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Birungi, K.

Publications and source records attributed to Birungi, K..

3 recordsLinked to original sources

Estimation of adult census size from close-kin dyads in the malaria mosquito Anopheles gambiae

Accurate estimates of adult mosquito abundance are central to the design and evaluation of vector control strategies, yet they are difficult to obtain from natural populations. Conventional mark-recapture methods for estimating adult mosquito census size pose logistical and other challenges. A recently developed close-kin mark-recapture (CKMR) approach is a promising alternative. However, application of CKMR has been largely confined to long-lived vertebrates. Validation on empirical data from short-lived, highly fecund insects is lacking. Here, we apply CKMR to a natural population of Anopheles gambiae, the primary African malaria mosquito, sampled from a small island in Lake Victoria, Uganda. Using a high-diversity amplicon panel of genome-wide markers, we genotyped 714 adult mosquitoes collected over a 20-day period. We classified pairs to close-kin categories by implementing probabilistic latent-kinship estimation rather than using a deterministic threshold-based framework. We observe numerous full-sibling pairs but no parent-offspring pairs, a pattern indicative of extreme variance in reproductive success owing to frequent failure of mosquito egg clutches to produce adults. To adapt the CKMR framework to mosquito life history, we explicitly modeled the mosquito life cycle including the possibility of clutch failure. By incorporating probabilities of both parent-offspring and full-sibling relationships, we estimate an adult female census size of 26,887 (95% credible interval: 6,979 - 146,011), and a clutch failure probability of 97.6% (CrI: 91.3 - 99.6%). We use these estimates to calculate the predicted variance in reproductive success and effective population size. Through individual-based simulations we confirm our estimates and the necessity of modeling reproductive variance to explain observed kinship patterns. Our results demonstrate that CKMR can be applied successfully to mosquitoes, provided that appropriate adjustments are made to account for their natural history.

ecology↗

Assessing the population genetic structure and demographic history of Anopheles gambiae and Anopheles arabiensis at island and mainland populations in Uganda: Implications for testing novel malaria vector control approaches.

Despite substantial investments in malaria control, the disease remains a major burden in sub-Saharan Africa, particularly Uganda. Novel tools such as gene drive systems are being developed to suppress malaria vector populations, but their deployment requires detailed knowledge of mosquito population genetics. We assessed the genetic structure, diversity, and demographic history of Anopheles gambiae and Anopheles arabiensis from six sites in Uganda: three islands in Lake Victoria and three mainland sites. A total of 2918 Anopheles gambiae and 173 Anopheles arabiensis were genotyped using targeted amplicon sequencing of 62 loci across coding and non-coding regions of the genome. Population structure analyses revealed clear separation between the two species but little differentiation within each species across sites. Pairwise FST values among An. gambiae populations were low (0.00054-0.028) but often significant, with mainland populations showing higher connectivity and island populations exhibiting greater isolation. Anopheles arabiensis mainland populations showed no statistically significant differentiation, suggesting panmixia. Principal Component Analysis and Bayesian clustering similarly distinguished species-level structure but no obvious substructure within sites. Mainland An. gambiae populations displayed higher nucleotide diversity than island populations, while An. arabiensis showed the lowest diversity overall. Tajimas D values were negative across sites, consistent with recent population expansions. Effective population size estimates indicated small populations at the islands (146 to 249) compared to large mainland populations (4,054 to 8,190). These findings demonstrate strong genetic differentiation between Anopheles gambiae and Anopheles arabiensis, and subtle but meaningful structure between island and mainland Anopheles gambiae populations. The reduced diversity and small effective population sizes at island sites suggest stronger genetic drift and limited gene flow, in contrast to the highly connected mainland populations. For malaria control, this contrast has direct implications. High connectivity among mainland populations may facilitate the spread of insecticide resistance alleles, while island populations, with their relative isolation and smaller sizes, may serve as suitable sites for contained field trials of gene drive strategies. This study highlights how geographic and ecological factors shape mosquito population structure and provides critical evidence for the design and monitoring of genetic-based vector control interventions.

evolutionary biology↗

Convergent epitope specificities, V gene usage and public clones elicited by primary exposure to SARS-CoV-2 variants

An important consequence of infection with a SARS-CoV-2 variant is protective humoral immunity against other variants. The basis for such cross-protection at the molecular level is incompletely understood. Here we characterized the repertoire and epitope specificity of antibodies elicited by Beta, Gamma and ancestral variant infection and assessed their cross-reactivity to these and the more recent Delta and Omicron variants. We developed a high-throughput approach to obtain immunoglobulin sequences and produce monoclonal antibodies for functional assessment from single B cells. Infection with any variant elicited similar cross-binding antibody responses exhibiting a remarkably conserved hierarchy of epitope immunodominance. Furthermore, convergent V gene usage and similar public B cell clones were elicited regardless of infecting variant. These convergent responses despite antigenic variation may represent a general immunological principle that accounts for the continued efficacy of vaccines based on a single ancestral variant.

immunology↗