Abstract:
Much of sub-Saharan Africa suffers from high malaria infection rates in spite of several vector-control strategies set up to control Plasmodium transmission. Currently, these approaches are only partially effective, compromised by the evolution of insecticide resistant mosquitoes and adaptive changes in mosquito feeding patterns. Therefore, there has been an expanding search for novel strategies to control both the vector densities and parasite transmission. Such techniques include the concept of using mosquito symbionts for transmission blocking. This study focused on a novel symbiotic Microsporidian species (Microsporidia MB) isolated from Anopheles gambiae s.l. mosquitoes collected in parts of Mwea and Mbita, Kenya. It aimed at understanding the molecular biology of the strain, its phylogenetic classification and tissue distribution. The amount of Plasmodium falciparum sporozoites was established in each sample using Enzyme-linked Immunosorbent Assay (ELISA). Additionally, a highly sensitive and specific probe-based quantitative PCR assay was designed to quantify Microsporidia MB within each sample. Phylogeny studies using the highly conserved and variable 18S small subunit rRNA gene demonstrated the classification of Microsporidia MB within the same clade as Crispospora chironomi- a Microsporidian species isolated from non-biting midges in Siberia. In field collected samples, a 5% prevalence of the microorganism was observed in both Mbita and Mwea areas. Fluorescence microscopy on infected larvae indicated that there was a cyst-like infection within the larval gut tissue. Furthermore, the correlation between the presence of the novel mosquito Microsporidia MB and the Plasmodium parasite was examined. Interestingly, a negative correlation between Plasmodium falciparum and Microsporidia MB quantity was revealed both in the field and laboratory colonized mosquitoes. These findings are promising as they point at Microsporidia MB being a plausible transmission-blocking agent against malaria in Anopheles mosquitoes.
Description:
A Thesis Submitted to the University of Nairobi, Center for Biotechnology and Bioinformatics in Partial Fulfillment for the Requirements for the Award of the Degree of Master of Science in Bioinformatics