Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 May 28;15(6):393.
doi: 10.3390/insects15060393.

Dengue Virus Serotype 1 Effects on Mosquito Survival Differ among Geographically Distinct Aedes aegypti Populations

Milan S G Keirsebelik  1   2 , Mariana R David  1 , Márcio Galvão Pavan  1 , Dinair Couto-Lima  1 , Miriam Palomino  3 , Rafi Ur Rahman  4 , Ary A Hoffmann  5 , Ana C Bahia  6 , Guy Caljon  2 , Rafael Maciel-de-Freitas  1   7
Affiliations

Dengue Virus Serotype 1 Effects on Mosquito Survival Differ among Geographically Distinct Aedes aegypti Populations

Milan S G Keirsebelik et al. Insects. .

Abstract

The mosquito Aedes aegypti is distributed worldwide and is recognized as the primary vector for dengue in numerous countries. To investigate whether the fitness cost of a single DENV-1 isolate varies among populations, we selected four Ae. aegypti populations from distinct localities: Australia (AUS), Brazil (BRA), Pakistan (PAK), and Peru (PER). Utilizing simple methodologies, we concurrently assessed survival rates and fecundity. Overall, DENV-1 infection led to a significant decrease in mosquito survival rates, with the exception of the PER population. Furthermore, infected Ae. aegypti from PAK, the population with the lowest infection rate among those tested, exhibited a noteworthy reduction in egg laying. These findings collectively suggest that local mosquito-virus adaptations may influence dengue transmission in endemic settings.

Keywords: Aedes aegypti; dengue; fecundity; mosquito-virus interaction; survival; vector competence; vectorial capacity.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
DENV-1 copies per population. Each dot represents a DENV-1 infected mosquito. No statistical difference in DENV-1 load was found among the populations (H = 6.1, df = 3, p-value = 0.107). The dark line represents the median DENV-1 load per population.
Figure 2
Figure 2
Kaplan–Meier survival curves depicting the survival probability of control (blue) and DENV-exposed mosquitoes (red).
Figure 3
Figure 3
Cox proportional hazard ratios. Pop: comparing mortality among populations with AUS as reference; DENV_Exp: showing a significant cumulative risk increase for the event of death to occur in individuals exposed to DENV-1 as opposed to the control populations. Wing: demonstrating a significant increase in the event of death in larger mosquito individuals. Error bars represent a 95% confidence interval. N = Number of mosquitos used, AUS = Australia; BRA = Brazil; PAK = Pakistan; PER= Peru. *p < 0.05; *** p < 0.001.
Figure 4
Figure 4
Survival analysis and Cox regressions by population. Left figures indicate survival probability over time (days) with log-rank p-values, right figures show the corresponding Cox models with the respective hazard ratio for treatments and wing length. In the infection status, the control group was used as a reference. Wing length was used as a covariate but showed no influence on mosquito mortality for the populations. Note that the cumulative hazard for the event of death to occur did not rise significantly for PER mosquitoes, differently from the other populations tested. Error bars represent a 95% confidence interval. N = Number of mosquitos used. AUS = Australia; BRA = Brazil; PAK = Pakistan; PER = Peru. * p < 0.05; *** p < 0.001.
Figure 5
Figure 5
Linear regression showing the effect of wing size on Ae. aegypti mortality from the four tested populations. The shaded area represents the 95% confidence level interval for predictions from a linear model. AUS = Australia; BRA = Brazil; PAK = Pakistan; PER = Peru; Pop = Population.
Figure 6
Figure 6
Box plot of fecundity comparing all females in a population with each other and infection status as well as with females in other populations. The only population where we saw a significant difference between status was the Pakistan population (W = 468, p-value = 0.0167). AUS = Australia; BRA = Brazil; PAK = Pakistan; PER = Peru; Pop= Population. The asterisk represents a p < 0.05.
See this image and copyright information in PMC

References

    1. Weaver S.C., Charlier C., Vasilakis N., Lecuit M. Zika, Chikungunya, and Other Emerging Vector-Borne Viral Diseases. Annu. Rev. Med. 2018;69:395–408. doi: 10.1146/annurev-med-050715-105122. - DOI - PMC - PubMed
    1. Souza-Neto J.A., Powell J.R., Bonizzoni M. Aedes Aegypti Vector Competence Studies: A Review. Infect. Genet. Evol. 2019;67:191–209. doi: 10.1016/j.meegid.2018.11.009. - DOI - PMC - PubMed
    1. 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. doi: 10.1038/nature12060. - DOI - PMC - PubMed
    1. Brady O.J., Hay S.I. The Global Expansion of Dengue: How Aedes Aegypti Mosquitoes Enabled the First Pandemic Arbovirus. Annu. Rev. Entomol. 2020;65:191–208. doi: 10.1146/annurev-ento-011019-024918. - DOI - PubMed
    1. Golding N., Wilson A.L., Moyes C.L., Cano J., Pigott D.M., Velayudhan R., Brooker S.J., Smith D.L., Hay S.I., Lindsay S.W. Integrating Vector Control across Diseases. BMC Med. 2015;13:249. doi: 10.1186/s12916-015-0491-4. - DOI - PMC - PubMed

LinkOut - more resources