Biology subjects

Tripet, F.

Publications and source records attributed to Tripet, F..

5 recordsLinked to original sources

bioRxiv2025

A target product profile for a rapid diagnostic test to monitor mosquito gene drive presence and frequency

Malaria remains a major global health challenge, with over 263 million cases and nearly 600,000 deaths reported in 2023, the majority in sub-Saharan Africa. While conventional interventions such as insecticide-treated nets, indoor residual spraying and antimalarial drugs have reduced transmission, progress has stalled due to the limitations of these interventions and the emergence of resistance. Gene drive-modified mosquitoes represent a promising, potentially transformative vector control strategy, capable of spreading malaria-refractory traits or suppressing mosquito populations. Successful field deployment will depend upon monitoring systems to track the presence and frequency of gene drive constructs as they spread and persist. Current molecular surveillance techniques, though effective, are resource-intensive and reliant on laboratory infrastructure and technical competencies. Here, we make the case for a near-universal and low-cost rapid diagnostic test (RDT) designed to detect gene drive mosquitoes in the field, to complement existing surveillance infrastructure. Two use cases are outlined: i) to detect the presence of the drive construct in a new population, and ii) to provide an estimate of drive frequency prior to more accurate laboratory-based measurements. We provide a target product profile for the RDT outlining minimally essential and ideal characteristics, including test procedures, sensitivity, specificity, usability by a range of stakeholders in field settings, and compatibility with pooled testing of mosquito samples. An RDT for gene drive construct detection would support community access and participation in monitoring, enhance regulatory oversight, and promote transparency in field trials, thereby facilitating responsible deployment of gene drive-based malaria interventions.

genetics↗

bioRxiv2025

Microsatellite Analysis of Genetic Differentiation Among Populations of the Malaria Vector, Anopheles funestus, across Mainland Tanzania Reveals Contrasted Patterns of Geographic Isolation and Gene Flow

BackgroundDespite Anopheles funestus s.s. being a highly competent and widespread malaria vector in Africa, its population structure remains largely understudied in many countries, including Tanzania. Herein, we examine the genetic diversity, geographic isolation, and gene flow of An. funestus populations across 10 administrative regions in mainland Tanzania. MethodsWe employed 12 previously used microsatellite DNA markers to describe genetic diversity, isolation by distance, and gene flow patterns among 10 An. funestus s.s. populations (n = 654) and one An. parensis population (n = 28), used as an outgroup, sampled across 10 regions in mainland Tanzania. ResultsOverall, allelic richness (Na) and genetic diversity (HS) did not differ significantly among populations. Although some loci and populations showed significant departures from Hardy-Weinberg equilibrium, the patterns were not indicative of sub-structuring within locations. Pairwise genetic divergence (FST) values indicated clear separation between An. parensis and An. funestus s.s., with values exceeding 0.2, consistent with species-level differentiation. Among An. funestus s.s. populations, the highest divergence was observed between southeastern coastal populations (Mtwara, Ruvuma, Lindi) and inland populations, with FST values up to 0.288. There was no evidence of isolation by distance. Instead, patterns of genetic divergence suggested connectivity across the Rift Valley and heterogeneity among southeastern populations. Neighbour-joining analysis and Bayesian genotype clustering identified three distinct population groups: (i) An. parensis (Dodoma), (ii) a genetically distinct An. funestus s.s. population from Mtwara, and (iii) a more homogeneous cluster comprising the remaining An. funestus s.s. populations. Notably, the Mtwara population appeared highly differentiated, with divergence approaching that between An. Funestus s.s. and An. parensis, supporting its distinctiveness but not undermining the role of An. parensis as an outgroup. ConclusionExcept for the Mtwara population, whose status will need to be clarified through whole genome sequencing, moderate genetic divergence was found among An. funestus s.s. populations across Tanzania, despite geographical separation and the Rift Valley. The observed genetic structure suggests that anthropogenic gene flow may play a key role in shaping population divergence. Future studies should aim to delineate the effects of local adaptation from recent gene flow to further explore these dynamics.

genetics↗

bioRxiv2025

Characterization of a new laboratory colony of Anopheles funestus mosquitoes established in Ifakara, Tanzania

BackgroundAnopheles funestus, a major vector of malaria in Africa, has proven difficult to colonize in laboratory settings, impeding research on its biology and control. After several attempts, our team recently succeeded in colonizing a strain of An. funestus from Tanzania (FUTAZ). The objective of this study was to analyse the key fitness and genotypic characteristics of these mosquitoes during multiple filial generations of laboratory adaptation and compare them to wild An. funestus from Tanzania and a pre-existing colony of An. funestus from Mozambique (FUMOZ). MethodsMeasures of mating success (percentage of female mosquitoes inseminated), body size (wing length), fecundity (number of eggs laid per female), and insecticide susceptibility (percentage of 24-hour mortality after exposure to insecticides) were compared between the newly established colonies of Tanzanian An. funestus (FUTAZ colonies), the long-established FUMOZ colonies, and a colony of Anopheles arabiensis maintained in the same laboratory. The maternal lineages of the An. funestus mosquitoes were investigated through a hydrolysis probe analysis of their mitochondrial DNA to identify distinct clades, I and II. Additionally, other intragenomic variations were examined through a PCR analysis of restriction fragment length polymorphisms (RFLP) on the third domain of 28S ribosomal DNA. These molecular markers were used to compare the FUTAZ colonies, FUMOZ colonies in Tanzania and South Africa, and the wild-collected An. funestus from Tanzania. ResultThe mating success and body size of FUTAZ females declined significantly from filial generations F1 to F6 relative to the founder population (F0), but then increased from F7 onwards eventually matching FUMOZ by F9. Fecundity was similar across all colonies tested. However, it took significantly longer for 50% of the females in the FUTAZ and FUMOZ colonies (over 10 days) to mate compared to females in the An. arabiensis colony (approximately 5 days). Insecticide resistance appeared to be lost during colonization, but this varied with insecticide classes. Majority of mosquitoes in the FUTAZ colony, as well as the wild-caught Tanzanian An. funestus belonged to Clade I (80.4-89.4%) and RFLP type "Y" (90.5-91.4%), while the FUMOZ colonies were mostly Clade II (65.5-88.5%) and RFLP type "MW" (90.5-91.5%). ConclusionThis study suggests that the mating success and body size of An. funestus decreases significantly during the early stages of colonization, then increase as the mosquitoes adapt to laboratory conditions. It is therefore crucial to have a large enough founder population to persist through these early generations in order to achieve stable colonization of An. funestus. The Clade and RFLP genotyping demonstrated the genetic similarities between the FUTAZ mosquitoes and wild-caught Tanzanian An. funestus, but also showed that the new colony can be distinguished from the FUMOZ colony.

ecology↗

bioRxiv2025

Distinct Genetic Populations and Resistance Backgrounds of the Malaria Vector Anopheles funestus in Tanzania

Population genetic analysis of mosquitoes is becoming increasingly important for understanding the distribution of insecticide resistance alleles, devising sustainable insecticide-based vector control approaches, and how malaria vector populations are structured in space. Anopheles funestus is the dominant malaria vector in Tanzania and most parts of East and Southern Africa. To better understand its population genomic structure in Tanzania, we sequenced the genomes of 334 individual An. funestus mosquitoes from 11 administrative regions. We found two genetically differentiated populations; one inland and at high altitude (found in Katavi, Kagera, Kigoma, and Mwanza) and a second coastal, at low altitude (found in Pwani, Morogoro, Tanga, Ruvuma, Mtwara, Dodoma, and Lindi), with differences in genetic diversity and inbreeding. We found asynchronous selective sweeps, associated with insecticide resistance phenotypes, at the Cyp9k1 gene, and Cyp6p gene cluster, with distinct copy number-variant profiles between the coastal and inland populations. These results suggest that inland and coastal An. funestus populations have divergent histories, with the arid, central region of Tanzania, which also contains the Rift Valley being a possible barrier to gene flow. Such population disconnectedness should be considered for insecticide deployment, resistance management, and the rollout of novel genetic- based vector control approaches. These findings provide the most detailed study of Tanzanian An. funestus population structure and resistance genetics to date. Future research should examine the epidemiological relevance of this discontinuity in gene flow and whether these populations have different malaria transmission abilities.

genetics↗

bioRxiv2022

High resolution species assignment of Anopheles mosquitoes using k-mer distances on targeted sequences

The ANOSPP amplicon panel is a genus-wide targeted sequencing panel to facilitate large-scale monitoring of Anopheles species diversity. Combining information from the 62 nuclear amplicons present in the ANOSPP panel allows for a more nuanced species assignment than single gene (e.g. COI) barcoding, which is desirable in the light of permeable species boundaries. Here, we present NNoVAE, a method using Nearest Neighbours (NN) and Variational Autoencoders (VAE), which we apply to k-mers resulting from the ANOSPP amplicon sequences in order to hierarchically assign species identity. The NN step assigns a sample to a species-group by comparing the k-mers arising from each haplotypes amplicon sequence to a reference database. The VAE step is required to distinguish between closely related species, and also has sufficient resolution to reveal population structure within species. In tests on independent samples with over 80% amplicon coverage, NNoVAE correctly classifies to species level 98% of samples within the An. gambiae complex and 89% of samples outside the complex. We apply NNoVAE to over two thousand new samples from Burkina Faso and Gabon, identifying unexpected species in Gabon. NNoVAE presents an approach that may be of value to other targeted sequencing panels, and is a method that will be used to survey Anopheles species diversity and Plasmodium transmission patterns through space and time on a large scale, with plans to analyse half a million mosquitoes in the next five years.

evolutionary biology↗