The molecular mechanisms mediating a trade-off between insecticide resistance and development in an invasive pest

The molecular mechanisms mediating a trade-off between insecticide resistance and development in an invasive pest | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The molecular mechanisms mediating a trade-off between insecticide resistance and development in an invasive pest Xueqing Yang, Chao Hu, Yuxi Liu, Xin Yang, Jiyuan Liu, Yuting Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8791607/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The evolution of insecticide resistance represents a global challenge to human food security and health. Resistance is often associated with fitness costs such as altered development and reproduction, however, the molecular mechanisms that underpin this evolutionary trade-off are poorly understood. Here we reveal the regulatory pathways underlying the trade-off between insecticide resistance and developmental regulation in the global invasive moth, Cydia pomonella. Using multi-omics approaches in combination with gene editing and transgenic approaches we show that overexpression of the glutathione S-transferase CpGSTd1 confers resistance to the pyrethroid insecticide λ-cyhalothrin. Computational alanine scanning (CAS), and site-specific mutagenesis reveal that the amino acid Tyr114 is a key structure-function determinant of CpGSTd1 metabolism of λ-cyhalothrin. CpGSTd1 is positively regulated by the transcription factor CpCncC, which is overexpressed in resistant C. pomonella, following its activation by reactive oxygen species (ROS). However, overexpression of CpCncC also promotes increased expression of the ecdysteroid biosynthesis gene CYP306A1, leading to elevated 20-hydroxyecdysone (20E) levels. Elevated 20E antagonized juvenile hormone (JH) synthesis, results in extended developmental durations and diminished reproductive capacity in resistant populations. Collectively, these findings provide insight into the molecular mechanisms underpinning insecticide resistance and highlight the role of transcription factors like CncC in mediating the trade-off between resistance and developmental homeostasis via their role as master regulators of genes involved in xenobiotic detoxification and hormonal pathways in insects. Biological sciences/Zoology/Entomology Scientific community and society/Agriculture Biological sciences/Biochemistry/Hormones Biological sciences/Biological techniques/Genetic techniques/Gene targeting/CRISPR-Cas9 genome editing insecticide resistance development trade-off transcriptional regulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction For more than half a century insecticides have remained a key tool to control many highly damaging insect crop pests and disease vectors worldwide ( 1, 2 ). However, their widespread use has resulted in the evolution of resistance, threatening human food security and health ( 3, 4 ). Resistance commonly results from two main mechanisms: 1) Mutation of the insecticide target site leading to a reduction in sensitivity ( 5 ), or, 2) enhanced expression and/or activity of enzymes, including cytochrome P450 monooxygenases (P450s), carboxylesterases (CarEs), glutathione S -transferases (GSTs) and UDP-Glucuronosyltransferases (UGTs), that metabolize or sequester the insecticide ( 6-8 ). These mechanisms can result in fitness costs, as mutation of insecticide target proteins can compromise their native function, and enhanced expression of detoxification enzymes carries a metabolic cost ( 9, 10 ). These fitness costs often manifest as reproductive impairments; for example, in Bemisia tabaci , elevated resistance to neonicotinoids correlates with downregulation of oogenesis-related genes, leading to ovarian developmental defects and reduced female fecundity ( 11 ). Similarly, multiple generations of selection in Spodoptera exigua exposed to tebufenozide resulted in resistance accompanied by a significant fitness cost in egg production ( 12 ). Additionally, resistance-driven resource reallocation can disturb developmental homeostasis, leading to alterations in developmental duration ( 13 ). Previous studies have demonstrated that among 18 pest species resistant to Bacillus thuringiensi —including Helicoverpa armigera , S. exigua , and Plutella xylostella— the average fitness costs associated with resistance, concerning survival and developmental duration, are approximately 15.5% and 7.4%, respectively ( 9 ). Nonetheless, the mechanisms driving the evolutionary trade-off between resistance and altered development and reproduction remain poorly understood. Transcriptional regulation of genes is integral to the connection between genotype and phenotype in organisms, which is essential for maintaining normal physiological functions ( 14, 15 ). Insecticide exposure can activate transcription factors that function as exogenous sensors, driving detoxification gene expression and facilitating resistance evolution ( 16 ). Currently, transcription factors involved in resistance regulation are typically classified into three families: basic leucine zipper (bZIP), basic helix-loop-helix/Per ARNT Sim (bHLH/PAS), and nuclear receptor (NR). The bZIP family member, cap 'n' collar isoform C ( CncC ), has been extensively validated as a key regulator of insecticide resistance genes ( 16, 17 ). For example, constitutive overexpression of CncC in S. exigua has been identified as a primary factor in upregulating CYP321A8 , mediating resistance to chlorpyrifos and cypermethrin ( 18 ). However, in insects, CncC also facilitates the transcriptional activation of key genes in hormone biosynthesis and catabolism, such as CYP306A1 involved in 20E synthesis and hormone esterase/hydrolase (JHEH), which degrades JH, indicating its pivotal role in hormonal regulation ( 19 ). Thus, aberrations in developmental duration observed in resistant populations may result from hormonal regulation mediated by these transcription factors. However, comprehensive investigations into the adaptive regulatory mechanisms underlying the resistance-development trade-off remain limited. The codling moth, Cydia pomonella (L.), is a globally invasive pest and exhibits notable issues of insecticide resistance (https://irac-online.org) ( 20 ). Previous studies have indicated a significant correlation between λ-cyhalothrin resistance and elevated detoxification enzyme activities, such as GST and P450 levels, in both field-evolved ( 21 ) and laboratory-selected resistant populations ( 22 ). However, the molecular basis of resistance in C. pomonella , along with potential trade-offs between resistance and development and the underpinning mechanisms, remains largely unexplored. Here we address this knowledge gap by investigating the regulatory mechanisms underlying the resistance-developmental trade-off and its regulation in C. pomonella. Results Multi-omics analysis identified CpGSTd1 as overexpressed in λ-cyhalothrin-resistant C. pomonella population s The laboratory-selected resistant C. pomonella population (LCR) exhibited a stable moderate level of resistance in the 15th (G15) ( 22 ) and 30th (G30) generations under continuous λ-cyhalothrin exposure, relative to the susceptible strain (SS) (Figure 1A). Compared to the SS strain, LCR demonstrated prolonged larval (Figure 1B) and pupal (Figure 1C) developmental durations, accompanied by reduced reproductive capacity (Figure 1D, Table S1). Thus, resistance to λ-cyhalothrin in C. pomonella is associated with significant fitness costs in the absence of insecticide exposure. To explore the molecular basis of λ-cyhalothrin-resistance, we initially analyzed the sequence of the voltage-gated sodium channel ( VGSC ), the target protein of pyrethroid insecticides, in resistant and susceptible populations. No mutations were observed within the VGSC gene of the LCR strain (Figure S1) suggesting that target-site mutations are not involved in the resistance of this strain to λ-cyhalothrin. We next employed transcriptomic and proteomic analyses to identify differentially overexpressed detoxification-related genes between resistant and susceptible populations. Transcriptome analysis revealed fourteen P450 genes, seven CarE genes, three GST genes, two UGT genes, and two ABC transporter genes exhibiting fold changes ranging from 1.01 to 11.7 (log 2 fold change) in the LCR population compared to the SS strain (Figure 1E, Table S6). RT-qPCR confirmed that these detoxification genes were upregulated by 1.13- to 4.0-fold in the LCR population relative to the SS strain (Figure 1F). Proteomic analysis indicated lower variability within the susceptible strain’s midgut (SS_MG) and distinct differential protein expression profiles between the SS_MG and resistant population midgut tissue (LCR_MG) (Figure S1). A total of 2,560 proteins were quantified across all samples; among these, differentially expressed proteins (DEPs) were categorized as 116 upregulated and 137 downregulated based on fold change thresholds (>1.2 or <0.83) and statistical significance ( P < 0.05) (Figure 1G, Table S4). The DEPs profile ranged from 1.20- to 1.94-fold, with only two detoxification enzymes—cytochrome P450 (CpCYP337B79, A3RIC1; FC = 1.55) and delta glutathione S -transferase (CpGSTd1, Q60GK5; FC = 1.40)—being significantly overexpressed (Figure 1H). Correlation analysis demonstrated a significant concordance between mRNA levels and proteomic data (r = 0.69, P < 0.05) (Figure 1I, Table S5). Notably, CpGSTd1 and CpCYP337B19 exhibited significantly increased protein (Figure 1G) and transcript levels (Figure 1E). Gene ontology (GO) enrichment analysis highlighted prominent roles in 'metabolic process' and 'single-organism metabolic process' pathways (Figure S2B, Table S2). KEGG pathway analysis identified 15 enriched pathways, primarily related to metabolism, including two xenobiotic metabolism pathways: 'Xenobiotics metabolism by cytochrome P450' and 'Drug metabolism—cytochrome P450' (Figure S2C, Table S3). CpGSTd1 was the only detoxification gene differentially upregulated within these pathways. Western blot and RT-qPCR validation showed no significant difference in CpGSTd1 mRNA (Figures 1J) and protein expression (Figures 1K) levels between resistant populations G15 and G30. Based on these results, we focused further investigation on the role of CpGSTd1 in λ-cyhalothrin resistance in C. pomonella . Overexpression of CpGSTd1 confers λ-cyhalothrin resistance To demonstrate the causal role of CpGSTd1 in resistance, RNAi was used to knockdown its expression and the impact of this on C. pomonella susceptibility to λ-cyhalothrin examined. The transcript levels of CpGSTd1 were significantly reduced following injection of dsRNA with peak interference efficiency of 46.68% at 24 h post-injection ( P < 0.05) (Figure 2A). Following gene knockdown, the LD 50 values for both the SS and LCR were significantly decreased (Figure 2B). To further assess whether overexpression of CpGSTd1 contributes to λ-cyhalothrin resistance, we generated transgenic Drosophila lines. The results confirmed successful integration of CpGSTd1 (Figure S3A), with transcript levels approximately 14.84-fold higher in the 10UAS- CpGSTd1 +Tub-GAL4,GAL80ts line than in the control line (10UAS- CpGSTd1 ) (Figure 2C, Figure S3B and S3C). Toxicity assays demonstrated that Drosophila lines heterologously expressing CpGSTd1 displayed a 2.02-fold increase in tolerance to λ-cyhalothrin compared to controls (Figure 2D). Notably, this overexpression did not enhance resistance to other insecticides tested (Table S7), indicating that CpGSTd1 -mediated resistance is specific to λ-cyhalothrin. To generate a loss-of-function mutant, CRISPR/Cas9-mediated knockout of exon three of CpGSTd1 was performed on embryos from the LCR population (Figure S4A). Out of 630 injected embryos, 28.57% (44/154) developed into pupae, and genotyping of 44 adults revealed a 13.64% (6/44) heterozygous mutation rate involving various deletions of 2 to 12 bp (Figure 2E, Figure S4B). Subsequent crossing among heterozygotes yielded a G1 generation, of which 24.2% (8/33) harbored 4-bp heterozygous deletions, and homozygous mutants were established over two generations (Figure 2F). Bioassays demonstrated a 5.59-fold decrease in the LD 50 of the LCR-CpGSTd1KO population compared to the control (Figure 2G), providing additional evidence of the role of CpGSTd1 overexpression in mediating λ-cyhalothrin resistance. Molecular docking-based validation of CpGSTd1's role in λ-cyhalothrin metabolism To explore the structure-function determinants of CpGSTd1 mediated λ-cyhalothrin resistance, molecular binding models were constructed using homology modeling and AI-driven computational techniques. Both methodologies yielded highly consistent 3D enzyme conformations, with minor conformational discrepancies (RMSD = 0.41 Å) (Figure 2H, Figure S5). Docking simulations revealed that λ-cyhalothrin's diaryl ether moiety interacts within a hydrophobic pocket comprising Tyr114 and Phe118, with Tyr114 forming a hydrogen bond (H-bond) at a distance of 3.1 Å (Figure 1I). Further AI-based docking analyses confirmed the pivotal role of Tyr114 in ligand affinity (iPTM = 0.87), with Val53—a proximal residue—contributing to the pocket' hydrophobic environment and forming a H-bond with the cyano group at 3.2 Å (Figure J). CAS computational analysis indicated the absence of significant energetic 'hot spots' among amino acids (side chain energy < -4.0 kcal/mol) ( 23 ), with Tyr114 exhibiting the lowest energy below 1.0 kcal/mol, followed by Leu34 near -1.0 kcal/mol (Figure 2K). To functionally demonstrate the role of these amino acids in insecticide metabolism, recombinant variants harboring Y114A, F118A, V53A mutations (within the GST G-site), and the L34A mutation (within the GST H-site) were expressed in bacteria (Figure S6). Mutant enzymes demonstrated decreased K m and V max relative to the wild-type enzyme (Table S8). HPLC assays revealed no significant difference in the depletion rate of λ-cyhalothrin by the L34A mutant compared to wild-type CpGSTd1, whereas the V53A, Y114A and F118A mutants exhibited significantly increased metabolic rates (Figure 2L, Table S8). Docking analyses of the mutants with λ-cyhalothrin revealed that, aside from V53A, Y114A and F118A showed increased binding affinity (Figure S7), suggesting that these residues within this binding cavity are critical for substrate interaction and enzymatic metabolism. The transcription factor CpCncC regulates CpGSTd1 -mediated λ-cyhalothrin resistance To identify the transcription factors involved in regulating λ-cyhalothrin resistance in C. pomonella , comprehensive transcriptomic and proteomic analyses were conducted, revealing 47 transcription factors across 20 taxonomic groups expressed in the midgut, a key site of insecticide detoxification (Figure S8, Table S9). Transcriptome data indicated that CpOsa (2.04-fold) was significantly overexpressed in the LCR_MG compared to the SS_MG (Figure 3A). The expression levels of these factors were validated via further RT-qPCR, which demonstrated that seven transcription factors ( CpLola-C , CpLola-D , CpARID4B , CpCncC , CpHNF4 , CpOsa and CpMlx ) were upregulated by 1.41- to 2.70-fold (Figure 3B). Proteomics analysis further confirmed that four factors— CpHNF4 , CpLola-D , CpCncC , and CpARID4B —were overexpressed at the protein level in the LCR population (1.16-fold to 1.59-fold increase) (Figure 3C). RNAi experiments showed that silencing CpCncC and CpHNF4 (Figure S9) significantly enhanced mortality upon λ-cyhalothrin exposure at the LD 50 dose (Figure 3D). Further analysis of mortality following exposure to multiple doses of λ-cyhalothrin revealed a significant reduction in LD 50 values to 421.60 ng μL -1 and 475.71 ng μL -1 after knockdown of CpCncC and CpHNF4 expression in the LCR population compared to the LD 50 value of 1182.39 ng μL -1 of the dsGFP control (Figure 3E). These findings suggest that these transcription factors may play a regulatory role in mediating insecticide resistance in C. pomonella. Additionally, knockdown of CpMaf , a molecular chaperone associated with CpCncC , also significantly increased susceptibility in LCR larvae (Figure 3E). To further investigate the regulatory roles of CpCncC and CpHNF4 on CpGSTd1 expression, transcriptomic analyses was conducted post-RNAi. Results indicated that knockdown of CpCncC significantly decreased CpGSTd1 expression ( P < 0.05), whereas silencing CpHNF4 had no effect on CpGSTd1 expression (Figure 3F, Figure S10), which was confirmed via RT-qPCR (Figure 3G). Activation of CpCncC with curcumin (2.0 mg g − 1 ), a CncC agonist, resulted in a 9.83-fold increase in CpCncC transcript levels, accompanied by a concurrent significant upregulation of CpGSTd1 (Figure 3H, Figure S11). Dual luciferase reporter assays were conducted to assess transcription factor binding to the CpGSTd1 promoter. Constructs were created containing sequences of varying lengths upstream of the CpGSTd1 translation start site (Figure 3I) . The promoter region spanning −1,911 to +1 relative to the transcription start site showed the highest relative transcriptional activity compared to shorter regions and the pGL4.10 control ( P < 0.05, F = 98.34, df = 31) (Figure 3I), indicating its role as the core promoter. Co-expression with pAC5.1b- CpCncC significantly increased CpGSTd1 promoter activity by 2.4-fold ( P < 0.05), while CpHNF4 showed no binding activity ( P = 0.7235) (Figure 3J). Bioinformatic analysis identified five high-confidence binding sites for the cnc:maf-S transcription factor within the CpGSTd1 promoter (Figure 3K), one with the forward sequence AGTGCCAATACAATA located precisely in the core promoter region (Figure S12). Site-directed mutagenesis of this binding site abolished CpCncC binding activity in reporter assays ( P < 0.05, F = 46.90, df = 11) (Figure 3L), confirming its functional relevance. These findings suggest that in collaboration with CpMaf , CpCncC acts as a transcription factor mediating the regulation of CpGSTd1 expression through cis -element binding. ROS activates the CpCncC -mediated regulatory signaling pathway To assess whether reactive oxygen species (ROS) bursts serve as a signaling mechanism within the CpCncC regulatory pathway following λ-cyhalothrin exposure, ROS levels were quantitatively analyzed in different C. pomonella populations. The LCR population exhibited inherently higher baseline ROS concentrations compared to the SS strain (Figure 4A), while both populations showed elevated ROS levels after exposure to the LD 10 dose of λ-cyhalothrin (Figure 4B). Additionally, key antioxidant enzymes—catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD)—displayed significantly increased activity within the larval antioxidant defense system of the LCR strain relative to SS, with further enhancement observed in both populations upon LD 10 λ-cyhalothrin exposure (Figure S13). To verify ROS pathway involvement, different concentrations of the ROS scavenger N-acetylcysteine (NAC) were applied to LCR larvae. NAC at 5% or higher concentrations resulted in larval mortality (Figure 4C), however, NAC at 2% and above significantly diminished ROS levels in LCR larvae ( P < 0.05, F = 22.38, df = 14) (Figure 4D). Based on these findings, 2% NAC was determined to be an effective concentration for ROS inhibition, concomitant with substantial downregulation of CpCncC and CpGSTd1 expression (Figure 4E) and an increased susceptibility of larvae to λ-cyhalothrin (Figure 4F). CpCncC orchestrates developmental duration and pupal homeostasis through hormonal regulation In addition to its role in modulating resistance pathways, Cp CncC was further investigated for its potential involvement in controlling developmental duration. The LCR population exhibited extended larval and pupal stages and showed reduced female reproductive capacity (Table S1), likely as a result of endocrine disruption (Table S1) driven by hormonal imbalances. Throughout the fourth instar and pupal stages, the 20E titer in LCR remained consistently higher than those in SS (Figure 5A), whereas JH levels were persistently lower (Figure 5B). While the LCR population displayed an increase in developmental duration (Figure 1B), the short-term response following sublethal λ-cyhalothrin exposure did not alter larval developmental duration (Figure 5C). The 20E titer in larvae was significantly elevated at 24 h and 48 h post exposure to the LD 10 of λ-cyhalothrin compared to controls, returning to baseline levels after 72 h (Figure 5D). In contrast, JH titers exhibited only a slight reduction at 48 h following sublethal λ-cyhalothrin treatment compared to controls (Figure 5E). To determine whether these developmental duration variations are mediated via CpCncC expression influencing hormone titers, CRISPR/Cas9 gene editing was used to generate homozygous mutants of CpCncC in C. pomonella (Figure S14A). Embryos were microinjected with Cas9 combined with sgRNA targeting distinct exons of CpCncC (Figure S14A). Of 33 surviving pupal-stage individuals, all exhibited mutations (Figure S14A). G0 heterozygous mutants, including both males and females, were produced following injections targeting the 5th exon (Figure S14A, Figure S14B), with an egg hatching rate of 11.10% (233/2100) and a pupal survival rate of 21.03% (49/233) among hatched larvae (Figure S14A). Genotyping revealed 10.20% (5/49) heterozygous mutants harboring various indels (Figure S14C). A single female with a 1 bp deletion was mated with a male carrying a distinct 1 bp deletion to generate the next progeny (Figure S14D). However, out of 124 eggs, only 72 G1 larvae hatched, with 61 carrying the parental heterozygous mutant allele, none of which reached healthy reproductive maturity (Figure S14E). Thus, the CRISPR/Cas9 system targeting various exons of CpCncC failed to generate homozygous mutant lines in C. pomonella . Furthermore, heterozygous G1 individuals (CpCncC +/- ) exhibited reduced viability, with survival rates lower than wild-type (CpCncC +/+ ) controls (Figure 5F). Developmental duration analysis revealed that each larval instar duration in CpCncC +/- individuals was significantly prolonged compared to wild-type counterparts, with the most pronounced delay observed at the fifth instar, where development was extended by 1.20-fold. This developmental delay became more prominent with advancing larval instars (Figure 5G). Moreover, all surviving fifth instar CpCncC +/- larvae displayed pupation defects, including a markedly increased pupation failure rate compared to the LCR population or CpCncC +/+ individuals (Figure 5H). RT-qPCR demonstrated that CpCncC transcript level in heterozygotes were reduced by 8.07-fold compared to wild-type (Figure 5I). Transcriptome profiling following dsCpCncC injection revealed significant modulation of the insect endocrine biosynthesis pathway (bmor00981), with a notable downregulation of CYP306A1 and significant upregulation of genes involved in juvenile hormone regulation, including farnesyl pyrophosphate phosphatase ( FPP ), farnesyl dehydrogenase ( FD1 and FD2 ), and juvenile hormone epoxide hydrolase ( JHEH ) (Figure 5J, Table S10). RT-qPCR validation corroborated these gene expression trends (Figure 5K and 5L), implying that CpCncC is involved in the regulation of hormonal balance. Further validation demonstrated that suppression of Cp CncC led to decreased titers of 20E (Figure 5M) and increased JH titers (Figure 5N). Exogenous application of synthetic 20E (50 ng/μL) to fourth-instar larvae restored hormone levels to baseline and normalized developmental duration ( P < 0.05, F = 16.38, df = 134) (Figure 5O, Figure S15). During maturation, dsCpCncC-injected individuals, exhibited a significantly higher pupation failure rate compared to dsGFP-injected controls, whereas 20E supplementation significantly enhanced pupation success ( P < 0.05, F = 38.6, df = 8) (Figure 5P). These findings suggest that CpCncC overexpression mediates λ-cyhalothrin resistance while delaying developmental duration through its action in regulating key hormones involved in insect development. Discussion Although resistance offers an adaptive advantage for insects exposed to insecticide, it usually leads to trade-offs with other life-history traits. In this study, we demonstrate that the transcription factor CpCncC regulates the adaptive trade-off between insecticide resistance, by upregulating the detoxification enzyme CpGSTd1 while modulating developmental homeostasis controlled by the hormones 20E and JH in C. pomonella . Our data provide insight into the mechanisms of resistance in a global crop pest and reveal how changes to gene regulatory pathways can underpin evolutionary trade-offs. Previous synergistic bioassays on the LCR population and correlation analyses between resistance ratios and detoxification enzyme activities suggested that C. pomonella primarily relies on GST enzymes for detoxification of λ-cyhalothrin ( 22 ). In this study, we utilized integrated multi-omics methodologies to identify detoxification genes overexpressed in the LCR population, and the consistent upregulation of CpGSTd1 in transcriptomic and proteomic datasets. GSTs belonging to the delta class have been previously linked to insecticide resistance in insects ( 24 ). For example, in Tetranychus urticae , the delta GST TuGSTd05 has been associated with resistance to cyflumetofen, exhibiting significant overexpression in a resistant population ( 25 ). Furthermore, consistent with our findings, CpGSTd1 was shown to be upregulated in a λ-cyhalothrin resistant strain of C. pomonella previously ( 26 ). It is important to acknowledge that CpGSTd1 was only modestly upregulated in the LCR population in our study. Thus, the overexpression of this gene is unlikely to fully explain the λ-cyhalothrin resistant phenotype of the LCR population, and further investigation of alternative mechanisms of resistance in this strain is warranted (see also below). Nevertheless, we conducted comprehensive functional analyses utilizing RNAi (inhibition-of-function), transgenic Drosophila models (gain-of-function) and gene editing techniques (loss-of function) to unequivocally demonstrate that CpGSTd1 confers resistance to λ-cyhalothrin. Similar studies on GST-mediated pyrethroid resistance have been reported in other pests; for instance, silencing SlGSTd1 in Spodoptera litura via RNAi significantly increased susceptibility to cypermethrin and cyfluthrin ( 27 ) . Furthermore, in Anopheles funestus , GSTe3 and GSTe4 were overexpressed in transgenic Drosophila via the GAL4-UAS binary expression system, and these overexpression lines demonstrated decreased susceptibility to permethrin and deltamethrin ( 28 ). We found that knockout of CpGSTd1 significantly decreased λ-cyhalothrin resistance, reducing the LD 50 from moderate to low levels, supporting the role of CpGSTd1 as an important determinant of insecticide sensitivity in C. pomonella . However, complete susceptibility was not restored following CpGSTd1 knockout, suggesting the participation of other mechanisms in mediating resistance. In this regard previous studies have demonstrated that three members of the CYP9A P450 subfamily, CpCYP9A120 , CpCYP9A121 , CpCYP9A122 , play a role in λ-cyhalothrin resistance through functional redundancy in C. pomonella (29) . In our study, only CYP337B19 , a member of the mitochondrial Clan P450, was overexpressed at both mRNA and protein levels. Further investigation of the potential role of this P450 in mediating insecticide resistance in C. pomonella is warranted . The formation of binding pockets by detoxification enzymes, facilitated by critical amino acid residues that interact with insecticides, is fundamental to enhanced metabolic activity ( 26 ). AI-driven molecular modeling and CAS analyses indicated that the cavity formed by key amino acid residues such as Tyr114, Phe118, and Val 53 is crucial for the binding affinity of C. pomonella CpGSTd1 to λ-cyhalothrin. Similar findings have been reported in other insect species; for example, in P. xylostella , Tyr115 and Phe119 of PxGSTD3 are homologous amino acids to Tyr114 and Phe118 of C. pomonella CpGSTd1, which form a binding pocket to encapsulate the phenyl group of λ-cyhalothrin, strengthening binding activity ( 30 ). These findings suggest that the conserved amino acids forming this binding pocket could be critical for delta class GST-mediated detoxification of pyrethroid insecticides across diverse insect taxa. If confirmed, a strategic framework could be developed to leverage AI for virtual screening and the rational design of small-molecule inhibitors targeting this binding domain ( 31 ). Such compounds could potentially be used synergistically with insecticides to enhance pest control efficacy by overcoming GST-mediated metabolic resistance. Collectively these findings advance our understanding of the structure-function determinants of GST-mediated insecticide resistance in pests and can be used to inform the development of strategies to combat this form of resistance. Insecticide resistance in insects has been linked to transcription factors that regulate the transcription of detoxification genes ( 16, 32 ). CncC, as a homolog of mammalian Nuclear Factor E2-Related Factor 2 (Nrf2), is activated by ROS bursts triggered by insecticide exposure, leading to the transcriptional activation of downstream detoxification enzymes ( 17, 19 ). Regulatory pathways involving CncC have been documented across various insect species; for example, exposure of S. litura larvae to λ-cyhalothrin increases H 2 O 2 levels, which activates the transcription of Sl CncC and CYP6AB12 , thereby enhancing larval insecticide tolerance ( 33 ). Compared to P450 regulation, the role of CncC in modulating GST expression to mediate insecticide resistance remains poorly characterized. In S. exigua , SeGSTe6 is co-induced by λ-cyhalothrin, chlorpyrifos, and chlorantraniliprole, with subsequent significant activation of transcriptional signaling observed via a reporter plasmid containing the SeGSTe6 promoter driven by a CncC expression construct ( 34 ). Additionally, AiCncC binds to a specific site within the promoter region of AiGSTz1 which is induced by octreotide in Agrotis ipsilon , and silencing AiCncC results in marked down-regulation of AiGSTz1 expression ( 35 ). Our study systematically demonstrates that CpCncC mediates metabolic resistance to λ-cyhalothrin in C. pomonella through the activation of CpGSTd1 expression via binding to a cis -regulatory element in its promoter. These findings provide novel insights into the less-characterized regulatory mechanisms through which CpCncC modulates GST gene expression, and provides further evidence of the importance of this regulatory pathway in the development of insecticide resistance in pest populations. However, like other transcription factors ( 18, 34 ), the change in the expression of CpCncC in resistant versus susceptible populations in our study was modest. Thus, alternative mechanisms may act in concert with transcriptional upregulation to alter CpCncC activity in C. pomonella . For example, variation in the phosphorylation state of this transcription factor in insecticide resistant and susceptible strains of C. pomonella may also play a role in resistance, as reported for other transcription factors involved in the regulation of resistance genes ( 19 ). Intriguingly, previous studies have demonstrated that knockdown of an alternative transcription factor, CpAhR , results in reduced expression of the GST gene CpGSTe3 , thereby increasing susceptibility of C. pomonella to λ-cyhalothrin ( 36 ). This illustrates that multiple transcription factors that regulate detoxification gene networks in an insect species have the potential to be recruited in the evolution of insecticide resistance. Insecticide resistance is often accompanied by a fitness costs in the absence of insecticide ( 9, 13 ), however, the molecular mechanisms underpinning these costs are poorly resolved. Our results reveal that C. pomonella employs the transcription factor CpCncC to regulate the expression of key detoxification and developmental genes, mediating a trade-off between resistance mechanisms and developmental retardation. This regulatory mechanism is mediated by hormone biosynthesis, specifically involving CYP306A1 , a member of the Halloween gene family ( 37 ), which is directly regulated by CpCncC , thereby influencing the biosynthesis of 20E—a crucial component of the hormonal regulation pathway. This hormone-mediated trade-off develops in response to sustained insecticide selection pressure, since transient hormonal fluctuations induced by short-term sublethal dosage insecticide stress are minimal and inconsistent, with negligible effects on developmental duration. Our findings also indicate that CpCncC 's role in modulating 20E levels is vital, as either partial loss-of-function or brief suppression of gene expression can markedly disrupt developmental duration. A similar regulatory network has been observed in Tribolium castaneum , where CncC regulates deltamethrin resistance and influences the expression of the 20E synthesis-related gene TcPhantom , TcShade , and JH degradation-associated gene TcJHEH-r3 , leading to reduced JH titers and decreased vitellogenin ( Vg ) expression( 19 ). In contrast, in C. pomonella , CpCncC does not regulate JHEH but overexpression leads to elevated 20E levels, dysregulation of JH pathway genes and reduced JH titers through antagonistic hormonal interactions ( 38 ). Conversely, insecticide resistance development in B. tabaci , which incurs fitness costs, is governed by a distinct mechanism involving CncC activation through phosphorylation by the p38 and ERK pathways, subsequently repressing critical genes associated with oogenesis, such as exuperantia ( Ex ), vasa ( Va ), and genes involved in germ cell tumor formation ( Bg ), impacting zygomorphogenesis ( 11 ). Thus, the trade-off between the regulation of insecticide resistance through the CncC pathway and developmental duration may represent a common phenomenon associated with resistance in crop pests. Additionally, CncC functions as a pivotal regulator of oxidative stress responses, lifespan, and immune system enhancement, with its expression finely balanced to prevent detrimental over- or under-expression ( 17, 33 ). This regulatory precision may explain the challenge in generating homozygous CpCncC mutants in our study even after multiple targeting attempts and extensive trials, despite the availability of mature CRISPR/Cas9 gene editing tools for C. pomonella ( 39 ). Indeed, to date, no studies have established successful knockout lines of CncC in insects or invertebrates; only in medical research involving tumor cell lines has a knockout of Nrf2 been achieved ( 40 ), suggesting CncC is indispensable. This finding suggests that CncC is under strong functional constraint in insects to ensure the integrity of key regulatory networks. In this regard, our study illustrates how the exceptionally strong selection pressure exerted by insecticides on insect pest population can result in changes in the regulation of even tightly controlled essential genes. In summary, this study systematically elucidates the function of CpGSTd1 providing new insights into the metabolic pathways by which the transcription factor CpCncC modulates GST expression to confer insecticide resistance. We demonstrate how the modulation of this resistance gene pathway underpins fitness costs associated with resistance, advancing understanding of the molecular mechanisms underpinning an iconic example of an evolutionary trade-off. The identified resistance regulatory mechanisms present promising targets for integrated pest management strategies, including ROS, transcriptional regulators, and detoxification enzymes. MATERIALS AND METHODS Insects and rearing A susceptible strain of C. pomonella (SS) was maintained for over 100 generations without exposure to insecticide ( 41 ). A population LCR(G15) with moderate-level resistance to λ-cyhalothrin was established in the laboratory through continuous manual selection from SS ( 22 ). Based on this, the LCR population was subjected to further selection for 15 additional generations, resulting in the LCR(G30) population. Both populations were reared at 26 ± 1°C under a 16:8 hours photoperiod in an incubator (Panasonic, MLR-352H-PC, Japan). Equal proportions of adult males and females were housed in custom plastic containers and mated to oviposit after supplementation with a 10% honey solution. Newly hatched larvae were transferred to an artificial diet to complete larval development until pupation, with relative humidity maintained at 60% to prevent desiccation of the diet. Sample collection Developmental stages and tissues of fourth-instar larvae from C. pomonella samples were prepared as described by Hu et al. (2020) ( 41 ). All samples were flash-frozen in liquid nitrogen and stored at -80℃ for subsequent analysis. Protein extraction and digestion A 150 mg midgut sample of the LCR (LCR_MG) and SS (SS_MG) populations was pulverized in liquid nitrogen and lysed with 200 µL of SDT buffer (100 mM DTT, 100 mM Tris HCl), followed by 5 min of on-ice ultrasonication ( 42 ). The lysate was heated at 95℃ for 15 min, then cooled in an ice bath for 2 min. After centrifugation at 12,000 g for 30 min, the supernatant was alkylated with 1/5 volume of 500 mM iodoacetamide solution for 1 h at room temperature in the dark. Subsequently, the sample was fully mixed with 800 µL of pre-cooled acetone and incubated at -20°C for 2 h. The mixture was centrifuged again at 12,000 g for 15 min at 4°C, and the precipitate was collected. The precipitate was resuspended and washed with 1 mL of pre-cooled acetone to recover the total pelleted proteins. Tandem mass tags (TMT) proteomic quantification Each sample was reconstituted with 100 μL of 0.1 M TEAB buffer (Sigma, Germany). Then, 41 μL of acetonitrile-dissolved TMT labeling reagent (Thermo, USA) was added, and the mixture was shaken for 2 h at room temperature ( 42 ). The reaction was quenched with 8% ammonia solution. All labeled peptides from each sample were pooled in equal volumes, desalted, and lyophilized. Each fraction was analyzed via ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) using a Q ExactiveTM HF-X (Thermo Fisher, Germany) and Orbitrap Exploris 480 mass spectrometer (Thermo Fisher, Germany). For each analysis, 1 μg of peptide was separated using solvents: Liquid A (100% water, 0.1% formic acid) and Liquid B (80% acetonitrile, 0.1% formic acid) over a 60-minute gradient. Protein identification was performed by searching the silkworm protein database (https://www.uniprot.org/uniprotkb?query=Bombyx+mori) with Proteome Discoverer. To ensure high-quality results, peptide spectrum matches (PSMs) with confidence levels ≥99%, along with proteins containing at least one unique peptide, were retained. False discovery rate (FDR) validation was applied to exclude peptides and proteins with an FDR exceeding 1%. RNA extraction, cDNA synthesis and relative expression analysis Total RNA was isolated using RNAiso Plus (Takara, Beijing, China) following the manufacturer's protocol. RNA quantity and integrity were assessed with a NanoDrop 2000 spectrophotometry (ThermoFisher Scientific, Waltham, the United States of America). First-strand cDNA was synthesized using 1 μg of total RNA utilizing the PrimeScript™ II 1st Strand cDNA Synthesis Kit (Takara, Beijing, China). Real-time quantitative PCR (RT-qPCR) was conducted on a Bio-Rad CFX96 system (Bio-Rad, Singapore) with the following thermal cycling conditions: initial denaturation at 95℃ for 30 s, followed by 40 cycles of denaturation at 95℃ for 5 s, annealing at 50-60℃ for 30 s, and extension at 72℃ for 30 s. Reactions were prepared in 20 μL volumes containing 1 μL of cDNA template, 10 μL of TB Green® Premix Ex Taq™ 2 (Tli RNaseH Plus), 0.8 μL of each primer, and nuclease-free water to volume. Internal control genes, EF-1α (MN037793) and GAPDH (MT116773) (Table S11), were used as reference standards ( 21 ). Relative expression levels were calculated using the 2 -ΔΔCT method ( 43 ). RNA-Seq data analysis RNA integrity was assessed using the RNA Nano 6000 Assay Kit on the Bioanalyzer 2100 system (Agilent Technologies, USA). Sequencing libraries were prepared using the TruSeq PE Cluster Kit v3-cBot-HS (Illumia) on a cBotCluster Generation System according to the manufacturer's instructions ( 44 ). The reference genome and gene annotation files for C. pomonella were obtained from InsectBase 2.0 (http://v2.insect-genome.com). Genome indexing was performed, and paired-end reads were aligned using Hisat2 v2.0.5. The number of reads per gene was calculated using Counts v1.5.0-p3 and FPKM (Fragments Per Kilobase of transcript per Million mapped reads) was quantified based on the length of the gene. Differential expression analysis was performed using the DESeq2 R 1.20.0 software on data from different groups, using a model based on the negative binomial distribution to determine differential gene expression. Benjamini and Hochberg's method was used to adjust the false discovery rate and thus calculate the corrected P -value, with a threshold of 0.05 set as the baseline for differential expression. Bioassay The insecticidal activity of λ-cyhalothrin (Aladdin, Shanghai, China) was evaluated through a topical droplet bioassay on fourth-instar C. pomonella larvae, following the method described by Li et al. (2023) ( 29 ). λ-cyhalothrin solutions were prepared by dissolving the compound in acetone, followed by serial dilutions. A 1 μL droplet was applied to the pronotum of each freshly molted fourth-instar larva, ensuring complete penetration. Treated larvae were transferred to 24-well plates containing 1 cm³ of artificial diet. Each concentration involved 45 larvae, with three replicates per concentration. Control groups received an equivalent volume of acetone. Mortality was assessed at designated time points post-treatment; larvae unresponsive to stimuli were recorded as dead. RNA Interference (RNAi) The synthesized double-stranded RNA (dsRNA) was administered into larvae via microinjection to suppress gene transcription ( 45 ). Briefly, cDNA templates were amplified using specific primers (Table S11) containing a T7 promoter sequence, and dsRNA was synthesized employing the T7 RiboMAXTM Express RNAi System (Promega, USA) in accordance with the manufacturer's protocol. Larvae were immobilized by incubation on ice for approximately 10 min before injection while still paralyzed. One μL of dsRNA at a concentration of 1000 ng μL -1 was injected into the posterior end of each larva (at three to five segments). A minimum of 30 individuals, with three biological replicates, were used. An equivalent volume of dsGFP was injected as a control. Samples were collected at various time points post-injection for gene expression analysis to determine the optimal interference timing. Establishment of the transgenic Drosophila melanogaster and bioassay The attP-PhiC31 recombinase system was employed to generate a CpGSTd1 transgenic D. melanogaster line, leveraging the GAL4-UAS binary expression system to achieve gene overexpression ( 46 ). Briefly, the CpGSTd1 coding sequence was cloned into the transgenic Drosophila expression vector pNP and injected into embryos of the attP40 strain. Integration into chromosome 2 was mediated by PhiC31 integrase. Progeny reaching adulthood were screened for the red-eye phenotype, indicating successful transgene insertion, producing the 10UAS-CpGSTd1 line. This line was crossed with the Tub-GAL4 and GAL80ts balancer line carrying the Bc/CyO second chromosome balancer to establish a stable transgenic line, 10UAS-CpGSTd1+Tub-GAL4,GAL80ts, with balanced segregation on chromosomes 2 and 3. The insecticide bioassay involved coating the inner surfaces of glass vials with formulated insecticide solutions to assess toxicity across different transgenic lines ( 5 ). Insecticides were dissolved in acetone at varying concentrations, then 200 μL of each solution was dispensed into 20 mL clear cylindrical glass vials (bottom diameter, 2.5 cm; top diameter, 2.0 cm; height, 4.5 cm), followed by rapid rotary evaporation to remove solvent, leaving a uniform film. After a 1-hour drying period, approximately 15 flies within one day of emergence were transferred into each vial via tapping. Vials were sealed with foam stoppers containing a cotton ball saturated with 10% honey solution. Control vials received an equivalent volume of acetone. Each concentration was tested in triplicate. Mortality was recorded after 24 h; flies unresponsive to gentle shaking were classified as dead. Western blot analysis Total proteins were extracted from samples utilizing the Column Animal Tissue Protein Extraction Kit (Epizyme Biotech, Shanghai, China), following the manufacturer's instructions. A 20 mg tissue sample was lysed in 200 μL of RIPA buffer containing 1/100 volume of PMSF protease inhibitor, then homogenized using a high-throughput grinder (SolenBio, Beijing, China). Following centrifugation at 12,000 g for 10 min at 4°C, the supernatant was collected, and protein concentration was determined using the BCA Protein Assay Kit (SolenBio, Beijing, China). Proteins were separated on a 5% SDS-PAGE concentrated gel and 12% SDS-PAGE separation gel (Bio-Platform, Shanghai, China) at 120 V for 1 h. Proteins were transferred onto PVDF membranes (Millipore, Ireland), which were blocked for 2 h with TBST buffer containing 5% skim milk powder. Membranes were incubated overnight at 4°C with primary rabbit polyclonal antibodies (1:1000) targeting the respective proteins. After washing, membranes were incubated with secondary goat anti-rabbit IgG (1:10,000; Bio-Platform, Shanghai, China). Beta-actin (from Drosophila ) rabbit polyclonal antibody (1:1500) served as an internal control. Protein bands were visualized using an ECL detection system (SolenBio, Beijing, China) for quantitative analysis. Protein structure construction and molecular docking The three-dimensional (3D) conformation of the CpGSTd1 enzyme was modeled using AlphaFold ( 47 ). The highest confidence prediction was selected based on the local distance difference test (LDDT) score to validate structural reliability. An alternative crystal structure of a GST protein (PDB ID: 3vk9) from B. mori was used as a template for homology modeling of CpGSTd1 with Modeller 9.10 ( 26 ). The 3D structural model of CpGSTd1 generated through AlphaFold and Modeller 9.10 simulations were superimposed using PyMOL, with a root-mean-square deviation (RMSD) below 1.0 Å indicating a high degree of structural congruence. The λ-cyhalothrin ligand structure was obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and converted to PDB format with Open Babel 3.0 for compatibility with molecular docking simulations. The AlphaFold-based modeling platform was utilized to calculate the interface predicted template modeling-score (iPTM) to assess the reliability of the predicted molecular conformation, with docking simulations performed across at least five independent runs to evaluate binding conformations. Molecular docking of CpGSTd1 with λ-cyhalothrin was executed using the GOLD 2020.3 software, and binding free energies were calculated via the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach ( 48 ). The ligand-protein complex was visualized to analyze interaction patterns using PyMOL. Additionally, computational alanine scanning (CAS) was obtained to evaluate the binding free energy (ΔΔG binding ) difference before and after alanine substitution using the Molecular Mechanics Poisson Boltzmann/Generalized Born Surface Area (MM-PB/GBSA) method in AMBER 9.10 ( 49 ). The mutant complexes were generated by a single truncation of the mutated side chain, replacing Cγ with a hydrogen atom and setting the Cβ-H direction to that of the former Cβ-Cγ ( 50 ). ΔΔG binding was defined as the difference between the mutant complex (cpx-mutant) and the wild-type complex (cpx-WT) obtained by calculating ΔΔG binding = ΔΔG cpx-mutant - ΔΔG cpx-WT ( 50 ). Expression and binding activity of mutant CpGSTd1 proteins Informed by the CpGSTd1 sequence and CAS results, three amino acids—Val53, Tyr114, and Phe118—were targeted for site-directed mutagenesis. The mutated coding sequences were cloned into the pET-28a(+) expression vector and transformed into Escherichia coli BL21 (DE3) ( 26 ). The recombinant mutants were expressed and purified, then assayed for enzymatic activity using a spectrophotometric assay measuring the change in absorbance at 340 nm upon reaction with different concentrations of CDNB (0.01–0.32 mM) and 10 mM GSH. Kinetic parameters ( K m and V max ) were derived by fitting the Michaelis-Menten equation (GraphPad Prism 5). To evaluate inhibitory effects, 0.8 μg of purified mutant proteins was incubated with varying concentrations of λ-cyhalothrin (50–2000 μM) for 5 min at 30°C, and residual GST activity was measured after addition of 2 mM CDNB to determine the IC 50 value. S-hexylglutathione (GTX) served as a positive control, with three replicates for each experiment. Determination of the metabolic capacity of CpGSTd1 in vitro The in vitro metabolic capacity was assessed by quantifying residual λ-cyhalothrin following incubation with wild-type and mutant CpGSTd1 proteins ( 26 ). The reaction mixture contained 20 mg of recombinant protein, 2.5 mM GSH, and 0.6 mM λ-cyhalothrin in 0.5 mL of 50 mM potassium phosphate buffer (pH 7.2). Incubation was performed at 30°C for 60 min with agitation at 300 rpm. Reactions were halted by adding 0.5 mL of ethyl acetate, followed by centrifugation at 14,000 rpm for 20 min at room temperature. The supernatant was analyzed under a mobile phase of 75% acetonitrile for residual insecticide content, with heat-inactivated enzyme used as a control. Promoter cloning and analysis The genomic DNA of C. pomonella was extracted utilizing the DNA extraction kit (BayBiopure, Guangzhou, China), and primers (Table S11) were designed for cloning the upstream promoter regions based on the genomic sequence data (http://v2.insect-genome.com). Transcription factor binding sites within the promoter regions were predicted using JASPAR (https://jaspar.elixir.no/), with the promoter segments segmented into intervals of 200 to 400 bp depending on the prediction results. Promoter fragments of varying lengths were amplified via PCR using PrimeSTAR Max DNA Polymerase (Takara, Beijing, China), and the fragments were ligated into the firefly luciferase report vector pGL4.10-Basic (Promega, the United States of America) through the Infusion Kit (Takara, Beijing, China) ( 11 ). Dual-luciferase reporter assays All recombinant plasmids were purified with the Mini Plasmid Kit (TIANGEN, Beijing, China) to remove endotoxin, and used for dual-luciferase reporter assays in D. melanogaster S2 cells ( 11 ). Briefly, 200 µL of SFX-insect medium and 100 µL of pre-activated cells were added into 24-well culture plates for adherence. Co-transfection was performed once cell coverage reached approximately 80%, involving 600 ng of promoter plasmids, 100 ng of pGL4.73 control plasmids, and the Lipofectamine 2000 reagent (Invitrogen, USA). The pGL4.73 vector contains the luciferase reporter gene used internally for normalization. Similarly, the CDS sequence of the transcription factor was inserted into the pAC5.1b/V5/His B expression vector pre-cut with EcoRV restriction enzyme for ligation. For binding activity analysis, cells were co-transfected with 600 ng of transcription factor plasmids, 200 ng of promoter plasmids, and 100 ng of pGL4.73. Post-transfection, cells were incubated at 27°C for 48 h, then lysed with agitation at 200 rpm for 15 min. Luciferase activity was measured using the GloMax 96 Discover system (Promega, USA) while applying the Dual-Luciferase Reporter Assay System (Promega, USA). The ratio of firefly to Renilla luciferase activity was calculated for each sample and normalized against the control (empty vector). Each assay was performed in quadruplicate. Synthesis of single guide RNA (sgRNA) The sgRNA target sequences were designed within different exons using the CRISPOR program (https://crispor.gi.ucsc.edu/). Target sites were selected based on the 5'-N20NGG-3' motif, with preference given to sites with minimal or no off-target potential. Oligonucleotides corresponding to the sgRNA target sites, including the T7 polymerase binding site, were used as upstream primer (Table S11), with fixed downstream primers ( 39 ). PCR-based synthesis of template DNA involved a 50 μL reaction mixture containing 25 μL of PrimeSTAR Max Premix (TaKaRa, Beijing, China), 2 μL each of upstream and downstream primers, and 21 μL of RNase-Free Water. The PCR protocol was executed at 98°C for 2 min, followed by 35 cycles of 10 s at 98°C, 10 s at 70°C, 30 s at 72°C, and a 10-minute extension step at 72°C. PCR products served as templates for in vitro sgRNA synthesis using the Precision gRNA Synthesis Kit (Invitrogen, USA), following manufacturer instructions. The synthesized sgRNA was stored at -80°C. Embryonic injection and mutagenesis detection Embryonic injection was conducted as previously described with minor modifications ( 39 ). Eggs laid within 1 h were rinsed with PBS buffer and the egg paper was sectioned into small fragments affixed firmly to double-sided tape inside a Petri dish. A solution containing 100 ng μL −1 of sgRNA and 100 ng μL −1 of Cas9 endonuclease (Invitrogen, the United States of America) was microinjected into each egg using the FemtoJet 4i Micro-Injection System (Eppendorf, Germany). Post-injection, the Petri dishes were transferred to an incubator (Panasonic, MLR-352H-PC, Japan) for rearing according to standard population rearing protocols. A mutation screening strategy was employed to establish homozygous mutant populations. Briefly, G0 individuals harboring the desired mutation were intercrossed to generate the G1 progeny for further amplification. Subsequent gene sequencing analyses identified homozygous mutants within the G1 generation, which were then self-crossed to produce the G2 generation of stabilized homozygous mutants. Evaluation of oxidative stress markers and antioxidant responses Reactive oxygen species (ROS) levels in larvae subjected to various treatments were quantified using the Reactive Oxygen Species Red-Fluorescent Assay Kit (BestBio, Shanghai, China). Specifically, the BBoxiProbe® O13 dye was oxidized by tissue ROS to generate a red-fluorescent compound, with fluorescence intensity measured at excitation/emission wavelengths of 535/606 nm to reflect ROS concentrations. Enzymatic activities of key antioxidant enzymes—peroxidase, catalase, and superoxide dismutase—were assessed using corresponding enzyme activity kits (Jiancheng Bioengineering Institute, Nanjing, China). To determine if ROS scavenging influences the CncC pathway, fourth-instar larvae were fed an artificial diet supplemented with the ROS scavenger N-acetylcysteine (NAC) for 48 h ( 19 ). Data analysis Differences among experimental groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey's post hoc test ( P < 0.05) utilizing SPSS Statistics 22. Student's t -test (*, P < 0.05) was applied for pairwise comparisons. Data are expressed as mean ± standard error (SE) and illustrated with graphs generated via GraphPad Prism 9 software (GraphPad, CA). Declarations Supplementary Materials This PDF file includes: Figure S1-S15 and Table S1-S11. Acknowledgments: We thank Prof. You-Jun Zhang, Dr. Bu-Li Fu, Dr. Jing Yang, Dr. Pei-Pan Gong from the Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China, for the support in the dual luciferase reporter assay. For the purpose of open access, the author has applied a ‘Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. Funding: This research was supported by the National Natural Science Foundation of China (32272588), Liaoning Provincial Natural Science Foundation for Distinguished Young Scholars (2024JH3/50100027)，and National Key R&D Program of China (2021YFD1400200). Author contributions: Conceptualization: C. H. and X.Q. Y. Methodology: C. H., Y.X. L., X. Y., J.Y. L., Y.T. L. and X.Q. Y. Software: C. H., Y.X. L., X. Y. and J.Y. L. Data curation: C. H. and Y.X. L. Visualization: C. H., Y.X. L. and J.Y. L. Validation: C. H., Y.X. L, C. B. and X.Q. Y. Investigation: C. H., Y.X. L., Y.T. L. and X.Q. Y.F ormal analysis: C. H., C. B. and X.Q. Y. Original draft: C. H. Writing—review and editing: C. H., C. B. and X.Q. Y. Resources: C. B. and X.Q. Y. Funding acquisition: X.Q. Y. Competing interests: All authors declare that there are no conflicts of interest. 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Li, Antagonistic actions of juvenile hormone and 20-hydroxyecdysone within the ring gland determine developmental transitions in Drosophila . Proc. Natl. Acad. Sci. U. S. A. 115 , 139-144 (2018). Z. H. Wei, C. Wang, X. Zhang, Y. Lv, Y. Li, P. Gao, X. Q. Yang, CRISPR/Cas9-mediated knockout of Tektin 4-like gene ( TEKT4L ) causes male sterility of Cydia pomonella . Insect Biochem. Mol. Biol. 177 , 104257 (2025). A. Anandhan, M. Dodson, A. Shakya, J. Chen, P. Liu, Y. Wei, H. Tan, Q. Wang, Z. Jiang, K. Yang, J. G. Garcia, S. K. Chambers, E. Chapman, A. Ooi, Y. Yang-Hartwich, B. R. Stockwell, D. D. Zhang, NRF2 controls iron homeostasis and ferroptosis through HERC2 and VAMP8. Sci. Adv. 9 , eade9585 (2023). C. Hu, W. Wang, D. Ju, G. M. Chen, X. L. Tan, D. Mota-Sanchez, X. Q. Yang, Functional characterization of a novel λ-cyhalothrin metabolizing glutathione S-transferase, CpGSTe3 , from the codling moth Cydia pomonella . Pest Manag. Sci. 76 , 1039-1047 (2019). C. Friedrich, C. Friedrich, S. Schallenberg, M. Kirchner, M. Ziehm, S. Niquet, M. Haji, C. Beier, J. Neudecker, F. Klauschen, P. Mertins, Comprehensive micro-scaled proteome and phosphoproteome characterization of archived retrospective cancer repositories. Nat. Commun. 12 , 3576 (2021). J. L. Kenneth, D. S. Thomas, Analysis of relative gene expression data using real-time quantitative PCR and the 2 −ΔΔCT method. Methods 25 , 402-408 (2001). W. S. Leal, Y. M. Choo, P. Xu, C. S. da Silva, C. Ueira-Vieira, Differential expression of olfactory genes in the southern house mosquito and insights into unique odorant receptor gene isoforms. Proc. Natl. Acad. Sci. U. S. A. 110 , 18704-18709 (2013). Y. X. Liu, C. Hu, Z. N. Xia, Y. Wang, Y. T. Li, P. Gao, Y. T. Lv, J. L, X. Q. Yang, Overexpression of G protein-coupled receptors (GPCRs) contributing to lambda-cyhalothrin resistance in Cydia pomonella . Pestic. Biochem. Physiol. 214 , 106608 (2025). T. Osterwalder, K. S. Yoon, B. H. White, H. Keshishian, A conditional tissue-specific transgene expression system using inducible GAL4. Proc. Natl. Acad. Sci. U. S. A. 98 , 12596-12601 (2001). J. Abramson, J. Adler, J. Dunger, R. Evans, T. Green, A. Pritzel , O. Ronneberger, L. Willmore, A. J. Ballard, J. Bambrick, S. W. Bodenstein, D. A. Evans, C. C. Hung, M. O'Neill, D. Reiman, K. Tunyasuvunakool, Z. Wu, A. Žemgulytė , E. Arvaniti, C. Beatti, O. Bertolli, Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630 , 493-500 (2024). J. Y. Liu, X. Q. Yang, Y. Zhang, Characterization of a lambda-cyhalothrin metabolizing glutathione S-transferase CpGSTd1 from Cydia pomonella (L.). Appl. Microbiol. Biotechnol. 98 8947-62 (2014). X. Q. Yang, J. Y. Liu, X. C. Li, M. H. Chen, Y. L. Zhang, Key amino acid associated with acephate detoxification by Cydia pomonella carboxylesterase based on molecular dynamics with alanine scanning and site-directed mutagenesis. J. Chem. Inf. Model. 54 , 1356-1370 (2014). R. M. Ramos, I. S. Moreira, Computational alanine scanning mutagenesis-an improved methodological approach for protein-DNA complexes. J. Chem. Theory. Comput. 9 , 4243-4256 (2013). Additional Declarations There is NO Competing Interest. Supplementary Files GraphicalAbstract.pdf Graphical Abstract SupportingInformation.docm Supporting Information Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8791607","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":596414795,"identity":"b8790cde-4d69-4e74-b190-d544321d21cb","order_by":0,"name":"Xueqing Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYPACGyjNRryWNNK1HCZBi8HxHMPPBb/O2xscP2PA8KHsMAP/7Ab8WiR73hhLz+y7nbjhTI4B44xzhxkk7hzAr4VfIsdAmrfndoLBgRwDZt62wwwGEgn4tbBJ5Bj/5u05Z29w/o0B819itABtMZPm+XGAccMNoC2MxGiR7HlWZs3bkJw488azgoM959J5JG4Q0GJwPHnzbZ4/dvZ855M3PvhRZi3HP4OAFgaGDAMGxjYGBoUDDAxAxMBDSD0QpD9gYPjDwCDfQITaUTAKRsEoGJkAADCqRUt+gjBtAAAAAElFTkSuQmCC","orcid":"","institution":"College of Plant Protection, Shenyang Agricultural University, Shenyang","correspondingAuthor":true,"prefix":"","firstName":"Xueqing","middleName":"","lastName":"Yang","suffix":""},{"id":596414796,"identity":"d4934643-8d8a-4648-a9ce-b3e7b4823e9e","order_by":1,"name":"Chao Hu","email":"","orcid":"","institution":"shenyang agricultural university","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Hu","suffix":""},{"id":596414797,"identity":"ef12e075-6cf9-4091-8761-ac88059e3188","order_by":2,"name":"Yuxi Liu","email":"","orcid":"","institution":"College of Plant Protection, Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yuxi","middleName":"","lastName":"Liu","suffix":""},{"id":596414798,"identity":"c4caf09f-8f5b-40a8-bf67-542baee8e08c","order_by":3,"name":"Xin Yang","email":"","orcid":"","institution":"Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Yang","suffix":""},{"id":596414799,"identity":"6aba42dc-cc21-4dd2-b032-8cc2ea652edd","order_by":4,"name":"Jiyuan Liu","email":"","orcid":"","institution":"Northwest A\u0026F Universit","correspondingAuthor":false,"prefix":"","firstName":"Jiyuan","middleName":"","lastName":"Liu","suffix":""},{"id":596414800,"identity":"3a13fc3c-195a-4eb1-a40a-b55a53d0376c","order_by":5,"name":"Yuting Li","email":"","orcid":"","institution":"College of Plant Protection, Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yuting","middleName":"","lastName":"Li","suffix":""},{"id":596414801,"identity":"3625818c-c80a-4c95-af52-3c25b07a4f16","order_by":6,"name":"Chris Bass","email":"","orcid":"https://orcid.org/0000-0002-2590-1492","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Chris","middleName":"","lastName":"Bass","suffix":""}],"badges":[],"createdAt":"2026-02-05 03:15:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8791607/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8791607/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104209330,"identity":"f28aab64-8a27-4852-b5b8-68fdca950a48","added_by":"auto","created_at":"2026-03-09 07:28:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":950762,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of GST genes overexpressed in λ-cyhalothrinin resistant \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e populations. \u003c/strong\u003e(A) LD\u003csub\u003e50\u003c/sub\u003e values of the SS and LCR populations after 15 generations (LCR(G15)) and 30 generations (LCR(G30)) of λ-cyhalothrinin exposure. (B) Larval duration, (C) pupal duration, and (D) reproductive capacity of female adults of the SS and LCR populations. (E) Heatmap visualization of differentially up-regulated detoxification genes in transcriptome analysis, with FPKM values representing gene expression transformed in logarithms. (F) RT-qPCR-based validation of relative transcript levels of differentially up-regulated detoxification genes in transcriptome analysis. (G) Volcano plot of differentially expressed proteins in proteomics analysis. Black dots, red dots, and green dots represent proteins with non-significant differential expression, significantly up-regulated proteins, and significantly down-regulated proteins, respectively. (H) Protein expression levels of overexpressed detoxification enzymes in proteomic analysis. (I) Correlation analysis of transcriptional and protein expression for differentially expressed genes in association analysis. (J) RT-qPCR analysis of mRNA expression of \u003cem\u003eCpGSTd1\u003c/em\u003e in different populations. (K) Western blot analysis and quantitative result of CpGSTd1 expression in different populations. All error bar represents the standard error of the mean. Asterisks indicate statistically significant differences as determined by student's t-test (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Letters on the error bars indicate significant differences analyzed by ANOVA with multiple-comparison Tukey's test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/95dfe6ab6d7f3c4b72c5bd1f.png"},{"id":104209287,"identity":"0aa551e5-2d1a-43d0-a341-75922153f2f2","added_by":"auto","created_at":"2026-03-09 07:28:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1612087,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eContribution of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCpGSTd1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eto λ-cyhalothrin resistance in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A) Interference efficiency of \u003cem\u003eCpGSTd1 \u003c/em\u003eby RNAi. (B) Susceptibility of different populations of \u003cem\u003eC. pomonella\u003c/em\u003e to λ-cyhalothrin following RNAi knockdown of \u003cem\u003eCpGSTd1\u003c/em\u003e. (C) Transcriptional levels of \u003cem\u003eCpGSTd1 \u003c/em\u003ein different transgenic \u003cem\u003eDrosophila\u003c/em\u003e lines. (D) Susceptibility of different \u003cem\u003eDrosophila \u003c/em\u003elines to λ-cyhalothrin. UAS represents the \u003cem\u003eDrosophila \u003c/em\u003eline 10UAS-CpGSTd1; GAL represents the \u003cem\u003eDrosophila \u003c/em\u003eline 10UAS-CpGSTd1+Tub-GAL4,GAL80ts. (E) Verification of \u003cem\u003eCpGSTd1 \u003c/em\u003emutations by Sanger sequencing. Target gene sequences and PAM sequences are annotated in blue and red, respectively. Missing bases are indicated by black horizontal bars. (F) Schematic diagram of the screening process for the homozygous mutant population LCR-GSTd1KO. (G) Susceptibility of the homozygous mutant population LCR-GSTd1KO to λ-cyhalothrin. (H) Conformational alignment between CpGSTd1 3D models based on the program GOLD (blue) and AlphaFold (yellow) software. (I) Simulated docking of CpGSTd1 with λ-cyhalothrin based on traditional homology modelling. A crystal GST structure from \u003cem\u003eB. mori\u003c/em\u003e (PDB ID:3vk9) was selected as template. (J) Simulated docking of CpGSTd1 with λ-cyhalothrin based on the AlphaFold model. (K) Side chain free energy contribution of the complex of CpGSTd1 with λ-cyhalothrin. (L) \u003cem\u003eIn vitro\u003c/em\u003e metabolic rates of λ-cyhalothrin by recombinant WT CpGSTd1 and mutant proteins. The error bar represents the standard error of the mean. Asterisks indicate statistically significant differences as determined by student's t-test (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/539da3b5d5bc255498b8dace.png"},{"id":104209284,"identity":"5b810726-731d-4025-ae33-6eed6fe7d2bd","added_by":"auto","created_at":"2026-03-09 07:28:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1095460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVerification of transcriptional regulation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCpCncC \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCpGSTd1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A) Heatmap visualization of expression levels of transcription factors in transcriptome analysis, with FPKM values representing gene expression transformed in logarithms. (B) RT-qPCR-based validation of relative transcript levels of transcription factors in transcriptome analysis. (C) Protein expression levels of differentially expressed transcription factor proteins in proteomic analysis. (D) Heatmap visualization of the mortality of the LCR population under λ-cyhalothrin treatment at different times after injection of dsRNA targeting different transcription factor. (E) Susceptibility of the LCR population of \u003cem\u003eC. pomonella\u003c/em\u003e to λ-cyhalothrin following injection of different dsRNAs. (F) FPKM values of \u003cem\u003eCpGSTd1 \u003c/em\u003efollowing dsRNA injection based on transcriptome analysis. (G) Transcriptional levels of \u003cem\u003eCpGSTd1 \u003c/em\u003efollowing injection of dsCpCncC and dsCpHNF4 based on RT-qPCR. (H) Transcriptional levels of \u003cem\u003eCpCncC \u003c/em\u003eand \u003cem\u003eCpGSTd1 \u003c/em\u003ein \u003cem\u003eC. pomonella\u003c/em\u003e following curcumin treatment. (I) Transcriptional activity of putative promoter sequences upstream of \u003cem\u003eCpGSTd1\u003c/em\u003e in dual luciferase reporter gene assays. (J) Effects of two different transcription factors on the activity of the \u003cem\u003eCpGSTd1\u003c/em\u003epromoter in reporter gene assays. Empty pAC5.1b was used as a control. (K) Schematic of the \u003cem\u003ecis\u003c/em\u003e-acting elements predicted in the \u003cem\u003eCpGSTd1 \u003c/em\u003epromoter. Different colored boxes represent predicted transcription factor binding sites within the \u003cem\u003eCpGSTd1\u003c/em\u003e promoter. The sequence at the most upstream \u003cem\u003eCpCncC\u003c/em\u003e binding site in the transcriptional activity region was targeted for mutation, with mutated bases highlighted in red. (L) Effects of \u003cem\u003eCpCncC\u003c/em\u003e on the activity of the mutated \u003cem\u003eCpGSTd1\u003c/em\u003e promoter in reporter gene assays. Error bars represent the standard error of the mean. Asterisks indicates statistically significant differences as determined by student's t-test (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Letters above error bars indicate significant differences analyzed by ANOVA with multiple-comparison Tukey's test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/e020a763f328d0f6edcc1024.png"},{"id":104209280,"identity":"21497710-facc-479c-8c83-b6daedca5c4f","added_by":"auto","created_at":"2026-03-09 07:28:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":220258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of ROS activation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCpCncC\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-mediated transcriptional regulation in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e (A) ROS levels in different \u003cem\u003eC. pomonella \u003c/em\u003epopulations. (B) ROS levels in different \u003cem\u003eC. pomonella \u003c/em\u003epopulations 24 h after treatment with an LD\u003csub\u003e10\u003c/sub\u003e dose of λ-cyhalothrin. (C) Survival rate of \u003cem\u003eC. pomonella\u003c/em\u003e following treatment with different concentrations of the ROS scavenger NAC. (D) Changes in ROS levels within the LCR population following treatment with different concentrations of NAC. (E) Transcriptional levels of \u003cem\u003eCpCncC \u003c/em\u003eand \u003cem\u003eCpGSTd1 \u003c/em\u003ein \u003cem\u003eC. pomonella\u003c/em\u003e following NAC treatment. (F) Susceptibility of the LCR population of \u003cem\u003eC. pomonella\u003c/em\u003e to λ-cyhalothrin following NAC treatment. Error bars represent the standard error of the mean. Asterisks indicate statistically significant differences as determined by student's t-test (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Letters above error bars indicate significant differences analyzed by ANOVA with multiple-comparison Tukey's test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/9f2d66bd681707502948806e.png"},{"id":104209268,"identity":"04077256-4da4-44f1-8d51-e2014a953f4c","added_by":"auto","created_at":"2026-03-09 07:28:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1336732,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of the role of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCpCncC\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in mediating key developmental processes in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e by regulating hormone levels.\u003c/strong\u003e (A) 20E titer in the SS and LCR populations. (B) JH titer in the SS and LCR populations. (C) The developmental duration of fourth-instar larvae\u003cem\u003e \u003c/em\u003eafter exposure to the LD\u003csub\u003e10\u003c/sub\u003e dose of λ-cyhalothrin. (D) 20E titer of fourth-instar larvae after exposure to the LD\u003csub\u003e10\u003c/sub\u003e dose of λ-cyhalothrin. (E) JH titer of fourth-instar larvae after exposure to the LD\u003csub\u003e10\u003c/sub\u003e dose of λ-cyhalothrin. (F) Survival curves for CpCncC\u003csup\u003e+/+\u003c/sup\u003e and CpCncC\u003csup\u003e+/-\u003c/sup\u003e heterozygous individuals. (G) Developmental duration at different larval instars of CpCncC\u003csup\u003e+/-\u003c/sup\u003e heterozygotes. (H) Pupal phenotype and pupation failure rate of CpCncC\u003csup\u003e+/-\u003c/sup\u003e heterozygotes. (I) Relative expression level of \u003cem\u003eCpCncC \u003c/em\u003ein\u003cem\u003e \u003c/em\u003eCpCncC\u003csup\u003e+/-\u003c/sup\u003e heterozygotes. (J) Schematic of the KEGG pathway for insect hormone biosynthesis after injection of dsCpCncC. Green boxes denote genes with downregulated transcriptional expression; red boxes denote genes with upregulated transcriptional expression. (K) The relative expression level of \u003cem\u003eCYP306A1 \u003c/em\u003ebased on RT qPCR following injection of dsCpCncC. (L) The relative expression levels of key genes in JH-related pathways based on RT-qPCR\u003cem\u003e \u003c/em\u003efollowing injection of dsCpCncC. \u003cem\u003eFPP\u003c/em\u003e, \u003cem\u003efarnesyl pyrophosphate phosphatase\u003c/em\u003e; \u003cem\u003eFD\u003c/em\u003e, \u003cem\u003efarnesyl dehydrogenase\u003c/em\u003e; \u003cem\u003eJHEH\u003c/em\u003e,\u003cem\u003e juvenile hormone epoxide hydrolase\u003c/em\u003e. (M) 20E titer after the injection of dsCpCncC in LCR population. (N) JH titer after the injection of dsCpCncC in LCR population. (O) Effects of dsCpCncC injection and 20E supplementation on developmental duration of \u003cem\u003eC. pomonella\u003c/em\u003e. (P) Pupation rate after dsCpCncC injection and 20E supplementation. Error bars represents the standard error of the mean. Asterisks indicate statistically significant differences as determined by student's t-test (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Letters above error bars indicate significant differences analyzed by ANOVA with multiple-comparison Tukey's test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/4bb02e2cb1f6476ba3bea575.png"},{"id":104209253,"identity":"ece56188-1081-49b7-9923-af44e6392e26","added_by":"auto","created_at":"2026-03-09 07:28:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":130900,"visible":true,"origin":"","legend":"Graphical Abstract","description":"","filename":"GraphicalAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/2b116218ac0298fc2462f619.pdf"},{"id":104209261,"identity":"aa19ced1-2ddb-4b44-9394-a318ba2c169a","added_by":"auto","created_at":"2026-03-09 07:28:22","extension":"docm","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5485283,"visible":true,"origin":"","legend":"Supporting Information","description":"","filename":"SupportingInformation.docm","url":"https://assets-eu.researchsquare.com/files/rs-8791607/v1/e1414d4b32b3f64b78f0ccf6.docm"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"The molecular mechanisms mediating a trade-off between insecticide resistance and development in an invasive pest","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFor more than half a century insecticides have remained a key tool to control many highly damaging insect crop pests and disease vectors worldwide (\u003cem\u003e1, 2\u003c/em\u003e). However, their widespread use has resulted in the evolution of resistance, threatening human food security and health (\u003cem\u003e3, 4\u003c/em\u003e). Resistance commonly results from two main mechanisms: 1) Mutation of the insecticide target site leading to a reduction in sensitivity (\u003cem\u003e5\u003c/em\u003e), or, 2) enhanced expression and/or activity of enzymes, including cytochrome P450 monooxygenases (P450s), carboxylesterases (CarEs), glutathione \u003cem\u003eS\u003c/em\u003e-transferases (GSTs) and UDP-Glucuronosyltransferases (UGTs), that metabolize or sequester the insecticide (\u003cem\u003e6-8\u003c/em\u003e). These mechanisms can result in fitness costs, as mutation of insecticide target proteins can compromise their native function, and enhanced expression of detoxification enzymes carries a metabolic cost (\u003cem\u003e9, 10\u003c/em\u003e). These fitness costs often manifest as reproductive impairments; for example, in \u003cem\u003eBemisia tabaci\u003c/em\u003e, elevated resistance to neonicotinoids correlates with downregulation of oogenesis-related genes, leading to ovarian developmental defects and reduced female fecundity (\u003cem\u003e11\u003c/em\u003e). Similarly, multiple generations of selection in \u003cem\u003eSpodoptera exigua\u003c/em\u003e exposed to tebufenozide resulted in resistance accompanied by a significant fitness cost in egg production (\u003cem\u003e12\u003c/em\u003e). Additionally, resistance-driven resource reallocation can disturb developmental homeostasis, leading to alterations in developmental duration (\u003cem\u003e13\u003c/em\u003e). Previous studies have demonstrated that among 18 pest species resistant to \u003cem\u003eBacillus thuringiensi\u003c/em\u003e\u0026mdash;including \u003cem\u003eHelicoverpa armigera\u003c/em\u003e, \u003cem\u003eS. exigua\u003c/em\u003e, and \u003cem\u003ePlutella xylostella\u0026mdash;\u003c/em\u003ethe average fitness costs associated with resistance, concerning survival and developmental duration, are approximately 15.5% and 7.4%, respectively (\u003cem\u003e9\u003c/em\u003e). Nonetheless, the mechanisms driving the evolutionary trade-off between resistance and altered development and reproduction remain poorly understood.\u003c/p\u003e\n\u003cp\u003eTranscriptional regulation of genes is integral to the connection between genotype and phenotype in organisms, which is essential for maintaining normal physiological functions (\u003cem\u003e14, 15\u003c/em\u003e). Insecticide exposure can activate transcription factors that function as exogenous sensors, driving detoxification gene expression and facilitating resistance evolution (\u003cem\u003e16\u003c/em\u003e). Currently, transcription factors involved in resistance regulation are typically classified into three families: basic leucine zipper (bZIP), basic helix-loop-helix/Per ARNT Sim (bHLH/PAS), and nuclear receptor (NR). The bZIP family member, cap \u0026apos;n\u0026apos; collar isoform C (\u003cem\u003eCncC\u003c/em\u003e), has been extensively validated as a key regulator of insecticide resistance genes (\u003cem\u003e16, 17\u003c/em\u003e). For example, constitutive overexpression of \u003cem\u003eCncC\u003c/em\u003e in \u003cem\u003eS. exigua\u003c/em\u003e has been identified as a primary factor in upregulating \u003cem\u003eCYP321A8\u003c/em\u003e, mediating resistance to chlorpyrifos and cypermethrin (\u003cem\u003e18\u003c/em\u003e). However, in insects, \u003cem\u003eCncC\u003c/em\u003e also facilitates the transcriptional activation of key genes in hormone biosynthesis and catabolism, such as \u003cem\u003eCYP306A1\u003c/em\u003e involved in 20E synthesis and hormone esterase/hydrolase (JHEH), which degrades JH, indicating its pivotal role in hormonal regulation (\u003cem\u003e19\u003c/em\u003e). Thus, aberrations in developmental duration observed in resistant populations may result from hormonal regulation mediated by these transcription factors. However, comprehensive investigations into the adaptive regulatory mechanisms underlying the resistance-development trade-off remain limited.\u003c/p\u003e\n\u003cp\u003eThe codling moth, \u003cem\u003eCydia pomonella\u003c/em\u003e (L.), is a globally invasive pest and exhibits notable issues of insecticide resistance (https://irac-online.org) (\u003cem\u003e20\u003c/em\u003e). Previous studies have indicated a significant correlation between \u0026lambda;-cyhalothrin resistance and elevated detoxification enzyme activities, such as GST and P450 levels, in both field-evolved (\u003cem\u003e21\u003c/em\u003e) and laboratory-selected resistant populations (\u003cem\u003e22\u003c/em\u003e). However, the molecular basis of resistance in \u003cem\u003eC. pomonella\u003c/em\u003e, along with potential trade-offs between resistance and development and the underpinning mechanisms, remains largely unexplored. Here we address this knowledge gap by investigating the regulatory mechanisms underlying the resistance-developmental trade-off and its regulation in \u003cem\u003eC. pomonella.\u003c/em\u003e\u003c/p\u003e\n"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMulti-omics analysis identified\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eCpGSTd1\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;as overexpressed in \u0026lambda;-cyhalothrin-resistant \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003epopulation\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe laboratory-selected resistant \u003cem\u003eC. pomonella\u003c/em\u003e population (LCR) exhibited a stable moderate level of resistance in the 15th (G15) (\u003cem\u003e22\u003c/em\u003e) and 30th (G30) generations under continuous \u0026lambda;-cyhalothrin exposure, relative to the susceptible strain (SS) (Figure 1A). Compared to the SS strain, LCR demonstrated prolonged larval (Figure 1B) and pupal (Figure 1C) developmental durations, accompanied by reduced reproductive capacity (Figure 1D, Table S1). Thus, resistance to \u0026lambda;-cyhalothrin in \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eis associated with significant fitness costs in the absence of insecticide exposure.\u003c/p\u003e\n\u003cp\u003eTo explore the molecular basis of \u0026lambda;-cyhalothrin-resistance, we initially analyzed the sequence of the voltage-gated sodium channel (\u003cem\u003eVGSC\u003c/em\u003e), the target protein of pyrethroid insecticides, in resistant and susceptible populations. No mutations were observed within the\u0026nbsp;\u003cem\u003eVGSC\u003c/em\u003e gene of the LCR strain (Figure S1) suggesting that target-site mutations are not involved in the resistance of this strain to \u0026lambda;-cyhalothrin. We next employed transcriptomic and proteomic analyses to identify differentially overexpressed detoxification-related genes between resistant and susceptible populations. Transcriptome analysis revealed fourteen P450 genes, seven CarE genes, three GST genes, two UGT genes, and two ABC transporter genes exhibiting fold changes ranging from 1.01 to 11.7 (log\u003csub\u003e2\u0026nbsp;\u003c/sub\u003efold change) in the LCR population compared to the SS strain (Figure 1E, Table S6). RT-qPCR confirmed that these detoxification genes were upregulated by 1.13- to 4.0-fold in the LCR population relative to the SS strain (Figure 1F). Proteomic analysis indicated lower variability within the susceptible strain\u0026rsquo;s midgut (SS_MG) and distinct differential protein expression profiles between the SS_MG and resistant population midgut tissue (LCR_MG) (Figure S1). A total of 2,560 proteins were quantified across all samples; among these, differentially expressed proteins (DEPs) were categorized as 116 upregulated and 137 downregulated based on fold change thresholds (\u0026gt;1.2 or \u0026lt;0.83) and statistical significance (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Figure 1G, Table S4). The DEPs profile ranged from 1.20- to 1.94-fold, with only two detoxification enzymes\u0026mdash;cytochrome P450 (CpCYP337B79, A3RIC1; FC = 1.55) and delta glutathione\u0026nbsp;\u003cem\u003eS\u003c/em\u003e-transferase (CpGSTd1, Q60GK5; FC = 1.40)\u0026mdash;being significantly overexpressed (Figure 1H). Correlation analysis demonstrated a significant concordance between mRNA levels and proteomic data (r = 0.69, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Figure 1I, Table S5). Notably, CpGSTd1 and CpCYP337B19 exhibited significantly increased protein (Figure 1G) and transcript levels (Figure 1E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGene ontology (GO) enrichment analysis highlighted prominent roles in \u0026apos;metabolic process\u0026apos; and \u0026apos;single-organism metabolic process\u0026apos; pathways (Figure S2B, Table S2). KEGG pathway analysis identified 15 enriched pathways, primarily related to metabolism, including two xenobiotic metabolism pathways: \u0026apos;Xenobiotics metabolism by cytochrome P450\u0026apos; and \u0026apos;Drug metabolism\u0026mdash;cytochrome P450\u0026apos; (Figure S2C, Table S3). \u003cem\u003eCpGSTd1\u003c/em\u003e was the only detoxification gene differentially upregulated within these pathways. Western blot and RT-qPCR validation showed no significant difference in \u003cem\u003eCpGSTd1\u003c/em\u003e mRNA (Figures 1J) and protein expression (Figures 1K) levels between resistant populations G15 and G30. Based on these results, we focused further investigation on the role of CpGSTd1 in \u0026lambda;-cyhalothrin resistance in \u003cem\u003eC. pomonella\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverexpression of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003econfers \u0026lambda;-cyhalothrin resistance\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo demonstrate the causal role of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003ein resistance, RNAi was used to knockdown its expression and the impact of this on \u003cem\u003eC. pomonella\u003c/em\u003e susceptibility to \u0026lambda;-cyhalothrin examined. The transcript levels of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003ewere significantly reduced following injection of dsRNA with peak interference efficiency of 46.68% at 24 h post-injection (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Figure 2A). Following gene knockdown, the LD\u003csub\u003e50\u003c/sub\u003e values for both the SS and LCR were significantly decreased (Figure 2B). To further assess whether overexpression of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003econtributes to \u0026lambda;-cyhalothrin resistance, we generated transgenic \u003cem\u003eDrosophila\u0026nbsp;\u003c/em\u003elines. The results confirmed successful integration of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003e(Figure S3A), with transcript levels approximately 14.84-fold higher in the 10UAS-\u003cem\u003eCpGSTd1\u003c/em\u003e+Tub-GAL4,GAL80ts line than in the control line (10UAS-\u003cem\u003eCpGSTd1\u003c/em\u003e) (Figure 2C, Figure S3B and S3C). Toxicity assays demonstrated that \u003cem\u003eDrosophila\u003c/em\u003e lines heterologously expressing \u003cem\u003eCpGSTd1\u003c/em\u003e displayed a 2.02-fold increase in tolerance to \u0026lambda;-cyhalothrin compared to controls (Figure 2D). Notably, this overexpression did not enhance resistance to other insecticides tested (Table S7), indicating that \u003cem\u003eCpGSTd1\u003c/em\u003e-mediated resistance is specific to \u0026lambda;-cyhalothrin.\u003c/p\u003e\n\u003cp\u003eTo generate a loss-of-function mutant, CRISPR/Cas9-mediated knockout of exon three of \u003cem\u003eCpGSTd1\u003c/em\u003e was performed on embryos from the LCR population (Figure S4A). Out of 630 injected embryos, 28.57% (44/154) developed into pupae, and genotyping of 44 adults revealed a 13.64% (6/44) heterozygous mutation rate involving various deletions of 2 to 12 bp (Figure 2E, Figure S4B). Subsequent crossing among heterozygotes yielded a G1 generation, of which 24.2% (8/33) harbored 4-bp heterozygous deletions, and homozygous mutants were established over two generations (Figure 2F). Bioassays demonstrated a 5.59-fold decrease in the LD\u003csub\u003e50\u003c/sub\u003e of the LCR-CpGSTd1KO population compared to the control (Figure 2G), providing additional evidence of the role of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003eoverexpression in mediating \u0026lambda;-cyhalothrin resistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular docking-based validation of CpGSTd1\u0026apos;s role in \u0026lambda;-cyhalothrin metabolism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the structure-function determinants of CpGSTd1 mediated \u0026lambda;-cyhalothrin resistance, molecular binding models were constructed using homology modeling and AI-driven computational techniques. Both methodologies yielded highly consistent 3D enzyme conformations, with minor conformational discrepancies (RMSD = 0.41 \u0026Aring;) (Figure 2H, Figure S5). Docking simulations revealed that \u0026lambda;-cyhalothrin\u0026apos;s diaryl ether moiety interacts within a hydrophobic pocket comprising Tyr114 and Phe118, with Tyr114 forming a hydrogen bond (H-bond) at a distance of 3.1 \u0026Aring; (Figure 1I). Further AI-based docking analyses confirmed the pivotal role of Tyr114 in ligand affinity (iPTM = 0.87), with Val53\u0026mdash;a proximal residue\u0026mdash;contributing to the pocket\u0026apos; hydrophobic environment and forming a H-bond with the cyano group at 3.2 \u0026Aring; (Figure J). CAS computational analysis indicated the absence of significant energetic \u0026apos;hot spots\u0026apos; among amino acids (side chain energy \u0026lt; -4.0 kcal/mol) (\u003cem\u003e23\u003c/em\u003e), with Tyr114 exhibiting the lowest energy below 1.0 kcal/mol, followed by Leu34 near -1.0 kcal/mol (Figure 2K). To functionally demonstrate the role of these amino acids in insecticide metabolism, recombinant variants harboring Y114A, F118A, V53A mutations (within the GST G-site), and the L34A mutation (within the GST H-site) were expressed in bacteria (Figure S6). Mutant enzymes demonstrated decreased\u0026nbsp;\u003cem\u003eK\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e and\u0026nbsp;\u003cem\u003eV\u003csub\u003emax\u003c/sub\u003e\u003c/em\u003e relative to the wild-type enzyme (Table S8). HPLC assays revealed no significant difference in the depletion rate of \u0026lambda;-cyhalothrin by the L34A mutant compared to wild-type CpGSTd1, whereas the V53A, Y114A and F118A mutants exhibited significantly increased metabolic rates (Figure 2L, Table S8). Docking analyses of the mutants with \u0026lambda;-cyhalothrin revealed that, aside from V53A, Y114A and F118A showed increased binding affinity (Figure S7), suggesting that these residues within this binding cavity are critical for substrate interaction and enzymatic metabolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe transcription factor \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003eregulates \u003cem\u003eCpGSTd1\u003c/em\u003e-mediated \u0026lambda;-cyhalothrin resistance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify the transcription factors involved in regulating \u0026lambda;-cyhalothrin resistance in\u0026nbsp;\u003cem\u003eC. pomonella\u003c/em\u003e, comprehensive transcriptomic and proteomic analyses were conducted, revealing 47 transcription factors across 20 taxonomic groups expressed in the midgut, a key site of insecticide detoxification (Figure S8, Table S9). Transcriptome data indicated that \u003cem\u003eCpOsa\u003c/em\u003e (2.04-fold) was significantly overexpressed in the LCR_MG compared to the SS_MG (Figure 3A). The expression levels of these factors were validated via further RT-qPCR, which demonstrated that seven transcription factors (\u003cem\u003eCpLola-C\u003c/em\u003e, \u003cem\u003eCpLola-D\u003c/em\u003e, \u003cem\u003eCpARID4B\u003c/em\u003e, \u003cem\u003eCpCncC\u003c/em\u003e, \u003cem\u003eCpHNF4\u003c/em\u003e, \u003cem\u003eCpOsa\u003c/em\u003e and \u003cem\u003eCpMlx\u003c/em\u003e) were upregulated by 1.41- to 2.70-fold (Figure 3B). Proteomics analysis further confirmed that four factors\u0026mdash;\u003cem\u003eCpHNF4\u003c/em\u003e, \u003cem\u003eCpLola-D\u003c/em\u003e, \u003cem\u003eCpCncC\u003c/em\u003e, and \u003cem\u003eCpARID4B\u003c/em\u003e\u0026mdash;were overexpressed at the protein level in the LCR population (1.16-fold to 1.59-fold increase) (Figure 3C). RNAi experiments showed that silencing\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eCpCncC\u003c/em\u003e and \u003cem\u003eCpHNF4\u003c/em\u003e (Figure S9) significantly enhanced mortality upon \u0026lambda;-cyhalothrin exposure at the LD\u003csub\u003e50\u003c/sub\u003e dose (Figure 3D). Further analysis of mortality following exposure to multiple doses of \u0026lambda;-cyhalothrin revealed a significant reduction in LD\u003csub\u003e50\u003c/sub\u003e values to 421.60 ng \u0026mu;L\u003csup\u003e-1\u003c/sup\u003e and 475.71 ng \u0026mu;L\u003csup\u003e-1\u003c/sup\u003e after knockdown of \u003cem\u003eCpCncC\u003c/em\u003e and \u003cem\u003eCpHNF4\u003c/em\u003e expression in the LCR population compared to the LD\u003csub\u003e50\u003c/sub\u003e value of 1182.39 ng \u0026mu;L\u003csup\u003e-1\u003c/sup\u003e of the dsGFP control (Figure 3E). These findings suggest that these transcription factors may play a regulatory role in mediating insecticide resistance in \u003cem\u003eC. pomonella.\u0026nbsp;\u003c/em\u003eAdditionally, knockdown of \u003cem\u003eCpMaf\u003c/em\u003e, a molecular chaperone associated with \u003cem\u003eCpCncC\u003c/em\u003e, also significantly increased susceptibility in LCR larvae (Figure 3E).\u003c/p\u003e\n\u003cp\u003eTo further investigate the regulatory roles of \u003cem\u003eCpCncC\u003c/em\u003e and \u003cem\u003eCpHNF4\u0026nbsp;\u003c/em\u003eon \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003eexpression, transcriptomic analyses was conducted post-RNAi. Results indicated that knockdown of \u003cem\u003eCpCncC\u003c/em\u003e significantly decreased \u003cem\u003eCpGSTd1\u003c/em\u003e expression (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), whereas silencing \u003cem\u003eCpHNF4\u003c/em\u003e had no effect on \u003cem\u003eCpGSTd1\u003c/em\u003e expression (Figure 3F, Figure S10), which was confirmed via RT-qPCR (Figure 3G). Activation of \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003ewith curcumin (2.0 mg g\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003csup\u003e1\u003c/sup\u003e), a \u003cem\u003eCncC\u0026nbsp;\u003c/em\u003eagonist, resulted in a 9.83-fold increase in \u003cem\u003eCpCncC\u003c/em\u003e transcript levels, accompanied by a concurrent significant upregulation of \u003cem\u003eCpGSTd1\u003c/em\u003e (Figure 3H, Figure S11).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDual luciferase reporter assays were conducted to assess transcription factor binding to the \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003epromoter. Constructs were created containing sequences of varying lengths upstream of the \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003etranslation start site (Figure 3I)\u003cem\u003e.\u003c/em\u003e The promoter region spanning \u0026minus;1,911 to +1 relative to the transcription start site showed the highest relative transcriptional activity compared to shorter regions and the pGL4.10 control (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, F = 98.34, df = 31) (Figure 3I), indicating its role as the core promoter. Co-expression with pAC5.1b-\u003cem\u003eCpCncC\u003c/em\u003e significantly increased \u003cem\u003eCpGSTd1\u003c/em\u003e promoter activity by 2.4-fold (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), while \u003cem\u003eCpHNF4\u003c/em\u003e showed no binding activity (\u003cem\u003eP\u003c/em\u003e = 0.7235) (Figure 3J). Bioinformatic analysis identified five high-confidence binding sites for the cnc:maf-S transcription factor within the \u003cem\u003eCpGSTd1\u003c/em\u003e promoter (Figure 3K), one with the forward sequence AGTGCCAATACAATA located precisely in the core promoter region (Figure S12). Site-directed mutagenesis of this binding site abolished \u003cem\u003eCpCncC\u003c/em\u003e binding activity in reporter assays (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, F = 46.90, df = 11) (Figure 3L), confirming its functional relevance. These findings suggest that in collaboration with \u003cem\u003eCpMaf\u003c/em\u003e, \u003cem\u003eCpCncC\u003c/em\u003e acts as a transcription factor mediating the regulation of \u003cem\u003eCpGSTd1\u003c/em\u003e expression through \u003cem\u003ecis\u003c/em\u003e-element binding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROS activates the \u003cem\u003eCpCncC\u003c/em\u003e-mediated regulatory signaling pathway\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess whether reactive oxygen species (ROS) bursts serve as a signaling mechanism within the \u003cem\u003eCpCncC\u003c/em\u003e regulatory pathway following \u0026lambda;-cyhalothrin exposure, ROS levels were quantitatively analyzed in different \u003cem\u003eC. pomonella\u003c/em\u003e populations. The LCR population exhibited inherently higher baseline ROS concentrations compared to the SS strain (Figure 4A), while both populations showed elevated ROS levels after exposure to the LD\u003csub\u003e10\u003c/sub\u003e dose of \u0026lambda;-cyhalothrin (Figure 4B). Additionally, key antioxidant enzymes\u0026mdash;catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD)\u0026mdash;displayed significantly increased activity within the larval antioxidant defense system of the LCR strain relative to SS, with further enhancement observed in both populations upon LD\u003csub\u003e10\u003c/sub\u003e \u0026lambda;-cyhalothrin exposure (Figure S13). To verify ROS pathway involvement, different concentrations of the ROS scavenger N-acetylcysteine (NAC) were applied to LCR larvae. NAC at 5% or higher concentrations resulted in larval mortality (Figure 4C), however, NAC at 2% and above significantly diminished ROS levels in LCR larvae (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, F = 22.38, df = 14) (Figure 4D). Based on these findings, 2% NAC was determined to be an effective concentration for ROS inhibition, concomitant with substantial downregulation of \u003cem\u003eCpCncC\u003c/em\u003e and \u003cem\u003eCpGSTd1\u003c/em\u003e expression (Figure 4E) and an increased susceptibility of larvae to \u0026lambda;-cyhalothrin (Figure 4F).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eorchestrates developmental duration and pupal homeostasis through hormonal regulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn addition to its role in modulating resistance pathways, \u003cem\u003eCp\u003c/em\u003e\u003cem\u003eCncC\u003c/em\u003e was further investigated for its potential involvement in controlling developmental duration. The LCR population exhibited extended larval and pupal stages and showed reduced female reproductive capacity (Table S1), likely as a result of endocrine disruption (Table S1) driven by hormonal imbalances. Throughout the fourth instar and pupal stages, the 20E titer in LCR remained consistently higher than those in SS (Figure 5A), whereas JH levels were persistently lower (Figure 5B). While the LCR population displayed an increase in developmental duration (Figure 1B), the short-term response following sublethal \u0026lambda;-cyhalothrin exposure did not alter larval developmental duration (Figure 5C). The 20E titer in larvae was significantly elevated at 24 h and 48 h post exposure to the LD\u003csub\u003e10\u003c/sub\u003e of \u0026lambda;-cyhalothrin compared to controls, returning to baseline levels after 72 h (Figure 5D). In contrast, JH titers exhibited only a slight reduction at 48 h following sublethal \u0026lambda;-cyhalothrin treatment compared to controls (Figure 5E). To determine whether these developmental duration variations are mediated via \u003cem\u003eCpCncC\u003c/em\u003e expression influencing hormone titers, CRISPR/Cas9 gene editing was used to generate homozygous mutants of \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003ein \u003cem\u003eC. pomonella\u003c/em\u003e (Figure S14A). Embryos were microinjected with Cas9 combined with sgRNA targeting distinct exons of \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003e(Figure S14A). Of 33 surviving pupal-stage individuals, all exhibited mutations (Figure S14A). G0 heterozygous mutants, including both males and females, were produced following injections targeting the 5th exon (Figure S14A, Figure S14B), with an egg hatching rate of 11.10% (233/2100) and a pupal survival rate of 21.03% (49/233) among hatched larvae (Figure S14A). Genotyping revealed 10.20% (5/49) heterozygous mutants harboring various indels (Figure S14C). A single female with a 1 bp deletion was mated with a male carrying a distinct 1 bp deletion to generate the next progeny (Figure S14D). However, out of 124 eggs, only 72 G1 larvae hatched, with 61 carrying the parental heterozygous mutant allele, none of which reached healthy reproductive maturity (Figure S14E). Thus, the CRISPR/Cas9 system targeting various exons of \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003efailed to generate homozygous mutant lines in \u003cem\u003eC. pomonella\u003c/em\u003e. Furthermore, heterozygous G1 individuals (CpCncC\u003csup\u003e+/-\u003c/sup\u003e) exhibited reduced viability, with survival rates lower than wild-type (CpCncC\u003csup\u003e+/+\u003c/sup\u003e)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003econtrols (Figure 5F). Developmental duration analysis revealed that each larval instar duration in CpCncC\u003csup\u003e+/-\u003c/sup\u003e individuals was significantly prolonged compared to wild-type counterparts, with the most pronounced delay observed at the fifth instar, where development was extended by 1.20-fold. This developmental delay became more prominent with advancing larval instars (Figure 5G). Moreover, all surviving fifth instar CpCncC\u003csup\u003e+/-\u003c/sup\u003e larvae displayed pupation defects, including a markedly increased pupation failure rate compared to the LCR population or CpCncC\u003csup\u003e+/+\u003c/sup\u003e individuals (Figure 5H). RT-qPCR demonstrated that \u003cem\u003eCpCncC\u003c/em\u003e transcript level in heterozygotes were reduced by 8.07-fold compared to wild-type (Figure 5I).\u003c/p\u003e\n\u003cp\u003eTranscriptome profiling following dsCpCncC injection revealed significant modulation of the insect endocrine biosynthesis pathway (bmor00981), with a notable downregulation of \u003cem\u003eCYP306A1\u003c/em\u003e and significant upregulation of genes involved in juvenile hormone regulation, including \u003cem\u003efarnesyl pyrophosphate phosphatase\u003c/em\u003e (\u003cem\u003eFPP\u003c/em\u003e), \u003cem\u003efarnesyl dehydrogenase\u0026nbsp;\u003c/em\u003e(\u003cem\u003eFD1\u003c/em\u003e and\u003cem\u003e\u0026nbsp;FD2\u003c/em\u003e), and \u003cem\u003ejuvenile hormone epoxide hydrolase\u003c/em\u003e (\u003cem\u003eJHEH\u003c/em\u003e) (Figure 5J, Table S10). RT-qPCR validation corroborated these gene expression trends (Figure 5K and 5L), implying that \u003cem\u003eCpCncC\u003c/em\u003e is involved in the regulation of hormonal balance. Further validation demonstrated that suppression of\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eCp\u003c/em\u003e\u003cem\u003eCncC\u003c/em\u003e led to decreased titers of 20E (Figure 5M) and increased JH titers (Figure 5N). Exogenous application of synthetic 20E (50 ng/\u0026mu;L) to fourth-instar larvae restored hormone levels to baseline and normalized developmental duration (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, F = 16.38, df = 134) (Figure 5O, Figure S15). During maturation, dsCpCncC-injected individuals, exhibited a significantly higher pupation failure rate compared to dsGFP-injected controls, whereas 20E supplementation significantly enhanced pupation success\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, F = 38.6, df = 8) (Figure 5P). These findings suggest that \u003cem\u003eCpCncC\u003c/em\u003e overexpression mediates \u0026lambda;-cyhalothrin resistance while delaying developmental duration through its action in regulating key hormones involved in insect development.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough resistance offers an adaptive advantage for insects exposed to insecticide, it usually leads to trade-offs with other life-history traits. In this study, we demonstrate that the transcription factor \u003cem\u003eCpCncC\u003c/em\u003e regulates the adaptive trade-off between insecticide resistance, by upregulating the detoxification enzyme \u003cem\u003eCpGSTd1\u003c/em\u003e while modulating developmental homeostasis controlled by the hormones 20E and JH in \u003cem\u003eC. pomonella\u003c/em\u003e. Our data provide insight into the mechanisms of resistance in a global crop pest and reveal how changes to gene regulatory pathways can underpin evolutionary trade-offs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevious synergistic bioassays on the LCR population and correlation analyses between resistance ratios and detoxification enzyme activities suggested that \u003cem\u003eC. pomonella\u003c/em\u003e primarily relies on GST enzymes for detoxification of \u0026lambda;-cyhalothrin (\u003cem\u003e22\u003c/em\u003e). In this study, we utilized integrated multi-omics methodologies to identify detoxification genes overexpressed in the LCR population, and the consistent upregulation of \u003cem\u003eCpGSTd1\u003c/em\u003e in transcriptomic and proteomic datasets.\u0026nbsp;GSTs belonging to the delta class have been previously linked to insecticide resistance in insects\u0026nbsp;(\u003cem\u003e24\u003c/em\u003e). For example, in \u003cem\u003eTetranychus urticae\u003c/em\u003e, the delta GST \u003cem\u003eTuGSTd05\u003c/em\u003e has been associated with resistance to cyflumetofen, exhibiting significant overexpression in a resistant population\u0026nbsp;(\u003cem\u003e25\u003c/em\u003e). Furthermore, consistent with our findings, \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003ewas shown to be upregulated in a \u0026lambda;-cyhalothrin resistant strain of \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003epreviously\u0026nbsp;(\u003cem\u003e26\u003c/em\u003e). It is important to acknowledge that \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003ewas only modestly upregulated in the LCR population in our study. Thus, the overexpression of this gene is unlikely to fully explain the \u0026lambda;-cyhalothrin resistant phenotype of the LCR population, and further investigation of alternative mechanisms of resistance in this strain is warranted (see also below). Nevertheless, we conducted comprehensive functional analyses utilizing RNAi (inhibition-of-function), transgenic \u003cem\u003eDrosophila\u0026nbsp;\u003c/em\u003emodels (gain-of-function) and gene editing techniques (loss-of function) to unequivocally demonstrate that \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003econfers resistance to \u0026lambda;-cyhalothrin. Similar studies on GST-mediated pyrethroid resistance have been reported in other pests; for instance, silencing \u003cem\u003eSlGSTd1\u003c/em\u003e in \u003cem\u003eSpodoptera litura\u003c/em\u003e via RNAi significantly increased susceptibility to cypermethrin and cyfluthrin\u0026nbsp;(\u003cem\u003e27\u003c/em\u003e)\u003cem\u003e.\u0026nbsp;\u003c/em\u003eFurthermore, in \u003cem\u003eAnopheles funestus\u003c/em\u003e, \u003cem\u003eGSTe3\u0026nbsp;\u003c/em\u003eand \u003cem\u003eGSTe4\u003c/em\u003e were overexpressed in transgenic \u003cem\u003eDrosophila\u003c/em\u003e via the GAL4-UAS binary expression system, and these overexpression lines demonstrated decreased susceptibility to permethrin and deltamethrin (\u003cem\u003e28\u003c/em\u003e). We found that knockout of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003esignificantly decreased\u0026nbsp;\u0026lambda;-cyhalothrin resistance, reducing the LD\u003csub\u003e50\u003c/sub\u003e from moderate to low levels, supporting the role of \u003cem\u003eCpGSTd1\u003c/em\u003e as an important determinant of insecticide sensitivity in \u003cem\u003eC. pomonella\u003c/em\u003e. However, complete susceptibility was not restored following \u003cem\u003eCpGSTd1\u003c/em\u003e knockout, suggesting the participation of other mechanisms in mediating resistance. In this regard previous studies have demonstrated that three members of the CYP9A P450 subfamily, \u003cem\u003eCpCYP9A120\u003c/em\u003e, \u003cem\u003eCpCYP9A121\u003c/em\u003e, \u003cem\u003eCpCYP9A122\u003c/em\u003e, play a role in \u0026lambda;-cyhalothrin resistance through functional redundancy in \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003e\u003cem\u003e(29)\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eIn our study, only \u003cem\u003eCYP337B19\u003c/em\u003e, a member of the mitochondrial Clan P450, was overexpressed at both mRNA and protein levels. Further investigation of the potential role of this P450 in mediating insecticide resistance in \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eis warranted\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe formation of binding pockets by detoxification enzymes, facilitated by critical \u0026nbsp;amino acid residues that interact with insecticides, is fundamental to enhanced metabolic activity (\u003cem\u003e26\u003c/em\u003e). AI-driven molecular modeling and CAS analyses indicated that the cavity formed by key amino acid residues such as Tyr114, Phe118, and Val 53 is crucial for the binding affinity of \u003cem\u003eC. pomonella\u003c/em\u003e CpGSTd1 to \u0026lambda;-cyhalothrin. Similar findings have been reported in other insect species; for example, in \u003cem\u003eP. xylostella\u003c/em\u003e, Tyr115 and Phe119 of PxGSTD3 are homologous amino acids to Tyr114 and Phe118 of \u003cem\u003eC. pomonella\u003c/em\u003e CpGSTd1, which form a binding pocket to encapsulate the phenyl group of \u0026lambda;-cyhalothrin, strengthening binding activity (\u003cem\u003e30\u003c/em\u003e). These findings suggest that the conserved amino acids forming this binding pocket could be critical for delta class GST-mediated detoxification of pyrethroid insecticides across diverse insect taxa. If confirmed, a strategic framework could be developed to leverage AI for virtual screening and the rational design of small-molecule inhibitors targeting this binding domain (\u003cem\u003e31\u003c/em\u003e). Such compounds could potentially be used synergistically with insecticides to enhance pest control efficacy by overcoming GST-mediated metabolic resistance. Collectively these findings advance our understanding of the structure-function determinants of GST-mediated insecticide resistance in pests and can be used to inform the development of strategies to combat this form of resistance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInsecticide resistance in insects has been linked to transcription factors that regulate the transcription of detoxification genes (\u003cem\u003e16, 32\u003c/em\u003e). CncC, as a homolog of mammalian Nuclear Factor E2-Related Factor 2 (Nrf2), is activated by ROS bursts triggered by insecticide exposure, leading to the transcriptional activation of downstream detoxification enzymes (\u003cem\u003e17, 19\u003c/em\u003e). Regulatory pathways involving CncC have been documented across various insect species; for example, exposure of \u003cem\u003eS. litura\u003c/em\u003e larvae to \u0026lambda;-cyhalothrin increases H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels, which activates the transcription of \u003cem\u003eSl\u003c/em\u003e\u003cem\u003eCncC\u003c/em\u003e and \u003cem\u003eCYP6AB12\u003c/em\u003e, thereby enhancing larval insecticide tolerance (\u003cem\u003e33\u003c/em\u003e). Compared to P450 regulation, the role of CncC in modulating GST expression to mediate insecticide resistance remains poorly characterized. In \u003cem\u003eS. exigua\u003c/em\u003e, \u003cem\u003eSeGSTe6\u0026nbsp;\u003c/em\u003eis co-induced by \u0026lambda;-cyhalothrin, chlorpyrifos, and chlorantraniliprole, with subsequent significant activation of transcriptional signaling observed via a reporter plasmid containing the \u003cem\u003eSeGSTe6\u0026nbsp;\u003c/em\u003epromoter driven by a CncC expression construct (\u003cem\u003e34\u003c/em\u003e). Additionally, AiCncC binds to a specific site within the promoter region of \u003cem\u003eAiGSTz1\u0026nbsp;\u003c/em\u003ewhich is induced by octreotide in \u003cem\u003eAgrotis ipsilon\u003c/em\u003e, and silencing \u003cem\u003eAiCncC\u0026nbsp;\u003c/em\u003eresults in marked down-regulation of \u003cem\u003eAiGSTz1\u0026nbsp;\u003c/em\u003eexpression (\u003cem\u003e35\u003c/em\u003e). Our study systematically demonstrates that \u003cem\u003eCpCncC\u003c/em\u003e mediates metabolic resistance to \u0026lambda;-cyhalothrin in \u003cem\u003eC. pomonella\u003c/em\u003e through the activation of\u003cem\u003e\u0026nbsp;CpGSTd1\u003c/em\u003e expression via binding to a \u003cem\u003ecis\u003c/em\u003e-regulatory element in its promoter. These findings provide novel insights into the less-characterized regulatory mechanisms through which \u003cem\u003eCpCncC\u003c/em\u003e modulates GST gene expression, and provides further evidence of the importance of this regulatory pathway in the development of insecticide resistance in pest populations. However, like other transcription factors (\u003cem\u003e18, 34\u003c/em\u003e), the change in the expression of \u003cem\u003eCpCncC\u003c/em\u003e in resistant versus susceptible populations in our study was modest. Thus, alternative mechanisms may act in concert with transcriptional upregulation to alter \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003eactivity in \u003cem\u003eC. pomonella\u003c/em\u003e. For example, variation in the phosphorylation state of this transcription factor in insecticide resistant and susceptible strains of \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003emay also play a role in resistance, as reported for other transcription factors involved in the regulation of resistance genes (\u003cem\u003e19\u003c/em\u003e). Intriguingly, previous studies have demonstrated that knockdown of an alternative transcription factor, \u003cem\u003eCpAhR\u003c/em\u003e, results in reduced expression of the GST gene \u003cem\u003eCpGSTe3\u003c/em\u003e, thereby increasing susceptibility of \u003cem\u003eC. pomonella\u003c/em\u003e to \u0026lambda;-cyhalothrin (\u003cem\u003e36\u003c/em\u003e). This illustrates that multiple transcription factors that regulate detoxification gene networks in an insect species have the potential to be recruited in the evolution of insecticide resistance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInsecticide resistance is often accompanied by a fitness costs in the absence of insecticide (\u003cem\u003e9, 13\u003c/em\u003e), however, the molecular mechanisms underpinning these costs are poorly resolved. Our results reveal that \u003cem\u003eC. pomonella\u003c/em\u003e employs the transcription factor \u003cem\u003eCpCncC\u003c/em\u003e to regulate the expression of key detoxification and developmental genes, mediating a trade-off between resistance mechanisms and developmental retardation. This regulatory mechanism is mediated by hormone biosynthesis, specifically involving \u003cem\u003eCYP306A1\u003c/em\u003e, a member of the \u003cem\u003eHalloween\u003c/em\u003e gene family (\u003cem\u003e37\u003c/em\u003e), which is directly regulated by \u003cem\u003eCpCncC\u003c/em\u003e, thereby influencing the biosynthesis of 20E\u0026mdash;a crucial component of the hormonal regulation pathway. This hormone-mediated trade-off develops in response to sustained insecticide selection pressure, since transient hormonal fluctuations induced by short-term sublethal dosage insecticide stress are minimal and inconsistent, with negligible effects on developmental duration. Our findings also indicate that \u003cem\u003eCpCncC\u003c/em\u003e\u0026apos;s role in modulating 20E levels is vital, as either partial loss-of-function or brief suppression of gene expression can markedly disrupt developmental duration. A similar regulatory network has been observed in\u003cem\u003e\u0026nbsp;Tribolium castaneum\u003c/em\u003e, where \u003cem\u003eCncC\u003c/em\u003e regulates deltamethrin resistance and influences the expression of the 20E synthesis-related gene \u003cem\u003eTcPhantom\u003c/em\u003e, \u003cem\u003eTcShade\u003c/em\u003e, and JH degradation-associated gene \u003cem\u003eTcJHEH-r3\u003c/em\u003e, leading to reduced JH titers and decreased \u003cem\u003evitellogenin\u003c/em\u003e (\u003cem\u003eVg\u003c/em\u003e) expression(\u003cem\u003e19\u003c/em\u003e). In contrast, in \u003cem\u003eC. pomonella\u003c/em\u003e, \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003edoes not regulate \u003cem\u003eJHEH\u003c/em\u003e but overexpression leads to elevated 20E levels, dysregulation of JH pathway genes and reduced JH titers through antagonistic hormonal interactions (\u003cem\u003e38\u003c/em\u003e). Conversely, insecticide resistance development in \u003cem\u003eB. tabaci\u003c/em\u003e, which incurs fitness costs, is governed by a distinct mechanism involving \u003cem\u003eCncC\u003c/em\u003e activation through phosphorylation by the p38 and ERK pathways, subsequently repressing critical genes associated with oogenesis, such as \u003cem\u003eexuperantia\u003c/em\u003e (\u003cem\u003eEx\u003c/em\u003e), \u003cem\u003evasa\u003c/em\u003e (\u003cem\u003eVa\u003c/em\u003e), and genes involved in germ cell tumor formation (\u003cem\u003eBg\u003c/em\u003e), impacting zygomorphogenesis (\u003cem\u003e11\u003c/em\u003e). Thus, the trade-off between the regulation of insecticide resistance through the CncC pathway and developmental duration may represent a common phenomenon associated with resistance in crop pests. Additionally, CncC functions as a pivotal regulator of oxidative stress responses, lifespan, and immune system enhancement, with its expression finely balanced to prevent detrimental over- or under-expression (\u003cem\u003e17, 33\u003c/em\u003e). This regulatory precision may explain the challenge in generating homozygous \u003cem\u003eCpCncC\u0026nbsp;\u003c/em\u003emutants in our study even after multiple targeting attempts and extensive trials, despite the availability of mature CRISPR/Cas9 gene editing tools for\u0026nbsp;\u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003e(\u003cem\u003e39\u003c/em\u003e). Indeed, to date, no studies have established successful knockout lines of \u003cem\u003eCncC\u003c/em\u003e in insects or invertebrates; only in medical research involving tumor cell lines has a knockout of Nrf2 been achieved\u0026nbsp;(\u003cem\u003e40\u003c/em\u003e), suggesting \u003cem\u003eCncC\u003c/em\u003e is indispensable. This finding suggests that CncC is under strong functional constraint in insects to ensure the integrity of key regulatory networks. In this regard, our study illustrates how the exceptionally strong selection pressure exerted by insecticides on insect pest population can result in changes in the regulation of even tightly controlled essential genes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, this study systematically elucidates the function of \u003cem\u003eCpGSTd1\u0026nbsp;\u003c/em\u003eproviding new insights into the metabolic pathways by which the transcription factor \u003cem\u003eCpCncC\u003c/em\u003e modulates GST expression to confer insecticide resistance. We demonstrate how the modulation of this resistance gene pathway underpins fitness costs associated with resistance, advancing understanding of the molecular mechanisms underpinning an iconic example of an evolutionary trade-off. The identified resistance regulatory mechanisms present promising targets for integrated pest management strategies, including ROS, transcriptional regulators, and detoxification enzymes.\u0026nbsp;\u003c/p\u003e"},{"header":"MATERIALS AND METHODS ","content":"\u003cp\u003e\u003cstrong\u003eInsects and rearing\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA susceptible strain of \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003e(SS)\u003cem\u003e\u0026nbsp;\u003c/em\u003ewas maintained for over 100 generations without exposure to insecticide (\u003cem\u003e41\u003c/em\u003e). A population LCR(G15) with moderate-level resistance to \u0026lambda;-cyhalothrin was established in the laboratory through continuous manual selection from SS (\u003cem\u003e22\u003c/em\u003e). Based on this, the LCR population was subjected to further selection for 15 additional generations, resulting in the LCR(G30) population. Both populations were reared at 26 \u0026plusmn; 1\u0026deg;C under a 16:8 hours photoperiod in an incubator (Panasonic, MLR-352H-PC, Japan). Equal proportions of adult males and females were housed in custom plastic containers and mated to oviposit after supplementation with a 10% honey solution. Newly hatched larvae were transferred to an artificial diet to complete larval development until pupation, with relative humidity maintained at 60% to prevent desiccation of the diet.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDevelopmental stages and tissues of fourth-instar larvae from \u003cem\u003eC. pomonella\u003c/em\u003e samples were prepared as described by Hu et al. (2020) (\u003cem\u003e41\u003c/em\u003e). All samples were flash-frozen in liquid nitrogen and stored at -80℃ for subsequent analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein extraction and digestion\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA 150 mg midgut sample of the LCR (LCR_MG) and SS (SS_MG) populations was pulverized in liquid nitrogen and lysed with 200 \u0026micro;L of SDT buffer (100 mM DTT, 100 mM Tris HCl), followed by 5 min of on-ice ultrasonication (\u003cem\u003e42\u003c/em\u003e). The lysate was heated at 95℃ for 15 min, then cooled in an ice bath for 2 min. After centrifugation at 12,000 g for 30 min, the supernatant was alkylated with 1/5 volume of 500 mM iodoacetamide solution for 1 h at room temperature in the dark. Subsequently, the sample was fully mixed with 800 \u0026micro;L of pre-cooled acetone and incubated at -20\u0026deg;C for 2 h. The mixture was centrifuged again at 12,000 g for 15 min at 4\u0026deg;C, and the precipitate was collected. The precipitate was resuspended and washed with 1 mL of pre-cooled acetone to recover the total pelleted proteins.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTandem mass tags (TMT) proteomic quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach sample was reconstituted with 100 \u0026mu;L of 0.1 M TEAB buffer (Sigma, Germany). Then, 41 \u0026mu;L of acetonitrile-dissolved TMT labeling reagent (Thermo, USA) was added, and the mixture was shaken for 2 h at room temperature (\u003cem\u003e42\u003c/em\u003e). The reaction was quenched with 8% ammonia solution. All labeled peptides from each sample were pooled in equal volumes, desalted, and lyophilized. Each fraction was analyzed via ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) using a Q ExactiveTM HF-X (Thermo Fisher, Germany) and Orbitrap Exploris 480 mass spectrometer (Thermo Fisher, Germany). For each analysis, 1 \u0026mu;g of peptide was separated using solvents: Liquid A (100% water, 0.1% formic acid) and Liquid B (80% acetonitrile, 0.1% formic acid) over a 60-minute gradient. Protein identification was performed by searching the silkworm protein database (https://www.uniprot.org/uniprotkb?query=Bombyx+mori) with Proteome Discoverer. To ensure high-quality results, peptide spectrum matches (PSMs) with confidence levels \u0026ge;99%, along with proteins containing at least one unique peptide, were retained. False discovery rate (FDR) validation was applied to exclude peptides and proteins with an FDR exceeding 1%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA extraction, cDNA synthesis and relative expression analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTotal RNA was isolated using RNAiso Plus (Takara, Beijing, China) following the manufacturer\u0026apos;s protocol. RNA quantity and integrity were assessed with a NanoDrop 2000 spectrophotometry (ThermoFisher Scientific, Waltham, the United States of America). First-strand cDNA was synthesized using 1 \u0026mu;g of total RNA utilizing the PrimeScript\u0026trade; II 1st Strand cDNA Synthesis Kit (Takara, Beijing, China). Real-time quantitative PCR (RT-qPCR) was conducted on a Bio-Rad CFX96 system (Bio-Rad, Singapore) with the following thermal cycling conditions: initial denaturation at 95℃ for 30 s, followed by 40 cycles of denaturation at 95℃ for 5 s, annealing at 50-60℃ for 30 s, and extension at 72℃ for 30 s. Reactions were prepared in 20 \u0026mu;L volumes containing 1 \u0026mu;L of cDNA template, 10 \u0026mu;L of TB Green\u0026reg; Premix Ex Taq\u0026trade; 2 (Tli RNaseH Plus), 0.8 \u0026mu;L of each primer, and nuclease-free water to volume. Internal control genes, \u003cem\u003eEF-1\u0026alpha;\u003c/em\u003e (MN037793) and \u003cem\u003eGAPDH\u003c/em\u003e (MT116773) (Table S11), were used as reference standards (\u003cem\u003e21\u003c/em\u003e). Relative expression levels were calculated using the 2\u003csup\u003e-\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method (\u003cem\u003e43\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-Seq data analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRNA integrity was assessed using the RNA Nano 6000 Assay Kit on the Bioanalyzer 2100 system (Agilent Technologies, USA). Sequencing libraries were prepared using the TruSeq PE Cluster Kit v3-cBot-HS (Illumia) on a cBotCluster Generation System according to the manufacturer\u0026apos;s instructions (\u003cem\u003e44\u003c/em\u003e). The reference genome and gene annotation files for \u003cem\u003eC. pomonella\u003c/em\u003e were obtained from InsectBase 2.0 (http://v2.insect-genome.com). Genome indexing was performed, and paired-end reads were aligned using Hisat2 v2.0.5. The number of reads per gene was calculated using Counts v1.5.0-p3 and FPKM (Fragments Per Kilobase of transcript per Million mapped reads) was quantified based on the length of the gene. Differential expression analysis was performed using the DESeq2 R 1.20.0 software on data from different groups, using a model based on the negative binomial distribution to determine differential gene expression. Benjamini and Hochberg\u0026apos;s method was used to adjust the false discovery rate and thus calculate the corrected \u003cem\u003eP\u003c/em\u003e-value, with a threshold of 0.05 set as the baseline for differential expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioassay\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe insecticidal activity of \u0026lambda;-cyhalothrin (Aladdin, Shanghai, China) was evaluated through a topical droplet bioassay on fourth-instar \u003cem\u003eC. pomonella\u003c/em\u003e larvae, following the method described by Li et al. (2023) (\u003cem\u003e29\u003c/em\u003e). \u0026lambda;-cyhalothrin solutions were prepared by dissolving the compound in acetone, followed by serial dilutions. A 1 \u0026mu;L droplet was applied to the pronotum of each freshly molted fourth-instar larva, ensuring complete penetration. Treated larvae were transferred to 24-well plates containing 1 cm\u0026sup3; of artificial diet. Each concentration involved 45 larvae, with three replicates per concentration. Control groups received an equivalent volume of acetone. Mortality was assessed at designated time points post-treatment; larvae unresponsive to stimuli were recorded as dead.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Interference (RNAi)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe synthesized double-stranded RNA (dsRNA) was administered into larvae via microinjection to suppress gene transcription (\u003cem\u003e45\u003c/em\u003e). Briefly, cDNA templates were amplified using specific primers (Table S11) containing a T7 promoter sequence, and dsRNA was synthesized employing the T7 RiboMAXTM Express RNAi System (Promega, USA) in accordance with the manufacturer\u0026apos;s protocol. Larvae were immobilized by incubation on ice for approximately 10 min before injection while still paralyzed. One \u0026mu;L of dsRNA at a concentration of 1000 ng \u0026mu;L\u003csup\u003e-1\u003c/sup\u003e was injected into the posterior end of each larva (at three to five segments). A minimum of 30 individuals, with three biological replicates, were used. An equivalent volume of dsGFP was injected as a control. Samples were collected at various time points post-injection for gene expression analysis to determine the optimal interference timing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of the transgenic \u003cem\u003eDrosophila melanogaster\u0026nbsp;\u003c/em\u003eand bioassay\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe attP-PhiC31 recombinase system was employed to generate a \u003cem\u003eCpGSTd1\u003c/em\u003e transgenic \u003cem\u003eD. melanogaster\u003c/em\u003e line, leveraging the GAL4-UAS binary expression system to achieve gene overexpression (\u003cem\u003e46\u003c/em\u003e). Briefly, the \u003cem\u003eCpGSTd1\u003c/em\u003e coding sequence was cloned into the transgenic \u003cem\u003eDrosophila\u003c/em\u003e expression vector pNP and injected into embryos of the attP40 strain. Integration into chromosome 2 was mediated by PhiC31 integrase. Progeny reaching adulthood were screened for the red-eye phenotype, indicating successful transgene insertion, producing the 10UAS-CpGSTd1 line. This line was crossed with the Tub-GAL4 and GAL80ts balancer line carrying the Bc/CyO second chromosome balancer to establish a stable transgenic line, 10UAS-CpGSTd1+Tub-GAL4,GAL80ts, with balanced segregation on chromosomes 2 and 3.\u003c/p\u003e\n\u003cp\u003eThe insecticide bioassay involved coating the inner surfaces of glass vials with formulated insecticide solutions to assess toxicity across different transgenic lines (\u003cem\u003e5\u003c/em\u003e). Insecticides were dissolved in acetone at varying concentrations, then 200 \u0026mu;L of each solution was dispensed into 20 mL clear cylindrical glass vials (bottom diameter, 2.5 cm; top diameter, 2.0 cm; height, 4.5 cm), followed by rapid rotary evaporation to remove solvent, leaving a uniform film. After a 1-hour drying period, approximately 15 flies within one day of emergence were transferred into each vial via tapping. Vials were sealed with foam stoppers containing a cotton ball saturated with 10% honey solution. Control vials received an equivalent volume of acetone. Each concentration was tested in triplicate. Mortality was recorded after 24 h; flies unresponsive to gentle shaking were classified as dead.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blot analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal proteins were extracted from samples utilizing the Column Animal Tissue Protein Extraction Kit (Epizyme Biotech, Shanghai, China), following the manufacturer\u0026apos;s instructions. A 20 mg tissue sample was lysed in 200 \u0026mu;L of RIPA buffer containing 1/100 volume of PMSF protease inhibitor, then homogenized using a high-throughput grinder (SolenBio, Beijing, China). Following centrifugation at 12,000 g for 10 min at 4\u0026deg;C, the supernatant was collected, and protein concentration was determined using the BCA Protein Assay Kit (SolenBio, Beijing, China). Proteins were separated on a 5% SDS-PAGE concentrated gel and 12% SDS-PAGE separation gel (Bio-Platform, Shanghai, China) at 120 V for 1 h. Proteins were transferred onto PVDF membranes (Millipore, Ireland), which were blocked for 2 h with TBST buffer containing 5% skim milk powder. Membranes were incubated overnight at 4\u0026deg;C with primary rabbit polyclonal antibodies (1:1000) targeting the respective proteins. After washing, membranes were incubated with secondary goat anti-rabbit IgG (1:10,000; Bio-Platform, Shanghai, China). Beta-actin (from \u003cem\u003eDrosophila\u003c/em\u003e) rabbit polyclonal antibody (1:1500) served as an internal control. Protein bands were visualized using an ECL detection system (SolenBio, Beijing, China) for quantitative analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein structure construction and molecular docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe three-dimensional (3D) conformation of the CpGSTd1 enzyme was modeled using AlphaFold (\u003cem\u003e47\u003c/em\u003e). The highest confidence prediction was selected based on the local distance difference test (LDDT) score to validate structural reliability. An alternative crystal structure of a GST protein (PDB ID: 3vk9) from \u003cem\u003eB. mori\u003c/em\u003e was used as a template for homology modeling of CpGSTd1 with Modeller 9.10 (\u003cem\u003e26\u003c/em\u003e). The 3D structural model of CpGSTd1 generated through AlphaFold and Modeller 9.10 simulations were superimposed using PyMOL, with a root-mean-square deviation (RMSD) below 1.0 \u0026Aring; indicating a high degree of structural congruence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe \u0026lambda;-cyhalothrin ligand structure was obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and converted to PDB format with Open Babel 3.0 for compatibility with molecular docking simulations. The AlphaFold-based modeling platform was utilized to calculate the interface predicted template modeling-score (iPTM) to assess the reliability of the predicted molecular conformation, with docking simulations performed across at least five independent runs to evaluate binding conformations. Molecular docking of CpGSTd1 with \u0026lambda;-cyhalothrin was executed using the GOLD 2020.3 software, and binding free energies were calculated via the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach (\u003cem\u003e48\u003c/em\u003e). The ligand-protein complex was visualized to analyze interaction patterns using PyMOL. Additionally, computational alanine scanning (CAS) was obtained to evaluate the binding free energy (\u0026Delta;\u0026Delta;G\u003csub\u003ebinding\u003c/sub\u003e) difference before and after alanine substitution using the Molecular Mechanics Poisson Boltzmann/Generalized Born Surface Area (MM-PB/GBSA) method in AMBER 9.10 (\u003cem\u003e49\u003c/em\u003e). The mutant complexes were generated by a single truncation of the mutated side chain, replacing C\u0026gamma; with a hydrogen atom and setting the C\u0026beta;-H direction to that of the former C\u0026beta;-C\u0026gamma; (\u003cem\u003e50\u003c/em\u003e). \u0026Delta;\u0026Delta;G\u003csub\u003ebinding\u003c/sub\u003e was defined as the difference between the mutant complex (cpx-mutant) and the wild-type complex (cpx-WT) obtained by calculating \u0026Delta;\u0026Delta;G\u003csub\u003ebinding\u003c/sub\u003e = \u0026Delta;\u0026Delta;G\u003csub\u003ecpx-mutant\u003c/sub\u003e - \u0026Delta;\u0026Delta;G\u003csub\u003ecpx-WT\u003c/sub\u003e (\u003cem\u003e50\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression and binding activity of mutant CpGSTd1 proteins\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed by the CpGSTd1 sequence and CAS results, three amino acids\u0026mdash;Val53, Tyr114, and Phe118\u0026mdash;were targeted for site-directed mutagenesis. The mutated coding sequences were cloned into the pET-28a(+) expression vector and transformed into \u003cem\u003eEscherichia coli\u003c/em\u003e BL21 (DE3) (\u003cem\u003e26\u003c/em\u003e). The recombinant mutants were expressed and purified, then assayed for enzymatic activity using a spectrophotometric assay measuring the change in absorbance at 340 nm upon reaction with different concentrations of CDNB (0.01\u0026ndash;0.32 mM) and 10 mM GSH. Kinetic parameters (\u003cem\u003eK\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003eV\u003csub\u003emax\u003c/sub\u003e\u003c/em\u003e) were derived by fitting the Michaelis-Menten equation (GraphPad Prism 5). To evaluate inhibitory effects, 0.8 \u0026mu;g of purified mutant proteins was incubated with varying concentrations of \u0026lambda;-cyhalothrin (50\u0026ndash;2000 \u0026mu;M) for 5 min at 30\u0026deg;C, and residual GST activity was measured after addition of 2 mM CDNB to determine the IC\u003csub\u003e50\u003c/sub\u003e value. S-hexylglutathione (GTX) served as a positive control, with three replicates for each experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of the metabolic capacity of CpGSTd1 \u003cem\u003ein vitro\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e metabolic capacity was assessed by quantifying residual \u0026lambda;-cyhalothrin following incubation with wild-type and mutant CpGSTd1 proteins (\u003cem\u003e26\u003c/em\u003e). The reaction mixture contained 20 mg of recombinant protein, 2.5 mM GSH, and 0.6 mM \u0026lambda;-cyhalothrin in 0.5 mL of 50 mM potassium phosphate buffer (pH 7.2). Incubation was performed at 30\u0026deg;C for 60 min with agitation at 300 rpm. Reactions were halted by adding 0.5 mL of ethyl acetate, followed by centrifugation at 14,000 rpm for 20 min at room temperature. The supernatant was analyzed under a mobile phase of 75% acetonitrile for residual insecticide content, with heat-inactivated enzyme used as a control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePromoter cloning and analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genomic DNA of \u003cem\u003eC. pomonella\u003c/em\u003e was extracted utilizing the DNA extraction kit (BayBiopure, Guangzhou, China), and primers (Table S11) were designed for cloning the upstream promoter regions based on the genomic sequence data (http://v2.insect-genome.com). Transcription factor binding sites within the promoter regions were predicted using JASPAR (https://jaspar.elixir.no/), with the promoter segments segmented into intervals of 200 to 400 bp depending on the prediction results. Promoter fragments of varying lengths were amplified via PCR using PrimeSTAR Max DNA Polymerase (Takara, Beijing, China), and the fragments were ligated into the firefly luciferase report vector pGL4.10-Basic (Promega, the United States of America) through the Infusion Kit (Takara, Beijing, China) (\u003cem\u003e11\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual-luciferase reporter assays\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll recombinant plasmids were purified with the Mini Plasmid Kit (TIANGEN, Beijing, China) to remove endotoxin, and used for dual-luciferase reporter assays in \u003cem\u003eD. melanogaster\u0026nbsp;\u003c/em\u003eS2 cells (\u003cem\u003e11\u003c/em\u003e). Briefly, 200 \u0026micro;L of SFX-insect medium and 100 \u0026micro;L of pre-activated cells were added into 24-well culture plates for adherence. Co-transfection was performed once cell coverage reached approximately 80%, involving 600 ng of promoter plasmids, 100 ng of pGL4.73 control plasmids, and the Lipofectamine 2000 reagent (Invitrogen, USA). The pGL4.73 vector contains the luciferase reporter gene used internally for normalization. Similarly, the CDS sequence of the transcription factor was inserted into the pAC5.1b/V5/His B expression vector pre-cut with EcoRV restriction enzyme for ligation. For binding activity analysis, cells were co-transfected with 600 ng of transcription factor plasmids, 200 ng of promoter plasmids, and 100 ng of pGL4.73. Post-transfection, cells were incubated at 27\u0026deg;C for 48 h, then lysed with agitation at 200 rpm for 15 min. Luciferase activity was measured using the GloMax 96 Discover system (Promega, USA) while applying the Dual-Luciferase Reporter Assay System (Promega, USA). The ratio of firefly to Renilla luciferase activity was calculated for each sample and normalized against the control (empty vector). Each assay was performed in quadruplicate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSynthesis of single guide RNA (sgRNA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sgRNA target sequences were designed within different exons using the CRISPOR program (https://crispor.gi.ucsc.edu/). Target sites were selected based on the 5\u0026apos;-N20NGG-3\u0026apos; motif, with preference given to sites with minimal or no off-target potential. Oligonucleotides corresponding to the sgRNA target sites, including the T7 polymerase binding site, were used as upstream primer (Table S11), with fixed downstream primers (\u003cem\u003e39\u003c/em\u003e). PCR-based synthesis of template DNA involved a 50 \u0026mu;L reaction mixture containing 25 \u0026mu;L of PrimeSTAR Max Premix (TaKaRa, Beijing, China), 2 \u0026mu;L each of upstream and downstream primers, and 21 \u0026mu;L of RNase-Free Water. The PCR protocol was executed at 98\u0026deg;C for 2 min, followed by 35 cycles of 10 s at 98\u0026deg;C, 10 s at 70\u0026deg;C, 30 s at 72\u0026deg;C, and a 10-minute extension step at 72\u0026deg;C. PCR products served as templates for \u003cem\u003ein vitro\u003c/em\u003e sgRNA synthesis using the Precision gRNA Synthesis Kit (Invitrogen, USA), following manufacturer instructions. The synthesized sgRNA was stored at -80\u0026deg;C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmbryonic injection and mutagenesis detection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmbryonic injection was conducted as previously described with minor modifications (\u003cem\u003e39\u003c/em\u003e). Eggs laid within 1 h were rinsed with PBS buffer and the egg paper was sectioned into small fragments affixed firmly to double-sided tape inside a Petri dish. A solution containing 100 ng \u0026mu;L\u003csup\u003e\u0026minus;1\u003c/sup\u003e of sgRNA and 100 ng \u0026mu;L\u003csup\u003e\u0026minus;1\u003c/sup\u003e of Cas9 endonuclease (Invitrogen, the United States of America) was microinjected into each egg using the FemtoJet 4i Micro-Injection System (Eppendorf, Germany). Post-injection, the Petri dishes were transferred to an incubator (Panasonic, MLR-352H-PC, Japan) for rearing according to standard population rearing protocols. A mutation screening strategy was employed to establish homozygous mutant populations. Briefly, G0 individuals harboring the desired mutation were intercrossed to generate the G1 progeny for further amplification. Subsequent gene sequencing analyses identified homozygous mutants within the G1 generation, which were then self-crossed to produce the G2 generation of stabilized homozygous mutants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of oxidative stress markers and antioxidant responses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReactive oxygen species (ROS) levels in larvae subjected to various treatments were quantified using the Reactive Oxygen Species Red-Fluorescent Assay Kit (BestBio, Shanghai, China). Specifically, the BBoxiProbe\u0026reg; O13 dye was oxidized by tissue ROS to generate a red-fluorescent compound, with fluorescence intensity measured at excitation/emission wavelengths of 535/606 nm to reflect ROS concentrations. Enzymatic activities of key antioxidant enzymes\u0026mdash;peroxidase, catalase, and superoxide dismutase\u0026mdash;were assessed using corresponding enzyme activity kits (Jiancheng Bioengineering Institute, Nanjing, China). To determine if ROS scavenging influences the CncC pathway, fourth-instar larvae were fed an artificial diet supplemented with the ROS scavenger N-acetylcysteine (NAC) for 48 h (\u003cem\u003e19\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences among experimental groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey\u0026apos;s post hoc test (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) utilizing SPSS Statistics 22. Student\u0026apos;s \u003cem\u003et\u003c/em\u003e-test (*, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) was applied for pairwise comparisons. Data are expressed as mean \u0026plusmn; standard error (SE) and illustrated with graphs generated via GraphPad Prism 9 software (GraphPad, CA).\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis PDF file includes:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure S1-S15 and Table S1-S11.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe thank Prof. You-Jun Zhang, Dr. Bu-Li Fu, Dr. Jing Yang, Dr. Pei-Pan Gong from the Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China, for the support in the dual luciferase reporter assay. For the purpose of open access, the author has applied a \u0026lsquo;Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding:\u003c/strong\u003e This research was supported by the National Natural Science Foundation of China (32272588), Liaoning Provincial Natural Science Foundation for Distinguished Young Scholars (2024JH3/50100027)，and National Key R\u0026amp;D Program of China (2021YFD1400200).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eConceptualization: C. H. and X.Q. Y. Methodology: C. H., Y.X. L., X. Y., J.Y. L., Y.T. L. and X.Q. Y. Software: C. H., Y.X. L., X. Y. and J.Y. L. Data curation: C. H. and Y.X. L. Visualization: C. H., Y.X. L. and J.Y. L. Validation: C. H., Y.X. L, C. B. and X.Q. Y. Investigation: C. H., Y.X. L., Y.T. L. and X.Q. Y.F ormal analysis: C. H., C. B. and X.Q. Y. Original draft: C. H. Writing\u0026mdash;review and editing: C. H., C. B. and X.Q. Y. Resources: C. B. and X.Q. Y. Funding acquisition: X.Q. Y.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e All authors declare that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and materials availability:\u0026nbsp;\u003c/strong\u003eAll data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eT. K. Walsh,\u003cem\u003e \u003c/em\u003eD. G. Heckel, Y. Wu, S. Downes, K. H. J. Gordon, J. G. Oakeshott, Determinants of insecticide resistance evolution: comparative analysis among heliothines. \u003cem\u003eAnnu. Rev. Entomol.\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 387-406 (2022).\u003c/li\u003e\n\u003cli\u003eJ. E. Casida, G. B. 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Comput.\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 4243-4256 (2013).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"insecticide resistance, development, trade-off, transcriptional regulation","lastPublishedDoi":"10.21203/rs.3.rs-8791607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8791607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The evolution of insecticide resistance represents a global challenge to human food security and health. Resistance is often associated with fitness costs such as altered development and reproduction, however, the molecular mechanisms that underpin this evolutionary trade-off are poorly understood. Here we reveal the regulatory pathways underlying the trade-off between insecticide resistance and developmental regulation in the global invasive moth, Cydia pomonella. Using multi-omics approaches in combination with gene editing and transgenic approaches we show that overexpression of the glutathione S-transferase CpGSTd1 confers resistance to the pyrethroid insecticide λ-cyhalothrin. Computational alanine scanning (CAS), and site-specific mutagenesis reveal that the amino acid Tyr114 is a key structure-function determinant of CpGSTd1 metabolism of λ-cyhalothrin. CpGSTd1 is positively regulated by the transcription factor CpCncC, which is overexpressed in resistant C. pomonella, following its activation by reactive oxygen species (ROS). However, overexpression of CpCncC also promotes increased expression of the ecdysteroid biosynthesis gene CYP306A1, leading to elevated 20-hydroxyecdysone (20E) levels. Elevated 20E antagonized juvenile hormone (JH) synthesis, results in extended developmental durations and diminished reproductive capacity in resistant populations. Collectively, these findings provide insight into the molecular mechanisms underpinning insecticide resistance and highlight the role of transcription factors like CncC in mediating the trade-off between resistance and developmental homeostasis via their role as master regulators of genes involved in xenobiotic detoxification and hormonal pathways in insects.","manuscriptTitle":"The molecular mechanisms mediating a trade-off between insecticide resistance and development in an invasive pest","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-09 07:25:38","doi":"10.21203/rs.3.rs-8791607/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"10d72bc5-6d01-46be-a3fa-cd08292c54eb","owner":[],"postedDate":"March 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63462846,"name":"Biological sciences/Zoology/Entomology"},{"id":63462847,"name":"Scientific community and society/Agriculture"},{"id":63462848,"name":"Biological sciences/Biochemistry/Hormones"},{"id":63462849,"name":"Biological sciences/Biological techniques/Genetic techniques/Gene targeting/CRISPR-Cas9 genome editing"}],"tags":[],"updatedAt":"2026-03-09T07:25:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-09 07:25:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8791607","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8791607","identity":"rs-8791607","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}