| Literature DB >> 32429180 |
Maria Vittoria Mancini1,2, Claudia Damiani1,3, Sarah M Short4,5, Alessia Cappelli1,3, Ulisse Ulissi1, Aida Capone1, Aurelio Serrao1,3, Paolo Rossi1,3, Augusto Amici1, Cristina Kalogris1, George Dimopoulos5, Irene Ricci1,3, Guido Favia1,3.
Abstract
Mosquitoes can transmit many infectious diseases, such as malaria, dengue, Zika, yellow fever, and lymphatic filariasis. Current mosquito control strategies are failing to reduce the severity of outbreaks that still cause high human morbidity and mortality worldwide. Great expectations have been placed on genetic control methods. Among other methods, genetic modification of the bacteria colonizing different mosquito species and expressing anti-pathogen molecules may represent an innovative tool to combat mosquito-borne diseases. Nevertheless, this emerging approach, known as paratransgenesis, requires a detailed understanding of the mosquito microbiota and an accurate characterization of selected bacteria candidates. The acetic acid bacteria Asaia is a promising candidate for paratransgenic approaches. We have previously reported that Asaia symbionts play a beneficial role in the normal development of Anopheles mosquito larvae, but no study has yet investigated the role(s) of Asaia in adult mosquito biology. Here we report evidence on how treatment with a highly specific anti-Asaia monoclonal antibody impacts the survival and physiology of adult Anopheles stephensi mosquitoes. Our findings offer useful insight on the role of Asaia in several physiological systems of adult mosquitoes, where the influence differs between males and females.Entities:
Keywords: Anopheles; Asaia; symbiont
Year: 2020 PMID: 32429180 PMCID: PMC7281548 DOI: 10.3390/pathogens9050380
Source DB: PubMed Journal: Pathogens ISSN: 2076-0817
Figure 1Immunofluorescence assay (IFA) on mosquito midguts using anti-Asaia monoclonal antibody (mAb). (A,B) Bright field microscopic and immunofluorescence images (40X) of male midgut using anti-Asaia mAbs; (C) different magnification (100X) of the tissues highlighting bacteria cells with the circle; (D) the corresponding immunofluorescent staining showing red-labelled bacteria recognized by the mAb; and (E) the superimposed image for localization. Scale bar = 20 μm (A,B) and = 5 μm (C–E).
Figure 2IFA on mosquito midguts colonized with Asaia-GFP using anti-Asaia monoclonal antibody. (A) Bright-field and (B) corresponding fluorescent images showing the green signal from an Asaia strain expressing the green fluorescent protein (Asaia-GFP); (C) red-labelled bacteria recognized by anti-Asaia mAbs, and (D) the co-localization of the signals on the merged image. Microscopy magnification is 100X and scale bar = 5 μm for all panels.
Figure 3Longevity of An. stephensi male and female mosquitoes treated with anti-Asaia antibody. (A,B) Graphs show the survival rate of male and female mosquitoes treated with anti-Asaia antibody (blue), Herc antibody (green), and PBS (red). (C) Survival probability of male and female mosquitoes treated with anti-Asaia antibody. (D) Survival probability of male mosquitoes treated with anti-Asaia antibody vs. Herc antibody treatment. (E) Survival probability of male mosquitoes treated with anti-Asaia antibody vs. PBS treatment. Data represent the means of three independent replicates performed on different An. stephensi populations. Statistical analysis was performed using Kaplan–Meier methods in R showing high statistical significance (p < 0.0001) between anti-Asaia males and controls (D,E) and treated anti-Asaia males and females (C).
Figure 4Transcriptomic analysis investigating the response to the anti-Asaia antibody in male and female An. stephensi. Male and female An. stephensi mosquitoes were injected with the anti-Asaia or Herc antibody, and the transcriptomic response of each sex to Anti-Asaia vs. Herc antibody treatment was assessed. (A) Venn diagram indicating the number of genes up- or down-regulated in males only, females only, or both males and females in response to anti-Asaia treatment. (B,C) Molecular function Gene Ontology (GO) distribution of transcripts affected by anti-Asaia treatment in a male- or female-specific manner. GO assignment for differentially regulated transcripts and chart generation was performed in Blast2GO. GO assignments are “multi-level,” meaning all terminal GO terms (i.e., terms at terminal nodes in the directed acyclic graph) for each dataset are included, regardless of GO level. Numbers in parentheses indicate the number of sequences assigned to each GO term; note that individual sequences can belong to more than one GO category.