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Mosquito microevolution drives Plasmodium falciparum dynamics

Abstract

Malaria, a major cause of child mortality in Africa, is engendered by Plasmodium parasites that are transmitted by anopheline mosquitoes. Fitness of Plasmodium parasites is closely linked to the ecology and evolution of its anopheline vector. However, whether the genetic structure of vector populations impacts malaria transmission remains unknown. Here, we describe a partitioning of the African malaria vectors into generalists and specialists that evolve along ecological boundaries. We next identify the contribution of mosquito species to Plasmodium abundance using Granger causality tests for time-series data collected over two rainy seasons in Mali. We find that mosquito microevolution, defined by changes in the genetic structure of a population over short ecological timescales, drives Plasmodium dynamics in nature, whereas vector abundance, infection prevalence, temperature and rain have low predictive values. Our study demonstrates the power of time-series approaches in vector biology and highlights the importance of focusing local vector control strategies on mosquito species that drive malaria dynamics.

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Fig. 1: TEP1 diversity and classification.
Fig. 2: TEP1 population genetics.
Fig. 3: Genetic and ecotype structures of Anopheles gambiae s.l.
Fig. 4: Granger causality analysis.

Data availability

The full-length TEP1 and TEP1–TED sequences are available at the NCBI GenBank under accession numbers MF098568 to MF098592 and MF035727 to MF035924, respectively. The data that support the findings of this study are available from the corresponding author upon request.

References

  1. Coluzzi, M., Sabatini, A., Petrarca, V. & Di Deco, M. A. Chromosomal differentiation and adaptation to human environments in the Anopheles gambiae complex. Trans. R. Soc. Trop. Med. Hyg. 73, 483–497 (1979).

    CAS  Article  Google Scholar 

  2. Coluzzi, M., Sabatini, A., Della Torre, A., Di Deco, M. A. & Petrarca, V. A polytene chromosome analysis of the Anopheles gambiae species complex. Science 298, 1415–1418 (2002).

    CAS  Article  Google Scholar 

  3. Pinto, J. et al. Geographic population structure of the African malaria vector Anopheles gambiae suggests a role for the forest–savannah biome transition as a barrier to gene flow. Evol. Appl. 6, 910–924 (2013).

    CAS  Article  Google Scholar 

  4. Simard, F. et al. Ecological niche partitioning between Anopheles gambiae molecular forms in Cameroon. BMC Ecol. 9, 17 (2009).

    Article  Google Scholar 

  5. Gillies, M. T. & Shute, G. T. Environmental influences and the maxillary index in Anopheles gambiae. Nature 173, 409–410 (1954).

    CAS  Article  Google Scholar 

  6. Dao, A. et al. Signatures of aestivation and migration in Sahelian malaria mosquito populations. Nature 516, 387–390 (2014).

    CAS  Article  Google Scholar 

  7. Fryxell, R. T. T. et al. Differential Plasmodium falciparum infection of Anopheles gambiae s.s. molecular and chromosomal forms in Mali. Malaria J. 11, 133 (2012).

    Article  Google Scholar 

  8. Boissière, A. et al. Application of a qPCR Assay in the investigation of susceptibility to malaria infection of the M and S molecular forms of An. gambiae s.s. in Cameroon. PLoS ONE 8, e54820 (2013).

    Article  Google Scholar 

  9. Eldering, M. et al. Variation in susceptibility of African Plasmodium falciparum malaria parasites to TEP1 mediated killing in Anopheles gambiae mosquitoes. Sci. Rep. 10, 20440 (2016).

    Article  Google Scholar 

  10. White, B. J. et al. Adaptive divergence between incipient species of Anopheles gambiae increases resistance to Plasmodium. Proc. Natl Acad. Sci. USA 108, 244–249 (2011).

    CAS  Article  Google Scholar 

  11. Gnémé, A. et al. Equivalent susceptibility of Anopheles gambiae M and S molecular forms and Anopheles arabiensis to Plasmodium falciparum infection in Burkina Faso. Malaria J. 14, 204 (2013).

    Article  Google Scholar 

  12. Granger, C. W. J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424 (1969).

    Article  Google Scholar 

  13. Fanello, C., Santolamazza, F. & Della Torre, A. Simultaneous identification of species and molecular forms of the Anopheles gambiae complex by PCR–RFLP. Med. Vet. Entomol. 16, 461–464 (2002).

    CAS  Article  Google Scholar 

  14. Wondji, C., Simard, F. & Fontenille, D. Evidence for genetic differentiation between the molecular forms M and S within the Forest chromosomal form of Anopheles gambiae in an area of sympatry. Insect Mol. Biol. 11, 11–19 (2002).

    CAS  Article  Google Scholar 

  15. Della Torre, A. et al. Speciation within Anopheles gambiae—the glass is half full. Science 298, 115–117 (2002).

    Article  Google Scholar 

  16. Obbard, D. J. et al. The evolution of TEP1, an exceptionally polymorphic immunity gene in Anopheles gambiae. BMC Evol. Biol. 7, 274 (2008).

    Article  Google Scholar 

  17. Levashina, E. A. et al. Conserved role of a complement-like protein in phagocytosis revealed by dsRNA knockout in cultured cells of the mosquito Anopheles gambiae. Cell 104, 709–718 (2001).

    CAS  Article  Google Scholar 

  18. Yassine, H.,Kamareddine, L. & Osta, M. A. The mosquito melanization response is implicated in defense against the entomopathogenic fungus Beauveria bassiana. PLoS Pathog. 8, e1003029 (2012).

    CAS  Article  Google Scholar 

  19. Blandin, S. et al. Complement-like protein TEP1 is a determinant of vectorial capacity in the malaria vector Anopheles gambiae. Cell 116, 661–670 (2004).

    CAS  Article  Google Scholar 

  20. Blandin, S. A. et al. Dissecting the genetic basis of resistance to malaria parasites in Anopheles gambiae. Science 326, 147–150 (2009).

    CAS  Article  Google Scholar 

  21. Baxter, R. H. G. et al. Structural basis for conserved complement factor-like function in the antimalarial protein TEP1. Proc. Natl Acad. Sci. USA 104, 11615–11620 (2007).

    CAS  Article  Google Scholar 

  22. Le, B. V., Williams, M. & Logarajah, S. & Baxter, R. H. Molecular basis for genetic resistance of Anopheles gambiae to Plasmodium: Structural analysis of TEP1 susceptible and resistant alleles. PLoS Pathog. 8, e1002958 (2012).

    CAS  Article  Google Scholar 

  23. Mwangangi, J. M. et al. Shifts in malaria vector species composition and transmission dynamics along the Kenyan coast over the past 20 years. Malaria J. 8, 13 (2013).

    Article  Google Scholar 

  24. Sinka, M. E. et al. The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis. Parasit. Vectors 4, 89 (2011).

    Article  Google Scholar 

  25. Diabaté, A. et al. Larval development of the molecular forms of Anopheles gambiae (Diptera: Culicidae) in different habitats: a transplantation experiment. J. Med. Entomol. 42, 548–553 (2005).

    Article  Google Scholar 

  26. Diabaté, A. et al. Evidence for divergent selection between the molecular forms of Anopheles gambiae: Role of predation. BMC Evol. Biol. 8, 5 (2008).

    Article  Google Scholar 

  27. Burton, O. J., Phillips, B. L. & Travis, J. M. J. Trade-offs and the evolution of life-histories during range expansion. Ecol. Lett. 13, 1210–1220 (2010).

    Article  Google Scholar 

  28. Pompon, J., & Levashina, E. A. A new role of the mosquito complement-like cascade in male fertility in Anopheles gambiae. PLoS Biol. 13, 1002255 (2015).

    Article  Google Scholar 

  29. Mancini, E. et al. Adaptive potential of hybridization among malaria vectors: Introgression at the immune locus TEP1 between Anopheles coluzzii and A. gambiae in ‘Far-West’ Africa. PLoS ONE 10, 0127804 (2015).

    Google Scholar 

  30. Librado, P. & Rozas, J. DnaSPv5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452 (2009).

    CAS  Article  Google Scholar 

  31. Tamura, K., Dudley, J., Nei, M. & Kumar, S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599 (2007).

    CAS  Article  Google Scholar 

  32. Posada, D. jModelTest: Phylogenetic model averaging. Mol. Biol. Evol. 25, 1253–1256 (2008).

    CAS  Article  Google Scholar 

  33. Posada, D. Selection of models of DNA evolution with jModelTest. Methods Mol. Biol. 537, 93–112 (2009).

    CAS  Article  Google Scholar 

  34. Team, R. D. C. The genetics package. Bioinformatics 3, 9–13 (2008).

    Google Scholar 

  35. Nei, M. F‐statistics and analysis of gene diversity in subdivided populations. Ann. Hum. Genet. 41, 225–233 (1977).

    CAS  Article  Google Scholar 

  36. R Development Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2016).

  37. Pfaff, B. VAR, SVAR and SVEC models: implementation within R package vars. J. Stat. Softw. 27, i04 (2008).

    Article  Google Scholar 

  38. Toda, H. Y. & Yamamoto, T. Statistical inference in vector autoregressions with possibly integrated processes. J. Econom. 66, 225–250 (1995).

    Article  Google Scholar 

  39. Metzger, M. J. et al. A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring. Glob. Ecol. Biogeogr. 22, 630–638 (2013).

    Article  Google Scholar 

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Acknowledgements

We thank A. Telschow, F. Grziwotz and S. F. Traore for helpful suggestions; L. Spohr, S. Koppitz, D. Coulibaly, M. Coulibaly, C. Omogo, J. Shikaya, L. Abate, E. Onana, J. P. Agbor, J. Mwaura and A. Gildenhard for technical support; and M. Doumbia, B. Doumbia and C. Okech for their help with sample collections. This research was supported by funds from EC FP7 under grant agreements N°223601 (MALVECBLOK) and N°242095 (EVIMalar). E.K.R. was a DAAD fellow.

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Authors and Affiliations

Authors

Contributions

F.C., D.M., M.D., I.M., D.S. and E.A.L. conceived and designed the study. D.S., M.D., A.Diabaté, R.K.D., P.A.-A., D.M. and I.M. designed and managed sample collections, genotyping and sequencing. E.K.R., A.B., I.M. and E.A.L. contributed molecular tools. J.T., J.P., P.A.-A., M.M., A.B., S.E.N., P.B.S., P.M., A.T., D.S., M.D., M.K.R., E.K.R., C.V.Y. and H.K. conducted sample collections, processing and genotyping. P.B., A.B., P.M., P.B.S. and E.K.R. performed sequencing. E.K.R., A.B., P.B., M.G., I.M., F.C. and E.A.L. analysed the data. M.G. and E.A.L. conceived and designed the time series. M.G., Y.R., M.D. and D.S. designed and managed time-series collections. D.C., R.M., H.K., M.G., D.S. and A.Diarra performed time-series collections and genotyping. E.A.L. and M.G. analysed time-series data. M.G. designed and carried out population genetic analyses and time-series modelling. P.C.-B. contributed to time-series analyses. M.G., E.K.R., P.C.B. and E.A.L. wrote the manuscript.

Corresponding author

Correspondence to Elena A. Levashina.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Tables 1–3, Supplementary Tables 6–9, Supplementary Figures 1–6 and Supplementary References.

Reporting Summary

Supplementary Table 4

Sampling sites across Africa.

Supplementary Table 5

Vector autoregression models.

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Gildenhard, M., Rono, E.K., Diarra, A. et al. Mosquito microevolution drives Plasmodium falciparum dynamics. Nat Microbiol 4, 941–947 (2019). https://doi.org/10.1038/s41564-019-0414-9

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