Metabolic resistance to pyrethroids with possible involvement of non-coding ribonucleic acids in Anopheles funestus, the major malaria vector in western Kenya

Abstract

Background: The resurgence of Anopheles funestus, a dominant vector of human malaria in western Kenya was partly attributed to insecticide resistance. However, evidence on the molecular basis of pyrethroid resistance in western Kenya is limited. Here, we reported metabolic resistance mechanisms and demonstrated that multiple non-coding Ribonucleic Acids (ncRNAs) could play a potential role in An. funestus resistance to pyrethroid in western Kenya. Anopheles funestus mosquitoes were sampled using aspiration methods in Bungoma, Teso, Siaya, Port Victoria and Kombewa in western Kenya. The F1 progenies were exposed to deltamethrin (0.05%), permethrin (0.75%), DDT (4%) and pirimiphos-methyl (0.25%) following WHO test guidelines. A synergist assay using piperonyl butoxide (PBO) (4%) was conducted to determine cytochrome P450s' role in pyrethroid resistance. RNA-seq was conducted on a combined pool of specimens that were resistant and unexposed, and the results were compared with those of the FANG susceptible reference strain. This approach aimed to uncover the molecular mechanisms underlying the observed phenotypic pyrethroid resistance.

Results: Pyrethroid resistance was observed in all sites with an average mortality rate (MR) of 57.6%. Port Victoria had the highest level of pyrethroid resistance to permethrin (MR = 53%) and deltamethrin (MR = 11%. Teso had the lowest level of resistance to permethrin (MR = 70%) and deltamethrin (MR = 87%). Resistance to DDT was observed only in Kombewa (MR = 89%) and Port Victoria (MR = 85%). A full susceptibility to P-methyl (0.25%) was observed in all sites. PBO synergist assay revealed high susceptibility (> 98%) to pyrethroids in all the sites except for Port Victoria (MR = 96%). Whole transcriptomic analysis showed that most gene families associated with pyrethroid resistance comprised non-coding RNAs (67%), followed by immunity proteins (10%), cytochrome P450s (6%), cuticular proteins (5%), olfactory proteins (4%), glutathione S-transferases (3%), UDP-glycosyltransferases (2%), ATP-binding cassettes (2%) and carboxylesterases (1%).

Conclusion: This study unveils the molecular basis of insecticide resistance in An. funestus in western Kenya, highlighting for the first time the potential role of non-coding RNAs alongside metabolic detoxification in pyrethroid resistance. Targeting non-coding RNAs for intervention development could help in insecticide resistance management.

Keywords: Anopheles Funestus; Insecticide resistance; Non-coding RNAs; RNA-seq; Western Kenya.

Fig. 1

Map of study sites where mosquitoes were sampled in western Kenya. The software ArcGIS Pro 2.6 was used to create the map. Map sources: USGS, ESRI, and CGIAR (www.esri.com)

Fig. 2

Volcano plot indicating upregulation and downregulation for resistant vs. susceptible (A), resistant vs. unexposed (B) and unexposed (control) vs. susceptible (C). The X-axis indicates the log2 fold-change- positive and negative values are up and down-regulated respectively relative to the susceptible group in A and C. The Y-axis indicates -log₁₀ of the adjusted P-value (FDR) (-log₁₀FDR values > 200 for A, > 9 for B and > 80 for C). In each volcano plot, genes that are overexpressed in the population are > 0 on the x-axis. Adjusted P-values of < 0.05 are indicated by the horizontal line, while 2-fold expression differences are indicated by vertical dotted lines. The 14,176 variables indicate the total number of genes tested.

Fig. 3

A principal component analysis showing the gene expression pattern of the sample groups relative to the susceptible group

Fig. 4

Heatmap indicating the expression of all genes in the sample groups relative to the susceptible group

Fig. 5

Venn diagram comparing upregulated and downregulated genes between-group comparisons. A indicates upregulated genes between the groups and B indicates downregulated genes between groups. R-S: field-resistant population that survived pyrethroid exposure vs. susceptible colony, R-C: field-resistant population that survived pyrethroid exposure vs. unexposed (control) field population and C-S: unexposed (control) field population vs. susceptible colony

Fig. 6

Pie chart showing the proportion of gene family associated with pyrethroid resistance. IMPs: Immunity proteins, CYPs: Cytochrome P450s, CPs: cuticular proteins, OPs: olfactory proteins, GSTs: Glutathione S-transferases, UGTs: UDP-glycosyltransferases, ABCs: ATP-binding cassettes, COEs: carboxylesterases and ncRNA: non-coding RNA

Fig. 7

Comparative analysis of ncRNA against major gene associated with pyrethroid resistance in the resistance vs. susceptible clusters. Volcano plot representation of fold change between ncRNA and families of genes associated with pyrethroid resistance. A) ABCs: ATP-binding cassettes; B) COEs: carboxylesterases; C) CYPs: Cytochrome P450s; D) CPs: cuticular proteins; E) GSTs: Glutathione S-transferases; F) OPs: olfactory proteins, G) UGTs: UDP-glycosyltransferases; H) IMPs: Immunity proteins; G) Others. An unpaired t-test was used to compare means between two groups, p-value < 0.05 was considered statistically significant

Fig. 8

Gene Ontology (GO) enrichment analysis of the differentially expressed genes