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. 2025 May 14;18(1):174.
doi: 10.1186/s13071-025-06675-5.

Characterization of the transcriptional cellular response in midgut tissue of temephos-resistant Aedes aegypti larvae

Affiliations

Characterization of the transcriptional cellular response in midgut tissue of temephos-resistant Aedes aegypti larvae

Elisama Helvecio et al. Parasit Vectors. .

Abstract

Background: Resistance to organophosphate compounds is a serious concern in dealing with the control of mosquito vectors. Understanding the genetic and molecular basis of resistance is important not only to create strategies aimed at detecting and monitoring resistance in the field but also to implement efficient control measures and support the development of new insecticides. Despite the extensive literature on insecticide resistance, the molecular basis of metabolic resistance is still poorly understood.

Methods: To better understand the mechanisms of Aedes aegypti resistance to temephos, we performed high-throughput sequencing of RNA from the midgut tissue of Aedes aegypti larvae from a temephos-resistant laboratory colony, with long-term and continuous exposure to this insecticide (RecR), as well as from a reference, temephos-susceptible, colony (RecL). Bioinformatic analyses were then performed to assess the biological functions of differentially expressed genes, and the sequencing data were validated by quantitative reverse transcription-polymerase chain reaction (RT-qPCR).

Results: The transcriptome analysis mapped 6.084 genes, of which 202 were considered upregulated in RecR, including known and new genes representing many detoxification enzyme families, such as cytochrome-P450 oxidative enzymes, glutathione-S-transferases and glucosyl transferases. Other upregulated genes were mainly involved in the cuticle, carbohydrates and lipid biosynthesis. For the downregulated profiles, we found 106 downregulated genes in the RecR colony, with molecules involved in protein synthesis, immunity and apoptosis process. Furthermore, we observed an enrichment of KEGG metabolic pathways related to resistance mechanisms. The results found in RT-qPCR confirm the findings of the transcriptome data.

Conclusions: In this study, we investigated transcriptome-level changes maintained in a temephos-resistant Ae. aegypti colony under continuous and prolonged selection pressure. Our results indicate that metabolic resistance might involve a larger and more significant number of detoxification enzymes, with different functional roles, than previously shown with other mechanisms, also contributing to the resistance phenotype in the Ae. aegypti RecR colony.

Keywords: Aedes aegypti; Metabolic resistance; Temephos; Transcriptome.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Differential expression analysis of RNAseq data. a Statistical analysis of mapping the RecR and RecL libraries' Aedes aegypti strains after quality control; b principal component analysis (PCA) of the RecL (RL1, RL2 and RL3, represented by red dots) and RecR (RR1, RR2 and RR3, represented by blue dots) replicates. c Heatmap of the RecR and RecL gene expression profile in Ae. aegypti. Upregulated genes are represented in green and downregulated genes in red. d MA plot showing the upregulated (green; cutoff > 1) and downregulated (red; cutoff < – 1) genes. All other genes (5775 in total, represented in gray) showed no significant differences in expression (p ≤ 0.05). In the MA plot, each dot represents a gene
Fig. 2
Fig. 2
RT-qPCR assay for validating selected DEGs from RNAseq data. a Glutathione-S-transferase epsilon 2 (GSTE2); b cytochrome P450 9J24 (CYP9J24); c cytochrome P450 12F6 (CYP12F6); d calreticulin (Cal); e hexaprenyldihydroxybenzoate methyltransferase (Methyl); f metalloproteinase (Metallo). Gene expression levels are relative to those from the endogenous control genes, actin and RPS17, used for normalization. Means and standard errors were obtained from three biological replicates. *p < 0.0001, **p < 0.0006, ***p < 0.0026, ****p < 0.0056 and *****p < 0.0166
Fig. 3
Fig. 3
Protein-protein interaction networks are visualized using Cytoscape program. Functional protein-protein interaction networks of differentially expressed genes (DEGs) in the RecR strain. The colors and diameters of the nodes change according to the LFC, with the intensity variation of the colors shifting towards blue indicating more negative LFC values and towards red indicating more positive LFC values. The attributes of the nodes in the STRING interaction network are provided in Supplementary Table 5

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