Biology subjects

Beeton, N.

Publications and source records attributed to Beeton, N..

2 recordsLinked to original sources

bioRxiv2021

Spatial modelling for population replacement of mosquito vectors at continental scale

Malaria is one of the deadliest vector-borne diseases in the world. Researchers are developing new genetic and conventional vector control strategies to attempt to limit its burden. Novel control strategies require detailed safety assessment to ensure responsible and successful deployments. Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii, two closely related subspecies within the species complex Anopheles gambiae sensu lato (s.l.), are among the dominant malaria vectors in sub-Saharan Africa. These two subspecies readily hybridise and compete in the wild and are also known to have distinct niches, each with spatially and temporally varying carrying capacities driven by precipitation and land use factors. We model the spread and persistence of a population-modifying gene drive system in these subspecies across sub-Saharan Africa by simulating introductions of genetically modified mosquitoes across the African mainland and its offshore islands. We explore transmission of the gene drive between the two subspecies that arise from different hybridisation mechanisms, the effects of both local dispersal and potential wind-aided migration to the spread, and the development of resistance to the gene drive. Given the best current available knowledge on the subspecies life histories, we find that an introduced gene drive system with typical characteristics can plausibly spread from even distant offshore islands to the African mainland with the aid of wind-driven migration, with resistance taking over within a decade. Our model accounts for regional to continental scale mechanisms, and demonstrates a range of realistic dynamics including the effect of prevailing wind on spread and spatio-temporally varying carrying capacities for subspecies. As a result, it is well-placed to answer future questions relating to mosquito gene drives as important life history parameters become better understood.

synthetic biology↗

bioRxiv2021

Serological and Molecular Investigation of Foot and Mouth Disease Virus and other animal pathogens at the Interface of Akagera National Park and Surrounding Cattle Farms between 2017 and 2020

BackgroundFoot-and-Mouth Disease Virus (FMDV) is a positive-sense RNA virus of the family of the picornaviridae and responsible for the disease with the highest economic impact, the Foot-and-Mouth Disease (FMD). FMD is endemic in Rwanda but there are gaps in knowing the seroprevalence and molecular epidemiology. This study reports the FMD seroprevalence and molecular characterization of FMDV in Eastern Rwanda. Surveillance in FMDV wild reservoirs, the African buffaloes, was also carried out revealing the presence of other pathogens and commensals. ResultsThe overall seroprevalence of FMD in the study area is at 9.36% in cattle and 2.65% in goats. We detected FMDV using molecular diagnostic tools such as RT-PCR and RT-LAMP and the phylogenetic analysis of the obtained sequences revealed the presence of serotype SAT 2, lineage II. Sequencing of oropharyngeal fluids collected from African buffaloes revealed the presence of several pathogens and commensals but no FMDV was detected in buffaloes. The plethora of pathogens identified from the buffalo gut gives an idea of the health challenges faced by cattle keepers in Eastern Rwanda due to possible cross infectivity on wildlife-domestic animals interface regions. ConclusionsWe recommend further studies to focus on sampling more African buffaloes since the number sampled was statistically insignificant to conclusively exclude the presence or absence of FMDV in Eastern Rwanda buffaloes. The use of RT-PCR alongside RT-LAMP demonstrates that the latter can be adopted in endemic areas such as Rwanda to fill in the gaps in terms of molecular diagnostics. The identification of lineage II of SAT 2 in Rwanda for the first time shows that the pools as previously established are not static over time.

molecular biology↗