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. 2018 Oct 3;9(10):479.
doi: 10.3390/genes9100479.

Detection and Monitoring of Insecticide Resistance Mutations in Anopheles gambiae: Individual vs Pooled Specimens

Konstantinos Mavridis  1 , Nadja Wipf  2   3 , Pie Müller  4   5 , Mohamed M Traoré  6 , Gunter Muller  7 , John Vontas  8   9
Affiliations

Detection and Monitoring of Insecticide Resistance Mutations in Anopheles gambiae: Individual vs Pooled Specimens

Konstantinos Mavridis et al. Genes (Basel). .

Abstract

Bioassays and molecular diagnostics are routinely used for the monitoring of malaria vector populations to support insecticide resistance management (IRM), guiding operational decisions on which insecticides ought to be used for effective vector control. Previously developed TaqMan assays were optimised to distinguish the wild-type L1014 from the knockdown resistance (kdr) point mutations 1014F and 1014S (triplex reaction), and the N1575 wild-type from the point mutation 1575Y (duplex reaction). Subsequently, artificial pools of Anopheles gambiae (An. gambiae) specimens with known genotypes of L1014F, L1014S, and N1575Y were created, nucleic acids were extracted, and kdr mutations were detected. These data were then used to define a linear regression model that predicts the allelic frequency within a pool of mosquitoes as a function of the measured ΔCt values (Ct mutant - Ct wild type probe). Polynomial regression models showed r2 values of >0.99 (p < 0.05). The method was validated with populations of variable allelic frequencies, and found to be precise (1.66⁻2.99%), accurate (3.3⁻5.9%), and able to detect a single heterozygous mosquito mixed with 9 wild type individuals in a pool of 10. Its pilot application in field-caught samples showed minimal differences from individual genotyping (0.36⁻4.0%). It allowed the first detection of the super-kdr mutation N1575Y in An. gambiae from Mali. Using pools instead of individuals allows for more efficient resistance allele screening, facilitating IRM.

Keywords: L1014F; L1014S; N1575Y; SNPs; TaqMan assays; insecticide resistant management; kdr; molecular diagnostics; pooled samples; vector monitoring.

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Conflict of interest statement

The authors declare no conflict 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, and in the decision to publish the results.

Figures

Figure 1
Figure 1
Development of regression models. A-F: Reaction curves for L1014F showing the increasing difference between cycling of mutant and wild type probes from higher to lower population frequencies of the mutant allele. G: Polynomial regression curve for 1014F.
Figure 1
Figure 1
Development of regression models. A-F: Reaction curves for L1014F showing the increasing difference between cycling of mutant and wild type probes from higher to lower population frequencies of the mutant allele. G: Polynomial regression curve for 1014F.
See this image and copyright information in PMC

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