Singapore : a large proportion of the population is susceptible to DENV3 infection


Singapore saw 1,158 dengue cases in the week ending 13 June 2020, the highest number of weekly dengue cases ever recorded since 2014.

The dengue virus serotype 3 (DENV3), which is currently circulating in Singapore, can undergo dramatic structural changes that enable it to resist vaccines and therapeutics, reveal findings from a study by scientists from Duke-NUS Medical School.

The findings, published in Nature Communications, could guide the development of effective vaccines and therapeutics against dengue infection.

Dengue infections are rising, even as public health authorities are battling to contain the spread of the coronavirus. Dengue virus serotype 2 (DENV2) had previously been the predominant serotype but DENV3 has re-emerged in Singapore after almost three decades.

This means the Singapore population has lower immunity to DENV3 and, consequently, a large proportion of the population is susceptible to DENV3 infection.

So far, there are no highly protective vaccines or therapeutic agents that target DENV. This is due to the possibility that antibodies raised against any one of the four known serotypes (DENV1-4) may enhance disease severity when an individual is infected with a different serotype in a secondary infection.

This suggests an effective vaccine has to be able to stimulate equally strong protective responses simultaneously against all four serotypes. Adding further complication to vaccine development is the fact that there are different virus strains within each serotype, and different strains can exhibit vastly different shapes, enabling them to escape detection by a host’s immune system.

The Duke-NUS team had previously discovered that the surface of the DENV2 can change from smooth to bumpy depending on host conditions.

“Previous structural work focused mostly on DENV2, and therefore the other serotypes that are equally important are not well studied,” said Professor Sheemei Lok from the Duke-NUS’ Emerging Infectious Diseases (EID) program and corresponding author of this study.

“In this study, we found that DENV3 can dramatically transform itself from a smooth, round particle to a club-shaped particle—like golf clubs, which would help the virus to evade hosts’ immune response, vaccines and therapeutics.”

The team also found some strains capable of transforming into club-shaped particles in DENV1, DENV2 and zika, though these exist as a minority of the virus population.

Nonetheless, this suggests that flaviviruses have the potential to turn themselves into a conformation that is vastly different from their original structure, which can make vaccines and therapeutics ineffective against them.

“While Singapore has seen a recent spike in dengue cases, annually this virus infects about 400 million people worldwide, with a high prevalence in tropical and sub-tropical regions. In line with Duke-NUS vision of transforming medicine, this study gives new direction to developing better therapies and vaccines to treat or prevent dengue infections, and contribute to public health outcomes,” said Prof Patrick Casey, Senior Vice Dean for Research at Duke-NUS.

The team is currently studying more DENV3 clinical strains to determine if this structural transformation is common.

In many invertebrate host-pathogen systems, infection success depends on the specific pairing of host and pathogen genotypes [1]. Such genotype-by-genotype (G x G) interactions have been observed, for example, between crustaceans and bacteria [2], bumblebees and intestinal trypanosomes [3], nematodes and bacteria [4], anopheline mosquitoes and malaria parasites [5, 6] and butterflies and protozoan parasites [7]. In some instances, G x G interactions can result in extreme levels of host-pathogen specificity [8].

Understanding this genetic specificity in invertebrate host-pathogen systems has generated great enthusiasm because it may uncover new facets of invertebrate immunity [9, 10].

Although invertebrates lack the adaptive immunity of vertebrates, their immune system can generate a considerable diversity of immune receptors, revealing an unsuspected molecular complexity [11, 12].

Alternatively, G x G interactions could be mediated by variation in the host microbiota [13] or any other interplay between host and pathogen genomes. G x G interactions can be detected at the level of gene expression [14] and mapped to physical locations in the host genome [15–17].

Accumulating observations on G x G interactions have led to some controversy [18–20] because they challenge the prevailing view that invertebrate defense against pathogens relies on broad-spectrum recognition and effector mechanisms.

A central aspect of the controversy is that the molecular mechanisms underlying G x G interactions between invertebrate hosts and pathogens are yet to be elucidated.

We previously documented significant G x G interactions between dengue virus (DENV) and its main mosquito vector Aedes aegypti [21, 22]. Both DENV and Ae. aegypti are genetically diverse in nature. DENV exists worldwide as four genetic types (DENV-1, DENV-2, DENV-3, and DENV-4) that loosely cluster antigenically [23] and are often referred to as serotypes.

The mosquito Ae. aegypti consists of two major genetic subspecies that contain substantial genetic diversity [24]. In the last few decades, DENV has become a major public health threat worldwide with an estimated 390 million human infections per year [25].

The lack of an efficient vaccine and the failure of insecticide-based methods to control mosquito populations on the long term have stimulated basic research to develop novel vector control strategies [26]. One of these strategies aims at rendering mosquitoes resistant to pathogen infection [27].

The premise of this strategy makes it critical to understand G x G interactions because engineered mosquito resistance should be effective against all possible pathogen genotypes.

Dissecting the genetic basis of G x G interactions between DENV and Ae. aegypti was previously hampered by the large size of the Ae. aegypti genome and the paucity of genetic markers available [28].

Although G x G interactions between DENV and Ae. aegypti were statistically assigned to individual mosquito genetic markers [15, 17], the specific mosquito genes underlying these quantitative trait loci (QTL) have not been identified. In particular, it is unknown whether DENV type- or strain-specific resistance relies on allelic variants of the same genes or on distinct gene sets.

Here, we combined a natural phenotype of DENV type-specific resistance in Ae. aegypti and the power of high-throughput sequencing to provide insights into the genetic architecture of G x G interactions in this system.

We previously established a laboratory colony from a wild Ae. aegypti population in Bakoumba, Gabon that is differentially susceptible to DENV types. Using dose-response experiments, we found the Bakoumba population to be strongly resistant to DENV-1 and only moderately resistant to DENV-3 infection.

We took advantage of this field-derived colony to investigate the genetic basis for discriminating between different DENV types. We used a modified genome-wide association study design, in which replicate pools of individuals with contrasted phenotypes are pooled by phenotype and analyzed for differences in allele frequencies [29, 30].

We compared the genetic basis of Bakoumba resistance to DENV-1 and DENV-3 from extremes of the phenotypic distribution (i.e., resistant = uninfected at a high virus dose vs. susceptible = infected at a low virus dose).

We estimated and compared allele frequencies among the phenotypic pools using the contrast statistic recently implemented in the software BayPass [31, 32]. Because the genome of Ae. aegypti is large and repetitive, we performed exome sequencing as a cost-effective genotyping method targeting the exons of all protein-coding genes [33], as was previously implemented in Ae. aegypti [34–36].

We combined SNP-specific contrasts of allele frequency to compute gene-wide scores reflecting the statistical significance of association with DENV-1 and/or DENV-3 infection. The results of our exome-wide association study (EWAS) show that largely distinct gene sets underlie specific resistance to DENV-1 and DENV-3 infection in this Ae. aegypti population.

Our EWAS revealed that the DENV type-specific resistance phenotype displayed by an Ae. aegypti population from Bakoumba, Gabon reflects a distinct genetic architecture of resistance to DENV-1 and DENV-3 infection.

The midgut infection phenotype we focused on is an important component of vector competence, which also depends on subsequent virus dissemination from the midgut and virus release in saliva [37].

We unveiled a set of SNPs and genes that are significantly associated with DENV-1 and/or DENV-3 infection in the Bakoumba population, which open the way to future studies to functionally characterize the genetic basis of DENV type-specific resistance.

The overlap between SNPs and genes associated with resistance to either DENV-1 or DENV-3 was only partial and demonstrated that DENV type-specific resistance relies on both shared and unique genes in this Ae. aegypti population.

Although the mechanisms of DENV type-specific resistance in Ae. aegypti remain to be elucidated, this study is a leap forward to understand G x G specificity between Ae. aegypti and DENV at the molecular level.

G x G specificity between pathogens and their invertebrate hosts has been observed in many systems [1], but to date the molecular nature of this specificity is largely unknown. We previously detected G x G interactions between DENV and Ae. aegypti [21, 22] that could be statistically associated with QTL in the mosquito genome [15, 17].

However, the specific mosquito genes underlying these QTL have not been identified. One important question to elucidate the genetic basis of host-pathogen specificity is whether pathogen genotype-specific resistance relies on different alleles or different genes of the host.

In the “matching-allele” model of host-pathogen interactions, a resistant allele against a given pathogen strain becomes a susceptible allele against another strain of the same pathogen [38].

This was observed, for example, by experimental viral evolution to specific mouse MHC genotypes [39] and by genetic crosses between genotypes of the crustacean Daphnia magna with different levels of resistance to the parasitic bacterium Pasteuria ramosa [40, 41].

In other host-pathogen systems, host resistance to different strains of the same pathogen relies on allelic variation at different genes. For example, genome-to-genome analysis of associations between human genetic variation and HIV-1 sequence found SNPs in different HLA class I genes [42]. Likewise, Arabidopsis thaliana SNPs exhibited genetic effects only when paired with certain Xanthomonas arboricola variants [43].

In the mosquito Anopheles gambiae, discrimination between human and rodent malaria species was shown to rely on different paralogs of the APL1 gene family [44]. Resistant and susceptible alleles of the TEP1 gene of An. gambiae explained resistance to some but not all strains of the human malaria parasite Plasmodium falciparum [45, 46].

We took advantage of the striking DENV type-specific phenotype of our Bakoumba Ae. aegypti colony to use it as a simplified model of G x G interactions that could be subjected to a genetic association study. Note that in this study, we focused on the host factors involved in the G x G interaction but the virus factors remain to be elucidated.

We found that in the Bakoumba population, about half of the genes associated with resistance to DENV-1 infection did not confer resistance to DENV-3 infection and vice versa. Whether the genetic architecture of DENV type-specific resistance in the Bakoumba population is representative of G x G interactions between Ae. aegypti and DENV, and in other invertebrate host-pathogen systems in general, is unknown.

Additional work will be necessary to extend these results to other mosquito populations, other DENV types and strains, and other host-pathogen systems. Moreover, our association study focused on the discovery of SNPs in exons, which represent only about 2% of the entire Ae. aegypti genome [17, 28].

It is possible that our exome-sequencing approach may have missed important genetic determinants underlying DENV type-specific resistance because they are not readily detected by SNPs (e.g., structural variants) and/or they occur in introns or intergenic regions.

As sequencing technologies become more affordable, whole-genome sequencing will allow more comprehensive surveys of genetic variation in the Ae. aegypti genome. Nevertheless, detection of different exome variants associated with resistance to DENV-1 and resistance to DENV-3 is sufficient to support our conclusion that their respective genetic architecture is distinct.

It is worth noting that regardless of the biases introduced by exome sequencing, these biases are consistent across experimental conditions. In other words, comparing the genetic basis of resistance to DENV-1 infection to the genetic basis of resistance to DENV-3 infection remains valid despite shortcomings in the genotyping method, because it was performed with the same initial population.

Our finding that only about one third of the top 5% genes was jointly associated with both DENV-1 resistance and DENV-3 resistance cannot be explained by differences in genetic ascertainment because for both DENV types the genes were identified with the same set of SNPs in the same population.

The bulk of significant SNPs and genes were found on chromosome 1, particularly around the centromere. This observation could be due to at least two, non-mutually exclusive explanations. First, most of the genetic loci underlying DENV susceptibility in the Bakoumba population could be truly located on chromosome 1.

QTL associated with DENV susceptibility in Ae. aegypti were previously detected on all three chromosomes [15, 17, 47, 48], and the genetic architecture of pathogen susceptibility is known to vary across host populations [49]. Second, the centromeric region of chromosome 1 contains the M locus responsible for sex determination in Ae. aegypti [17, 50].

We previously reported that the M locus is surrounded by a large region of reduced recombination between the sex chromosomes, which is associated with sex-specific genetic differentiation and elevated linkage disequilibrium (LD) over about 100 Mb in natural Ae. aegypti populations [51].

Because statistical power to detect genotype-phenotype associations increases with LD, it is possible that elevated LD may have inflated the proportion of significant genotype-phenotype associations in the centromeric region of chromosome 1. Nevertheless, as mentioned above, comparisons using the same population and the same markers remain valid because any genotyping bias should be consistent across experimental conditions.

The candidate genes that we identified deserve further investigation at the functional level. Although a genetic association does not necessarily imply differential expression, it would be interesting to determine whether candidate genes also display allelic differences in gene expression.

Gene knockdown assays could be used to confirm the functional implication of the candidate genes [52, 53], although gene knockouts would provide a more definitive answer [54] because they are less prone to false negatives.

Mosquito genes uniquely associated with resistance to DENV-3 infection were enriched in genes with zinc ion binding activity, whereas genes associated with resistance to both DENV-1 and DENV-3 infection were enriched in genes with ATP binding activity and sulfur compound transmembrane transporter activity.

Zinc is an essential cofactor that ensures the proper folding and functioning of not only cellular proteins but also viral proteins [55]. To our knowledge, there is no prior evidence for a link between zinc ion binding activity and mosquito-virus interactions, however host cellular systems controlling zinc balance are known to interfere with virus replication [55].

Likewise, ATP binding activity and sulfur compound transmembrane transporter activity have not been specifically reported to participate in mosquito-virus interactions, however the high dependence of viruses on the cellular machinery makes any molecular function potentially relevant to host-virus interactions.

Although the forces driving the evolution of DENV resistance in Ae. aegypti are largely unknown, one evolutionary implication of the distinct gene set underlying resistance to DENV-1 and DENV-3 is that the evolution of resistance to one DENV type is not expected to lead to the correlated evolution of resistance to another DENV type.

This finding is consistent with the absence of virus cross-resistance [56] and the lack of genetic trade-offs between the levels of resistance to different viral genotypes [57] in Drosophila.

The epidemiological relevance of our results is difficult to assess because dengue epidemiology is poorly documented in Gabon. A recent study reported DENV-3 circulation in 2016–2017 [58] whereas previous dengue outbreaks were mainly associated with DENV-2 in 2007 and in 2010 [59], but this information is insufficient to make a link between the DENV-1 resistance phenotype of the Bakoumba population and the relative lack of this DENV type in recently reported outbreaks in Gabon.

In our experiments, we used a DENV-1 isolate from Thailand and a DENV-3 isolate from Gabon but the geographical origin of the virus is unlikely to have influenced the results due to the lack of evidence for DENV local adaptation to Ae. aegypti populations [60].

In conclusion, our results support a model where the genetic basis of resistance to DENV infection in Ae. aegypti has a “universal” component that acts across types and strains, and a type- or strain-specific component [15–17].

In the Bakoumba population, the DENV type-specific component of resistance consists, at least in part, of a distinct set of genes. Our gene enrichment analysis did not identify a functional overlap between the genes uniquely associated with DENV-1 resistance, uniquely associated with DENV-3 resistance, or associated with both.

We speculate that Ae. aegypti resistance to DENV infection may involve different pathways and different molecular mechanisms. Probing this hypothesis will require follow-up studies to functionally test the effect of candidate genes by reverse genetics.


1. Lambrechts L. Dissecting the genetic architecture of host-pathogen specificity. PLoS Pathog. 2010;6(8):e1001019 10.1371/journal.ppat.1001019 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

2. Carius HJ, Little TJ, Ebert D. Genetic variation in a host-parasite association: potential for coevolution and frequency-dependent selection. Evolution. 2001;55(6):1136–45. 10.1111/j.0014-3820.2001.tb00633.x . [PubMed] [CrossRef] [Google Scholar]

3. Schmid-Hempel P. On the evolutionary ecology of host-parasite interactions: addressing the question with regard to bumblebees and their parasites. Naturwissenschaften. 2001;88(4):147–58. Epub 2001/08/02. 10.1007/s001140100222 . [PubMed] [CrossRef] [Google Scholar]

4. Schulenburg H, Ewbank JJ. Diversity and specificity in the interaction between Caenorhabditis elegans and the pathogen Serratia marcescens. BMC Evol Biol. 2004;4(1):49 10.1186/1471-2148-4-49 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

5. Harris C, Lambrechts L, Rousset F, Abate L, Nsango SE, Fontenille D, et al. Polymorphisms in Anopheles gambiae Immune Genes Associated with Natural Resistance to Plasmodium falciparum. PLoS Pathog. 2010;6(9). 10.1371/journal.ppat.1001112 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

6. Lambrechts L, Halbert J, Durand P, Gouagna LC, Koella JC. Host genotype by parasite genotype interactions underlying the resistance of anopheline mosquitoes to Plasmodium falciparum. Malar J. 2005;4(1):3 10.1186/1475-2875-4-3 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

7. de Roode JC, Altizer S. Host-parasite genetic interactions and virulence-transmission relationships in natural populations of Monarch butterflies. Evolution. 2009;64(2):502–14. 10.1111/j.1558-5646.2009.00845.x . [PubMed] [CrossRef] [Google Scholar]

8. Luijckx P, Ben-Ami F, Mouton L, Du Pasquier L, Ebert D. Cloning of the unculturable parasite Pasteuria ramosa and its Daphnia host reveals extreme genotype-genotype interactions. Ecol Lett. 2011;14(2):125–31. 10.1111/j.1461-0248.2010.01561.x . [PubMed] [CrossRef] [Google Scholar]

9. Little TJ, Hultmark D, Read AF. Invertebrate immunity and the limits of mechanistic immunology. Nat Immunol. 2005;6(7):651–4. 10.1038/ni1219 . [PubMed] [CrossRef] [Google Scholar]

10. Schulenburg H, Boehnisch C, Michiels NK. How do invertebrates generate a highly specific innate immune response? Mol Immunol. 2007;44(13):3338–44. Epub 2007/03/30. 10.1016/j.molimm.2007.02.019 . [PubMed] [CrossRef] [Google Scholar]

11. Dong Y, Taylor HE, Dimopoulos G. AgDscam, a hypervariable immunoglobulin domain-containing receptor of the Anopheles gambiae innate immune system. PLoS Biol. 2006;4(7):e229 Epub 2006/06/16. 10.1371/journal.pbio.0040229 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

12. Watson F, Püttmann-Holgado R, Thomas F, Lamar D, Hughes M, Kondo M, et al. Extensive diversity of Ig-superfamily proteins in the immune system of insects. Science. 2005;309(5742):1874–8. 10.1126/science.1116887 [PubMed] [CrossRef] [Google Scholar]

13. Koch H, Schmid-Hempel P. Gut microbiota instead of host genotype drive the specificity in the interaction of a natural host-parasite system. Ecol Lett. 2012;15(10):1095–103. Epub 2012/07/07. 10.1111/j.1461-0248.2012.01831.x . [PubMed] [CrossRef] [Google Scholar]

14. Barribeau SM, Sadd BM, du Plessis L, Schmid-Hempel P. Gene expression differences underlying genotype-by-genotype specificity in a host-parasite system. Proc Natl Acad Sci U S A. 2014;111(9):3496–501. Epub 2014/02/20. 10.1073/pnas.1318628111 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

15. Fansiri T, Fontaine A, Diancourt L, Caro V, Thaisomboonsuk B, Richardson JH, et al. Genetic Mapping of Specific Interactions between Aedes aegypti Mosquitoes and Dengue Viruses. PLoS Genet. 2013;9(8):e1003621 Epub 2013/08/13. 10.1371/journal.pgen.1003621 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

16. Lambrechts L, Quillery E, Noel V, Richardson JH, Jarman RG, Scott TW, et al. Specificity of resistance to dengue virus isolates is associated with genotypes of the mosquito antiviral gene Dicer-2. Proc Biol Sci. 2013;280(1751):20122437 Epub 2012/11/30. 10.1098/rspb.2012.2437 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

17. Matthews BJ, Dudchenko O, Kingan SB, Koren S, Antoshechkin I, Crawford JE, et al. Improved reference genome of Aedes aegypti informs arbovirus vector control. Nature. 2018;563(7732):501–7. Epub 2018/11/16. 10.1038/s41586-018-0692-z . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

18. Hauton C, Smith VJ. Adaptive immunity in invertebrates: a straw house without a mechanistic foundation. Bioessays. 2007;29(11):1138–46. Epub 2007/10/16. 10.1002/bies.20650 . [PubMed] [CrossRef] [Google Scholar]

19. Little TJ, Colegrave N, Sadd BM, Schmid-Hempel P. Studying immunity at the whole organism level. Bioessays. 2008;30(4):404–5; Epub 2008/03/19. 10.1002/bies.20738 . [PubMed] [CrossRef] [Google Scholar]

20. Schmid-Hempel P. Natural insect host-parasite systems show immune priming and specificity: puzzles to be solved. Bioessays. 2005;27(10):1026–34. 10.1002/bies.20282 . [PubMed] [CrossRef] [Google Scholar]

21. Lambrechts L. Quantitative genetics of Aedes aegypti vector competence for dengue viruses: towards a new paradigm? Trends Parasitol. 2011;27(3):111–4. 10.1016/ . [PubMed] [CrossRef] [Google Scholar]

22. Lambrechts L, Chevillon C, Albright RG, Thaisomboonsuk B, Richardson JH, Jarman RG, et al. Genetic specificity and potential for local adaptation between dengue viruses and mosquito vectors. BMC Evol Biol. 2009;9:160 10.1186/1471-2148-9-160 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

23. Katzelnick LC, Fonville JM, Gromowski GD, Bustos Arriaga J, Green A, James SL, et al. Dengue viruses cluster antigenically but not as discrete serotypes. Science. 2015;349(6254):1338–43. Epub 2015/09/19. 10.1126/science.aac5017 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

24. Gloria-Soria A, Ayala D, Bheecarry A, Calderon-Arguedas O, Chadee DD, Chiappero M, et al. Global genetic diversity of Aedes aegypti. Mol Ecol. 2016;25(21):5377–95. 10.1111/mec.13866 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

25. Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496(7446):504–7. Epub 2013/04/09. 10.1038/nature12060 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

26. Shaw WR, Catteruccia F. Vector biology meets disease control: using basic research to fight vector-borne diseases. Nat Microbiol. 2019;4(1):20–34. Epub 2018/08/29. 10.1038/s41564-018-0214-7 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

27. Kean J, Rainey SM, McFarlane M, Donald CL, Schnettler E, Kohl A, et al. Fighting Arbovirus Transmission: Natural and Engineered Control of Vector Competence in Aedes Mosquitoes. Insects. 2015;6(1):236–78. Epub 2015/10/16. 10.3390/insects6010236 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

28. Nene V, Wortman JR, Lawson D, Haas B, Kodira C, Tu ZJ, et al. Genome sequence of Aedes aegypti, a major arbovirus vector. Science. 2007;316(5832):1718–23. 10.1126/science.1138878 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

29. Schlotterer C, Tobler R, Kofler R, Nolte V. Sequencing pools of individuals—mining genome-wide polymorphism data without big funding. Nat Rev Genet. 2014;15(11):749–63. Epub 2014/09/24. 10.1038/nrg3803 . [PubMed] [CrossRef] [Google Scholar]

30. Sham P, Bader JS, Craig I, O’Donovan M, Owen M. DNA Pooling: a tool for large-scale association studies. Nat Rev Genet. 2002;3(11):862–71. Epub 2002/11/05. 10.1038/nrg930 . [PubMed] [CrossRef] [Google Scholar]

31. Gautier M. Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics. 2015;201(4):1555–79. Epub 2015/10/21. 10.1534/genetics.115.181453 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

32. Olazcuaga L, Loiseau A, Parrinello H, Paris M, Fraimout A, Guedot C, et al. A whole-genome scan for association with invasion success in the fruit fly Drosophila suzukii using contrasts of allele frequencies corrected for population structure. Mol Biol Evol. msaa098. In press. Epub 2020/04/17. 10.1093/molbev/msaa098 [PubMed] [CrossRef] [Google Scholar]

33. Warr A, Robert C, Hume D, Archibald A, Deeb N, Watson M. Exome Sequencing: Current and Future Perspectives. G3. 2015;5(8):1543–50. Epub 2015/07/04. 10.1534/g3.115.018564 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

34. Crawford JE, Alves JM, Palmer WJ, Day JP, Sylla M, Ramasamy R, et al. Population genomics reveals that an anthropophilic population of Aedes aegypti mosquitoes in West Africa recently gave rise to American and Asian populations of this major disease vector. BMC Biol. 2017;15(1):16 10.1186/s12915-017-0351-0 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

35. Dickson LB, Campbell CL, Juneja P, Jiggins FM, Sylla M, Black WC. Exon-Enriched Libraries Reveal Large Genic Differences Between Aedes aegypti from Senegal, West Africa, and Populations Outside Africa. G3. 2017;7(2):571–82. 10.1534/g3.116.036053 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

36. Juneja P, Ariani CV, Ho YS, Akorli J, Palmer WJ, Pain A, et al. Exome and Transcriptome Sequencing of Aedes aegypti Identifies a Locus That Confers Resistance to Brugia malayi and Alters the Immune Response. PLoS Pathog. 2015;11(3):e1004765 Epub 2015/03/31. 10.1371/journal.ppat.1004765 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

37. Black WC, Bennett KE, Gorrochotegui-Escalante N, Barillas-Mury CV, Fernandez-Salas I, de Lourdes Munoz M, et al. Flavivirus susceptibility in Aedes aegypti. Arch Med Res. 2002;33(4):379–88. 10.1016/s0188-4409(02)00373-9 . [PubMed] [CrossRef] [Google Scholar]

38. Agrawal A, Lively CM. Infection genetics: gene-for-gene versus matching-alleles models and all points in between. Evol Ecol Res. 2002;4:79–90. [Google Scholar]

39. Kubinak JL, Ruff JS, Hyzer CW, Slev PR, Potts WK. Experimental viral evolution to specific host MHC genotypes reveals fitness and virulence trade-offs in alternative MHC types. Proc Natl Acad Sci U S A. 2012;109(9):3422–7. Epub 2012/02/11. 10.1073/pnas.1112633109 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

40. Bento G, Routtu J, Fields PD, Bourgeois Y, Du Pasquier L, Ebert D. The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model. PLoS Genet. 2017;13(2):e1006596 Epub 2017/02/22. 10.1371/journal.pgen.1006596 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

41. Luijckx P, Fienberg H, Duneau D, Ebert D. A matching-allele model explains host resistance to parasites. Curr Biol. 2013;23(12):1085–8. Epub 2013/05/28. 10.1016/j.cub.2013.04.064 . [PubMed] [CrossRef] [Google Scholar]

42. Bartha I, Carlson JM, Brumme CJ, McLaren PJ, Brumme ZL, John M, et al. A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control. eLife. 2013;2:e01123 Epub 2013/10/31. 10.7554/eLife.01123 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

43. Wang M, Roux F, Bartoli C, Huard-Chauveau C, Meyer C, Lee H, et al. Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes. Proc Natl Acad Sci U S A. 2018;115(24):E5440–E9. Epub 2018/06/01. 10.1073/pnas.1710980115 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

44. Mitri C, Jacques JC, Thiery I, Riehle MM, Xu J, Bischoff E, et al. Fine pathogen discrimination within the APL1 gene family protects Anopheles gambiae against human and rodent malaria species. PLoS Pathog. 2009;5(9):e1000576 Epub 2009/09/15. 10.1371/journal.ppat.1000576 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

45. Molina-Cruz A, DeJong RJ, Ortega C, Haile A, Abban E, Rodrigues J, et al. Some strains of Plasmodium falciparum, a human malaria parasite, evade the complement-like system of Anopheles gambiae mosquitoes. Proc Natl Acad Sci U S A. 2012;109(28):E1957–62. Epub 2012/05/25. 10.1073/pnas.1121183109 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

46. White BJ, Lawniczak MK, Cheng C, Coulibaly MB, Wilson MD, Sagnon N, et al. Adaptive divergence between incipient species of Anopheles gambiae increases resistance to Plasmodium. Proc Natl Acad Sci U S A. 2010;108(1):244–9. 10.1073/pnas.1013648108 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

47. Bosio CF, Fulton RE, Salasek ML, Beaty BJ, Black WC. Quantitative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti. Genetics. 2000;156(2):687–98. . [PMC free article] [PubMed] [Google Scholar]

48. Gomez-Machorro C, Bennett KE, del Lourdes Munoz M, Black WC. Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti. Insect Mol Biol. 2004;13(6):637–48. 10.1111/j.0962-1075.2004.00522.x . [PubMed] [CrossRef] [Google Scholar]

49. Wilfert L, Schmid-Hempel P. The genetic architecture of susceptibility to parasites. BMC Evol Biol. 2008;8:187 10.1186/1471-2148-8-187 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

50. Hall AB, Basu S, Jiang X, Qi Y, Timoshevskiy VA, Biedler JK, et al. A male-determining factor in the mosquito Aedes aegypti. Science. 2015;348(6240):1268–70. Epub 2015/05/23. 10.1126/science.aaa2850 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

51. Fontaine A, Filipovic I, Fansiri T, Hoffmann AA, Cheng C, Kirkpatrick M, et al. Extensive Genetic Differentiation between Homomorphic Sex Chromosomes in the Mosquito Vector, Aedes aegypti. Genome biology and evolution. 2017;9(9):2322–35. 10.1093/gbe/evx171 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

52. Merkling SH, Raquin V, Dabo S, Henrion-Lacritick A, Blanc H, Moltini-Conclois I, et al. Tudor-SN Promotes Early Replication of Dengue Virus in the Aedes aegypti Midgut. iScience. 2020;23(2):100870 Epub 2020/02/15. 10.1016/j.isci.2020.100870 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

53. Raquin V, Merkling SH, Gausson V, Moltini-Conclois I, Frangeul L, Varet H, et al. Individual co-variation between viral RNA load and gene expression reveals novel host factors during early dengue virus infection of the Aedes aegypti midgut. PLoS Negl Trop Dis. 2017;11(12):e0006152 Epub 2017/12/21. 10.1371/journal.pntd.0006152 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

54. Kistler KE, Vosshall LB, Matthews BJ. Genome engineering with CRISPR-Cas9 in the mosquito Aedes aegypti. Cell Rep. 2015;11(1):51–60. Epub 2015/03/31. 10.1016/j.celrep.2015.03.009 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

55. Lazarczyk M, Favre M. Role of Zn2+ ions in host-virus interactions. J Virol. 2008;82(23):11486–94. Epub 2008/09/13. 10.1128/JVI.01314-08 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

56. Cogni R, Cao C, Day JP, Bridson C, Jiggins FM. The genetic architecture of resistance to virus infection in Drosophila. Mol Ecol. 2016;25(20):5228–41. Epub 2016/07/28. 10.1111/mec.13769 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

57. Carpenter JA, Hadfield JD, Bangham J, Jiggins FM. Specific interactions between host and parasite genotypes do not act as a constraint on the evolution of antiviral resistance in Drosophila. Evolution. 2012;66(4):1114–25. Epub 2012/04/11. 10.1111/j.1558-5646.2011.01501.x . [PubMed] [CrossRef] [Google Scholar]

58. Abe H, Ushijima Y, Loembe MM, Bikangui R, Nguema-Ondo G, Mpingabo PI, et al. Re-emergence of dengue virus serotype 3 infections in Gabon in 2016–2017, and evidence for the risk of repeated dengue virus infections. Int J Infect Dis. 2020;91:129–36. Epub 2019/12/11. 10.1016/j.ijid.2019.12.002 . [PubMed] [CrossRef] [Google Scholar]

59. Caron M, Grard G, Paupy C, Mombo IM, Bikie Bi Nso B, Kassa Kassa FR, et al. First evidence of simultaneous circulation of three different dengue virus serotypes in Africa. PLoS ONE. 2013;8(10):e78030 Epub 2013/11/10. 10.1371/journal.pone.0078030 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

60. Fansiri T, Pongsiri A, Klungthong C, Ponlawat A, Thaisomboonsuk B, Jarman RG, et al. No evidence for local adaptation of dengue viruses to mosquito vector populations in Thailand. Evol Appl. 2016;9(4):608–18. Epub 2016/04/22. 10.1111/eva.12360 . [PMC free article] [PubMed] [CrossRef] [Google Scholar]

More information: Seamus R. Morrone et al. High flavivirus structural plasticity demonstrated by a non-spherical morphological variant, Nature Communications (2020). DOI: 10.1038/s41467-020-16925-y


Please enter your comment!
Please enter your name here

Questo sito usa Akismet per ridurre lo spam. Scopri come i tuoi dati vengono elaborati.