Are we losing the war against mosquito-borne diseases? The rise of insecticide resistance in mosquitoes threatens our ability to control diseases like Japanese encephalitis. But is it too late? A new study from Guizhou Province, China, sheds light on the genetic makeup of Culex tritaeniorhynchus, a major vector of Japanese encephalitis virus, and reveals a complex picture of insecticide resistance and population dynamics.
Published on November 21, 2025, in Parasites & Vectors, this open-access research, led by Weiyi Li, Zhihao Liu, and Jiahong Wu, investigates the knockdown resistance (kdr) gene and population genetic structure of Culex tritaeniorhynchus mosquitoes in Guizhou Province. Why is this important? Because understanding how these mosquitoes are evolving is crucial for developing effective control strategies.
Background: The Mosquito Threat
Culex tritaeniorhynchus is a mosquito species prevalent throughout tropical and subtropical Asia, including China, Japan, India, and Southeast Asia. In China, the eastern, central, and southwestern regions offer ideal habitats for this mosquito. Guizhou Province, with its humid climate and abundant rice paddies, creates a perfect breeding ground. Alarmingly, data from the Chinese Center for Disease Control and Prevention (CDC) indicates that the incidence of Japanese encephalitis virus (JEV) in Guizhou Province has consistently exceeded the national average. Culex tritaeniorhynchus not only transmits JEV but also a range of other viral diseases, such as West Nile fever, posing a significant risk to human health and public safety. It's not just about the annoyance of mosquito bites; it's about the very real threat of debilitating and potentially fatal diseases.
For decades, chemical insecticides have been the primary weapon in mosquito control. Organophosphates, carbamates, and pyrethroids are among the most commonly used insecticides. While these chemicals have effectively reduced mosquito populations, their long-term use has led to a concerning increase in insecticide resistance among Culex tritaeniorhynchus. Mutations in genes like the knockdown resistance (kdr) gene and the ace-1 acetylcholinesterase gene are key culprits in this resistance. Previous research has identified the Ace-1 F331W mutation, linked to organophosphorus resistance, in Culex tritaeniorhynchus populations across China. Another study of 12 Culex tritaeniorhynchus populations in China found that kdr mutation frequency fluctuated between 10% and 29.6%, with a direct correlation between pyrethroid resistance and the frequency of the kdr allele. Similar resistance has been observed in other countries. Locally in Guizhou Province, unpublished data suggests high resistance in Anopheles sinensis, which shares habitats with Culex tritaeniorhynchus, hinting at a potentially widespread resistance issue. But here's where it gets controversial: While the focus has been on these specific genes, could there be other, less-studied mechanisms contributing to resistance? Are we overlooking crucial pieces of the puzzle?
Population genetics, which focuses on the drivers of gene frequency changes, plays a critical role in vector mosquito control. The genetic structure of mosquito populations directly influences disease transmission and the development of resistance. Gene flow, the movement of genes between populations, is significantly linked to the spread of resistance genes. High gene flow facilitates the spread of resistance across populations, while genetic isolation can lead to localized resistance adaptations. Think of it like this: if resistant mosquitoes can easily travel and breed with other populations, the resistance problem will spread much faster.
To address this pressing issue, the researchers in this study collected Culex tritaeniorhynchus mosquitoes from various regions of Guizhou Province. They used molecular biology techniques to analyze variations in the kdr gene and the mitochondrial DNA–cytochrome c oxidase subunit I (mtDNA–COI) gene, exploring their geographical distribution and population genetic structure. By combining these analyses, they aimed to uncover genetic diversity and gene flow patterns, providing essential data for drug resistance monitoring and informing local mosquito-borne disease prevention strategies.
Methods: Unraveling the Mosquito's Secrets
From July to October 2023–2024, mosquitoes were collected from ten sampling sites in Guizhou Province using mosquito suction devices and trapping lamps. The collected mosquitoes were identified based on their morphological characteristics, initially screening for Culex tritaeniorhynchus. Samples were stored in freezing tubes and flash-frozen in liquid nitrogen, with detailed records of species, number, location, time, and collector to ensure traceability. Morphological identifications were further confirmed through mtDNA–COI sequencing. This meticulous approach ensured the accuracy of the data.
Genomic DNA was extracted using the TaKaRa MiniBEST Universal Genomic DNA Extraction Kit. mtDNA–COI gene-specific primers (COI-F: GGTCAACAAATCATAAAGATATTGG; COI-R: TAAACTTCAGGGGTGACCAAAAAATCA) were used. PCR amplification was performed in 25-μl reaction volumes with specific cycling parameters. Primers for the kdr gene (kdr-F: CTTCACCGACTTCATGCACTC; kdr-R: GATTTTGGGACAAAAGCAAGGC) were redesigned using NCBI primer-blast to amplify a 325bp fragment. The PCR products were electrophoresed on 1.0% agarose gel and sent for Sanger sequencing. Heterozygous samples were cloned using pClone007 Versatile Simple Vector and transferred into DH5a receptor cell culture, with single colony clones picked and sequenced for verification. This process ensured the accurate identification of mutations in the kdr gene.
Chromas software was used to analyze the sequencing results and identify kdr gene mutations. Resistance-related genotypes were calculated by counting the number of individuals with each genotype and dividing by the total number of individuals. Allele frequencies were calculated using standard heterozygote adjustment formulas: S% = SS% + 0.5 × RS% and R% = RR% + 0.5 × RS%, where SS is sensitive pure, RR is resistant pure, and RS is resistant heterozygous. On the basis of the mtDNA–COI sequences, haplotype diversity (Hd) and nucleotide diversity (π) were calculated. Neutrality testing was performed using Tajima’s D, Fu and Li’s F, and Fu and Li’s D in DnaSP, version 6. Genetic differentiation coefficient (Fst) and gene flow (Nm) were analyzed using Arlequin, version 3.5.2. Haplotype network diagrams were constructed using PopART, version 1.7 software. Genetic distances were calculated, and phylogenetic trees were constructed by the maximum likelihood method using MEGA, version 11.0, with a bootstrap value of 1000. And this is the part most people miss: the statistical rigor and multiple analytical approaches used in this study strengthen the reliability of the findings.
Results: A Glimpse into Mosquito Genetics
For all Culex tritaeniorhynchus specimens where the kdr gene was detected, mtDNA–COI sequences (685bp) were also obtained. The average mtDNA–COI base content was 39.6% A, 15.4% T, 29.3% C, and 15.7% G. A total of 267 haplotypes were detected in 365 sequences, with 12.0% shared haplotypes. The haplotype diversity (Hd) was 0.989, and the nucleotide diversity (Pi) was 0.023. Significant negative deviations from neutrality were observed only when all populations were considered collectively. Intrapopulation genetic distances ranged from 0.01 to 0.03, and interpopulation genetic distances ranged from 0.015 to 0.034. The Fst ranged from 0.001 to 0.140, and the gene flow Nm was greater than 1 in all cases. These results indicate high genetic diversity and significant gene exchange among Culex tritaeniorhynchus populations in Guizhou Province.
A haplotype network showed the distribution of 267 haplotypes, identifying two distinct groups: group 1, more distinct, and group 2, more dispersed. Haplotype Hap3 was dominant in group 1, while group 2 lacked a clearly dominant haplotype. The haplotypes of the ten regions did not show significant clustering by region in either group.
Phylogenetic tree analysis clustered all Culex tritaeniorhynchus samples into two major branches. Samples from different regions of Guizhou Province did not show obvious geographical aggregation but were evenly dispersed across the two branches. Branch 1 showed some aggregation from the Yunnan region of China and South Asia, while branch 2 showed some aggregation from northern China, Japan, and Korea. This suggests widespread distribution across East Asia.
Sequencing revealed only one mutant gene, L1014F (TTA → TTT), at locus 1014 of the kdr gene. The mutation frequency ranged from 0% to 8.8%, with the highest frequency in the DJ population. Resistant pure haplotypes (RR) were detected only in WN and AS populations, while sensitive pure haplotypes (SS) accounted for more than 82% of all populations. This data indicates that, for now, pyrethroid resistance is relatively low in these mosquito populations.
Discussion: Implications for Mosquito Control
Insecticide resistance is an adaptive evolutionary process driven by selective pressure. Continuous insecticide use eliminates sensitive individuals, leading to the accumulation of resistance genes. This study examined resistance genes and mtDNA–COI genes to analyze the population genetic structure of Culex tritaeniorhynchus in Guizhou Province.
The high haplotype diversity and low nucleotide diversity observed in Culex tritaeniorhynchus populations in Guizhou Province suggest a young, expansive population undergoing rapid ecological adaptation, as it has been shown in previous studies. This is often seen in tropical and subtropical regions where environmental conditions favor mosquito survival and dispersal. High genetic diversity enables faster accumulation of ecologically advantageous genes and resistance mutations, increasing the risk of disease transmission.
The genetic differentiation coefficient (Fst) and gene flow (Nm) results indicated that most populations are not genetically isolated, consistent with genetic exchange observed in other regions of mainland China. Factors such as tourism, water currents, and the flight ability of adult mosquitoes contribute to this. Anthropogenic and hydrological factors likely promote spatial dispersal and genetic homogenization. The ability of Culex tritaeniorhynchus to migrate long distances via monsoons facilitates gene exchange across regions and countries. Although kdr gene mutation frequency is currently low, frequent gene exchange necessitates continuous monitoring to prevent resistance spread.
Haplotype networks and phylogenetic trees indicated that the Culex tritaeniorhynchus population in Guizhou Province is divided into two groups, a pattern observed in China, Korea, and Japan, potentially indicating cryptic or novel species. Although further morphometric and genomic analyses are required, the lack of significant regional clustering supports the ability of Culex tritaeniorhynchus to exchange genes across regions.
The low kdr allele gene frequency in Guizhou Province compared to neighboring regions suggests that pyrethroid insecticides remain effective. However, integrated resistance mechanisms, including metabolic and behavioral adaptations, may also play a role. Given the high connectivity among populations, ongoing molecular monitoring remains critical. Local public health departments should strengthen surveillance to prevent the spread of insecticide resistance.
Conclusions: A Call for Vigilance
Only one mutation type (L1014F, TTA → TTT) was identified at the 1014 locus of the kdr gene in Culex tritaeniorhynchus across Guizhou Province. The low mutation frequency suggests that pyrethroid insecticides are still effective. However, high levels of gene flow could promote rapid spread of resistance alleles once established. These findings highlight the need for sustained molecular surveillance and adaptive insecticide management strategies to mitigate future resistance development.
What do you think? Given these findings, should we rethink our approach to mosquito control? Is relying on insecticides a sustainable long-term strategy, or should we invest more in alternative methods? And what role should international collaboration play in managing insecticide resistance across borders? Share your thoughts and concerns in the comments below!
