• 1.

    Brown JE, Evans BR, Zheng W, Obas V, Barrera-Martinez L, Egizi A, Zhao H, Caccone A, Powell JR, 2014. Human impacts have shaped historical and recent evolution in Aedes aegypti, the dengue and yellow fever mosquito. Evolution 68: 514525.

    • Search Google Scholar
    • Export Citation
  • 2.

    Marcondes CB, Contigiani M, Gleiser RM, 2017. Emergent and reemergent arboviruses in South America and the Caribbean: why so many and why now? J Med Entomol 54: 509532.

    • Search Google Scholar
    • Export Citation
  • 3.

    Otero M, Solari HG, 2010. Stochastic eco-epidemiological model of dengue disease transmission by Aedes aegypti mosquito. Math Biosci 223: 3246.

    • Search Google Scholar
    • Export Citation
  • 4.

    Pan American Health Organization, 2017. Platforma de Información en Salud de las Americas. Available at: www.paho.org/data. Accessed January 1, 2018.

  • 5.

    Kramer LD, 2016. Complexity of virus-vector interactions. Curr Opin Virol 21: 8186.

  • 6.

    Mbaika S, Lutomiah J, Chepkorir E, Mulwa F, Khayeka-Wandabwa C, Tigoi C, Oyoo-Okoth E, Mutisya J, Ng'ang'a Z, Sang R, 2016. Vector competence of Aedes aegypti in transmitting chikungunya virus: effects and implications of extrinsic incubation temperature on dissemination and infection rates. Virol J 13: 114.

    • Search Google Scholar
    • Export Citation
  • 7.

    Richards SL, Mores CN, Lord CC, Tabachnick WJ, 2007. Impact of extrinsic incubation temperature and virus exposure on vector competence of Culex pipiens quinquefasciatus Say (Diptera: Culicidae) for West Nile virus. Vector Borne Zoonotic Dis 7: 629636.

    • Search Google Scholar
    • Export Citation
  • 8.

    Kramer LD, Hardy JL, Presser SB, 1983. Effect of temperature of extrinsic incubation on the vector competence of Culex tarsalis for western equine enephalomyelitis virus. Am J Trop Med Hyg 32: 11301139.

    • Search Google Scholar
    • Export Citation
  • 9.

    Carrington LB, Seifert SN, Armijos MV, Lambrechts L, Scott TW, 2013. Reduction of Aedes aegypti vector competence for dengue virus under large temperature fluctuations. Am J Trop Med Hyg 88: 689697.

    • Search Google Scholar
    • Export Citation
  • 10.

    Lambrechts L, Paaijmans KP, Fansiri T, Carrington LB, Kramer LD, Thomas MB, Scott TW, 2011. Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti. Proc Natl Acad Sci U S A 108: 74607465.

    • Search Google Scholar
    • Export Citation
  • 11.

    Danforth ME, Reisen WK, Barker CM, 2016. The impact of cycling temperature on the transmission of West Nile virus. J Med Entomol 53: 681686.

  • 12.

    Kilpatrick AM, Meola MA, Moudy RM, Kramer LD, 2008. Temperature, viral genetics, and the transmission of West Nile virus by Culex pipiens mosquitoes. PLoS Pathog 4: e1000092.

    • Search Google Scholar
    • Export Citation
  • 13.

    Ciota AT, Matacchiero AC, Kilpatrick AM, Kramer LD, 2014. The effect of temperature on life history traits of Culex mosquitoes. J Med Entomol 51: 5562.

    • Search Google Scholar
    • Export Citation
  • 14.

    Christofferson RC, Mores CN, 2016. Potential for extrinsic incubation temperature to alter interplay between transmission potential and mortality of dengue-infected Aedes aegypti. Environ Health Insights 10: 5.

    • Search Google Scholar
    • Export Citation
  • 15.

    Kilpatrick AM, Fonseca DM, Ebel GD, Reddy MR, Kramer LD, 2010. Spatial and temporal variation in vector competence of Culex pipiens and Cx. restuans mosquitoes for West Nile virus. Am J Trop Med Hyg 83: 607613.

    • Search Google Scholar
    • Export Citation
  • 16.

    Pongsiri A, Ponlawat A, Thaisomboonsuk B, Jarman RG, Scott TW, Lambrechts L, 2014. Differential susceptibility of two field Aedes aegypti populations to a low infectious dose of dengue virus. PLoS One 9: e92971.

    • Search Google Scholar
    • Export Citation
  • 17.

    Behura SK, Gomez-Machorro C, deBruyn B, Lovin DD, Harker BW, Romero-Severson J, Mori A, Severson DW, 2014. Influence of mosquito genotype on transcriptional response to dengue virus infection. Funct Integr Genomics 14: 581589.

    • Search Google Scholar
    • Export Citation
  • 18.

    Lambrechts L, Quillery E, Noël V, Richardson JH, Jarman RG, Scott TW, Chevillon C, 2013. Specificity of resistance to dengue virus isolates is associated with genotypes of the mosquito antiviral gene Dicer-2. Proc Biol Sci 280: 20122437.

    • Search Google Scholar
    • Export Citation
  • 19.

    Fansiri T, Fontaine A, Diancourt L, Caro V, Thaisomboonsuk B, Richardson JH, Jarman RG, Ponlawat A, Lambrechts L, 2013. Genetic mapping of specific interactions between Aedes aegypti mosquitoes and dengue viruses. PLoS Genet 9: e1003621.

    • Search Google Scholar
    • Export Citation
  • 20.

    Zouache K, Fontaine A, Vega-Rua A, Mousson L, Thiberge JM, Lourenco-De-Oliveira R, Caro V, Lambrechts L, Failloux AB, 2014. Three-way interactions between mosquito population, viral strain and temperature underlying chikungunya virus transmission potential. Proc Biol Sci 281: pii: 20141078.

    • Search Google Scholar
    • Export Citation
  • 21.

    Gloria-Soria A, Armstrong PM, Powell JR, Turner PE, 2017. Infection rate of Aedes aegypti mosquitoes with dengue virus depends on the interaction between temperature and mosquito genotype. Proc Biol Sci 284: pii: 20171506.

    • Search Google Scholar
    • Export Citation
  • 22.

    Kauffman E, Payne A, Franke MA, Schmid MA, Harris E, Kramer LD, 2017. Rearing of Culex spp. and Aedes spp. mosquitoes. Bio Protoc 7: pii: e2542.

  • 23.

    OhAinle M et al. 2011. Dynamics of dengue disease severity determined by the interplay between viral genetics and serotype-specific immunity. Sci Transl Med 3: 114ra128.

    • Search Google Scholar
    • Export Citation
  • 24.

    Lanciotti RS, Kosoy OL, Laven JJ, Panella AJ, Velez JO, Lambert AJ, Campbell GL, 2007. Chikungunya virus in US travelers returning from India, 2006. Emerg Infect Dis 13: 764767.

    • Search Google Scholar
    • Export Citation
  • 25.

    Payne AF, Binduga-Gajewska I, Kauffman EB, Kramer LD, 2006. Quantitation of flaviviruses by fluorescent focus assay. J Virol Methods 134: 183187.

    • Search Google Scholar
    • Export Citation
  • 26.

    Muttis EBA, Chuchuy A, Mangudo C, Ciota AT, Kramer LD, 2018. Factors related to Aedes aegypti (Diptera: Culicidae) populations and temperature determine differences on life-history traits with regional implications in disease transmission. J Med Ent, doi: 10.1093/jme/tjy057.

    • Search Google Scholar
    • Export Citation
  • 27.

    Evans BR, Gloria-Soria A, Hou L, McBride C, Bonizzoni M, Zhao H, Powell JR, 2015. A multipurpose, high-throughput single-nucleotide polymorphism chip for the dengue and yellow fever mosquito, Aedes aegypti. G3 (Bethesda) 5: 711718.

    • Search Google Scholar
    • Export Citation
  • 28.

    Raj A, Stephens M, Pritchard JK, 2014. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197: 573589.

    • Search Google Scholar
    • Export Citation
  • 29.

    Pritchard JK, Stephens M, Donnelly P, 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945959.

  • 30.

    Earl D, vonHoldt B, 2012. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4: 359361.

    • Search Google Scholar
    • Export Citation
  • 31.

    Evanno G, Regnaut S, Goudet J, 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14: 26112620.

    • Search Google Scholar
    • Export Citation
  • 32.

    R Core Team, 2017. R: A Language and Environment for Statistical Computing. Vienna, Australia: R Foundation for Statistical Computing. Available at: http://www.r-project.org. Accessed June 1, 2018.

  • 33.

    Nguyet MN et al. 2013. Host and viral features of human dengue cases shape the population of infected and infectious Aedes aegypti mosquitoes. Proc Natl Acad Sci U S A 110: 90729077.

    • Search Google Scholar
    • Export Citation
  • 34.

    Gubler DJ, Nalem S, Tan R, Saipan H, Saroso JS, 1979. Variation in suseptibility to oral infection with dengue viruses among geographic strains of Aedes aegypti. Am J Trop Med Hyg 28: 10451052.

    • Search Google Scholar
    • Export Citation
  • 35.

    Armstrong PM, Rico-Hesse R, 2003. Efficiency of dengue serotype 2 virus strains to infect and disseminate in Aedes aegypti. Am J Trop Med Hyg 68: 539544.

    • Search Google Scholar
    • Export Citation
  • 36.

    Allicock OM, Lemey P, Tatem AJ, Pybus OG, Bennett SN, Mueller BA, Suchard MA, Foster JE, Rambaut A, Carrington CV, 2012. Phylogeography and population dynamics of dengue viruses in the Americas. Mol Biol Evol 29: 15331543.

    • Search Google Scholar
    • Export Citation
  • 37.

    Sahadeo NSD et al. 2017. Understanding the evolution and spread of chikungunya virus in the Americas using complete genome sequences. Virus Evol 3: vex010.

    • Search Google Scholar
    • Export Citation
  • 38.

    Tsetsarkin KA, Weaver SC, 2011. Sequential adaptive mutations enhance efficient vector switching by chikungunya virus and its epidemic emergence. PLoS Pathog 7: e1002412.

    • Search Google Scholar
    • Export Citation
  • 39.

    Tsetsarkin KA, Chen R, Sherman MB, Weaver SC, 2011. Chikungunya virus: evolution and genetic determinants of emergence. Curr Opin Virol 1: 310317.

    • Search Google Scholar
    • Export Citation
  • 40.

    Ciota AT, Ehrbar DJ, Matacchiero AC, Van Slyke GA, Kramer LD, 2013. The evolution of virulence of West Nile virus in a mosquito vector: implications for arbovirus adaptation and evolution. BMC Evol Biol 13: 71.

    • Search Google Scholar
    • Export Citation
  • 41.

    Black WC IV, Moore CG, 1996. Chapter 15. Population biology as a tool to study vector-borne diseases. Beaty BJ, Marquardt WC, eds. The Biology of Disease Vectors. San Diego, CA: Elsevier Academic, 187206.

    • Search Google Scholar
    • Export Citation
  • 42.

    Ruiz-Moreno D, 2016. Assessing chikungunya risk in a metropolitan area of Argentina through satellite images and mathematical models. BMC Infect Dis 16: 49.

    • Search Google Scholar
    • Export Citation
  • 43.

    Tittarelli E, Lusso SB, Goya S, Rojo GL, Natale MI, Viegas M, Mistchenko AS, Valinotto LE, 2017. Dengue virus 1 outbreak in Buenos Aires, Argentina, 2016. Emerg Infect Dis 23: 16841685.

    • Search Google Scholar
    • Export Citation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

 

Differential Effects of Temperature and Mosquito Genetics Determine Transmissibility of Arboviruses by Aedes aegypti in Argentina

View More View Less
  • 1 The Arbovirus Laboratory, Wadsworth Center, New York State Department of Health, Slingerlands, New York;
  • | 2 Department of Biomedical Sciences, Albany School of Public Health, State University of New York, Albany, New York;
  • | 3 Centro de Estudios Parasitológicos y de Vectores, CONICET, La Plata, Buenos Aires, Argentina;
  • | 4 Center for Vector Biology, Rutgers University, New Brunswick, New Jersey
Restricted access

Aedes aegypti (L.) (Diptera: Culicidae) have a global distribution and are the primary vector of a number of mosquito-borne viruses responsible for epidemics throughout the Americas. As in much of South America, the threat from pathogens including dengue virus (DENV; Flaviviridae, Flavivirus) and chikungunya virus (CHIKV; Togaviridae, Alphavirus) has increased in Argentina in recent years. The complexity of transmission cycles makes predicting the occurrence and intensity of arbovirus outbreaks difficult. To gain a better understanding of the risk of DENV and CHIKV in Argentina and the factors influencing this risk, we evaluated the role of population and temperature in the vector competence and vectorial capacity (VC) of Ae. aegypti from geographically and ecologically distinct locations. Our results demonstrate that intrinsic and extrinsic factors including mosquito population, viral species, and temperature significantly influence both vector competence and overall VC of Ae. aegypti in Argentina, yet also that the magnitude of these influences is highly variable. Specifically, results suggest that CHIKV competence is more dependent on mosquito genetics than is DENV competence, whereas temperature has a greater effect on DENV transmission. In addition, although there is an overall positive correlation between temperature and competence for both viruses, there are exceptions to this for individual virus–population combinations. Together, these data establish large variability in VC for these pathogens among distinct Ae. aegypti populations in Argentina and demonstrate that accurate assessment of arbovirus risk will require nuanced models that fully consider the complexity of interactions between virus, temperature, mosquito genetics, and hosts.

Author Notes

Address correspondence to Laura D. Kramer, The Arbovirus Laboratory, Wadsworth Center, New York State Department of Health, Slingerlands, NY 12159. E-mail: laura.kramer@health.ny.gov

Financial support: Financial support was provided in part by the Fulbright Visiting Scholar Program (https://hpc.nih.gov/apps/fastStructure.html).

Authors’ addresses: Alexander T. Ciota and Laura D. Kramer, The Arbovirus Laboratory, Wadsworth Center, New York State Department of Health, Slingerlands, NY, and Department of Biomedical Sciences, Albany School of Public Health, State University of New York, Albany, NY, E-mails: alexander.ciota@health.ny.gov and laura.kramer@health.ny.gov. Pamela A. Chin and Dylan J. Ehrbar, The Arbovirus Laboratory, Wadsworth Center, New York State Department of Health, Slingerlands, NY, E-mails: pamela.chin@health.ny.gov and dylan.ehrbar@health.ny.gov. Maria Victoria Micieli, Centro de Estudios Parasitológicos y de Vectores, CONICET, La Plata, Buenos Aires, Argentina, E-mail: victoria@cepave.edu.ar. Dina M. Fonseca, Center for Vector Biology, Rutgers University, New Brunswick, NJ, E-mail: dina.fonseca@rutgers.edu.

Save