaproteobacteria. Our findings reinforce the current evidence that the environment strongly shapes the composition and diversity of mosquito microbiota. A better understanding of mosquito-microbe interactions will contribute to identifying microbial candidates impacting host fitness and disease transmission.
Bioinformatics Support for Computational Resources [Service]
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 37127597
DOI 10.1186/s13071-023-05749-6
Crossref 10.1186/s13071-023-05749-6
pmc: PMC10150499
pii: 10.1186/s13071-023-05749-6