Biological Control of Mosquito-Borne Diseases: The Potential of Wolbachia-Based Interventions in an IVM Framework

Abstract

People living in the tropical and subtropical regions of the world face an enormous health burden due to mosquito-borne diseases such as malaria, dengue fever, and filariasis. Historically and today, targeting mosquito vectors with, primarily, insecticide-based control strategies have been a key control strategy against major mosquito-borne diseases. However, the success to date of such approaches is under threat from multiple insecticide resistance mechanisms while vector control (VC) options are still limited. The situation therefore requires the development of innovative control measures against major mosquito-borne diseases. Transinfecting mosquitos with symbiotic bacteria that can compete with targeted pathogens or manipulate host biology to reduce their vectorial capacity are a promising and innovative biological control approach. In this review, we discuss the current state of knowledge about the association between mosquitoes and Wolbachia, emphasizing the limitations of different mosquito control strategies and the use of mosquitoes' commensal microbiota as innovative approaches to control mosquito-borne diseases.

Figure 1

Electron microscopy of Wolbachia. (a) Wolbachia cocci (Scale bar: 1 μm). (b) Zoom of two Wolbachia cells (Scale bar: 500 nm). (c) Zoom of a single Wolbachia cell (Scale bar: 100 nm). (by El Hadji Amadou Niang).

Figure 2

Molecular Phylogenetic analysis of Anaplasmataceae by Maximum Likelihood method. The evolutionary history was inferred using the Maximum Likelihood method based on the Tamura-Nei model [30]. The tree with the highest log likelihood (-4338.5700) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying the Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with the higher log likelihood value. The analysis involved five nucleotide sequences. All positions containing gaps and missing data were eliminated. There was a total of 1,411 positions in the final dataset. Evolutionary analyses were conducted in MEGA7 [31].

Figure 3

Different phenotypes of Wolbachia's host reproductive manipulation.

Figure 4

Wolbachia in arthropods. (Modified from Russell & Steiner 2012, Myrmecological News Journal [57]). (a) Graph illustrating Wolbachia-infected (Blue shaded portion) and Wolbachia-uninfected (white portion) proportions by host taxon. (b) Histogram highlighting the frequencies Wolbachia infection of some dipteral families. The asterisk (∗) indicates the recent discovery of native Wolbachia within the Anopheles genus.

Figure 5

Classification of mosquitoes (DIPTERA: CULICIDAE) (by El Hadji Amadou Niang).