|Year : 2018 | Volume
| Issue : 3 | Page : 184-188
A laboratory simulation study on suppression of resistance genes by differential exposures to an insecticide in Anopheles stephensi Liston population
Vaishali Verma1, OP Agrawal2, Poonam Sharma Velamuri1, Kamaraju Raghavendra1
1 ICMR–National Institute of Malaria Research, New Delhi, India
2 School of Studies in Zoology, Jiwaji University, Gwalior, Madhya Pradesh, India
|Date of Submission||12-Dec-2017|
|Date of Acceptance||16-May-2018|
|Date of Web Publication||4-Jan-2019|
Raghavendra, Scientist ‘G’, Vector Control Division, ICMR-National Institute of Malaria Research, Sector-8, Dwarka, New Delhi-110 077
Source of Support: None, Conflict of Interest: None
Background & objectives: Insecticide applied at optimum dosage and coverage delays the development of resistance in disease vectors. The study was aimed to test the hypothesis whether decrease in exposure to insecticide leads to decrease in selection of insecticide resistance in mosquitoes. The mosquitoes were variably exposed to insecticide in the laboratory by simulating the variations in insecticide sprays applied in the field.
Methods: The study was carried out on DDT resistant adults of Anopheles stephensi. Mosquitoes were differentially exposed to impregnated papers of DDT (4%), that were differentially masked to 25, 50, and 75% area with an unimpregnated Whatman No.1 filter paper, and to a positive control without any masking, i.e. 100% exposure area. The study was conducted for five generations and at each generation mosquitoes were exposed to differentially masked impregnated papers, and percent mortality was calculated.
Results: The observed survival rate in differential exposures was more with the increase in heterozygous genotype resistance-susuceptible (RS) frequency. Resistant gene frequency with differential exposures (25 to 75%) was in the range of 0.38–0.54 for the F0 generation, which increased to 0.84–0.93 for the F4 generation. In 100% exposure it was 0.18 in F0 generation, which increased to 0.58 in the F4 generation. The resistant gene frequencies in the population showed increasing trend with decrease in exposure in contrast to complete exposure.
Interpretation & conclusion: Variable simulated exposures resulted in precipitation of increased resistance while complete exposure resulted in lower levels of resistance, signifying the importance of optimum dosage and coverage in the indoor residual spray in delaying/avoiding the development of insecticide resistance in the disease vectors.
Keywords: Differential exposure; genotype frequency; insecticide; mosquito; resistance
|How to cite this article:|
Verma V, Agrawal O P, Velamuri PS, Raghavendra K. A laboratory simulation study on suppression of resistance genes by differential exposures to an insecticide in Anopheles stephensi Liston population. J Vector Borne Dis 2018;55:184-8
|How to cite this URL:|
Verma V, Agrawal O P, Velamuri PS, Raghavendra K. A laboratory simulation study on suppression of resistance genes by differential exposures to an insecticide in Anopheles stephensi Liston population. J Vector Borne Dis [serial online] 2018 [cited 2021 Jun 21];55:184-8. Available from: https://www.jvbd.org/text.asp?2018/55/3/184/249126
| Introduction|| |
The evolution of insecticide resistance in the disease vectors is influenced mainly by genetic, biological and operational factors,. The biological factors relate to the life cycle of the insect (e.g. rate of reproduction, number of offspring/generation, rate of migration and isolation, etc.) while, the genetic factors include the intrinsic characteristics of the resistant genes (e.g. mono vs polygenic resistance, dominance, fitness cost and gene interaction), and operational factors are related to the vector control interventions that include method, frequency of application, dosage, residual activity and coverage. Mosquitoes with reduced susceptibility to an insecticide may still be controlled at the recommended optimal dose of application while variations in the dosages may increase the survivals leading to development of resistance. As a case for assumption, if S is susceptible and R is resistant allele in a population, large doses will kill all the SS and most RS, making the S allele functionally dominant. On the contrary, a small dose will kill most of SS, but leave RS and RR alleles, making the S allele functionally recessive. Resistance precipitation can be stopped only when the susceptible genotype is functionally dominant.
In the present study, mosquitoes were exposed to impregnated papers of DDT with variable exposure areas. The hypothesis tested here is that decrease in exposure to insecticides leads to decrease in selection of insecticide resistance. Phenotypic resistance in the exposed mosquitoes was determined at each generation to assess insecticide resistance due to simulated exposures.
| Material & Methods|| |
Anopheles stephensi Liston collected from Goa in 2009 was used in the present study. The strain, An. stephensi ListonGoa, is being maintained as continuous culture in the Institute's laboratory at the National Institute of Malaria Research, New Delhi, following standard mosquito rearing protocols without insecticide selection pressure. The insecticide susceptibility of the strain was determined initially in 2009 following the WHO adult susceptibility method by exposing the mosquitoes to prescribed diagnostic dosages of insecticide impregnated papers. The field collected strain was initially found 49% susceptible to DDT, 45 to malathion, 92 to deltamethrin, 9.5 to bendiocarb; and was 17.4% resistant to propoxur.
WHO adult mosquito insecticide susceptibility test
A total of four replicates, each consisting 20–25 sugar-fed, 3–5 day-old female mosquitoes were exposed to DDT (4%) diagnostic dosage impregnated papers, obtained from the VCRU, USM, Malaysia; and to two replicates of DDT control papers for 1 h. Inactive/dead (knock-down) mosquitoes were recorded every 5 min up to 1 h. After 1 h exposure the mosquitoes were transferred from exposure tubes to holding tubes. The tubes were kept in a climatic chamber maintained at 27 ± 2°C temperature and 80 ± 10% relative humidity for 24 h. Mortalities were recorded after 24 h holding period and percent mortality was calculated by using the formula given below:
The corrected percent mortality (CPM) was calculated if the mortality in control replicates was between 5 and 20% using the Abbott's formula.
If the mortalities in control replicates were >20%, the test was discarded. The criterion of level of susceptibility/resistance was : >98% mortality—susceptible; 81 to 97%—possible resistance; and <80%—mortality resistants.
Differential exposure of insecticide
Mosquitoes were differentially exposed to diagnostic dose impregnated papers of DDT (4%) in the laboratory using the WHO insecticide susceptibility tests as explained above. For this, mosquitoes were exposed to DDT impregnated papers that were differentially masked with unimpregnated Whatman No. 1 filter paper covering 25, 50 and 75% area, and to impregnated paper without any masking, i.e. 100% area exposed or unmasked DDT (4%) impregnated papers [Figure 1]. Unmasked DDT (4%) impregnated paper was considered as positive control to compare the effect due to differential exposures at each generation. The study was conducted for five generations, F0 to F4 and at each generation mosquitoes were exposed to differentially masked impregnated papers, and percent mortality was calculated and corrected as explained above.
|Figure 1: Illustration showing masking insecticide of impregnated papers with Whatman No. 1 filter paper to expose the mosquitoes: (a) 25%; (b) 50%; (c) 75%; and (d) 100% (0% masking positive control).|
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The data were further analyzed for calculation of lethal indices by log-probit regression analysis to determine lethal time values (LT50 and LT95) using PASW statistical software version 18.0.
Standard error (95% CL) for percent mortality was calculated using the formulae to rule out the possibilities of fluctuations in sampling.
Genotype frequencies of the susceptible, resistant and heterozygotes were calculated at each generation expecting Hardy-Weinberg equilibrium in the population using the formula p2+q2+2pq = 1, where, p is the frequency of susceptible gene, q of resistant gene and 2pq is the frequency of heterozygous population.
Percentage mortality data at each generation of differential exposure was subjected to one-way ANOVA to test the null hypothesis that the means of mortality of several populations were equal.
| Results|| |
The An. stephensi ListonGoa strain used in the study was 56% susceptible to DDT (4%). This line when exposed to differentially masked DDT (4%) impregnated papers (25, 50 and 75%) and to positive control, i.e. 100% exposure to DDT (4%) impregnated paper for one and 24 h holding showed variable mortalities [Table 1]. The percent mortality registered in F0 generation was 26.1, 30.7, 38.1, respectively for 25, 50 and 75% exposure area against the observed 56% mortality in positive control (100% exposure area). It was observed that the percent mortality registered in F0 generation was ~2 times less than that in positive control and thus showed a trend of increase in mortality with respect to the area of exposure. In the later generations no trend was observed in the percent mortalities in the exposures. In the F4 generation, increase in resistance to DDT was observed in all the four exposure areas. Relatively lower mortality was observed in differential area exposures compared to 100% exposure area. For 100% exposure area it was 23.8% while for 25, 50 and 75% exposure area, it was 3.2, 8.3 and 3.6%, respectively. In positive control the percent mortality was 17.17 in F1 generation which was 3.3×less than that in the F0 generation (56.7%). In the F2 generation it decreased to 12.9%, but in F3 and F4 generation it increased to 22.2 and 23.8%, respectively. Similarly, the calculated LT50 values (min) in the respective exposures (25, 50 and 75%) decreased in the F4 generation and were respectively 111, 81 and 208 min, while for 100% exposure area it was 80.15 min.
|Table 1: Comparative data of WHO adult susceptibility test (percent mortality and time mortality response) of An. stephensi ListonGoa exposed to DDT (4%) impregnated papers in the range of 25, 50, 75 and 100% exposures|
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The frequency of SS, RR and RS genotypes calculated for each generation is shown in [Table 2]. The RS genotype frequencies in F0 generation in 25, 50 and 75% masked exposure areas were 0.3856, 0.4251 and 0.4716 which decreased to 0.0625, 0.1527 and 0.0689 in F4 generation. However, in positive control exposure, the RS genotype frequency was 0.4911 in F0 which decreased to 0.3628 by F4 generation, and thus the decrease was relatively lower than that in 25, 50 and 75% exposure area. The graphic representation of RS genotype frequency showed stability in resistance with 100% exposure, whereas in other exposures, the resistance increased, with concomitant decrease in RS genotype [Figure 2]. From these results it was clear that when the susceptible population is suppressed differentially (25, 50 and 75%), the frequency of RS genotype in the population decrease, and it is faster than in the population that was exposed to unmasked insecticide impregnated paper, i.e. positive control. Increase in the frequency of resistant gene (RR) was observed in the lower exposures (25 to 75%) ranging from 0.38–0.54 in the F0 generation to 0.84–0.93 in F4 generation; while in 100% exposure it was 0.58 in F4 generation in comparison to 0.18 in F0 generation. Thus, it was observed that the increase in frequency of resistance gene was relatively higher in lower exposures than in the complete exposure (100%).
|Table 2: Calculated genotype frequencies in different generations for SS (homozygous susceptible), RR (homozygous resistant) and RS (heterozygous resistant) genes to differential exposures to DDT (25, 50, 75 and 100%) in Anopheles stephensi ListonGoa|
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|Figure 2: Calculated genotype frequencies of resistance-susceptible (RS) gene in different generations of An. stephensi to differential exposures to DDT (25, 50, 75 and 100% exposed).|
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The one-way ANOVA analysis showed that the F value was 0.60 (p = 0.62), while F critical value was 3.23 which is more than F value and found in contrast to the expected results. Thus, in masked exposures (25, 50 and 75%), the resistance increased faster than in 100% exposures. Hence, the hypothesis that decrease in exposure to insecticide leads to decreased selection is rejected.
| Discussion|| |
This study emphasizes that uniform spraying is important to maintain the susceptibility and sustain heterozygosity in the population and in turn prolong the bioefficacy of insecticide on the target mosquitoes. In a theoretical modeling study on insecticide mixtures Curtis has also suggested that from a genetic perspective, any dosage that left some susceptibles to survive will leave heterozygotes, resulting in slow increase in resistance in the population.
The extrapolation of the above observation to field for the possible practical implication for vector controlcan be explained as, indoor residual spray with improper dosage and non-uniformity leads to uneven coverage resulting in differential selection pressure that can increase the number of survivals, by raising their fitness. It may be due to the fitness cost of resistant phenotypes in a population as reduction was observed in the relative fitness of genes in absence of insecticide selection pressure. The difference between the fitness of a resistant phenotype and a homozygous susceptible individual in the absence of selection pressure is the fitness cost of resistance. This determines the resistance level in a population. In our previous study carried out in 2005 and 2006 in District Surat, India, deltamtherin-resistant An. culicifacies strain showed reversion to susceptibility in the absence of insecticide selection pressure reasoned to the presence of heterozygous and recessive resistant genes. Reversion of resistance depends on intrinsic fitness ratios of homozygotes/heterozygotes and frequency of resistance genes. Thus, from the present study it can be opined that the fitness of the resistant individuals in the population can be reduced through uniform and complete coverage of insecticide application in indoor residual spray operations for vector control with the prescribed optimum dosages that would delay or avoid the onset of resistance. In a study, Hess recommended to avoid speckled or sublethal dosages, and emphasized on thorough coverage of indoor residual spray to delay the resistance. The efficacy of insecticides can be enhanced if used judiciously for vector control.
A typical “trade-off’ was observed in few computer simulated studies, where, when the population size was more suppressed in the early generations, resistance evolved more quickly and when less suppressed, it evolved more slowly,,. Similar trend was observed in the present laboratory study; the resistance in F4 generation was less in unmasked than in masked exposure areas with constant dosage resulting in low bioavailability alike non uniform or speckled spray in the field.
| Conclusion|| |
In the present study, dosage of exposure was kept constant and the area of exposure was varied to assess the impact of insecticide in the differentially selected mosquitioes. Survival rate in differential exposure was more and RS genotype frequency in the population increased. The resistant gene frequencies in the population indicated increasing trend with decrease in exposure in contrast to complete exposure. The practical implication of this study to field vector control can be explained as, IRS with improper dosage and non-uniform coverage result in differential selection pressure that can impact the development of resistance. Development of insecticide resistance in vector can be delayed or avoided by quality spray with good coverage, optimum dosage including accurate frequency of spray rounds to sustain the insecticidal efficacy. Operational deficiencies may lead to lower efficacy in achieving the desired level of control and weigh down the ongoing efforts towards vector-borne disease elimination.
| Acknowledgements|| |
Authors sincerely thank the Director, National Institute of Malaria Research, New Delhi for providing the laboratory facilities for the study. Thanks are also due to Messrs Narender Sharma, Kamal Dev, Phool Kanwar and Om Prakash for their technical assistance in completing the work.
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