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The impact of indoor residual spraying on Plasmodium falciparum microsatellite variation in an area of high seasonal malaria transmission in Ghana, West Africa

Citation

Argyropoulos, Dionne et al. (2021), The impact of indoor residual spraying on Plasmodium falciparum microsatellite variation in an area of high seasonal malaria transmission in Ghana, West Africa, Dryad, Dataset, https://doi.org/10.5061/dryad.tht76hf0r

Abstract

Here, we report the first population genetic study to examine the impact of indoor residual spraying (IRS) on Plasmodium falciparum in humans. This study was conducted in an area of high seasonal malaria transmission in Bongo District, Ghana. IRS was implemented during the dry season (November-May) in three consecutive years between 2013 and 2015 to reduce transmission and attempt to bottleneck the parasite population in humans towards lower diversity with greater linkage disequilibrium. The study was done against a background of widespread use of long-lasting insecticidal nets, typical for contemporary malaria control in West Africa. Microsatellite genotyping with 10 loci was used to construct 392 P. falciparum multilocus infection haplotypes collected from two age-stratified cross-sectional surveys at the end of the wet seasons pre- and post-IRS. Three-rounds of IRS, under operational conditions, led to a >90% reduction in transmission intensity and a 35.7% reduction in the P. falciparum prevalence (p < .001). Despite these declines, population genetic analysis of the infection haplotypes revealed no dramatic changes with only a slight, but significant increase in genetic diversity (He : pre-IRS = 0.79 vs. post-IRS = 0.81, p = .048). Reduced relatedness of the parasite population (p < .001) was observed post-IRS, probably due to decreased opportunities for outcrossing. Spatiotemporal genetic differentiation between the pre- and post-IRS surveys (D = 0.0329 [95% CI: 0.0209 - 0.0473], p = .034) was identified. These data provide a genetic explanation for the resilience of P. falciparum to short-term IRS programmes in high-transmission settings in sub-Saharan Africa.

Methods

For all participants with microscopically confirmed P. falciparum infections (i.e., isolates), two 5 x 5 mm sections were cut from each dried blood spot and placed in a 1.5‐ml centrifuge tube, with genomic DNA (gDNA) being extracted using the QIAmp DNA mini kit (Qiagen) as previously described (Tiedje et al., 2017). A subset of 200 microscopic P. falciparum isolates from both the pre‐IRS (T1) and post‐IRS (T2) surveys were selected for microsatellite genotyping based on their multiplicity of infection (MOI) (i.e., number of genetically distinct P. falciparum genomes) as determined using var genotyping (see Supporting Information Methods, Figure S1). Briefly, using this approach we estimated the MOI based on the number of var DBLα types identified per isolate, using a cutoff value of 60 var DBLα types per P. falciparum genome. Isolates with ≤60 var DBLα types were classified as single‐clone infections (MOI = 1), while isolates with >60 var DBLα types were classified as multiple‐clone infections (MOI > 1). To facilitate a more accurate assignment of the fluorescent peaks during the analysis (described below), only those isolates with a MOI = 1 or 2, were selected for the microsatellite genotyping (Anderson et al., 1999).

The P. falciparum isolates (N = 400) selected from the pre‐ and post‐IRS surveys were genotyped using a verified panel of 12 putatively neutral microsatellite markers located across the 14 chromosomes as described by Anderson et al. (1999): TA1, 2490, TA81, TA87, TA109, TA60, POLYA, TA42, ARA2, PfG377, PfPK2, and TA40, with modified cycling conditions as specified in Ruybal‐Pesántez et al. (2017). Fluorescently‐labelled PCR products were sent to a commercial sequencing facility (Macrogen Inc., South Korea) for capillary electrophoresis and fragment analysis on an Applied Biosystems 3730xl DNA analyser (ThermoFisher Scientific). Raw data files were imported using GeneMarker (SoftGenetics LLC), normalised based on the size standard LIZ500, and scored using customised panels as previously described (Anderson et al., 1999; Ruybal‐Pesántez et al., 2017). All major peaks that were within the expected marker base pair (bp) range and were spaced at intervals corresponding to trinucleotide (3 bp) repeats were considered to be true alleles. Any peak less than 33% of the primary peak (i.e., local max) for a locus was considered a minor allele and not interpreted as a true allele. Background noise was defined as any peak <200 fluorescent units (Anderson et al., 1999). These data were cleaned using R package base v. 3.5.0 (R Core Team, 2018) and then processed using TANDEM v. 1.09 (Matschiner & Salzburger, 2009), which is optimal to assign an allele to each trinucleotide microsatellite locus for each isolate. We combined data from the pre‐ and post‐IRS surveys prior to binning alleles with TANDEM to ensure each survey could be compared accurately to each other.

For the 200 isolates investigated in the pre‐ and post‐IRS surveys, the median genotyping success was 89.2% in the pre‐IRS survey and 92.8% in the post‐IRS survey for the 12 microsatellite markers (Table S2) as expected for low‐density asymptomatic P. falciparum infections. Since isolate genotyping success for TA1 and TA42 was <75% pre‐IRS and/or post‐IRS (Table S2), these loci were subsequently removed, with 10 microsatellite loci included for the downstream multilocus microsatellite analyses (Note: All 12 microsatellite loci, including TA1 and TA42, were successfully amplified and genotyped for the 3D7 positive controls, thus the possibility of null alleles could not be excluded). Finally, only those isolates with genotyping data at ≥3 microsatellite loci were included, resulting in 192 (96.0%) and 200 (100%) isolates from the pre‐ and post‐IRS surveys, respectively (Table ​(Table1,1, Figure S1).

Funding

Fogarty International Center, Award: R01‐TW009670

National Institute of Allergy and Infectious Diseases, Award: R01‐AI149779