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. 2012;6(3):e1561.
doi: 10.1371/journal.pntd.0001561. Epub 2012 Mar 6.

Reciprocal tripartite interactions between the Aedes aegypti midgut microbiota, innate immune system and dengue virus influences vector competence

Jose Luis Ramirez  1 , Jayme Souza-Neto, Rolando Torres Cosme, Jose Rovira, Alma Ortiz, Juan M Pascale, George Dimopoulos
Affiliations

Reciprocal tripartite interactions between the Aedes aegypti midgut microbiota, innate immune system and dengue virus influences vector competence

Jose Luis Ramirez et al. PLoS Negl Trop Dis. 2012.

Abstract

Dengue virus is one of the most important arboviral pathogens and the causative agent of dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. It is transmitted between humans by the mosquitoes Aedes aegypti and Aedes albopictus, and at least 2.5 billion people are at daily risk of infection. During their lifecycle, mosquitoes are exposed to a variety of microbes, some of which are needed for their successful development into adulthood. However, recent studies have suggested that the adult mosquito's midgut microflora is critical in influencing the transmission of human pathogens. In this study we assessed the reciprocal interactions between the mosquito's midgut microbiota and dengue virus infection that are, to a large extent, mediated by the mosquito's innate immune system. We observed a marked decrease in susceptibility to dengue virus infection when mosquitoes harbored certain field-derived bacterial isolates in their midgut. Transcript abundance analysis of selected antimicrobial peptide genes suggested that the mosquito's microbiota elicits a basal immune activity that appears to act against dengue virus infection. Conversely, the elicitation of the mosquito immune response by dengue virus infection itself influences the microbial load of the mosquito midgut. In sum, we show that the mosquito's microbiota influences dengue virus infection of the mosquito, which in turn activates its antibacterial responses.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Phylogenetic tree of the field and laboratory-reared Ae. aegypti cultivable midgut microbiota.
Red dots: Gram-negative, blue dots: Gram-positive. Phylogenetic tree constructed from the alignment of complete 16s rRNA sequences using the Weighbor weighted neighbor-joining algorithm from the Ribosomal Database Project, with Fusobacterium simiae as an out-group. The phylogenetic tree was generated using MEGA (v5).
Figure 2
Figure 2. Characteristics of cultivable bacteria from the midgut of field-collected mosquitoes.
(A). Proportions of bacterial phylogenetic classes in the mosquito midgut. (B). Bacterial load and (C) Bacterial prevalence in the mosquito midgut at 3 days post-bacterial acquisition via sugar meal. This coincides with the time when mosquitoes were exposed to an infectious blood meal.
Figure 3
Figure 3. Bacterial influence of dengue virus infection in the mosquito midgut.
Dengue virus (DENV-2) loads in mosquito midguts after the introduction of a single-bacterium isolate (through blood meal (A) and sugar meal (B) into the mosquito midgut, as compared with control mosquitoes (PBS). Data were analyzed using a one-way ANOVA, followed by Dunnett's post-test; *, p<0.05; **, p<0.001.
Figure 4
Figure 4. Antimicrobial peptide gene transcript abundance upon midgut exposure to selected bacterial isolates.
Fold change in the transcript abundance of selected antimicrobial peptide genes in the midgut (A) and fat body (B) of mosquitoes 2 days after the introduction, via a sugar meal, of either Pantoea sp. Pasp_P, Proteus sp. Prsp_P, or Paenibacillus sp. Pnsp_P. Data was analyzed by one-way ANOVA with Dunnett's post-test; *, p<0.05.
Figure 5
Figure 5. Dengue virus infection modultaes the mosquito midgut microbiota.
(A) Total bacterial 16s RNA levels in the midguts of dengue virus-infected mosquitoes relative to those of uninfected mosquitoes. Bacterial loads were assessed by qPCR from pools of 10 midguts per replicate, and at least 4 independent biological replicates were included. Data were analyzed by one-way ANOVA with Dunnett's post-test; *, p<0.05. (B) Antimicrobial peptide gene transcript abundance in the midgut of dengue virus-infected mosquitoes relative to uninfected mosquitoes at 7 days and 10 days post-infection. Data were analyzed by Mann-Whitney U-test; *, p<0.05.
Figure 6
Figure 6. Effect of antimicrobial peptide gene silencing on themidgut microbiota bacterial species composition.
Bacterial composition in the midguts of lysozyme C, cecropin and GFP silenced mosquitoes at 3 days post-dsRNA injection. Two main bacterial types were observed in each group of mosquitoes. Data represent the microbial composition of 2 independent biological replicates (n = 20).
Figure 7
Figure 7. Bacterial loads in mosquito midguts following antimicrobial peptide gene silencing.
Bacterial load was assessed by a (A) culture-independent method and (B) culture-dependent method. Data were analyzed by one-way ANOVA with Dunnett's post-test; *, p<0.05.
Figure 8
Figure 8. Dengue virus titers following antimicrobial peptide gene silencing.
Dengue viral loads were assessed from (A) septic and (B) aseptic (antibiotic-treated) mosquito midguts. Data were analyzed by one-way ANOVA with Dunnett's post-test; *, p<0.05.
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