Next Article in Journal
Sodium Channel Mutations and Pyrethroid Resistance in Aedes aegypti
Next Article in Special Issue
Mosquito Oviposition Behavior and Vector Control
Previous Article in Journal
Susceptibility of Bemisia tabaci MEAM1 (Hemiptera: Aleyrodidae) to Imidacloprid, Thiamethoxam, Dinotefuran and Flupyradifurone in South Florida
Previous Article in Special Issue
Looking Backward, Looking Forward: The Long, Torturous Struggle with Mosquitoes
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches

Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA
Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
Author to whom correspondence should be addressed.
Insects 2016, 7(4), 58;
Received: 9 September 2016 / Revised: 24 October 2016 / Accepted: 25 October 2016 / Published: 30 October 2016


Dengue (DENV), yellow fever, chikungunya, and Zika virus transmission to humans by a mosquito host is confounded by both intrinsic and extrinsic variables. Besides virulence factors of the individual arboviruses, likelihood of virus transmission is subject to variability in the genome of the primary mosquito vector, Aedes aegypti. The “vectorial capacity” of A. aegypti varies depending upon its density, biting rate, and survival rate, as well as its intrinsic ability to acquire, host and transmit a given arbovirus. This intrinsic ability is known as “vector competence”. Based on whole transcriptome analysis, several genes and pathways have been predicated to have an association with a susceptible or refractory response in A. aegypti to DENV infection. However, the functional genomics of vector competence of A. aegypti is not well understood, primarily due to lack of integrative approaches in genomic or transcriptomic studies. In this review, we focus on the present status of genomics studies of DENV vector competence in A. aegypti as limited information is available relative to the other arboviruses. We propose future areas of research needed to facilitate the integration of vector and virus genomics and environmental factors to work towards better understanding of vector competence and vectorial capacity in natural conditions.

1. Introduction

The mosquito Aedes aegypti is the principal global vector that transmits dengue (DENV), yellow fever, chikungunya (CHIKV), and Zika virus to humans and is well adapted to urban environments. Dengue virus infection causes dengue fever and can lead to more severe symptoms such as hemorrhagic fever, plasma leakage, and organ impairments in humans. Evidence suggests that ~4 billion people in 128 countries are at risk of dengue infection [1]. Indeed, as many as 390 million cases of dengue likely occur each year globally, with many of these being unapparent [2]. Adding to dengue disease complexity, DENV exists as four common serotypes that circulate globally across most tropical and sub-tropical areas. Despite the long availability of an effective vaccine for yellow fever, epidemics with considerable human mortality continue to occur [3]. Re-emerging arboviruses like CHIKV represent persistent cyclical threats of epidemics [4], while emerging arboviruses like Zika will continue to cause massive outbreaks until sufficient herd immunity develops and will then remain cyclical threats [5]. At present, no effective vaccines are available or imminent for DENV, CHIKV, or Zika, and no drug therapies exist [4,5,6,7]. As a result, mosquito control remains the primary control strategy for prevention of dengue and other arboviruses, yet for multiple reasons, including inevitable emergence of insecticide resistant populations [8,9], it is often ineffective. Novel genetic control strategies are being pursued and developed that target A. aegypti [10,11,12], with some practical evidence for associated reductions in mosquito populations [13,14] and/or DENV transmission [15], although these remain to be validated in large-scale field trials. In this review, we focus on the current genomic information available for A. aegypti interactions with DENV, as little such information is available relative to other arboviruses.

2. Gene by Environment Interactions Determine Vector Competence

The susceptibility of A. aegypti to DENV and other arbovirus infection is determined by both intrinsic and extrinsic factors [16]. Adult females are exposed to DENV upon blood feeding on viremic humans, followed by virion infection of the mosquito’s midgut epithelium. Thereafter, the virus must successfully replicate and disseminate to other tissues, especially the salivary glands, in order to subsequently be transmitted to a naïve human host [17]. The likelihood for success or failure in establishment of a DENV infection in the midgut is one of the most important intrinsic factors that define vector competence of the mosquito host. The intrinsic ability of an arthropod vector to either host or defend against virus infection is generally referred to as “vector competence” [18]. Interpreting the association between A. aegypti and DENV is a dynamic process that is likely confounded by the inherent variability of the individual genotypes in both mosquito and virus, wherein infection outcome reflects genotype-by-genotype (GMxGV) interactions [19,20,21]. A wealth of information exists documenting genetic variability in DENV vector competence in A. aegypti populations both within and between geographic locations [22,23,24,25,26,27,28,29]. In addition, variability in vector competence to different DENV isolates both within the same serotype and across serotypes has been reported within single A. aegypti populations [30,31,32,33,34,35]. Further complicating this relationship, other biotic and abiotic factors are known to interact with and influence phenotypic variance in DENV vector competence [36,37,38]. Thus the association between A. aegypti and DENV in natural populations is a highly dynamic process that also involves interactions between mosquito (GM) and virus (GV) genotypes and prevailing environmental (E) factors (GMxGVxE). Vectorial capacity (VC) represents the average number of potentially infective bites a vertebrate host will receive per day among all vectors that feed on them [39]. Epidemiologically, VC can be estimated using the following equation derived after work by Ross and Macdonald, as reviewed elsewhere [40,41]:
V C = m b p n a 2 ln   p
where m = density of vectors (per host), p = survival rate of the vector (per day), a = biting rate, n = extrinsic incubation period, and b = vector competence.
Still, our practical knowledge of the phenotypic outcome of genes due to environmental interactions and the overall impact on vectorial capacity in any arthropod vector/pathogen system remains limited. Factors that influence larval development time can affect the size of adult females, which is considered to be an important aspect of vector competence, vectorial capacity, and overall vector biology including longevity, biting persistence, and blood meal frequency [42,43,44,45]. Further, the aquatic environment encountered by eggs and larvae may have an effect on the repertoire of the microbiome during development, and it is known that the microbiome does regulate mosquito development [46], and eventually egg production in adult females [47]. Nasci [43] demonstrated that the average size of host-seeking A. aegypti females is significantly larger than the average size of the emerging population of females, and suggested that the likelihood of surviving to a second gonotrophic cycle increases as adult body size increases. However, small adult mosquitoes are known to probe more often and to take multiple blood meals during a gonotrophic cycle [48], suggesting that small mosquitoes may be more likely to encounter an infective human during their lifetime and could potentially be a more epidemiologically relevant vector. Phenotypic outcome in A. aegypti adults is extremely plastic and reflects the interaction of genetic potential with environmental conditions encountered by developing larvae [49]. In general, the inorganic and organic nutrient contents of typical A. aegypti breeding sites are low as they are dependent on allochthonous inputs [50], and thus larval nutrition can be a limiting factor. Temperature can also have a major impact on disease transmission by influencing body size, development time, and container productivity [51,52,53].

3. Quantitative Genetics of Vector Competence

3.1. Innate Immune Response Defines Vector Competence

The innate immune system is broadly conserved across insects and mammals [54,55,56,57,58,59]. It has been well documented that an innate immune response is activated in mosquitoes following infection by a diverse array of pathogens [60,61,62,63,64,65,66]. However, this response has been most often shown to limit pathogenesis in the mosquito host, but does not necessarily prevent them from becoming competent vectors for subsequent pathogen transmission to a human host. Variability in vector competence is largely conditioned by the joint action of a small number of genes [67,68]. Such traits are generally referred to as multigene or quantitative traits, and the individual gene locations as quantitative trait loci (QTL). These QTL define the primary upstream loci directing the vector host response to infection by a pathogen and play key roles in conditioning a susceptible or refractory outcome in the host.

3.2. Primary Conditioners of Vector Competence Identified as Quantitative Trait Loci

Our current knowledge on the quantitative genetics of the innate immune response of mosquitoes to pathogen infection largely reflects a collection of diverse and independent studies that have employed various tools/strategies to investigate the fundamental basis for vector competence. Investigations of the quantitative genetics of DENV vector competence in A. aegypti females determined that the innate immune response can trigger molecular events that either prohibit the virus from successfully establishing an infection in their midgut epithelium (e.g., a midgut infection barrier, MIB) or following successful midgut epithelium infection and replication somehow prevents virus escape and dissemination to other tissues, particularly the salivary glands (e.g., a midgut escape barrier, MEB] [69]. Subsequent QTL mapping studies in A. aegypti have confirmed a multigene mode of DENV vector competence and defined genome regions containing multiple independent QTL [70,71,72]. In addition, QTL studies on other pathogens, including the filarial worm parasite, Brugia malayi, and the malaria parasite, Plasmodium gallinaceum, identified multiple QTL [73,74,75,76]. Of note, these QTL tend to cluster in only five specific genome regions, irrespective of the pathogen or genetic background of the mosquito host [77], suggesting that these regions (Figure 1) may contain key mutations in loci that ultimately determine vector competence. These loci could represent gene regulatory factors or clusters of genes that are associated with the A. aegypti innate immune system. Physical clustering of such genes may be constrained by selective forces. A good example of this can be derived from results of the hundreds of QTL studies performed in maize, where a synthesis of 50 independent QTL studies that examined disease resistance to multiple pathogens across diverse genetic backgrounds demonstrated that certain QTL tended to cluster in specific genome regions across a diverse array of pathogens [78]; the conclusion was that a relatively small number of loci are active in conditioning a susceptible versus resistant innate immune response to all pathogens in maize.

4. A. aegypti and DENV Interaction Post-Blood Feeding on Infected Human Host

In a genetically susceptible A. aegypti female a cascade of events occurs following acquisition of a DENV-infected blood meal from a human host that can ultimately result in infection of the salivary glands and transmission of the virus to naïve human hosts during subsequent blood feeding (Figure 2). The DENV life cycle in mosquito cells is generally homologous to that in human cells, which is well characterized [79]. Initially, the virus binds to surface receptors on midgut epithelia cells [80], followed by clathrin-mediated endocytosis and subsequent endosome maturation, which includes a decrease in pH that promotes viral envelope fusion with the endosome, thereby releasing the viral positive strand RNA genome for replication and translation [81,82]. This process is followed by virus assembly, maturation, and eventually exocytosis from the cell and dissemination to and infection of other cells.
Following ingestion of an infected blood meal, the time required for a susceptible mosquito host to be competent for oral transmission of the virus to another human host is defined as the extrinsic incubation period (EIP) [67]. The length of the EIP is dependent on multiple factors, including genotypes of both mosquito and virus, as well as environmental factors such as the prevailing temperature and the larval rearing conditions. Following ingestion, virus titer drops considerably over the next ~24–48 h (termed as the “eclipse” period) as endocytosis and replication are initiated in the midgut epithelia (Figure 2) [83]. This time period is likely the most critical for determining whether a given mosquito will eventually become competent to transmit virus. That is, for example, in Aedes albopictus C6/36 cells, DENV has been shown to successfully bind to the cell membrane and endocytose within 5–7 min following infection, and to colocalize with low pH vesicles like lysosomes by 30 min post-infection [82]. Following replication in a susceptible host, exocytosis occurs and the virus is able to disseminate to and replicate in other tissues, most importantly the salivary glands. The EIP is typically considered to be ~7–14 days, but has been shown to take only ~4 days with some mosquito/virus interactions [84]. Multiple tissues have been linked with barriers to arbovirus infection in mosquitoes [17] that not only include direct cellular activities but also physical barriers such as the basal lamina [84,85]. Of note, at this point no direct evidence exists for a salivary gland barrier to DENV infection in A. aegypti, so the prevailing conclusion is that if the virus successfully infects the midgut epithelium and escapes into the hemocoel, that mosquito will become competent for transmission. Thus, the events occurring during the first 3–4 days post-infected blood meal are critical to determining whether a given female becomes competent to transmit virus in a future blood meal. However, evidence does exist indicating that successful virus replication in the midgut and subsequent dissemination to other tissues including the salivary glands and saliva is dependent to some extent on virus titer in the initial blood meal [35,86,87,88]. Thus, virus dissemination to low titers, as evidenced by assessment of leg or head tissues, may not result in successful dissemination to salivary glands and saliva.

5. Functional Genomics of Innate Immune Response to DENV

The availability of the A. aegypti genome sequence [89] has greatly facilitated efforts to perform broad-scale transcriptome assays of the innate immune response to DENV infection (Table 1). These studies encompass a range of mosquito genetic backgrounds as well as the complete range of the viral EIP in the mosquito host, including multiple tissues. Many of these studies involved mosquito stocks known to be highly susceptible to infection by DENV [90,91,92,93,94], although several have focused on transcriptome comparisons of known susceptible and refractory mosquito stocks [95,96,97,98] as well as a diverse panel of mosquito stocks shown to reflect the full range of susceptibility as determined by midgut virus titers at 7 days post infected blood feeding [99]. Of note, all of these studies have been performed with the same two DENV-2 isolates, New Guinea C and JAM 1409.
The highly conserved nature of systemic innate immune responses of A. aegypti and other mosquitoes to various arboviruses including DENV has been reviewed extensively elsewhere and includes the classical immune signaling pathways as well as RNA interference (RNAi) and apoptosis [63,65,66,100,101,102]. Indeed, a consensus across A. aegypti transcriptome studies in Table 1 is that, independent of genetic background or post-infection sampling point or tissue in A. aegypti females, the innate immune system mounts a vigorous response to DENV infection that is commonly reflected by upregulation of both the Toll and JAK/STAT signaling pathways. Of note, however, the upregulation of these signaling pathways as well as RNAi and apoptotic pathways may be critical to limiting virus titers in mosquito cells; for example, suppression of the RNAi pathway in A. aegypti females exposed to Sindbis virus resulted in significant increases in virus titers and decreases in mosquito survival [103]. Thus, demonstration of the upregulation of components of the innate immune system does not in itself explain the basis for genetic refractoriness or susceptibility in a given individual. These findings likely reflect the evolution of mechanisms by DENV and other arboviruses to limit or even manipulate the innate immune system in A. aegypti to facilitate its own survival and replication in mosquito cells in a similar manner, as has been well described for DENV interaction with human cells [104]. Indeed, the concept of tolerance of infection vs. resistance to infection by a pathogen has been well documented [105,106]. Additionally, recent evidence suggests that DENV also likely induces autophagy in A. aegypti cells to facilitate infection [107] as has again been well documented in human cells [104,108]. To date, however, the key loci that determine a refractory vs. susceptible outcome have not been identified.

6. Genome Coevolution and Vector Competence

Arbovirus interactions with both the vertebrate and mosquito host have been shown to have association with coevolutionary processes that influence virus infection mechanisms and the immune systems in both hosts [109,110,111]. Using binomial logistic regression analyses to investigate known DENV responsive genes [96], we found that several intrinsic features such as gene context, intron presence, codon usage bias, paralogy, and derived versus ancestral origin of A. aegypti genes each show significant marginal effects with the observed transcriptional responses to DENV infection [112]. Among these features, genes with high codon usage bias were associated primarily with non-responsiveness to DENV infection, while intron-less genes and genes in A. aegypti with no ortholog in either Culex quinquefasciatus or Anopheles gambiae showed a greater association with responsiveness to DENV infection. These findings are consistent with the knowledge that, in general, housekeeping genes evolve slowly and show low intron frequency and high codon usage bias [112,113,114], while genes associated with innate immunity evolve quickly [59,115]. Indeed, the concept of a molecular “arms race” whereby selection by arboviruses may be driving genome evolution in the invertebrate host and vice versa has considerable support [116]. Under this scenario, selection for A. aegypti polymorphisms promoting resistance to DENV infection would be countered by matching virus polymorphisms to evade or suppress that response before fixation of resistance alleles in a mosquito population. This outcome also seems well supported by investigations of genotype-by-genotype interactions as they influence the observed A. aegypti vector competence at the local or regional levels [19,30,31,117], wherein a reciprocal selective response would reflect variability due to the prevailing environmental conditions. Indeed, we compared cis-regulatory element DNA sequences that control gene expression in A. aegypti between DENV susceptible and refractory strains and identified >3300 strain-specific single nucleotide polymorphisms within these elements [118].
Further, as DENV is dependent on the host translational apparatus, we and others have reported that DENV isolates show significant biases in synonymous codon usage that are consistent with their geographic origin and likely result from adaptive interaction with the mosquito and human hosts [109,119,120]. We also observed that codon context (the propensity of adjacent codons to consistently pair with themselves or another codon) among Asian and American DENV isolates showed a bias toward (A)(A/T)(A)-(A)(A/T)(A) coding sequences and general avoidance of (C/G)(C/A)(C/G)-(C/G)(C/A)(C/G) coding sequences across all four serotypes [119]. In addition to DENV, we also compared [121] the codon context bias of other flaviviruses, including West Nile virus (WNV) and yellow fever virus (YFV), and determined that codon context bias varies in a bicluster manner with A. aegypti genes that have been shown to be differentially expressed following infection by these viruses [92]. This result suggests that codon context sequences of A. aegypti and the flaviviruses may play an important role in determining successful infection by these viruses. A recent study demonstrated that host infection ability of DENV can be manipulated by appropriately altering codon context sequences in the virus genome so that it grows efficiently in insect cells but not in mammal cells [122], an approach that holds promise in developing novel attenuated viral vaccine candidates against dengue. Furthermore, DENV has been shown to undergo a bottleneck effect in genetic heterogeneity by alternative cycling in human and mosquito cells [123], thus further supporting the notion of a molecular arms race between mosquito host and virus.

7. Conclusions

Our inadequate ability to prevent or control DENV and most other vector-borne diseases demands that we pursue new paradigms. Considerable discussion and research effort is being directed toward applying transgenesis technology to arthropod-borne disease control, with an emphasis on population suppression or replacement [11,124,125,126,127,128,129]. A major focus is to use these techniques to generate mosquitoes that carry genes to disrupt their ability to transmit pathogens. The general concept would be to replace natural mosquito populations with individuals carrying a transgene construct. The most commonly discussed candidate genes for transformation would directly interfere with pathogen development in the mosquito, although genes that would minimize or prevent mosquito/pathogen contact would also be applicable. Transmission blocking vaccines, wherein mosquito antigens provide the basis for inducing pathogen inhibitory antibodies in humans, would prevent the infection and development of the pathogen in the mosquito and thereby interrupt disease transmission [128]. However, it is also well recognized that successful implementation of such strategies will require intensive pre-release and post-release investigations of mosquito ecology and population biology [130]. One important caveat regarding published studies of A. aegypti transcriptome responses to DENV and other arboviruses to date is that all have been conducted under optimum lab conditions; we and others [131] would argue that future studies should include similar investigations of the impact on the innate immune response of mosquito and DENV genotypes under typical environmental conditions. Efforts directed at detailed comparative transcriptome studies targeting CHIKV and Zika should be a research priority. This information has the potential to inform and enhance predictive models for vector/virus interaction and disease transmission. Integrative approaches could incorporate information gained on the molecular biology of the innate immune response with traditional aspects of basic mosquito biology such as body size, longevity, and larval density, along with environmental factors, to more accurately predict vector competence at the population level.


We dedicate this review to the memory of our colleague and dear friend Dave D. Chadee. This work was funded in part by a grant from the National Institutes of Health, National Institute of Allergy and Infectious Diseases (R56-AI110721) to David W. Severson.

Author Contributions

David W. Severson and Susanta K. Behura wrote the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.


The following abbreviations are used in this manuscript:
DENVDengue virus
GMGenotype of mosquito
GVGenotype of virus
VCVectorial capacity
QTLQuantitative trait locus
MIBMidgut infection barrier
MEBMidgut escape barrier
EIPExtrinsic incubation period
RNAiRNA interference
WNVWest Nile virus
YFYellow fever virus


  1. Brady, O.B.; Gething, P.W.; Bhatt, S.; Messina, J.P.; Brownstein, J.S.; Hoen, A.G.; Moyes, C.L.; Farlow, A.W.; Scott, T.W.; Hay, S.I. Refining the global spatial limits of dengue virus transmission by evidence-based consensus. PLoS Negl. Trop. Dis. 2012, 6, e1760. [Google Scholar] [CrossRef] [PubMed]
  2. Bhatt, S.; Gething, P.W.; Brady, O.J.; Messina, J.P.; Farlow, A.W.; Moyes, C.L.; Drake, J.M.; Brownstein, J.S.; Hoen, A.G.; Sankoh, O.; et al. The global distribution and burden of dengue. Nature 2013, 496, 504–507. [Google Scholar] [CrossRef] [PubMed]
  3. Monath, T.P.; Vasconcelos, P.F.C. Yellow fever. J. Clin. Virol. 2015, 64, 160–173. [Google Scholar] [CrossRef] [PubMed]
  4. Caglioti, C.; Lalle, E.; Castilletti, C.; Carletti, F.; Capobianchi, M.R.; Bordi, L. Chikungunya virus infections: An overview. New Microbiol. 2013, 36, 211–227. [Google Scholar] [PubMed]
  5. Weaver, S.C.; Costa, F.; Garcia-Blanco, M.; Ko, A.I.; Ribeiro, G.S.; Saade, G.; Shi, P.-Y.; Vasilakis, N. Zika virus: History, emergence, biology, and prospects for control. Antivir. Res. 2016, 130, 69–80. [Google Scholar] [CrossRef] [PubMed]
  6. Liu, Y.; Liu, J.; Cheng, G. Vaccines and immunization strategies for dengue prevention. Emerg. Microbes Infect. 2016, 5, e77. [Google Scholar] [CrossRef] [PubMed]
  7. Thomas, S.J.; Rothman, A.L. Trials and tribulations on the path to developing a dengue vaccine. Vaccine 2015, 33, D24–D31. [Google Scholar] [CrossRef] [PubMed]
  8. Hemingway, J.; Ranson, H. Insecticide resistance in insect vectors of human disease. Annu. Rev. Entomol. 2000, 45, 371–391. [Google Scholar] [CrossRef] [PubMed]
  9. Liu, N. Insecticide resistance in mosquitoes: Impact, mechanisms, and research directions. Annu. Rev. Entomol. 2015, 60, 537–559. [Google Scholar] [CrossRef] [PubMed]
  10. Alphey, L.; McKemey, A.; Nimmo, D.; Oviedo, M.N.; Lacroix, R.; Matzen, K.; Beech, C. Genetic control of Aedes mosquitoes. Pathog. Glob. Health 2013, 107, 170–179. [Google Scholar] [CrossRef] [PubMed]
  11. Alphey, L. Genetic control of mosquitoes. Annu. Rev. Entomol. 2014, 59, 205–224. [Google Scholar] [CrossRef] [PubMed]
  12. Franz, A.W.E.; Clem, R.J.; Passarelli, A.L. Novel genetic and molecular tools for the investigation and control of dengue virus transmission by mosquitoes. Curr. Trop. Med. Rep. 2014, 1, 21–31. [Google Scholar] [CrossRef] [PubMed]
  13. Harris, A.F.; McKemy, A.R.; Nimmo, D.; Curtis, Z.; Black, I.; Morgan, S.A.; Oviedo, M.N.; Lacroix, R.; Naish, N.; Morrison, N.I.; et al. Successful suppression of a field mosquito population by sustained release of engineering male mosquitoes. Nat. Biotechnol. 2012, 30, 828–830. [Google Scholar] [CrossRef] [PubMed]
  14. Wise De Valdez, M.R.; Nimmo, D.; Betz, J.; Gong, H.-F.; James, A.A.; Alphey, L.; Black, W.C., IV. Genetic elimination of dengue vector mosquitoes. Proc. Natl. Acad. Sci. USA 2011, 108, 4772–4775. [Google Scholar] [CrossRef] [PubMed]
  15. Walker, T.; Johnson, P.H.; Moreira, L.A.; Iturbe-Ormaetxe, I.; Frentiu, F.D.; McMeniman, C.J.; Leong, Y.S.; Dong, Y.; Axford, J.; Kriesner, P.; et al. The wMel Wolbachia strain blocks dengue and invades caged Aedes aegypti populations. Nature 2011, 476, 450–455. [Google Scholar] [CrossRef] [PubMed]
  16. Tabachnick, W.J. Nature, nurture and evolution of intra-species variation in mosquito arbovirus transmission competence. Int. J. Environ. Res. Public Health 2013, 10, 249–277. [Google Scholar] [CrossRef] [PubMed]
  17. Franz, A.W.E.; Kantor, A.M.; Passarelli, A.L.; Clem, R.J. Tissue barriers to arbovirus infection in mosquitoes. Viruses 2015, 7, 3741–3767. [Google Scholar] [CrossRef] [PubMed]
  18. Black, W.C., IV; Severson, D.W. Genetics of vector competence. In Biology of Disease Vectors, 2nd ed.; Marquardt, W.C., Ed.; Elsevier: London, UK, 2005; pp. 415–448. [Google Scholar]
  19. Lambrechts, L.; Chevillon, C.; Albright, R.G.; Thaisomboonsuk, B.; Richardson, J.H.; Jarman, R.G.; Scott, T.W. Genetic specificity and potential for local adaptation between dengue viruses and mosquito vectors. BMC Evol. Biol. 2009. [Google Scholar] [CrossRef] [PubMed]
  20. Lambrechts, L. Quantitative genetics of Aedes aegypti vector competence for dengue viruses: Towards a new paradigm? Trends Parasitol. 2011, 27, 111–114. [Google Scholar] [CrossRef] [PubMed]
  21. Lequime, S.; Fontaine, A.; Gouilh, M.A.; Moltini-Conclois, I.; Lambrechts, L. Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes. PLoS Genet. 2016, 12, e1006111. [Google Scholar] [CrossRef] [PubMed]
  22. Bennett, K.E.; Olson, K.E.; de Lourdes Munoz, M.; Fernandez-Salas, I.; Farfan-Ale, J.A.; Higgs, S.; Black, W.C., IV; Beaty, B.J. Variation in vector competence for dengue 2 virus among 24 collections of Aedes aegypti from Mexico and the United States. Am. J. Trop. Med. Hyg. 2002, 67, 85–92. [Google Scholar] [PubMed]
  23. Diallo, M.; Sall, A.A.; Moncayo, A.C.; Ba, Y.; Fernandez, Z.; Ortiz, D.; Coffey, L.L.; Mathiot, C.; Tesh, R.B.; Weaver, S.C. Potential role of sylvatic and domestic African mosquito species in dengue emergence. Am. J. Trop. Med. Hyg. 2005, 73, 445–449. [Google Scholar] [PubMed]
  24. Failloux, A.-B.; Vazeille, M.; Rodhain, F. Geographic genetic variation in populations of the dengue virus vector Aedes aegypti. J. Mol. Evol. 2002, 55, 653–663. [Google Scholar] [CrossRef] [PubMed]
  25. Goncalves, C.M.; Melo, F.F.; Bezerra, M.T.; Chaves, B.A.; Silva, B.M.; Silva, L.D.; Pessanha, J.E.M.; Arias, J.R.; Secundino, N.F.C.; Norris, D.E.; et al. Distinct variation in vector competence among nine field populations of Aedes aegypti from a Brazilian dengue-endemic risk city. Parasites Vectors 2014. [Google Scholar] [CrossRef] [PubMed]
  26. Gubler, D.J.; Nalim, S.; Tan, R.; Saipan, H.; Saroso, J.S. Variation in susceptibility to oral infection with dengue viruses among geographic strains of Aedes aegypti. Am. J. Trop. Med. Hyg. 1979, 28, 1045–1052. [Google Scholar] [PubMed]
  27. Schneider, J.R.; Mori, A.; Romero-Severson, J.; Chadee, D.D.; Severson, D.W. Investigations of dengue-2 susceptibility and body size among Aedes aegypti populations. Med. Vet. Entomol. 2007, 21, 370–376. [Google Scholar] [CrossRef] [PubMed]
  28. Sumanochitrapon, W.; Strickman, D.; Sithiprasasna, R.; Kittayapong, P.; Innis, B.L. Effect of size and geographic origin of Aedes aegypti on oral infection with dengue-2 virus. Am. J. Trop. Med. Hyg. 1998, 58, 283–286. [Google Scholar] [PubMed]
  29. Tardieux, I.; Poupel, O.; Lapchin, L.; Rodhain, F. Variation among strains of Aedes aegypti in susceptibility to oral infection with denge virus type 2. Am. J. Trop. Med. Hyg. 1990, 43, 308–313. [Google Scholar] [PubMed]
  30. Anderson, J.R.; Rico-Hesse, R. Aedes aegypti vectorial capacity is determined by the infecting genotype of the dengue virus. Am. J. Trop. Med. Hyg. 2006, 75, 886–892. [Google Scholar] [PubMed]
  31. Armstrong, P.M.; Rico-Hesse, R. Efficiency of dengue serotype 2 virus strains to infect and disseminate in Aedes aegypti. Am. J. Trop. Med. Hyg. 2003, 68, 539–544. [Google Scholar] [PubMed]
  32. Fernandes da Moura, A.J.; Varjal de Melo Santos, M.A.; Oliveira, C.M.F.; Guedes, D.R.D.G.; de Carvalho-Leandro, D.; da Cruz Brito, M.L.; Rocha, H.D.R.; Gomez, L.F.; Ayres, C.F.J. Vector competence of the Aedes aegypti population from Santiago Island, Cape Verde, to different serotypes of dengue virus. Parasites Vectors 2015. [Google Scholar] [CrossRef]
  33. Gaye, A.; Faye, O.; Diagne, C.T.; Faye, O.; Diallo, D.; Weaver, S.C.; Sall, A.A.; Diallo, M. Oral susceptibility of Aedes aegypti (Diptera: Culicidae) from Senegal for dengue serotypes 1 and 3 viruses. Trop. Med. Int. Health 2014, 19, 1355–1359. [Google Scholar] [CrossRef] [PubMed]
  34. Khoo, C.C.H.; Doty, J.B.; Held, N.L.; Olson, K.E.; Franz, A.W.E. Isolation of midgut escape mutants of two American genotype dengue 2 viruses from Aedes aegypti. Virol. J. 2013. [Google Scholar] [CrossRef] [PubMed]
  35. Lambrechts, L.; Fansiri, T.; Pongsiri, A.; Thalsomboonsuk, B.; Klungthong, C.; Richardson, J.H.; Ponlawat, A.; Jarman, R.G.; Scott, T.W. Dengue-1 virus clade replacement in Thailand associated with enhanced mosquito transmission. J. Virol. 2012, 86, 1853–1861. [Google Scholar] [CrossRef] [PubMed]
  36. Carrington, L.B.; Seifert, S.N.; Armijos, M.V.; Lambrechts, L.; Scott, T.W. Reduction of Aedes aegypti vector competence for dengue virus under large temperature fluctuations. Am. J. Trop. Med. Hyg. 2013, 88, 689–697. [Google Scholar] [CrossRef] [PubMed]
  37. Paupy, C.; Chantha, N.; Vazeille, M.; Reynes, J.-M.; Rodhain, F.; Failloux, A.-B. Variation over space and time of Aedes aegypti in Phnom Penh (Cambodia): Genetic structure and oral susceptibility to a dengue virus. Genet. Res. Camb. 2003, 82, 171–182. [Google Scholar] [CrossRef]
  38. Vazeille, M.; Gaborit, P.; Mousson, L.; Girod, R.; Failloux, A.-B. Competitive advantage of a dengue 4 virus when co-infecting the mosquito Aedes aegypti with dengue 1 virus. BMC Infect. Dis. 2016. [Google Scholar] [CrossRef] [PubMed]
  39. Black, W.C., IV; Moore, C.G. Population biology as a tool to study vector-borne diseases. In Biology of Disease Vectors, 2nd ed.; Marquardt, W.C., Ed.; Elsevier: London, UK, 2005; pp. 187–206. [Google Scholar]
  40. Smith, D.L.; Battle, K.E.; Hay, S.I.; Barker, C.M.; Scott, T.W.; McKensie, F.E. Ross, Macdonald, and a theory for the dynamics and control of mosquito-transmitted pathogens. PLoS Pathog. 2012, 8, e1002588. [Google Scholar] [CrossRef] [PubMed]
  41. Tabachnick, W.J. Ecological effects on arbovirus-mosquito cycles of transmission. Curr. Opin. Virol. 2016, 21, 124–131. [Google Scholar] [CrossRef] [PubMed]
  42. Maciel-de-Freitas, R.; Codeco, C.T.; Lourenco-de-Oliveira, R. Body size-associated survival and dispersal rates of Aedes aegypti in Rio de Janeiro. Med. Vet. Entomol. 2007, 21, 284–292. [Google Scholar] [CrossRef] [PubMed]
  43. Nasci, R.S. The size of emerging and host-seeking Aedes aegypti and the relationship of size to blood-feeding success in the field. J. Am. Mosq. Control Assoc. 1986, 2, 61–62. [Google Scholar] [PubMed]
  44. Nasci, R.S. Influence of larval and adult nutrition on biting persistence in Aedes aegypti (Diptera: Culicidae). J. Med. Entomol. 1991, 31, 522–526. [Google Scholar] [CrossRef]
  45. Yan, G.; Severson, D.W.; Christensen, B.M. Costs and benefits of mosquito refractoriness to malaria parasites: Implications for genetic variability of mosquitoes and genetic control of malaria. Evolution 1997, 51, 441–450. [Google Scholar] [CrossRef]
  46. Coon, K.L.; Vogel, K.J.; Brown, M.R.; Strand, M.R. Mosquitoes rely on their gut microbiota for development. Mol. Ecol. 2014, 23, 2727–2739. [Google Scholar] [CrossRef] [PubMed]
  47. Coon, K.L.; Brown, M.R.; Strand, M.R. Gut bacteria differentially affect egg production in the anautogenous mosquito Aedes aegypti and facultatively autogenous mosquito Aedes atropalpus (Diptera: Culicidae). Parasit. Vectors 2016. [Google Scholar] [CrossRef] [PubMed]
  48. Scott, T.W.; Amerasinghe, P.H.; Morrison, A.C.; Lorenz, L.H.; Clark, G.G.; Strickman, D.; Kittaypong, P.; Edman, J.D. Longitudinal studies of Aedes aegypti (Diptera: Culicidae) in Thailand and Puerto Rico: Blood feeding frequency. J. Med. Entomol. 2000, 37, 89–101. [Google Scholar] [CrossRef] [PubMed]
  49. Schneider, J.R.; Chadee, D.D.; Mori, A.; Romero-Severson, J.; Severson, D.W. Heritability and adaptive phenotypic plasticity of adult body size in the mosquito Aedes aegypti with implications for dengue vector competence. Infect. Genet. Evol. 2011, 11, 11–16. [Google Scholar] [CrossRef] [PubMed]
  50. Barrera, B.; Amador, M.; Clark, G.C. Ecological factors influencing Aedes aegypti (Diptera: Culicidae) productivity in artificial containers in Salinas, Puerto Rico. J. Med. Entomol. 2006, 43, 484–492. [Google Scholar] [CrossRef]
  51. Hemme, R.R.; Tank, J.L.; Chadee, D.D.; Severson, D.W. Environmental conditions in water storage drums and influences on Aedes aegypti in Trinidad, West Indies. Acta Trop. 2009, 112, 59–66. [Google Scholar] [CrossRef] [PubMed]
  52. Kamimura, K.; Matsuse, I.T.; Takahashi, H.; Komukai, J.; Fukuda, T.; Suzuki, K.; Aratani, M.; Shira, Y.; Mogi, M. Effect of temperature on the development of Aedes aegypti and Aedes albopictus. Med. Entomol. Zool. 2002, 53, 53–58. [Google Scholar] [CrossRef]
  53. Keirans, J.E.; Fay, R.W. Effect of food and temperature on Aedes aegypti (L.) and Aedes triseriatus (SAY) larval development. Mosq. News 1968, 28, 338–341. [Google Scholar]
  54. Dostert, C.; Jouanguy, E.; Irving, P.; Troxler, L.; Galiana-Arnoux, D.; Hetru, C.; Hoffmann, J.A.; Imler, J.-L. The Jak-STAT signaling pathway is required but not sufficient for the antiviral response of drosophila. Nat. Immunol. 2005, 6, 946–953. [Google Scholar] [CrossRef] [PubMed]
  55. Govind, S. Innate immunity in Drosophila: Pathogens and pathways. Insect Sci. 2008, 15, 29–43. [Google Scholar] [CrossRef] [PubMed]
  56. Lemaitre, B.; Hoffmann, J. The host defense of Drosophila melanogaster. Annu. Rev. Immunol. 2007, 25, 697–743. [Google Scholar] [CrossRef] [PubMed]
  57. Steinert, S.; Levashina, E.A. Intracellular immune responses of dipteran insects. Immunol. Rev. 2011, 240, 129–140. [Google Scholar] [CrossRef] [PubMed]
  58. Tzou, P.; De Gregorio, E.; Lemaitre, B. How Drosophila combats microbial infection: A model to study innate immunity and host-pathogen interactions. Curr. Opin. Microbiol. 2002, 5, 102–110. [Google Scholar] [CrossRef]
  59. Waterhouse, R.M.; Kriventseva, E.V.; Meister, S.; Xi, Z.; Alvarez, K.D.; Bartholomay, L.C.; Barillas-Mury, C.; Bian, G.; Blandin, S.; Christensen, B.M.; et al. Evolutionary dynamics of immune-related genes and pathways in disease-vector mosquitoes. Science 2007, 316, 1738–1743. [Google Scholar] [CrossRef] [PubMed]
  60. Arjona, A.; Wang, P.; Montgomery, R.R.; Fikrig, E. Innate immune control of West Nile virus infection. Cell. Microbiol. 2011, 13, 1648–1658. [Google Scholar] [CrossRef] [PubMed]
  61. Cirimotich, C.M.; Dong, Y.; Garver, L.S.; Sim, S.; Dimopoulos, G. Mosquito immune defenses against Plasmodium infection. Dev. Comp. Immunol. 2010, 34, 387–395. [Google Scholar] [CrossRef] [PubMed]
  62. Dimopoulos, G.; Muller, H.-M.; Levashina, E.A.; Kafatos, F.C. Innate immune defense against malaria infection in the mosquito. Curr. Opin. Immunol. 2001, 13, 79–88. [Google Scholar] [CrossRef]
  63. Fragkoudis, R.; Attarzadeh-Yazdi, G.; Nash, A.A.; Fazakerley, J.K.; Kohl, A. Advances in dissecting mosquito innate immune responses to arbovirus infection. J. Gen. Virol. 2009, 90, 2061–2072. [Google Scholar] [CrossRef] [PubMed]
  64. Kingsolver, M.B.; Huang, Z.; Hardy, R.W. Insect antiviral innate immunity: Pathways, effectors and connections. J. Mol. Biol. 2013, 425, 4921–4936. [Google Scholar] [CrossRef] [PubMed]
  65. Prasad, A.N.; Brackney, D.E.; Ebel, G.D. The role of innate immunity in conditioning mosquito susceptibility to West Nile Virus. Viruses 2013, 5, 3142–3170. [Google Scholar] [CrossRef] [PubMed]
  66. Sim, S.; Jupatanakul, N.; Dimopoulos, G. Mosquito immunity against arboviruses. Viruses 2014, 6, 4479–4504. [Google Scholar] [CrossRef] [PubMed]
  67. Black, W.C., IV; Bennett, K.E.; Gorrochotegui-Escalante, N.; Barillas-Mury, C.V.; Fernandez-Salas, I.; de Lourdes Munoz, M.; Farfan, J.A.; Olson, K.E.; Beaty, B.J. Flavivirus susceptibility in Aedes aegypti. Arch. Med. Res. 2002, 33, 379–388. [Google Scholar] [CrossRef]
  68. Severson, D.W.; Brown, S.E.; Knudson, D.L. Genetic and physical mapping in mosquitoes: Molecular approaches. Ann. Rev. Entomol. 2001, 46, 183–219. [Google Scholar] [CrossRef] [PubMed]
  69. Bosio, C.F.; Beaty, B.J.; Black, W.C., IV. Quantitative genetics of vector competence for dengue-2 virus in Aedes aegypti. Am. J. Trop. Med. Hyg. 1998, 59, 965–970. [Google Scholar] [PubMed]
  70. Bennett, K.E.; Flick, D.; Fleming, K.H.; Jochim, R.; Beaty, B.J.; Black, W.C., IV. Quantitative trait loci that control dengue-2 virus dissemination in the mosquito Aedes aegypti. Genetics 2005, 170, 185–194. [Google Scholar] [CrossRef] [PubMed]
  71. Bosio, C.F.; Fulton, R.E.; Salasek, M.L.; Beaty, B.J.; Black, W.C., IV. Quantative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti. Genetics 2000, 156, 687–698. [Google Scholar] [PubMed]
  72. Gomez-Machorro, C.; Bennett, K.E.; del Lourdes Munoz, M.; Black, W.C., IV. Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti. Insect Mol. Biol. 2004, 13, 637–648. [Google Scholar] [CrossRef] [PubMed]
  73. Beerntsen, B.T.; Severson, D.W.; Klinkhammer, J.A.; Kassner, V.A.; Christensen, B.M. Aedes aegypti: A quantitative trait locus (QTL) influencing filarial worm intensity is linked to QTL for susceptibility to other mosquito-borne pathogens. Exp. Parasitol. 1995, 81, 355–362. [Google Scholar] [CrossRef] [PubMed]
  74. Severson, D.W.; Mori, A.; Zhang, Y.; Christensen, B.M. Chromosomal mapping of two loci affecting filarial worm susceptibility in Aedes aegypti. Insect Mol. Biol. 1994, 3, 67–73. [Google Scholar] [CrossRef] [PubMed]
  75. Severson, D.W.; Thathy, V.; Mori, A.; Zhang, Y.; Christensen, B.M. Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti. Genetics 1995, 139, 1711–1717. [Google Scholar] [PubMed]
  76. Zhong, D.; Menge, D.M.; Temu, E.A.; Chen, H.; Yan, G. Amplified fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the yellow fever mosquito Aedes aegypti. Genetics 2006, 173, 1337–1345. [Google Scholar] [CrossRef] [PubMed]
  77. Timoshevskiy, V.A.; Severson, D.W.; deBruyn, B.S.; Black, W.C.; Sharakhov, I.V.; Sharakhova, M.V. An integrated linkage, chromosome, and genome map for the yellow fever mosquito Aedes aegypti. PLoS Negl. Trop. Dis. 2013, 7, e2052. [Google Scholar] [CrossRef] [PubMed]
  78. Wisser, R.J.; Balint-Kurti, P.J.; Nelson, R.J. The genetic architecture of disease resistance in maize: A synthesis of published studies. Phytopathology 2006, 96, 120–129. [Google Scholar] [CrossRef] [PubMed]
  79. Rodenhuis-Zybert, I.A.; Wilschut, J.; Smit, J.M. Dengue virus life cycle: Viral and host factors modulating infectivity. Cell. Mol. Life Sci. 2010, 67, 2773–2786. [Google Scholar] [CrossRef] [PubMed]
  80. Smith, D.R. An update on mosquito cell expressed dengue virus receptor proteins. Insect Mol. Biol. 2012, 21, 1–7. [Google Scholar] [CrossRef] [PubMed]
  81. Acosta, E.G.; Castilla, V.; Damonte, E.B. Functional entry of dengue virus into Aedes albopictus mosquito cells is dependent on clathrin-mediated endocytosis. J. Gen. Virol. 2008, 89, 474–484. [Google Scholar] [CrossRef] [PubMed]
  82. Mosso, C.; Galvan-Mendoza, I.J.; Ludert, J.E.; del Angel, R.M. Endocytic pathway followed by dengue virus to infect the mosquito cell line C6/36 HT. Virology 2008, 378, 193–199. [Google Scholar] [CrossRef] [PubMed]
  83. Richardson, J.; Molina-Cruz, A.; Salazar, M.I.; Black, W.B., IV. Quantitative analysis of dengue-2 virus RNA during the extrinsic incubation period in individual Aedes aegypti. Am. J. Trop. Med. Hyg. 2006, 74, 132–141. [Google Scholar] [PubMed]
  84. Salazar, M.I.; Richardson, J.H.; Sanchez-Vargas, I.; Olson, K.E.; Beaty, B.J. Dengue virus type 2: Replication and tropisms in orally infected Aedes aegypti mosquitoes. BMC Microbiol. 2007. [Google Scholar] [CrossRef] [PubMed]
  85. Thomas, R.E.; Wu, W.-K.; Verleye, D.; Rai, K.S. Midgut basal lamina thickness and dengue-1 virus dissemination rates in laboratory strains of Aedes albopictus (Diptera: Culicidae). J. Med. Entomol. 1993, 30, 326–331. [Google Scholar] [CrossRef] [PubMed]
  86. Nguyet, M.N.; Kien, D.T.H.; Tuan, T.V.; Quyen, N.T.H.; Tran, C.N.B.; Thi, L.V.; Thi, D.L.; Nguyen, H.L.; Nguyen, H.T.C.; Nguyen, L.T.H.; et al. Host and viral features of human dengue cases shape the population of infected and infectious Aedes aegypti mosquitoes. Proc. Natl. Acad. Sci. USA 2013, 110, 9072–9077. [Google Scholar] [PubMed]
  87. Ye, Y.H.; Ng, T.S.; Frentiu, F.D.; Walker, T.; van den Hurk, A.F.; O’Neill, S.L.; Beebe, N.W.; McGraw, E.A. Comparative susceptibility of mosquito populations in North Queensland, Australia to oral infection with dengue virus. Am. J. Trop. Med. Hyg. 2014, 90, 422–430. [Google Scholar] [CrossRef] [PubMed]
  88. Ye, Y.H.; Chenoweth, S.F.; Carrasco, A.M.; Allen, S.L.; Frentiu, F.D.; van den Hurk, A.F.; Beebe, N.W.; McGraw, E.A. Evolutionary potential of the extrinsic incubation period of dengue virus in Aedes aegypti. Evolution 2016. [Google Scholar] [CrossRef] [PubMed]
  89. Nene, V.; Wortman, J.R.; Lawson, D.; Haas, B.; Kodira, C.; Tu, Z.; Loftus, B.; Xi, Z.; Megy, K.; Grabherr, M.; et al. Genome sequence of Aedes aegypti, a major arbovirus vector. Science 2007, 316, 1718–1723. [Google Scholar] [CrossRef] [PubMed]
  90. Xi, Z.; Ramirez, J.L.; Dimopoulos, G. The Aedes aegypti Toll pathway controls dengue virus infection. PLoS Pathog. 2008, 4, e1000098. [Google Scholar] [CrossRef] [PubMed]
  91. Souza-Neto, J.A.; Sim, S.; Dimopoulos, G. An evolutionary conserved function of the JAK-STAT pathway in anti-dengue defense. Proc. Natl. Acad. Sci. USA 2009, 106, 17841–17846. [Google Scholar] [CrossRef] [PubMed]
  92. Colpitts, T.M.; Cox, J.; Vanlandingham, D.L.; Feitosa, F.M.; Cheng, G.; Kurscheid, S.; Wang, P.; Kishnan, M.N.; Higgs, S.; Fikrig, E. Alterations in the Aedes aegypti transcriptome during infection with West Nile, dengue and yellow fever viruses. PLoS Pathog. 2011, 7, e1002189. [Google Scholar] [CrossRef] [PubMed]
  93. Bonizzoni, M.; Dunn, W.A.; Campbell, C.L.; Olson, K.E.; Marinotti, O.; James, A.A. Complex modulation of the Aedes aegypti transcriptome in response to dengue virus infection. PLoS ONE 2012, 7, e50512. [Google Scholar] [CrossRef] [PubMed]
  94. Sim, S.; Ramirez, J.L.; Dimopoulos, G. Dengue virus infection of the Aedes aegypti salivary gland and chemosensary apparatus induces genes that modulate infection and blood-feeding behavior. PLoS Pathog. 2012, 8, e1002631. [Google Scholar] [CrossRef] [PubMed]
  95. Baron, O.L.; Ursic-Bedoya, R.J.; Lowenberger, C.A.; Ocampo, C.B. Differential gene expression from midguts of refractory and susceptible lines of the mosquito, Aedes aegypti, infected with dengue-2 virus. J. Insect Sci. 2008. [Google Scholar] [CrossRef] [PubMed]
  96. Behura, S.K.; Gomez-Machorro, C.; Harker, B.W.; deBruyn, B.; Lovin, D.D.; Hemme, R.R.; Mori, A.; Romero-Severson, J.; Severson, D.W. Global cross-talk of genes of the mosquito Aedes aegypti in response to dengue virus infection. PLoS Negl. Trop. Dis. 2011, 5, e1385. [Google Scholar] [CrossRef] [PubMed]
  97. Behura, S.K.; Gomez-Machorro, C.; deBruyn, B.; Lovin, D.D.; Harker, B.W.; Romero-Severson, J.; Mori, A.; Severson, D.W. Influence of mosquito genotype on transcriptional response to dengue virus infection. Funct. Integr. Genom. 2014, 14, 581–589. [Google Scholar] [CrossRef] [PubMed]
  98. Chauhan, C.; Behura, S.K.; deBruyn, B.; Lovin, D.D.; Harker, B.W.; Gomez-Machorro, C.; Mori, A.; Romero-Severson, J.; Severson, D.W. Comparative expression profiles of midgut genes in dengue virus refractory and susceptible Aedes aegypti across critical period for virus infection. PLoS ONE 2012, 7, e47350. [Google Scholar] [CrossRef] [PubMed]
  99. Sim, S.; Jupatanakul, N.; Ramirez, J.L.; Kang, S.; Romero-Vivas, C.M.; Mohammed, H.; Dimopoulos, G. Transcriptomic profiling of diverse Aedes aegypti strains reveals increased basal-level immune activation in dengue virus-refractory populations and identifies novel virus-vector molecular interactions. PLoS Negl. Trop. Dis. 2013, 7, e2295. [Google Scholar] [CrossRef] [PubMed]
  100. Cheng, G.; Liu, Y.; Wang, P.; Xiao, X. Mosquito defense strategies against viral infection. Trends Parasitol. 2016, 32, 177–186. [Google Scholar] [CrossRef] [PubMed]
  101. Clem, R.J. Arboviruses and apoptosis: The role of cell death in determining vector competence. J. Gen. Virol. 2016, 97, 1033–1036. [Google Scholar] [CrossRef] [PubMed]
  102. Olson, K.E.; Blair, C.D. Arbovirus-mosquito interactions: RNAi pathway. Curr. Opin. Virol. 2015, 15, 119–126. [Google Scholar] [CrossRef] [PubMed]
  103. Myles, K.M.; Wiley, M.R.; Morazzani, E.M.; Adelman, Z.N.A. Alphavirus-derived small RNAs modulate pathogenesis in disease vector mosquitoes. Proc. Natl. Acad. Sci. USA 2008, 105, 19938–19943. [Google Scholar] [CrossRef] [PubMed]
  104. Green, A.M.; Beatty, P.R.; Hadjilaou, A.; Harris, E. Innate immunity to dengue virus infection and subversion of antiviral responses. J. Mol. Biol. 2014, 426, 1148–1160. [Google Scholar] [CrossRef] [PubMed]
  105. Moreno-Garcia, M.; Conde, R.; Bello-Bedoy, R.; Lanz-Mendoza, H. The damage threshold hypothesis and the immune strategies of insects. Infect. Genet. Evol. 2014, 24, 25–33. [Google Scholar] [CrossRef] [PubMed]
  106. Ayres, J.S.; Schneider, D.S. Tolerance of infections. Annu. Rev. Immunol. 2012, 30, 271–294. [Google Scholar] [CrossRef] [PubMed]
  107. Eng, M.W.; van Zuylen, M.N.; Severson, D.W. Apoptosis-related genes control autophagy and influence DENV-2 infection in the mosquito vector, Aedes aegypti. Insect Biochem. Mol. Biol. 2016, 76, 70–83. [Google Scholar] [CrossRef] [PubMed]
  108. Jain, B.; Chaturvedi, U.C.; Jain, A. Role of intracellular events in the pathogenesis of dengue: An overview. Microb. Pathog. 2014, 69–70, 45–52. [Google Scholar] [CrossRef] [PubMed]
  109. Lobo, F.P.; Mota, B.E.F.; Pena, S.D.J.; Azevedo, V.; Macedo, A.M.; Tauch, A.; Machado, C.R.; Franco, G.R. Virus-host coevolution: Common patterns of nucleotide motif usage in Flaviviridae and their hosts. PLoS ONE 2009, 4, e6282. [Google Scholar] [CrossRef] [PubMed]
  110. Marques, J.T.; Carthew, R.W. A call to arms: Coevolution of animal viruses and host innate immune responses. Trends Genet. 2007, 23, 359–364. [Google Scholar] [CrossRef] [PubMed]
  111. Marques, J.T.; Imler, J.-L. The diversity of insect antiviral immunity: Insights from viruses. Curr. Opin. Microbiol. 2016, 32, 71–76. [Google Scholar] [CrossRef] [PubMed]
  112. Behura, S.K.; Severson, D.W. Intrinsic features of Aedes aegypti genes affect transcriptional responsiveness of mosquito genes to dengue virus infection. Infect. Genet. Evol. 2012, 12, 1413–1418. [Google Scholar] [CrossRef] [PubMed]
  113. Calvo, E.; Pham, V.M.; Marinotti, O.; Andersen, J.F.; Ribeiro, J.M. The salivary gland transcriptome of the neotropical malaria vector Anopheles darlingi reveals accelerated evolution of genes relevant to hematophagy. BMC Genom. 2009. [Google Scholar] [CrossRef] [PubMed]
  114. Zhang, L.; Li, W.H. Mammalian housekeeping genes evolve more slowly than tissue-specific genes. Mol. Biol. Evol. 2004, 21, 236–239. [Google Scholar] [CrossRef] [PubMed]
  115. Bryant, C.E.; Monie, T.P. Mice, men and the relatives: Cross-species studies underpin innate immunity. Open Biol. 2012. [Google Scholar] [CrossRef] [PubMed]
  116. Obbard, D.J.; Dudas, G. The genetics of host-virus coevolution in invertebrates. Curr. Opin. Virol. 2014, 8, 73–78. [Google Scholar] [CrossRef] [PubMed]
  117. Fransiri, T.; Pongsiri, A.; Klungthoung, C.; Ponlawat, A.; Thaisomboonsuk, B.; Jarman, R.G.; Scott, T.W.; Lambrechts, L. No evidence for local adaptation of dengue viruses to mosquito vector populations in Thailand. Evol. Appl. 2016, 9, 608–618. [Google Scholar] [CrossRef] [PubMed]
  118. Behura, S.K.; Sarro, J.; Li, P.; Mysore, K.; Severson, D.W.; Emrich, S.J.; Duman-Scheel, M. High-throughput cis-regulatory element discovery in the vector mosquito Aedes aegypti. BMC Genom. 2016. [Google Scholar] [CrossRef] [PubMed]
  119. Behura, S.K.; Severson, D.W. Nucleotide substitutions in dengue virus serotypes from Asian and American countries: Insights into intracodon recombination and purifying selection. BMC Microbiol. 2013. [Google Scholar] [CrossRef] [PubMed]
  120. Lara-Ramirez, E.E.; Salazar, M.I.; Lopez-Lopez, M.J.; Salas-Benito, J.S.; Sanchez-Varela, A.; Guo, X. Large-scale genomic analysis of codon usage in dengue virus and evaluation of its phylogenetic dependence. Biomed. Res. Int. 2014. [Google Scholar] [CrossRef] [PubMed]
  121. Behura, S.K.; Severson, D.W. Bicluster pattern of codon context usages between flavivirus and vector mosquito Aedes aegypti: Relevance to infection and transcriptome response of mosquito genes. Mol. Genet. Genom. 2014, 289, 885–894. [Google Scholar] [CrossRef] [PubMed]
  122. Shen, S.H.; Stauft, C.B.; Gorbatsevych, O.; Song, Y.; Ward, C.B.; Yurovsky, A.; Mueller, S.; Futcher, B.; Wimmer, E. Large-scale recoding of an arbovirus genome to rebalance its insect versus mammalian preference. Proc. Natl. Acad. Sci. USA 2015, 112, 4749–4754. [Google Scholar] [CrossRef] [PubMed]
  123. Vasilakis, N.; Deardorff, E.R.; Kenney, J.L.; Rossi, S.L.; Hanley, K.A.; Weaver, S.C. Mosquitoes put the brake on arbovirus evolution: Experimental evolution reveals slower mutation accumulation in mosquito than vertebrate cells. PLoS Pathog. 2009. [Google Scholar] [CrossRef] [PubMed]
  124. Adelman, Z.N.; Jasinskiene, N.; James, A.A. Development and applications of transgenesis in the yellow fever mosquito, Aedes aegypti. Mol. Biochem. Parasitol. 2002, 121, 1–10. [Google Scholar] [CrossRef]
  125. Burt, B. Heritable strategies for controlling insect vectors of disease. Philos. Trans. R. Soc. B 2014. [Google Scholar] [CrossRef]
  126. Moreira, L.A.; Ghosh, A.K.; Abraham, E.G.; Jacobs-Lorena, M. Genetic transformation of mosquitoes: A quest for malaria control. Int. J. Parasitol. 2002, 32, 1599–1605. [Google Scholar] [CrossRef]
  127. Robinson, A.S.; Franz, G.; Atkinson, P.W. Insect transgenesis and its potential role in agriculture and human health. Insect Biochem. Mol. Biol. 2004, 34, 113–120. [Google Scholar] [CrossRef] [PubMed]
  128. Dinglasan, R.R.; Jacobs-Lorena, M. Flipping the paradigm on malaria transmission-blocking vaccines. Trends Parasitol. 2008, 24, 364–370. [Google Scholar] [CrossRef] [PubMed]
  129. Terenius, O.; Marinotti, O.; Sieglaff, D.; James, A.A. Molecular genetic manipulation of vector mosquitoes. Cell Host Microbe 2014, 4, 417–423. [Google Scholar] [CrossRef] [PubMed]
  130. Scott, T.W.; Takken, W.; Knols, B.G.J.; Boete, C. The ecology of genetically modified mosquitoes. Science 2002, 298, 117–119. [Google Scholar] [CrossRef] [PubMed]
  131. Murdock, C.C.; Paaijmans, K.P.; Cox-Foster, D.; Read, A.F.; Thomas, M.B. Rethinking vector immunology: The role of environmental temperature in shaping resistance. Nat. Rev. Microbiol. 2012, 10, 869–876. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Physical chromosome locations of anchor markers for QTL conditioning vector competence to DENV-2, the protozoan parasite Plasmodium gallinaceum, and the metazoan parasite Brugia malayi. Adapted from [77].
Figure 1. Physical chromosome locations of anchor markers for QTL conditioning vector competence to DENV-2, the protozoan parasite Plasmodium gallinaceum, and the metazoan parasite Brugia malayi. Adapted from [77].
Insects 07 00058 g001
Figure 2. DENV infection and replication cycle in A. aegypti. Compiled from [69,79,83,84].
Figure 2. DENV infection and replication cycle in A. aegypti. Compiled from [69,79,83,84].
Insects 07 00058 g002
Table 1. Broad-scale transcriptome assays of the innate immune response of Aedes aegypti to dengue virus infection.
Table 1. Broad-scale transcriptome assays of the innate immune response of Aedes aegypti to dengue virus infection.
StudyAedes aegypti strain(s)Strain SusceptibilityDengue Strain 3Mosquito InfectionSample Point(s) Post-Infection and TissuesTranscriptome Assay
[90]RockefellerSusceptible 1Aoral10 days, midgutAgilent microarrays
10 days, carcass
[91]RockefellerSusceptibleAoral3 days, 7 days, whole bodyAgilent microarrays
[95]CaliSusceptibleAoral48 h, midgutSuppressive subtractive hybridization
[92]RockefellerSusceptibleAinjection1 day, 2 days, 7 days, whole bodyNimbleGen
[96]Moyo-RRefractoryBoral3 h, 18 h, whole bodyNimbleGen
[98]Moyo-DRefractoryBoral1 h, 4 h, 1 day, 2 days, 4 days, midgutCustom cDNA microarrays
[93]ChetumalSusceptibleBoral1 day, 4 days, midgutIllumina, RNA-Seq
14 days, salivary glands
1 day, 4 days, 14 days, carcass
[94]RockefellerSusceptibleAoral14 days, salivary glandsAgilent microarrays
14 days, carcass
[99]RockefellerHigh 2Aoral7 days, midgutAgilent microarrays
OrlandoLow 7 days, carcass
Puerto RicoIntermediate
Saint KittsIntermediate
Por FinIntermediate
Puerto TriunfoHigh
[97]D2S3SusceptibleBoral3 h, 3 days, midgutCustom cDNA microarrays
1 Susceptible vs. refractory status based on dissemination from the midgut; 2 High, intermediate, low status based on midgut titers relative to Rockefeller strain; 3 A = DENV-2 New Guinea C, B = DENV-2 JAM 1409.

Share and Cite

MDPI and ACS Style

Severson, D.W.; Behura, S.K. Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches. Insects 2016, 7, 58.

AMA Style

Severson DW, Behura SK. Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches. Insects. 2016; 7(4):58.

Chicago/Turabian Style

Severson, David W., and Susanta K. Behura. 2016. "Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches" Insects 7, no. 4: 58.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop