Cytochrome P450 drives divergent adaptation to quercetin in invasive and native fruit borers

Cytochrome P450 drives divergent adaptation to quercetin in invasive and native fruit borers | 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 Cytochrome P450 drives divergent adaptation to quercetin in invasive and native fruit borers Xueqing Yang, Bing Bai, Nan-Xia Fu, Bo-Kun Wang, Ting-Ting Wen, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9176885/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The coevolutionary arms race between plants and herbivores is a key driver of insect adaptation. While the global invasive fruit borer Cydia pomonella shows slower adaptation to the plant secondary metabolite quercetin compared to native species Grapholita molesta, the molecular basis remains unclear. Here, we clarify the divergent evolutionary mechanisms governing the adaptation of these two species to quercetin. Results revealed enhanced quercetin metabolic capacity in adapted populations of both species relative to their non-adapted counterparts. G. molesta relies on the canonical detoxification-associated P450 genes CYP6AB364 and CYP341Q10 belonging to the CYP3 and CYP4 clans, respectively, showing positive correlation with adaptation. In contrast, C. pomonella employs a member of the CYP3 clan (CYP337B19) and specific mitochondrial P450 genes (CYP333B119 and CYP333B118). Artificial intelligence (AI)-based molecular docking assay confirmed strong binding interactions between these P450 enzymes and quercetin. Knockdown of these genes reduced metabolic adaptation, and in vitro assays showed decreased metabolic efficiency post-silencing. Notably, recombinant P450 enzymes from C. pomonella (with the exception of CYP337B19) exhibited lower quercetin metabolic capability than G. molesta's. These findings suggest divergent adaptive strategies between species, with the invasive C. pomonella potentially employing neofunctionalized mitochondrial P450s for quercetin detoxification and facilitate adaption. G. molesta's superior quercetin metabolism likely drives its greater adaptability, advancing our understanding of host adaptation and interspecific interactions in pest species. Biological sciences/Evolution/Coevolution Biological sciences/Evolution/Molecular evolution Plant-insect interactions adaptive mechanism P450 enzyme neofunctionalization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Biological invasions have become one of the five major global environmental issues of the 21st century 1 . The interspecific relationships between invasive insects and native insects are typically characterized by competition 2 , predation 3 , mutualism 4 , and commensalism 5 . Such diverse and complex interactions ultimately shape population dynamics and drive insect adaptive evolution 6 . In addition, a coevolutionary arms race characterized by iterative cycles of plant defense and herbivore counter-defense is recognized as the primary driver of adaptive evolution in the plant-insect interaction systems 7,8 . Plants have evolved a diverse array of morphological, molecular, and biochemical defenses to deter herbivory 8 . Among biochemical defenses, plant secondary metabolites (PSMs) represent the most diverse and potent chemical defense mechanism 9 . PSMs are typically stored as inactive, non-toxic precursors and enzymatically activated upon herbivory 10 , which subsequently influence insect physiological processes and nutrient utilization 11 . For example, quercetin has been shown to affect the survival rate of Acyrthosiphon pisum 12 , while salicin and rutin can impact the body weight, relative growth, food conversion efficiency, and digestion efficiency of Lymantria dispar larvae 13 . To utilize such plants as hosts, insects generally must eveolve highly specific adaptative strategies, including behavioral, morphological, and biochemical mechanisms, to overcome the toxic effects of PSMs 14 . For instance, some host-highly adapted insects, such as the whitefly ( Bemisia tabaci ) and the brown planthopper ( Nilaparvata lugens ), manipulate host plant tomato volatile emissions to transmit 'defensive signals' that suppress to neighboring plants' defenses, rendering them more vulnerable to their infestation 15 . Helicoverpa zea elevates glucose oxidase levels in its saliva to inhibit plant immune responses and reduces nicotine accomulation in tobacco plants 16 . Zygaena filipendulae employs detoxification enzyme systems to neutralize cyanide toxicity 17 . Furthermore, variations in PSM tolerancebetween invasive and native herbivorous insects may lead to differences in detoxification strategies 18 . For example, Spodoptera frugiperda utilizes P450 monooxygenases to detoxify xanthotoxin 19 , whereas S. litura predominantly relies on UDP-glucuronosyltransferases (UGT) 20 . Additionally, in B. tabaci , the B biotype exhibits elevated esterase activity to counter host plant incompatibility, contrasting with native populations 21 . Consequently, invasive and native insect species serve as an ideal comparative system for uncovering the mechanisms underlying rapid evolutionary responses to environmental pressures, resource competition, and survival challenges, providing critical insights into the formation of adaptive strategies. The invasive species Cydia pomonella (Linnaeus) and the native species Grapholita molesta (Busck) are typically regarded as competitors due to their shared reliance on common host plants such as pear and apple 22 . C. pomonella originates from Central Asia Minor and has expanded globally since 1900, now appearing in approximately 70 countries 23 . Genetic studies suggest that northeastern Chinese populations of C. pomonella may have originated from Russia 24 , where the quercetin contents in primary host fruits are consistently below 30 μg/g 25,26 , compared to the 74.79 μg/g detected in Nanguo pears from Northeast China 27 . Due to the lack of pre-adaptive traits for tolerating high quercetin concentrations, C. pomonella requires one additional generation compared to G. molesta to adapt to quercetin 28 . Its detoxification employs a biphasic process: an initial phase dominated by ABC transporter activity for short-term efflux, followed by a longer-term reliance on P450-mediated metabolism. In contrast, G. molesta primarily employs a synergistic enzymatic detoxification system involving multiple enzymes 28 . However, the precise molecular mechanisms underlying the adaptation of C. pomonella and G. molesta to quercetin remain poorly elucidated. To address this knowledge gap, we conducted integrated transcriptomic and proteomic analyses on quercetin-adapted populations to characterize their adaptive strategies and identify differentially expressed genes. Subsequent RT-qPCR assays were performed to examine the spatiol and temporal expression patterns of candidate genes. AlphaFold-based molecular docking confirmed strong binding interactions between these P450 enzymes and quercetin. Combining RNA interference (RNAi) technology with HPLC analysis, we tracked the dynamic levels of ingested quercetin within the insects. In vitro functional assays using recombinant enzymes were performed to validate the role of specific P450 enzymes in quercetin metabolism. These cutting-edge biological techniques were employed to elucidate the molecular and biochemical bases of adaptive divergence between these tow fruit borers, providing deeper insights into the adaptive evolutionary divergence between invasive and native insect species and contributes to a better understanding of the global invasion of C. pomonella . Results Investigation of quercetin contents in the main cultivated host plants of the countries along the invasion route of C. pomonella Through literature research, we analyzed the quercetin content in major host plant varieties of different countries and regions invaded by C. pomonella . The results indicate that in Canada, the United States, Chile, and southern Africa, the primary host pear variety is Bartlett, with a quercetin content of 55 μg/g 29 . In European regions, such as France, Germany, and Italy, the main affected host varieties are Cox's Orange Pippin Apple (2.3 µg/g), Elstar Apple (3.34 µg/g), and Gold Delicious Apple (1.6 µg/g), respectively 26 . In Argentina, India, and Australia, the principal hosts utilized by C. pomonella are Gala Apple (1.2 µg/g) 30 , Chinese Pear (15.3 µg/g) 31 , and Granny Smith Apple (1.6 µg/g) 26 . Key hosts in Russia include Boskoop (4.5 µg/g) and Gold Delicious Apples (1.6 µg/g) 26 , while in Tajikistan, it is the Kosimsarkori Apple (11.9 µg/g) 25 . For China, cultivated varieties such as the Nanguo pear (70.8 µg/g), Xuehua Pear (31.2 µg/g), and Huangguan Pear (12.7 µg/g) were noted 27,31 , with the Nanguo Pear from Liaoning exhibiting the highest quercetin levels (Figure 1a). These findings suggest that C. pomonella may not have encountered host-defensive selection pressure involving quercetin concentrations as high as 70.0 µg/g prior to its invasion into northeastern China. Integrated transcriptomic and proteomic analyses identified P450 genes positively correlated with G. molesta and C. pomonella adaptation processes to quercetin Our previous transcriptomic analysis revealed that adaptation processes to quercetin the oxidation-reduction process within Gene Ontology (GO) annotation exhibited the highest gene ratio in G. molesta , while ranking second in C. pomonella 28 . In this study, we found that during the adaptation process from G1 to G3 in G. molesta, a significant upregulation of P450 genes was observed. Specially, 3 P450 genes (one from the CYP3 clan and two from the CYP4 clan) were upregulated in G1, 9 genes (one from the CYP2 clan, three from the CYP3 clan, and five from the CYP4 clan) in G2, and 7 genes (four from the CYP3 clan and three from the CYP4 clan) in G3, all in comparison to the control group (G0). Similarly to G. molesta , C. pomonella exhibited upregulated P450 gene expression across generations G1 to G3. Specifically, G1 showed 11 P450 genes (1 from the CYP2 clan, 7 from the CYP3 clan, and 3 from the CYP4 clan), G2 had 10 P450 genes (1 from the CYP2 clan and 9 from the CYP3 clan), and G3 possessed 9 P450 genes (5 from the CYP3 clan and 4 from the CYP4 clan), all in comparison to the control group (G0). Notably, in the quercetin-adapted (GA) generation, G4 displayed 11 upregulated P450 genes, comprising 1 from the CYP2 clan, 7 from the CYP3 clan, 2 from the CYP4 clan, and an additional gene from the mitochondrial clan (Figure 1d; Table S4). Proteomic profiling of G. molesta and C. pomonella demonstrated that differentially expressed proteins (DEPs) were enriched across 12 and 18 GO pathways, respectively ( P < 0.05). The oxidation-reduction process was the most significantly enriched GO term in C. pomonella , whereas it ranked seventh in G. molesta (Figure S1). KEGG analysis indicated significant ( P < 0.05) enrichment of drug metabolism - cytochrome P450 (map00982) and xenobiotics metabolism via cytochrome P450 (map00980) in both species (Figure S2) . To elucidate the molecular mechanisms underlying quercetin adaptation in these fruit borers, integrated transcriptomic and proteomic data were analyzed. G. molesta yielded 8,375 transcripts and 7,385 proteins, while C. pomonella exhibited 8,088 transcripts and 7,909 proteins. Among these, 46 genes were significantly differentially expressed and shared between both species (Figure S3 a; b). In addition, GO pathways co-enriched in the transcriptome and proteome of G. molesta included aminoglycan metabolic process (GO: 0006022) and oxidation-reduction process (GO: 0055114), whereas C. pomonella showed enrichment in oxidation-reduction process (GO: 0055114) and proteolysis (GO: 0006508) (Figure 1b). These findings suggest that oxidation-reduction process serve as a conserved adaptive strategy to quercetinacross both species. Further validation employed strict selection criteria ( P 1) to identify genes with consistent upregulation at transcript and protein levels, reflecting functional gene expression (Figure 1b). Two P450 proteins in G. molesta were significantly upregulated by 2.19 and 1.6-fold, respectively, while three in C. pomonella were upregulated by 22.53, 1.635, and 1.483-fold, respectively (Figure 1c). Proteomic data confirmed the reproducibility of these five proteins, indicating reliable quantification (Figure S4). All five P450 genes were annotated and named by David Nelson of the P450 Nomenclature Committee. Phylogenetic analysis revealed that CYP6AB364 and CYP341Q10 from G. molesta belong to the CYP3 and CYP4 clans, respectively. In C. pomonella , CYP337B19 is classified within the CYP3 clan, while CYP333B119 and CYP333B118 fall under the mitochondrial clan (Figure 1e). Structural conservation among P450 proteins was observed, with all possessing typical P450 structural domains (Figure S5a). Chromosomal mapping indicated CYP6AB364 and CYP341Q10 are located on chromosomes 3 and 7, respectively, while CYP337B19 resides on chromosome 4 and CYP333B118 on chromosome 18 in C. pomonella (Figure S5b). Transcript abundance of quercetin adaptation-related P450 genes in G. molesta and C. pomonella To explore the potential role of these P450 genes, their expression patterns in two species were analyzed across various developmental stages and tissues. Results indicated that CYP341Q10 and CYP6AB364 in both QNA and QA G. molesta populations exhibited peak expression during the voracious feeding stage—the fourth instar larvae stage (Figure 2a). Similarly, CYP333B119 , CYP333B118 , and CYP337B19 in QNA and QA C. pomonella population also showed highest expression levels during the same developmental stage (Figure 2a). Furthermore, these genes were expressed across all tissues of fourth instar larvae in both species. Notably, CYP341Q10 and CYP6AB364 in the midgut of QNA G. molesta showed significantly higher expression relative to other tissues. Post-adaptation to quercetin, the expression of CYP341Q10 and CYP6AB364 was markedly upregulated in the midgut, Malpighian tubules, and cuticle of G. molesta . Similarly, in C. pomonella , CYP333B119 , CYP333B118 , and CYP337B19 in the midgut displayed higher expression compared to other tissues. Compared to QNA, the expression of CYP333B119 , CYP333B118 , and CYP337B19 was significantly increased in the midgut and fat body following quercetin adaptation (Figure 2b). These findings suggest that CYP341Q10 and CYP6AB364 in G. molesta , and CYP333B119 , CYP333B118 , and CYP337B19 in C. pomonella , may play crucial roles in the detoxification of quercetin. Protein levels analysis of quercetin adaptation-related P450 genes in G. molesta and C. pomonella To validate protein expression levels observed in the proteome, Western blot assays were performed for these P450 members. The P450 proteins exhibited molecular weights ranging from 46 to 60 kDa. Using Drosophila melanogaster β -actin as an internal control, results showed that CYP6AB364 and CYP341Q10 were upregulated by 1.85- and 1.81-fold, respectively, in QA G. molesta compared to QNA (Figure 2c). Likewise, CYP337B19, CYP333B119, and CYP333B118 in C. pomonella were elevated by 1.31-, 1.83-, and 7.15-fold, respectively, in the QA strains versus QNA (Figure 2d). These data indicate that the protein expression patterns are consistent with the proteomic findings, imply potential roles of these P450 in the detoxification of quercetin. AI-based docking reveals strong interaction between P450 and quercetin Using AlphaFold2, we predicted the 3D structures of CYP6AB364, CYP341Q10, CYP337B19, CYP333B118, and CYP333B119. Restricted molecular docking, based on predicted ligand-binding pockets, demonstrated that each P450 enzyme formed hydrogen bonds with quercetin: in CYP6AB364, ARG-204, GLU-212, and ALA-233; in CYP341Q10, TRP-125, LYS-101, and ILE-118; in CYP337B19, ASP-301, LEU-203, and ARG-98; in CYP333B118, THR-333; and in CYP333B119, ASN-383, ARG-114, THR-330, and THR-331. Binding energies ranged from -8.1 to -9.0 kcal/mol, indicating strong ligand affinity. Further molecular docking with AlphaFold3 yielded that the predicted complex structures of CYP341Q10, CYP337B19, and CYP333B119 with quercetin had high confidence scores (ipTM scores of 0.83, 0.88, and 0.82, respectively), whereas complexes with CYP6AB364 and CYP333B118 exhibited moderate confidence (ipTM scores of 0.74 and 0.76) (Figure 2e). These findings indicate a strong interaction between selected P450 proteins and quercetin. Knockdown P450 genes reduce quercetin adaptation of G. molesta and C. pomonella Microinjection of dsRNA effectively silenced gene expression Following the microinjection of ds CYP6AB364 and ds CYP341Q10 , the QNA and QA populations of G. molesta exhibited RNAi efficiencies at 6 and 12 h, with knockdown efficiencies exceeding 40%. (Figure 3a). In C. pomonella , after administration of ds CYP337B19 , ds CYP333B118 , and ds CYP333B119 , the QNA and QA populations exhibited RNAi efficiencies from 6 to 24 h, exceeding 30% (Figure 3a). These findings demonstrate robust gene silencing efficacy within 48 h in both populations. Quercetin reduces nutritional parameters in G. molesta and C. pomonella after knockdown of P450 genes Following RNAi via microinjection of ds CYP6AB364 and ds CYP341Q10 in to G. molesta QNA larvae fed on quercetin-free diet, no significant differences were observed in larval growth metrics, including weight gain, ECI, ECD, and GR, compared to ds GFP control between 12 to 48 h. Conversely, ds CYP6AB364 injection resulted in notable reduction in larval weight gain, ECD, ECI, and GR at 6 h post-injection. Similarly, ds CYP341Q10 injections caused significant decreases in ECD, ECI, and GR at 48 h (Figure S6). In C. pomonella , injections of ds CYP337B19 and ds CYP333B119 , into QNA and QA larvae fed a quercetin-free diet did not elicit significant differences in weight growth, ECI, ECD, and GR, from 6 to 48 h. However, ds CYP333B118 injections led to significant reductions in ECI at 6 and 24 h in QA larvae (Figure S7). These findings suggest that P450 gene knockdown via RNAi exerts minimal impact on larval nutritional indices in both QA and QNA populations. Additionally, ds CYP6AB364 and ds CYP341Q10 injections in G. molesta QA larvae fed a quercetin diet resulted in significant declines in larval weight gain, ECD, and ECI from 6 to 48 h, with GR significantly reduced at 24 and 48 h (Figure 3b-e). In C. pomonella , injections of dsCYP337B19 , dsCYP333B11 9, and dsCYP333B118 into QA larvae fed quercetin diets caused substantial decreases in larval growth parameters, including weight gain, ECD, ECI, and GR, between 6 to 24 h (Figure 3f-i). These results indicate the critical role of P450 genes in facilitating adaptive tolerance to dietary quercetin in both lepidopteran species . Knockdown P450 genes reduce metabolism of quercetin in G. molesta and C. pomonella Injection of dsRNA effectively silenced gene expression in tissues The RNAi efficacy in G. molesta populations was evaluated following injection with dsCYP6AB364 and dsCYP341Q10. In the QNA population, dsCYP6AB364 achieved greater than 60% gene knockdown in the midgut, fat body, and Malpighian tubules at both 2h and 5 h post-injection, whereas dsCYP341Q10 elicited over 60% suppression in all tissues except Malpighian tubules at 5 h (40.1%). Conversely, in the QA population, dsCYP6AB364 resulted in more than 70% silencing efficiency in the midgut and Malpighian tubules and over 40% in the fat body at both time points, with dsCYP341Q10 showing over 50% efficacy across tissues, except in the midgut at 2 h (41.7%) (Figure S8). In C. pomonella , the injections of dsCYP337B19 yielded over 80% RNAi efficiency in the midgut at 2h and 5 h, with more than 40% in the fat body and Malpighian tubules. Following dsCYP333B119 injection, the fat body demonstrated over 80% efficacy at both intervals, while the midgut and Malpighian tubules exhibited over 40%. Injection with dsCYP333B118 resulted in all three tissues achieving over 40% gene silencing at both time points. In the QA population, dsCYP337B19 achieved silencing efficiencies of 73.9% in the midgut, 60.7% in the fat body, and 53.9% in the Malpighian tubules at 2 h; these increased to 84.1%, 69.3%, and 47.1%, respectively, at 5 h. Post-injection with dsCYP333B119 or dsCYP333B118, all tissues maintained silencing efficiencies exceeding 50% at both time points (Figure S9). These findings demonstrate that all tissues exhibit robust gene interference within a 5-h timeframe. Knockdown P450 genes lead to quercetin accumulation in tissues of G. molesta and C. pomonella In both QNA and QA populations of G. molesta and C. pomonella , quercetin levels in tissues showed a gradual decline over time, while excretion in feces gradually increased. Furthermore, at all time points, tissue quercetin concentrations in the QNA populations consistently exceeded those in the QA populations (Figure 4b). This suggests that quercetin-adapted populations of G. molesta and C. pomonella possess enhanced metabolic capacity for quercetin detoxification. In addition, both QNA and QA populations of G. molesta completely excreted quercetin within 8 h. Consequently, 2-h and 5-h time points were selected for subsequent analytical assays. Following knockdown of P450 genes in G. molesta and C. pomonella , quercetin ingestion levels did not significantly differ from those observed in the ds GFP control group in either strain (Figure S10). In QNA G. molesta , knockdown of CYP341Q10 and ds CYP6AB364 resulted in increased quercetin accumulation in the midgut at 2 h and 5 h, compared to ds GFP . In QA population, midgut quercetin levels were significantly elevated at 2 h, with further increases observed in the midgut, fat body, and feces at 5 h (Figure 4c). In C. pomonella , knockdown of CYP337B19 did not significantly change tissue or fecal quercetin levels at either 2 or 5 h in both strains. Knockdown of CYP333B118 led to increased quercetin in the midgut at 2 h, and in the midgut, fat body, and feces at 5 h in QNA and QA population. After CYP333B119 suppression, both strains exhibited increased midgut quercetin at 2 h and significant rises in midgut and fecal quercetin at 5 h (Figure 4c). These findings implicate CYP341Q10 and CYP6AB364 in G. molesta , and CYP333B119 and CYP333B118 in C. pomonella , as key enzymes involved in quercetin metabolism. Assessment of the in vitro metabolism of quercetin in G. molesta and C. pomonella To verify whether these P450 could directly metabolic quercetin, the recombinant proteins were expressed. Recombinant bacmid containing successful transposition carried the target gene fragments, with PCR product lengths of 3824 bp for CYP341Q10 , 3800 bp for CYP6AB364 , 3790 bp for CYP337B19 , 3827 bp for CYP333B119 , and 3839 bp for CYP333B118 , consistent with the expected insert sizes (approximately 2300 bp plus fragment length). These results confirm successful integration of the target genes into the baculovirus expression system's bacmid vectors. The supernatant from infected cell cultures was harvested on day seven, corresponding to peak viral titers characterized by extensive cell lysis and virus release (Figure S11). Comparison of metabolize capability with and without NADPH showed that CYP6AB364 and CYP341Q10 proteins from G. molesta exhibited significant reductions in peak chromatographic areas upon NADPH addition (Figure 5a-b). Similarly, in C. pomonella , CYP333B119 and CYP333B118 showed significant decreases in peak areas with NADPH, while CYP337B19 displayed no significant change (Figure 5c-e). Quercetin depletion rates by these CYP enzymes were 18.16% (CYP6AB364), 17.99% (CYP341Q10), 13.93% (CYP333B118), and 8.99% (CYP333B119), indicating that G. molesta exhibits higher metabolic efficiency in quercetin detoxification compared to C. pomonella (Figure 5f). Discussion The differential adaptation of invasive versus native species to PSMs arise from their divergent tolerance levels 32 . Previous studies have demonstrated that exposure to quercetin inhibits the fecundity and population growth of C. pomonella , whereas G. molesta exhibits a stimulatory response 22 . These findings suggest that native species have evolved mechanisms to tolerate quercetin, while invasive species lack pre-adaptation to this compound 28 . In this study, we elucidate the evolutionary mechanisms of adaptation to quercetin in the global invasive fruit borer, C. pomonella , and its sympatric native congener, G. molesta . In insects, P450 play critical roles in the metabolism of xenobiotics, endogenous compound biosynthesis and degradation, and the synthesis and breakdown of plant secondary metabolites 33 . Insect P450 genes are categorized into six clans: CYP2, CYP3, CYP4, CYP16, CYP20, and mitochondrial (mito) 34 . The CYP3 and CYP4 clans, predominant in insects, are well-documented for their roles in chemical defense mechanisms 35,36 . Substantial evidence indicates that CYP3 clan P450 genes, predominantly CYP6 and CYP9 family members, primarily facilitate xenobiotic detoxification through direct substrate metabolism 37 . For example, Helicoverpa zea CYP6B8 catalyzes six PSMs, including xanthotoxin, quercetin, flavone, chlorogenic acid, indole-3-carbinol, and rutin, and metabolizes three insecticides 38 . Members of the CYP9A subfamily can detoxify imperatorin and xanthotoxin, facilitating the development of the broad host ranges of S. exigua and S. frugiperda over long evolutionary timeframes 39 . Additionally, mitochondrial P450 genes within insects are characterized by their rapid evolution driven by gene duplication and diversification of taxon-specific paralogs 34 . These maternally inherited enzymes influence adaptive evolution 40 . For instance, CYP12A1 in Musca domestica is induced by phenobarbital and constitutively overexpressed in insecticide-resistant strains 41 . Similarly, CYP337B3v2 is prevalent in pyrethroid-resistant Helicoverpa. armigera populations but scarce in susceptible populations 42 . Overexpression of CYP12A4 in the midgut and Malpighian tubules confers resistance to lufenuron in Drosophila melanogaster 43 . In this study, through comparative transcriptomic analysis across generations during the adaptation of two fruit borers to quercetin 28 , we observed that in G. molesta , both during the adaptation process and in fully adapted populations, transcript levels of several P450 members from the traditionally detoxification-related CYP3 and CYP4 clans were significantly upregulated. Conversely, C. pomonella also activated a cohort of CYP3 and CYP4 clan P450s during adaptation, but in its fully adapted population, two additional P450s from the mitochondrial clan, CYP333B118 and CYP333B119 , were recruited. This suggest that the canonical detoxification-associated P450 genes belonging CYP3 and CYP4 clans, are insufficient to ensure C. pomonella 's complete mitigation of quercetin pressures in newly invaded habitats. Consequently, there is a requirement for the temporary recruitment of mitochondrial P450 genes. This finding corroborates the viewpoint posited by Heidel-Fischer and Vogel (2015) that gene recruitment and neofunctionalization represent a pivotal molecular strategy by which insects evolve adaptations to PSMs 44 . For instance, neofunctionalization of duplicated CYP337B28 and CYP337B29 led to the evolution of pyrethroid resistance in African lineage, H. a. armigera 45 . Similarly, duplication and neofunctionalization of CYP6ER1 led to the evolution of imidacloprid resistance in Nilaparvata lugens 46 . Nonetheless, the detoxification capacity of these "temporarily recruited" mitochondrial P450 enzymes appears comparatively weaker than that of CYP3 and CYP4 clan enzymes, consistent with previous reports indicating lower catalytic activity of mitochondrial CYP339A1 toward esfenvalerate relative to CYP6 and CYP9 families in H. armigera 47,48 . These findings suggest that invasive species like C. pomonella may induce mitochondrial P450s to detoxify quercetin during host adaptation, while Clan 3 members, especially CYP6 and CYP9 families 35,36 , maintain broad conversation and detoxification functions against other PSMs and insecticides, potentially facilitating rapid invasion success (Figure 6). Detoxification is a complex, multisystem biochemical process involving various enzymatic pathways and regulatory factors 49 . For instance, Zygaena filipendulae employs two P450 and a UGT to mitigate cyanide toxicity 17 . In this study, we observed that, regardless of G. molesta or C. pomonella , the QA population exhibits lower levels of quercetin accumulation across tissues compared to the QNA population, indicating an enhanced metabolic adaptation to quercetin. Moreover, functional assays involving RNAi targeting key P450 genes identified through proteomic and transcriptomic correlation analyses revealed that silencing CYP6AB364 and CYP341Q10 in G. molesta resulted in greater increases in midgut quercetin accumulation than the gene suppression efficiencies would predict. Conversely, in the QA population of C. pomonella , gene knockdowns of CYP333B118 and CYP333B119 at efficiencies of approximately 40% and 63%, respectively, corresponded to quercetin accumulation proportions of approximately 82% and 40%, showing no direct positive correlation between gene silencing efficacy and metabolite accumulation. These findings imply that the current screening may not encompass all relevant P450 isoforms or other biotransformation enzymes involved in C. pomonella detoxification. Besides, this disparity could stem from the fact that quercetin detoxification in C. pomonella involves multiple parallel pathways, whereas our focus was limited to a single pathway. Future research should aim at an integrated characterization of differentially expressed detoxification enzymes, such as ABC and GST, which have been implicated in quercetin metabolism 28 . Understanding the substrate specificities and their roles within PSM metabolic networks will facilitate a more systematic understanding of the mechanisms underpinning adaptation in invasive versus native species to their host plants. Moreover, this study initially explored the adaptive mechanisms of both fruit borers under quercetin selection pressure. Future investigations should examine the influence of additional PSMs on these fruit borers host adaptation and assess whether PSMs adaptation influences their susceptibility to insecticides. Additionally, combined analysis of binding energy derived from traditional molecular docking and structural simulations using AlphaFold3 reveals that the P450 proteins of G. molesta and C. pomonella possess strong binding affinity for quercetin. These insights serve as a critical foundation for the rational design of P450-specific inhibitors, facilitating the advancement of targeted pest management strategies. Methods Insect species and populations The G. molesta and C. pomonella strains were maintained in the laboratory conditions without exposure to quercetin for over 50 generations. Larval rearing was performed on an artificial diet within a MLR-352H-PC growth chamber (Panasonic, Ehime Prefecture, Japan), maintained at 26 ± 1 o C, 60 ± 5% relative humidity, with a 16:8 h (L:D) photoperiod. Adults were supplied with a 10% honey solution. A quercetin-adapted population (QA) of C. pomonella is defined as a population continuously exposed to 70 μg/g quercetin across four generations, originating from a quercetin-non-adapted population (QNA). Similarly, a quercetin-adapted G. molesta population (QA) is defined as one subjected to the same quercetin concentraation across three generations 28 . Correlation analysis of transcriptomic and proteomic data Transcriptome and proteome analyses were conducted on fourth instar larvae of both species, comparing QNA and QA groups. Transcriptome datasets have been published previously 28 . Proteomic samples comprised 60 individuals per G. molesta and C. pomonella group, each with three biological replicates, conducted at Novogene Company (Tianjin, China). Quantitative proteomics employed Data Independent Acquisition (DIA) based on the GCA_0226743251.1 ( G. molesta ) and GCA_033807575.1 ( C. pomonella ) databases. Functional annotation was performed using InterProScan for Gene Ontology (GO) classification, including cellular components, molecular functions, and biological processes. Further pathways and proteins function analyses involved COG and KEGG databases. An integrated multi-omics approach was employed to elucidate regulatory mechanisms from transcription to translation, matching differentially expressed genes (DEGs) and proteins (DEPs) via common gene identifiers to generate paired mRNA and protein expression profiles. Given that protein levels more directly reflect functional gene output, and that transcript-protein correlation can be variable, key P450 genes involved in quercetin adaptation were identified using threshold criteria of |FC| > 1 and P < 0.05 on the proteomic dataset, corroborated by corresponding mRNA expression profiles. Identify of P450 candidates associated with quercetin adaptation Omics analysis was employed to identify P450 candidates associated with quercetin adaptation in G. molesta and C. pomonella . Candidate P450 genes were cloned using genespecific primers (Table S1), designed via Primer 5, synthesized by Suzhou Genewiz Biotechnology Co. Ltd. (Suzhou, China). PCR amplification conditions included an initial denaturation at 94 °C for 3 min, followed by 39 cycles of 30 seconds at 94 °C, 30 seconds at 56 °C, 1 min at 72 °C, with a final extension at 72 °C for 10 min. PCR products were gel-purified with TIANgel Midi Purification Kit (DP219, TIANGEN BIOTECH, Beijing, China), cloned into the pMD 19-T vector (TaKaRa, Dalian, China), transformed into Escherichia coli DH5ɑ (TaKaRa), and finally sequenced at Suzhou Genewiz Biotechnology Co. Ltd. Sequence similarities were assessed via DNAMAN 5.2.2 alignment . Phylogenetic analyses utilized P450 amino acid sequences from Bombyx mori , Plutella xylostella , Manduca sexta, H._armigera, Z._filipendulae , Spodoptera_exigua , Spodoptera_frugiperda , and Spodoptera_litura as reference sequences. Phylogenetic trees were constructed using MEGA 11 employing the neighbor-joining method with 1000 bootstrap repeats. Protein domains were determined via the NCBI (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi). RNA extraction and cDNA synthesis Total RNA was extracted from whole insects following the instructions provided by the manufacturer using Trizol Reagent (TaKaRa, Dalian, China). RNA purity and concentration were evaluated via NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA). For each sample, 1 μg of total RNA was reverse-transcribed into first-strand cDNA using PrimeScript™ RT reagent Kit with gDNA Eraser (TaKaRa). The cDNA samples were stored at -20 °C until further analysis. Transcript analysis of quercetin adaptation-related P450 genes A total of fifty eggs, thirty larvae of the first (1L), second (2L) and third (3L) instar stages, ten larvae of the fourth (4L) and fifth (5L) instar stages, as well as ten female pupae (P♀), male pupae (P♂), female adults (A♀), and male adults (A♂), along with various tissues from fourth-instar larvae (head, cuticle, fat body, midgut, and Malpighian tubules), were collected with three replicates each. Expression profiles of genes associated with quercetin adaptation were analyzed via real-time qPCR (RT-qPCR) on a Bio-Rad CFX96 system (Bio-Rad, Hercules, CA, USA). Each 20 μL qPCR reaction comprised 10 μL of TB Premix Ex Taq, 1 μL of cDNA, 1 μL each of forward and reverse primers, and 7 μL of nuclease-free water. EF-1α and Actin genes were employed as internal controls for C. pomonella 50 and G. molesta 51 . Primers sequences for RT-qPCR analysis of P450 genes were designed using Primer5 (Table S2). Three biological replicates each with three technical replicates were performed. Negative controls, including non-template controls (NTC) and non-reverse transcription controls (NRC), were incorporated to prevent potential genomic DNA contamination. Cycling conditions consisted of 95 °C for 30 seconds, followed by 40 cycles of 95 °C for 5 seconds, 50-60 °C for 30 seconds, and 72 °C for 30 seconds. Relative expression levels were calculated using the 2 −ΔΔ CT method 52 and visualized with GraphPad Prism software. Heterologous expression of recombinant P450 proteins The open reading frame (ORF) of CYP341Q10 , CYP6AB364 , CYP333B119 , CYP333B118 , CYP337B19 , and a NADPH-dependent cytochrome P450 reductase (CPR) was synthesized by Tsingke Science (Beijing, China) following the method described in Li et al. (2023) 53 . These sequences were cloned into the pFastBac1 vector via restriction enzyme digestion, and the recombinant plasmids were verified through PCR and sequencing before storage at -20 o C. To generate the recombinant bacmid DNA, the pFastBac1 constructs were transformed into the MAX Efficiency DH10Bac chemically competent cells (Thermo Fisher Scientific, Langenselbold, Germany). Positive clones containing recombinant bacmid DNA were confirmed via PCR using M13 forward and reverse primers. The recombinant bacmid DNA was isolated, quantified, aliquoted, and stored at -20 o C in TE buffer at approximately 500 ng/μL. Recombinant P450 proteins were expressed in Sf9 cells. Bacmids haboring CYP341Q10, CYP6AB364, CYP333B119, CYP333B118, and CYP337B19 were transfected into Sf9 cells using the Bac-to-Bac baculovirus expression system (Thermo Fisher Scientific, Langenselbold, Germany), following manufacturer instructions. The viral titers was determined as per protocol. Sf9 cells were co-infected with recombinant baculoviruses expressing P450 and CPR at multiplicities of infection (MOI) of 1 and 0.1, respectively. Cells were maintained at 27 o C in Sf-900 II SFM medium (LifeTechnologies, Carlsbad, CA, USA), supplemented with 2.5 μg/mL hemin and 0.3% ( v/v ) fetal bovine serum. After 72 h, cells were harvested to isolate microsomal fraction, which were aliquoted and stored at -80 o C after protein quantification via the Bradford assay (Beyotime, Shanghai, China). Western blotting analysis of quercetin adaptation-related P450 genes Microsomal fractions containing recombinant P450 enzymes and CPR were denatured at 100 o C for 10 min, then separated using 10 % SDS-PAGE. Proteins were blotted transferred onto polyvinylidene difluoride (PVDF) membrane (Merck Millipore, Darmstadt, Germany) using a Bio-Rad blotting system. Membranes were blocked with a 5% ( w/v ) non-fat dry milk in TBST buffer for 2 h, followed by overnight incubation at 4 o C primary antibody (1:1000; ProbeGene, Jiangsu, China). After washing, membranes were incubated with HRP-conjugated goat anti-rabbit secondary antibody (1:10000; Bio-Platform, China) for 1h. Detection was performed with Omni-ECL™ Femto Light Chemiluminescence Kit (Yamei, Shanghai, China) and chemiluminescent images were captured with a Tanon 5200 imaging system (Tanon, Shanghai, China). Molecular docking analysis of the interaction between P450 and quercetin The structures of P450 proteins were predicted using AlphaFold2. The three-dimensional (3D) structure of quercetin was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/). Active pockets of P450 enzymes were predicted using Proteins Plus. Molecular docking simulations between proteins and quercetin were conducted with AutoDock Vina 1.1.2, and results were analyzed using Discovery Studio and visualized with PyMOL 2.4.1. Lower docking free energies indicate stronger binding affinity. Furthermore, AlphaFold3 was employed to directly predict the structures of protein-ligand complexes. The Predicted Template Modeling (pTM) and Interface Predicted Template Modeling (iPTM) scores, derived from the Predicted Aligned Error (PAE) matrix through AlphaFold's internal algorithm, were employed to assess the structural confidence and interface accuracy of the modeled complexes, respectively. Functional analysis of P450 gene via RNA interference (RNAi) Double-stranded RNA (dsRNA) synthesis was performed following the instructions provided by the T7 RiboMAXTM Express RNAi System (Promega, USA). The resulting dsRNA solution was diluted to a concentration of 3000 ng/μL. Prior to microinjection, fourth instar larvae of QNA and QA populations of G. molesta and C. pomonella were starved for 12 h. A volume of 1 μL of dsRNA was microinjected into the third-to-fifth abdominal segment at the posterior end of each larva, with dsGFP serve as a control. Post-injection, fourth instar larvae of QNA and QA populations of G. molesta and C. pomonella were fed on quercetin-free artificial diets. Whole insect samples were collected at 6 h, 12 h, 24 h, and 48 h, with 10 larvae per group and 3 replicates per group. The RNAi efficiency of the target gene was detected using RT-qPCR. Moreover, fourth instar larvae of QNA and QA populations of G. molesta and C. pomonella were fed on 70 μg/g quercetin artificial diets for 2 h. Subsequently, the feed was removed. Tissue samples from the midgut, fat body, and Malpighian tubules were collected at 2 h and 5 h, with 20 larvae per group and 3 replicates per group. The RNAi efficiency of gene within these tissues was assessed via RT-qPCR. Assessment of nutritional parameters of two fruit borers following RNAi Post-injection of dsRNA, larvae were fed artificial diets containing either 0 μg/g or 70 μg/g quercetin. Nutritional parameters such as the efficiency of conversion of digested food (ECD), efficiency of conversion of ingested food (ECI) and relative growth rate (GR), were quantified at 6 h, 12 h, 24 h, and 48 h, according to previous documented method. 27 Weight of diet before feeding (WBF), weight of diet after feeding (WAF), weight of larvae feces (WLF) and weight growth (WG) were recorded according to previous documented 54 . In vivo metabolism of quercetin in G. molesta and C. pomonella Further experiments involved feeding QA and QNA populations with diets containing 70 μg/g quercetin post-starvation, with tissue and fecal sample collection at 2 h, 5 h, and 8 h intervals. Samples were rinsed with phosphate buffer (pH 7.4) and stored at -80°C for subsequent high-performance liquid chromatography (HPLC) analysis to quantify quercetin levels (Figure 4a). To assess the metabolic impact of P450 gene expression on quercetin biotransformation, larvae from the same populations underwent feeding with quercetin-enriched diets for 2 hours following starvation, with tissue and feces harvested at 2 h and 5 h post-feeding (Figure 4a). Quercetin was extracted and quantified following previously described protocols 28 with slight modifications. Frozen frass and tissue samples were homogenized in a 2:1 (v/w) ratio of methanol at 4°C. Post-centrifugation at 20, 000 × g for 10 min, the pellet was re-extracted with methanol, and the supernatants were combined. This extraction step was repeated to ensure comprehensive recovery. The pooled extracts were then diluted to a predetermined volume with methanol, filtered, and the final supernatant was subjected to HPLC analysis. Briefly, 20 μL of the prepared sample was injected into an Agilent 1260 HPLC system and separated on a reverse-phase XDB-C18 column (AG120, 5 μm, 4.6 × 150 mm) at a flow rate of 1.0 mL/min. The mobile phase comprised water with 0.1% phosphoric acid (70%) and acetonitrile (30%). Quercetin was detected at 372 nm using a Waters 996 photodiode array detector. All measurements were conducted in triplicate. A standard curve was prepared by serially diluting quercetin in methanol to concentrations of 2.5, 5, 10, 20, 40, 80, and 160 μg/mL for quantification. In vitro metabolism of quercetin in G. molesta and C. pomonella The metabolic activity assay was conducted following the protocol outlined by Zhang et al. (2024) 27 . The enzyme incubation mixtures included 20 pmol of recombinant cytochrome P450 isoforms, 5 μL of a 5 mM quercetin substrate solution, 0.5 mg of D-glucose-6-phosphate, 0.5 μL of glucose-6-phosphate dehydrogenase, and 50 μL of NADPH (1 mg/mL in 0.1 M phosphate buffer, pH 7.8), or 50 μL of phosphate buffer as a control lacking NADPH. The total reaction volume was adjusted to 500 μL with 0.1 M phosphate buffer (pH 7.8). Reactions were incubated at 30 o C for 90 minutes with gentle agitation in a water bath. Post-incubation, each reaction mixture was combined with an equal volume of acetone, vortexed, and subjected to centrifugation at 10,000 × g for 10 minutes at room temperature to separate metabolites. The resulting supernatants were analyzed via HPLC. The analyses for quercetin metabolism were repeated three times, and the depletion rate was calculated using the formula: depletion (%) = (peak area without NADPH - peak area with NADPH) / peak area without NADPH × 100%. Declarations Acknowledgments This research was supported by the National Key R&D Program of China (2021YFD1400200), Liaoning Distinguished Youth Scholars Science Foundation (2024JH3/50100027), and the Shenyang Special Project for Cultivating Young Scientific and Technological Innovation Talents U40 (RC230879). We express our gratitude to the Agricultural Invasive Species Control and Surveillance Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, for generously providing the susceptible strain (SS) of C. pomonella . Additionally, we extend our thanks to Professor Yanqiong Guo (College of Plant Protection, Shanxi Agricultural University) for providing the sensitive strains of G. molesta that were utilized in this study. Author contributions B. B: Conceived and designed the experiments, Performed the experiments, Analyzed the data, Wrote the paper. X.-Q.Y.: Conceived and designed the experiments, Contributed materials/analysis tools, Wrote the paper. 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08:41:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9176885/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9176885/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105779509,"identity":"078320b4-3bea-45e4-af37-edaeae03d125","added_by":"auto","created_at":"2026-03-31 04:31:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1133940,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of key P450s adapted to quercetin by \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. molesta\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003ea, Visualizing the quercetin content in apples and pears across selected global production regions. b, Screening process for key P450 proteins of \u003cem\u003eG. molesta\u003c/em\u003eand \u003cem\u003eC. pomonella\u003c/em\u003e. c, Volcano diagram of quercetin-adapted differential and key P450 proteins of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e. All data were visualized using GraphPad Prism 9 software (GraphPad Software, CA). d, Radar chart of upregulated P450 gene (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) counts in different clan of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e during quercetin adaptation, based on transcriptomic data. All data were visualized using Origin 2001 software. e, Evolutionary relationships of P450 proteins and figure was visualized using MEGA11 and iTOL (version 7.2.2).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/fe5a64423ad9681583d2620f.png"},{"id":107868575,"identity":"a2612cde-c6c9-41e5-a576-bd108239d523","added_by":"auto","created_at":"2026-04-27 07:27:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":810893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScreening for key P450s adapted to quercetin by \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. molesta\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003ea, Temporal expression pattern of the \u003cem\u003eP450\u003c/em\u003es in quercetin-non-adapted (QNA) and quercetin-adapted (QA) of \u003cem\u003eG. molesta and C. pomonella\u003c/em\u003e. b, Expression levels of P450 genes in different tissues of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella \u003c/em\u003ein quercetin-non-adapted (QNA) and quercetin-adapted (QA). c, Expression patterns of P450 protein of \u003cem\u003eG. molesta\u003c/em\u003e. HE; Head; MG; Midgut; FB; Fat Body; MT: Malpighian Tubules; CU: Cuticle. d, Expression patterns of P450 protein of \u003cem\u003eC. pomonella\u003c/em\u003e. The gray values of the bands were quantified using ImageJ software. e, Docking results of P450 protein and quercetin. The left column shows the results obtained from molecular docking (Autodock) based on the AlphaFold2 structural model. The right column presents the results directly predicted by AlphaFold3. The yellow region represents the active pocket of the P450 protein; amino acid residues involved in hydrogen bonding are indicated by pink region; green dashed lines represent hydrogen bonds; the blue region represents quercetin. Data are calculated based on the 2\u003csup\u003e−ΔΔCt\u003c/sup\u003e method with normalization. All data were presented as the mean of three replicates ± standard deviation (SD), the differences of data among different groups were marked with lower letter based on one-way analysis of variance (ANOVA) (Tukey’s HSD post hoc test, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and Student’ s \u003cem\u003et\u003c/em\u003e test (****\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; ns, \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05). Figures were visualized using GraphPad Prism 9 software (GraphPad Software, CA).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/c439fb3dee2ed5c02ab8b1e1.png"},{"id":105779505,"identity":"c92103b3-9471-4451-a578-0d6a8f606644","added_by":"auto","created_at":"2026-03-31 04:31:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":479122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssessment of nutritional parameters of two fruit borers following RNAi\u003c/strong\u003e. a, RNAi efficiency of P450 gene in quercetin-non-adapted (QNA) and quercetin-adapted (QA) of \u003cem\u003eG. molesta and C. pomonella\u003c/em\u003e. b-e, Weight growth, efficiency of conversion of digested food, efficiency of conversion of ingested food, and relative growth rate of quercetin-adapted strains (QA) \u003cem\u003eG. molesta\u003c/em\u003e fed on diets supplemented with 70 μg/g quercetin (Q) f-i,\u003cem\u003e \u003c/em\u003eWeight growth, efficiency of conversion of digested food, efficiency of conversion of ingested food, and relative growth rate of quercetin-adapted strains (QA) \u003cem\u003eC. pomonella\u003c/em\u003e fed on diets supplemented with 70 μg/g quercetin (Q). The ECD, ECI, GR and quercetin content ratio of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella \u003c/em\u003ewere transformed using arcsine square root transformation and assessed for normality via the Shapiro-Wilk test, with findings indicating a normal distribution \u003cem\u003eP \u003c/em\u003e\u0026gt; 0.05. Data of RNAi efficiency are calculated based on the 2\u003csup\u003e−ΔΔCt\u003c/sup\u003e method with normalization. All data were presented as the mean of three replicates ± standard deviation (SD), the differences between different groups were analyzed using independent samples Student’s \u003cem\u003et\u003c/em\u003e-tests by SPSS 20 (IBM, Chicago) (****\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Data were plotted using GraphPad Prism 9 software (GraphPad Software, CA) and Origin 2001 software.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/9c3aa5f2b37e748b979bc318.png"},{"id":105779511,"identity":"6d30271e-9758-4e2f-a64f-ac8e74ddbdcf","added_by":"auto","created_at":"2026-03-31 04:31:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":381692,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003emetabolism of quercetin in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. molesta \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003ea, Methods for detecting the role of P450 genes in the metabolism of quercetin in two fruit borers. b, The proportion of quercetin content in various tissues and faeces of quercetin-non-adapted strains (QNA) and quercetin-adapted strains (QA) of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella \u003c/em\u003eat 2h, 5h,and 8h. c, Determination of quercetin content in the quercetin-non-adapted (QNA) and quercetin-adapted (QA) strains of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella \u003c/em\u003eafter the injection of dsRNA. All data were presented as the mean of three replicates ± standard deviation (SD), the differences between different groups were based on Student’ s \u003cem\u003et\u003c/em\u003e test (****\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001; ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; ns, \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05). Figures were visualized using GraphPad Prism 9 software (GraphPad Software, CA), respectively.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/d5de62a5fea9dac1627ee791.png"},{"id":105779506,"identity":"be55cd2f-0215-4763-979e-9da6c55ae66d","added_by":"auto","created_at":"2026-03-31 04:31:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":400111,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic analysis of recombinant P450 proteins of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. molesta\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e against quercetin. \u003c/strong\u003ea-e, Peak area of recombinant P450 proteins against quercetin. All data are presented as mean ± SD of three replicates. Asterisks above represent statistically significant differences analyzed by Student's \u003cem\u003et\u003c/em\u003e test (***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; ns, \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05). f, Depletion of quercetin by P450 proteins. All data are presented as mean ± SD of three replicates. The differences of data among different groups were marked with lower letter based on one-way analysis of variance (ANOVA) (Tukey’s HSD post hoc test, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Figures were visualized using GraphPad Prism 9 software (GraphPad Software, CA), respectively.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/9f87d775dd9c12b1e1c4beb0.png"},{"id":105779507,"identity":"6fab8788-3d43-4397-ae4f-d2e854158eea","added_by":"auto","created_at":"2026-03-31 04:31:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":112340,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorking model diagram of the adaptation to quercetin in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. molesta\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. pomonella. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eG. molesta\u003c/em\u003e primarily adapts to quercetin through the conventional detoxification-related P450 genes from the CYP3 and CYP4 clans, while \u003cem\u003eC. pomonella\u003c/em\u003e recruits two additional P450 genes from mitochondrial clan , reflecting a different adaptation mechanism.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/7bb2b57af5e1267e47c50cc0.png"},{"id":108007115,"identity":"ee570e8a-7c64-41a9-9eae-02e544027660","added_by":"auto","created_at":"2026-04-28 12:58:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3890384,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/c9bbb3b4-6903-4e2d-ae16-6615cff86ae5.pdf"},{"id":105779510,"identity":"d37d4f26-ec29-4993-b8eb-e81908997997","added_by":"auto","created_at":"2026-03-31 04:31:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4742754,"visible":true,"origin":"","legend":"Supplementary materials","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/71b37b36d6f38fe0014ec8a4.docx"},{"id":105779504,"identity":"ae0c1d33-8331-4b75-89cb-2c7e4f92fc55","added_by":"auto","created_at":"2026-03-31 04:31:08","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":161399,"visible":true,"origin":"","legend":"Graphic Abstract","description":"","filename":"GraphicAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9176885/v1/a20a7326539eb568ceef96c0.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Cytochrome P450 drives divergent adaptation to quercetin in invasive and native fruit borers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBiological invasions have become one of the five major global environmental issues of the 21st century\u003csup\u003e1\u003c/sup\u003e. The interspecific relationships between invasive insects and native insects are typically characterized by competition\u003csup\u003e2\u003c/sup\u003e, predation\u003csup\u003e3\u003c/sup\u003e, mutualism\u003csup\u003e4\u003c/sup\u003e, and commensalism\u003csup\u003e5\u003c/sup\u003e. Such diverse and complex interactions ultimately shape population dynamics and drive insect adaptive evolution\u003csup\u003e6\u003c/sup\u003e.\u0026nbsp;In addition, a\u0026nbsp;coevolutionary arms race characterized by iterative cycles of plant defense and herbivore counter-defense is recognized as the primary driver of adaptive evolution in the plant-insect interaction systems\u003csup\u003e7,8\u003c/sup\u003e. Plants have evolved a diverse array of morphological, molecular, and biochemical defenses to deter herbivory\u003csup\u003e8\u003c/sup\u003e. Among biochemical defenses, plant secondary metabolites (PSMs) represent the most diverse and potent chemical defense mechanism\u003csup\u003e9\u003c/sup\u003e. PSMs are typically stored as inactive, non-toxic precursors and enzymatically activated upon herbivory\u003csup\u003e10\u003c/sup\u003e, which subsequently influence insect physiological processes and nutrient utilization\u003csup\u003e11\u003c/sup\u003e. For example,\u0026nbsp;quercetin has been shown to affect the survival rate of \u003cem\u003eAcyrthosiphon pisum\u003c/em\u003e\u003csup\u003e12\u003c/sup\u003e, while salicin and rutin can impact the body weight, relative growth, food conversion efficiency, and digestion efficiency of \u003cem\u003eLymantria dispar\u003c/em\u003e larvae\u003csup\u003e13\u003c/sup\u003e. To utilize such plants as hosts, insects generally must eveolve highly specific adaptative strategies, including behavioral, morphological, and biochemical mechanisms, to overcome the toxic effects of PSMs\u003csup\u003e14\u003c/sup\u003e. For instance, some host-highly adapted insects, such as the whitefly (\u003cem\u003eBemisia tabaci\u003c/em\u003e) and the brown planthopper (\u003cem\u003eNilaparvata lugens\u003c/em\u003e), manipulate host plant tomato volatile emissions to transmit \u0026apos;defensive signals\u0026apos; that suppress to neighboring plants\u0026apos; defenses, rendering them more vulnerable to their infestation\u003csup\u003e15\u003c/sup\u003e. \u003cem\u003eHelicoverpa zea\u003c/em\u003e elevates glucose oxidase levels in its saliva to inhibit plant immune responses and reduces nicotine accomulation in tobacco plants\u003csup\u003e16\u003c/sup\u003e.\u0026nbsp;\u003cem\u003eZygaena filipendulae\u0026nbsp;\u003c/em\u003eemploys detoxification enzyme systems to neutralize cyanide toxicity\u003csup\u003e17\u003c/sup\u003e. Furthermore, variations in PSM tolerancebetween invasive and native herbivorous insects may lead to differences in detoxification strategies\u003csup\u003e18\u003c/sup\u003e. For example,\u0026nbsp;\u003cem\u003eSpodoptera frugiperda\u0026nbsp;\u003c/em\u003eutilizes P450 monooxygenases to detoxify xanthotoxin\u003csup\u003e19\u003c/sup\u003e, whereas \u003cem\u003eS. litura\u003c/em\u003e predominantly relies on UDP-glucuronosyltransferases (UGT)\u003csup\u003e20\u003c/sup\u003e. Additionally, in \u003cem\u003eB. tabaci\u003c/em\u003e, the B biotype exhibits elevated esterase activity to counter host plant incompatibility, contrasting with native populations\u003csup\u003e21\u003c/sup\u003e. Consequently, invasive and native insect species serve as an ideal comparative system for uncovering the mechanisms underlying rapid evolutionary responses to environmental pressures, resource competition, and survival challenges, providing critical insights into the formation of adaptive strategies.\u003c/p\u003e\n\u003cp\u003eThe invasive species \u003cem\u003eCydia pomonella\u003c/em\u003e (Linnaeus) and the native species \u003cem\u003eGrapholita molesta\u003c/em\u003e (Busck) are typically regarded as competitors due to their shared reliance on common host plants such as pear and apple\u003csup\u003e22\u003c/sup\u003e. \u003cem\u003eC. pomonella\u003c/em\u003e originates from Central Asia Minor and has expanded globally since 1900, now appearing in approximately 70 countries\u003csup\u003e23\u003c/sup\u003e. Genetic studies suggest that northeastern Chinese populations of \u003cem\u003eC. pomonella\u003c/em\u003e may have originated from Russia\u003csup\u003e24\u003c/sup\u003e, where the quercetin contents in primary host fruits are consistently below 30 \u0026mu;g/g \u003csup\u003e25,26\u003c/sup\u003e, compared to the 74.79 \u0026mu;g/g detected in Nanguo pears from Northeast China\u003csup\u003e27\u003c/sup\u003e. Due to the lack of pre-adaptive traits for tolerating high quercetin concentrations, \u003cem\u003eC. pomonella\u003c/em\u003e requires one additional generation compared to \u003cem\u003eG. molesta\u003c/em\u003e to adapt to quercetin\u003csup\u003e28\u003c/sup\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eIts detoxification employs a biphasic process: an initial phase dominated by ABC transporter activity for short-term efflux, followed by a longer-term reliance on P450-mediated metabolism. In contrast, \u003cem\u003eG. molesta\u003c/em\u003e primarily\u003cem\u003e\u0026nbsp;\u003c/em\u003eemploys\u003cem\u003e\u0026nbsp;\u003c/em\u003ea synergistic enzymatic detoxification system involving multiple enzymes\u003csup\u003e28\u003c/sup\u003e. However, the precise molecular mechanisms underlying the adaptation of \u003cem\u003eC. pomonella\u003c/em\u003e and \u003cem\u003eG. molesta\u003c/em\u003e to quercetin remain poorly elucidated.\u003c/p\u003e\n\u003cp\u003eTo address this knowledge gap, we conducted integrated transcriptomic and proteomic analyses on quercetin-adapted populations to characterize their adaptive strategies and identify differentially expressed genes. Subsequent RT-qPCR assays were performed to examine the spatiol and temporal expression patterns of candidate genes. AlphaFold-based molecular docking confirmed strong binding interactions between these P450 enzymes and quercetin. Combining RNA interference (RNAi) technology with HPLC analysis, we tracked the dynamic levels of ingested quercetin within the insects. \u003cem\u003eIn vitro\u003c/em\u003e functional assays using recombinant enzymes were performed to validate the role of specific P450 enzymes in quercetin metabolism. These cutting-edge biological techniques were employed to elucidate the molecular and biochemical bases of adaptive divergence between these tow fruit borers, providing deeper insights into the adaptive evolutionary divergence between invasive and native insect species and contributes to a better understanding of the global invasion of \u003cem\u003eC. pomonella\u003c/em\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInvestigation of quercetin contents in the main cultivated host plants of the countries along the invasion route of \u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThrough literature research, we analyzed the quercetin content in major host plant varieties of different countries and regions invaded by \u003cem\u003eC. pomonella\u003c/em\u003e. The results indicate that in Canada, the United States, Chile, and southern Africa, the primary host pear variety is Bartlett, with a quercetin content of 55 \u0026mu;g/g\u003csup\u003e29\u003c/sup\u003e. In European regions, such as France, Germany, and Italy, the main affected host varieties are Cox\u0026apos;s Orange Pippin Apple (2.3 \u0026micro;g/g), Elstar Apple (3.34 \u0026micro;g/g), and Gold Delicious Apple (1.6 \u0026micro;g/g), respectively\u003csup\u003e26\u003c/sup\u003e. In Argentina, India, and Australia, the principal hosts utilized by \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eare Gala Apple (1.2 \u0026micro;g/g)\u003csup\u003e30\u003c/sup\u003e, Chinese Pear (15.3 \u0026micro;g/g)\u003csup\u003e31\u003c/sup\u003e, and Granny Smith Apple (1.6 \u0026micro;g/g)\u003csup\u003e26\u003c/sup\u003e. Key hosts in Russia include Boskoop (4.5 \u0026micro;g/g) and Gold Delicious Apples (1.6 \u0026micro;g/g)\u003csup\u003e26\u003c/sup\u003e, while in Tajikistan, it is the Kosimsarkori Apple (11.9 \u0026micro;g/g)\u003csup\u003e25\u003c/sup\u003e. For China, cultivated varieties such as the Nanguo pear (70.8 \u0026micro;g/g), Xuehua Pear (31.2 \u0026micro;g/g), and Huangguan Pear (12.7 \u0026micro;g/g) were noted\u003csup\u003e27,31\u003c/sup\u003e, with the Nanguo Pear from Liaoning exhibiting the highest quercetin levels (Figure 1a). These findings suggest that \u003cem\u003eC. pomonella\u003c/em\u003e may not have encountered host-defensive selection pressure involving quercetin concentrations as high as 70.0 \u0026micro;g/g prior to its invasion into northeastern China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntegrated transcriptomic and proteomic analyses identified P450 genes positively correlated with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;adaptation processes to quercetin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur previous transcriptomic analysis revealed that adaptation processes to quercetin\u003cem\u003e\u0026nbsp;\u003c/em\u003ethe oxidation-reduction process within Gene Ontology (GO) annotation exhibited the highest gene ratio in \u003cem\u003eG. molesta\u003c/em\u003e, while ranking second in\u0026nbsp;\u003cem\u003eC. pomonella\u003c/em\u003e\u003csup\u003e28\u003c/sup\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eIn this study, we found that during the adaptation process from G1 to G3 in \u003cem\u003eG. molesta,\u0026nbsp;\u003c/em\u003ea significant upregulation of P450 genes was observed.\u003cem\u003e\u0026nbsp;\u003c/em\u003eSpecially, 3 P450 genes (one from the CYP3 clan and two from the CYP4 clan) were upregulated in G1, 9 genes (one from the CYP2 clan, three from the CYP3 clan, and five from the CYP4 clan) in G2, and 7 genes (four from the CYP3 clan and three from the CYP4 clan) in G3, all in comparison to the control group (G0). Similarly to \u003cem\u003eG. molesta\u003c/em\u003e, \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eexhibited upregulated P450 gene expression across generations G1 to G3. Specifically, G1 showed 11 P450 genes (1 from the CYP2 clan, 7 from the CYP3 clan, and 3 from the CYP4 clan), G2 had 10 P450 genes (1 from the CYP2 clan and 9 from the CYP3 clan), and G3 possessed 9 P450 genes (5 from the CYP3 clan and 4 from the CYP4 clan), all in comparison to the control group (G0). Notably, in the quercetin-adapted (GA) generation, G4 displayed 11 upregulated P450 genes, comprising 1 from the CYP2 clan, 7 from the CYP3 clan, 2 from the CYP4 clan, and an additional gene from the mitochondrial clan\u0026nbsp;(Figure 1d; Table S4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProteomic profiling of\u0026nbsp;\u003cem\u003eG. molesta\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u0026nbsp;\u003cem\u003eC. pomonella\u003c/em\u003e demonstrated that differentially expressed proteins (DEPs) were enriched across 12 and 18 GO pathways, respectively (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). The oxidation-reduction process was the most significantly enriched GO term in \u003cem\u003eC. pomonella\u003c/em\u003e, whereas it ranked seventh in \u003cem\u003eG. molesta\u003c/em\u003e (Figure S1). KEGG analysis indicated significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) enrichment of drug metabolism - cytochrome P450 (map00982) and xenobiotics metabolism via cytochrome P450 (map00980) in both species\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Figure S2)\u003cem\u003e.\u003c/em\u003e To elucidate the molecular mechanisms underlying quercetin adaptation in these fruit borers, integrated transcriptomic and proteomic data were analyzed.\u0026nbsp;\u003cem\u003eG. molesta\u003c/em\u003e yielded 8,375 transcripts and 7,385 proteins, while\u0026nbsp;\u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eexhibited\u0026nbsp;8,088 transcripts and 7,909 proteins. Among these, 46 genes were significantly differentially expressed and shared between both species\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Figure S3 a; b). In addition, GO pathways co-enriched in the transcriptome and proteome of\u0026nbsp;\u003cem\u003eG. molesta\u003c/em\u003e included aminoglycan metabolic process (GO: 0006022) and oxidation-reduction process (GO: 0055114), whereas\u0026nbsp;\u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003eshowed enrichment in\u0026nbsp;oxidation-reduction process (GO: 0055114) and proteolysis (GO: 0006508) (Figure 1b). These findings suggest that oxidation-reduction process serve as a conserved adaptive strategy to quercetinacross both species.\u003c/p\u003e\n\u003cp\u003eFurther validation employed strict selection criteria (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, |FC| \u0026gt; 1) to identify genes with consistent upregulation at transcript and protein levels, reflecting functional gene expression (Figure 1b). Two P450 proteins in\u0026nbsp;\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003ewere significantly upregulated by 2.19 and 1.6-fold, respectively, while three in\u0026nbsp;\u003cem\u003eC. pomonella\u003c/em\u003e were upregulated by 22.53, 1.635, and 1.483-fold, respectively (Figure 1c). Proteomic data confirmed the reproducibility of these five proteins, indicating reliable quantification (Figure S4). All five P450 genes were annotated and named by David Nelson of the P450 Nomenclature Committee.\u003c/p\u003e\n\u003cp\u003ePhylogenetic analysis revealed that CYP6AB364 and CYP341Q10 from G. molesta belong to the CYP3 and CYP4 clans, respectively. In \u003cem\u003eC. pomonella\u003c/em\u003e, CYP337B19 is classified within the CYP3 clan, while CYP333B119 and CYP333B118 fall under the mitochondrial clan (Figure 1e). Structural conservation among P450 proteins was observed, with all possessing typical P450 structural domains (Figure S5a). Chromosomal mapping indicated CYP6AB364 and CYP341Q10 are located on chromosomes 3 and 7, respectively, while CYP337B19 resides on chromosome 4 and CYP333B118 on chromosome 18 in\u0026nbsp;\u003cem\u003eC. pomonella\u003c/em\u003e (Figure S5b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTranscript abundance of quercetin adaptation-related P450 genes in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the potential role of these P450 genes, their expression patterns in two species were analyzed across various developmental stages and tissues. Results indicated that\u0026nbsp;\u003cem\u003eCYP341Q10\u003c/em\u003e and \u003cem\u003eCYP6AB364\u003c/em\u003e in both QNA and QA \u003cem\u003eG. molesta\u003c/em\u003e populations exhibited peak expression during the voracious feeding stage\u0026mdash;the fourth instar larvae stage (Figure 2a). Similarly,\u0026nbsp;\u003cem\u003eCYP333B119\u003c/em\u003e, \u003cem\u003eCYP333B118\u003c/em\u003e, and \u003cem\u003eCYP337B19\u003c/em\u003e in QNA and QA \u003cem\u003eC. pomonella\u003c/em\u003e population also showed\u0026nbsp;highest expression levels during the same developmental stage (Figure 2a). Furthermore, these genes were expressed across all tissues of fourth instar larvae in both species. Notably,\u0026nbsp;\u003cem\u003eCYP341Q10\u003c/em\u003e and \u003cem\u003eCYP6AB364\u003c/em\u003e in the midgut of QNA \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eshowed\u003cem\u003e\u0026nbsp;\u003c/em\u003esignificantly higher expression relative to other tissues. Post-adaptation to quercetin, the expression of \u003cem\u003eCYP341Q10\u003c/em\u003e and\u003cem\u003e\u0026nbsp;CYP6AB364\u003c/em\u003e was markedly upregulated in the midgut, Malpighian tubules, and cuticle of \u003cem\u003eG. molesta\u003c/em\u003e. Similarly, in \u003cem\u003eC. pomonella\u003c/em\u003e, \u003cem\u003eCYP333B119\u003c/em\u003e, \u003cem\u003eCYP333B118\u003c/em\u003e, and \u003cem\u003eCYP337B19\u003c/em\u003e in the midgut displayed higher expression compared to other tissues. Compared to QNA, the expression of \u003cem\u003eCYP333B119\u003c/em\u003e, \u003cem\u003eCYP333B118\u003c/em\u003e, and \u003cem\u003eCYP337B19\u003c/em\u003e was significantly increased in the midgut and fat body following quercetin adaptation (Figure 2b). These findings suggest that \u003cem\u003eCYP341Q10\u003c/em\u003e and \u003cem\u003eCYP6AB364\u003c/em\u003e in \u003cem\u003eG. molesta\u003c/em\u003e, and \u003cem\u003eCYP333B119\u003c/em\u003e, \u003cem\u003eCYP333B118\u003c/em\u003e, and \u003cem\u003eCYP337B19\u003c/em\u003e in \u003cem\u003eC. pomonella\u003c/em\u003e, may play crucial roles in the detoxification of quercetin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein levels analysis of quercetin adaptation-related P450 genes in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate protein expression levels observed in the proteome, Western blot assays were performed for these P450 members. The P450 proteins exhibited molecular weights ranging from 46 to 60 kDa. Using \u003cem\u003eDrosophila melanogaster\u003c/em\u003e \u003cem\u003e\u0026beta;\u003c/em\u003e-actin as an internal control, results showed that CYP6AB364 and CYP341Q10 were upregulated by 1.85- and 1.81-fold, respectively, in QA \u003cem\u003eG. molesta\u003c/em\u003e compared to QNA (Figure 2c). Likewise, CYP337B19, CYP333B119, and CYP333B118 in \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003ewere elevated by 1.31-, 1.83-, and 7.15-fold, respectively, in the QA strains versus QNA (Figure 2d). These data indicate that the protein expression patterns are consistent with the proteomic findings,\u0026nbsp;imply potential roles of these P450 in the detoxification of quercetin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI-based docking reveals strong interaction between P450 and quercetin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing AlphaFold2, we predicted the 3D structures of CYP6AB364, CYP341Q10, CYP337B19, CYP333B118, and CYP333B119. Restricted molecular docking, based on predicted ligand-binding pockets, demonstrated that each P450 enzyme formed hydrogen bonds with quercetin: in CYP6AB364, ARG-204, GLU-212, and ALA-233; in CYP341Q10, TRP-125, LYS-101, and ILE-118; in CYP337B19, ASP-301, LEU-203, and ARG-98; in CYP333B118, THR-333; and in CYP333B119, ASN-383, ARG-114, THR-330, and THR-331. Binding energies ranged from -8.1 to -9.0 kcal/mol, indicating strong ligand affinity. Further molecular docking with AlphaFold3 yielded that the predicted complex structures of CYP341Q10, CYP337B19, and CYP333B119 with quercetin had high confidence scores (ipTM scores of 0.83, 0.88, and 0.82, respectively), whereas complexes with CYP6AB364 and CYP333B118 exhibited moderate confidence (ipTM scores of 0.74 and 0.76)\u0026nbsp;(Figure 2e). These findings indicate a strong interaction between selected P450 proteins and quercetin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnockdown P450 genes reduce quercetin adaptation of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMicroinjection of dsRNA effectively silenced gene expression\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the microinjection of ds\u003cem\u003eCYP6AB364\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003eds\u003cem\u003eCYP341Q10\u003c/em\u003e, the QNA and QA populations of \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eexhibited RNAi efficiencies at 6 and 12 h, with knockdown efficiencies exceeding 40%. (Figure 3a). In \u003cem\u003eC. pomonella\u003c/em\u003e, after administration of ds\u003cem\u003eCYP337B19\u003c/em\u003e, ds\u003cem\u003eCYP333B118\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003eand ds\u003cem\u003eCYP333B119\u003c/em\u003e, the QNA and QA populations exhibited RNAi efficiencies from 6 to 24 h, exceeding 30% (Figure 3a). These findings demonstrate robust gene silencing efficacy within 48 h in both populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eQuercetin reduces nutritional parameters in\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta and\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;after knockdown of P450 genes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing RNAi via microinjection of ds\u003cem\u003eCYP6AB364\u0026nbsp;\u003c/em\u003eand ds\u003cem\u003eCYP341Q10\u003c/em\u003e in to \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eQNA larvae fed on quercetin-free diet, no significant\u0026nbsp;differences were observed in larval growth metrics, including weight gain, ECI, ECD, and GR, compared to ds\u003cem\u003eGFP\u0026nbsp;\u003c/em\u003econtrol between 12 to 48 h. Conversely, ds\u003cem\u003eCYP6AB364\u003c/em\u003e injection resulted in notable reduction in larval weight gain, ECD, ECI, and GR at 6 h post-injection. Similarly, ds\u003cem\u003eCYP341Q10\u003c/em\u003e injections caused significant decreases in ECD, ECI, and GR at 48 h (Figure S6). In \u003cem\u003eC. pomonella\u003c/em\u003e, injections of ds\u003cem\u003eCYP337B19\u003c/em\u003e and ds\u003cem\u003eCYP333B119\u003c/em\u003e, into QNA and QA larvae fed a quercetin-free diet did not elicit significant differences in weight growth, ECI, ECD, and GR, from 6 to 48 h. However, ds\u003cem\u003eCYP333B118\u003c/em\u003e injections led to significant reductions in ECI at 6 and 24 h in QA larvae (Figure S7). These findings suggest that P450 gene knockdown via RNAi exerts minimal impact on larval nutritional indices in both QA and QNA populations.\u003c/p\u003e\n\u003cp\u003eAdditionally, ds\u003cem\u003eCYP6AB364\u0026nbsp;\u003c/em\u003eand ds\u003cem\u003eCYP341Q10\u003c/em\u003e injections in \u003cem\u003eG. molesta\u003c/em\u003e QA larvae fed a quercetin diet resulted in significant declines in larval weight gain, ECD, and ECI from 6 to 48 h, with GR significantly reduced at 24 and 48 h (Figure 3b-e). In \u003cem\u003eC. pomonella\u003c/em\u003e, injections of \u003cem\u003edsCYP337B19\u003c/em\u003e, \u003cem\u003edsCYP333B11\u003c/em\u003e9, and \u003cem\u003edsCYP333B118\u003c/em\u003e into QA larvae fed quercetin diets caused substantial decreases in larval growth parameters, including weight gain, ECD, ECI, and GR, between 6 to 24 h (Figure 3f-i). These results indicate the critical role of P450 genes in facilitating adaptive tolerance to dietary quercetin in both lepidopteran species .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnockdown P450 genes reduce metabolism of quercetin in \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInjection of dsRNA effectively silenced gene expression in\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003etissues\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNAi efficacy in \u003cem\u003eG. molesta\u003c/em\u003e populations was evaluated following injection with dsCYP6AB364 and dsCYP341Q10. In the QNA population, dsCYP6AB364 achieved greater than 60% gene knockdown in the midgut, fat body, and Malpighian tubules at both 2h and 5 h post-injection, whereas dsCYP341Q10 elicited over 60% suppression in all tissues except Malpighian tubules at 5 h (40.1%). Conversely, in the QA population, dsCYP6AB364 resulted in more than 70% silencing efficiency in the midgut and Malpighian tubules and over 40% in the fat body at both time points, with dsCYP341Q10 showing over 50% efficacy across tissues, except in the midgut at 2 h (41.7%) (Figure S8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn \u003cem\u003eC. pomonella\u003c/em\u003e, the injections of dsCYP337B19 yielded over 80% RNAi efficiency in the midgut at 2h and 5 h, with more than 40% in the fat body and Malpighian tubules. Following dsCYP333B119 injection, the fat body demonstrated over 80% efficacy at both intervals, while the midgut and Malpighian tubules exhibited over 40%. Injection with dsCYP333B118 resulted in all three tissues achieving over 40% gene silencing at both time points. In the QA population, dsCYP337B19 achieved silencing efficiencies of 73.9% in the midgut, 60.7% in the fat body, and 53.9% in the Malpighian tubules at 2 h; these increased to 84.1%, 69.3%, and 47.1%, respectively, at 5 h. Post-injection with dsCYP333B119 or dsCYP333B118, all tissues maintained silencing efficiencies exceeding 50% at both time points (Figure S9). These findings demonstrate that all tissues exhibit robust gene interference within a 5-h timeframe.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKnockdown\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eP450 genes lead to quercetin accumulation\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003ein tissues of G. molesta and\u0026nbsp;C. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn both QNA and QA populations of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e, quercetin levels in tissues showed a gradual decline over time, while excretion in feces gradually increased. Furthermore, at all time points, tissue quercetin concentrations in the QNA populations consistently exceeded those in the QA populations (Figure 4b). This suggests that quercetin-adapted populations of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e possess enhanced metabolic capacity for quercetin detoxification.\u0026nbsp;In addition, both QNA and QA populations of\u0026nbsp;\u003cem\u003eG. molesta\u003c/em\u003e completely excreted quercetin within 8 h. Consequently, 2-h and 5-h time points were selected for subsequent analytical assays.\u003c/p\u003e\n\u003cp\u003eFollowing knockdown of P450 genes in\u003cem\u003e\u0026nbsp;G. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e, quercetin ingestion levels did not significantly differ from those observed in the ds\u003cem\u003eGFP\u003c/em\u003e control group in either strain (Figure S10). In QNA \u003cem\u003eG. molesta\u003c/em\u003e, knockdown of \u003cem\u003eCYP341Q10\u003c/em\u003e and ds\u003cem\u003eCYP6AB364\u0026nbsp;\u003c/em\u003eresulted in increased quercetin accumulation in the midgut at 2 h and 5 h, compared to ds\u003cem\u003eGFP\u003c/em\u003e. In QA population, midgut quercetin levels were significantly elevated at 2 h, with further increases observed in the midgut, fat body, and feces at 5 h (Figure 4c). In \u003cem\u003eC. pomonella\u003c/em\u003e, knockdown of \u003cem\u003eCYP337B19\u003c/em\u003e did not significantly change tissue or fecal quercetin levels at either 2 or 5 h in both strains. Knockdown of \u003cem\u003eCYP333B118\u003c/em\u003e led to increased quercetin in the midgut at 2 h, and in the midgut, fat body, and feces at 5 h in QNA and QA population. After \u003cem\u003eCYP333B119\u003c/em\u003e suppression, both strains exhibited increased midgut quercetin at 2 h and significant rises in midgut and fecal quercetin at 5 h (Figure 4c). These findings implicate \u003cem\u003eCYP341Q10\u003c/em\u003e and \u003cem\u003eCYP6AB364\u0026nbsp;\u003c/em\u003ein \u003cem\u003eG. molesta\u003c/em\u003e, and \u003cem\u003eCYP333B119\u003c/em\u003e and \u003cem\u003eCYP333B118\u0026nbsp;\u003c/em\u003ein \u003cem\u003eC. pomonella\u003c/em\u003e, as key enzymes involved in quercetin metabolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of the \u003cem\u003ein vitro\u0026nbsp;\u003c/em\u003emetabolism of quercetin\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo verify whether these P450 could directly metabolic quercetin, the recombinant proteins were expressed. Recombinant bacmid containing successful transposition carried the target gene fragments, with PCR product lengths of 3824 bp for \u003cem\u003eCYP341Q10\u003c/em\u003e, 3800 bp for \u003cem\u003eCYP6AB364\u003c/em\u003e, 3790 bp for \u003cem\u003eCYP337B19\u003c/em\u003e, 3827 bp for \u003cem\u003eCYP333B119\u003c/em\u003e, and 3839 bp for \u003cem\u003eCYP333B118\u003c/em\u003e, consistent with the expected insert sizes (approximately 2300 bp plus fragment length). These results confirm successful integration of the target genes into the baculovirus expression system\u0026apos;s bacmid vectors. The supernatant from infected cell cultures was harvested on day seven, corresponding to peak viral titers characterized by extensive cell lysis and virus release (Figure S11).\u003c/p\u003e\n\u003cp\u003eComparison of metabolize capability with and without NADPH showed that CYP6AB364 and CYP341Q10 proteins from \u003cem\u003eG. molesta\u003c/em\u003e exhibited significant reductions in peak chromatographic areas upon NADPH addition (Figure 5a-b). Similarly, in \u003cem\u003eC. pomonella\u003c/em\u003e, CYP333B119 and CYP333B118 showed significant decreases in peak areas with NADPH, while CYP337B19 displayed no significant change (Figure 5c-e). Quercetin depletion rates by these CYP enzymes were 18.16% (CYP6AB364), 17.99% (CYP341Q10), 13.93% (CYP333B118), and 8.99% (CYP333B119), indicating that \u003cem\u003eG. molesta\u003c/em\u003e exhibits higher metabolic efficiency in quercetin detoxification compared to \u003cem\u003eC. pomonella\u003c/em\u003e (Figure 5f).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe differential adaptation of invasive versus native species to PSMs arise from their divergent tolerance levels\u003csup\u003e32\u003c/sup\u003e. Previous studies have demonstrated that exposure to quercetin inhibits the fecundity and population growth of\u003cem\u003e\u0026nbsp;C. pomonella\u003c/em\u003e, whereas\u0026nbsp;\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eexhibits a stimulatory response\u003csup\u003e22\u003c/sup\u003e. These findings suggest that native species have evolved mechanisms to tolerate quercetin, while invasive species lack pre-adaptation to this compound\u003csup\u003e28\u003c/sup\u003e. In this study, we elucidate the\u0026nbsp;evolutionary mechanisms of adaptation to quercetin in the global invasive fruit borer, \u003cem\u003eC. pomonella\u003c/em\u003e, and its sympatric native congener, \u003cem\u003eG. molesta\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn insects, P450 play critical roles in the metabolism of xenobiotics, endogenous compound biosynthesis and degradation, and the synthesis and breakdown of plant secondary metabolites\u003csup\u003e33\u003c/sup\u003e. Insect P450 genes are categorized into six clans: CYP2, CYP3, CYP4, CYP16, CYP20, and mitochondrial (mito)\u003csup\u003e34\u003c/sup\u003e. The CYP3 and CYP4 clans, predominant in insects, are well-documented for their roles in chemical defense mechanisms\u003csup\u003e35,36\u003c/sup\u003e. Substantial evidence indicates that CYP3 clan P450 genes, predominantly CYP6 and CYP9 family members, primarily facilitate xenobiotic detoxification through direct substrate metabolism\u003csup\u003e37\u003c/sup\u003e. For example, \u003cem\u003eHelicoverpa zea\u003c/em\u003e CYP6B8 catalyzes six PSMs, including xanthotoxin, quercetin, flavone, chlorogenic acid, indole-3-carbinol, and rutin, and metabolizes three insecticides\u003csup\u003e38\u003c/sup\u003e. Members of the CYP9A subfamily can detoxify imperatorin and xanthotoxin, facilitating the development of the broad host ranges of \u003cem\u003eS. exigua\u0026nbsp;\u003c/em\u003eand \u003cem\u003eS. frugiperda\u003c/em\u003e over long evolutionary timeframes\u003csup\u003e39\u003c/sup\u003e. Additionally, mitochondrial P450 genes within insects are characterized by their rapid evolution driven by gene duplication and diversification of taxon-specific paralogs\u003csup\u003e34\u003c/sup\u003e. These maternally inherited enzymes influence adaptive evolution\u003csup\u003e40\u003c/sup\u003e. For instance, \u003cem\u003eCYP12A1\u003c/em\u003e in \u003cem\u003eMusca domestica\u003c/em\u003e is induced by phenobarbital and constitutively overexpressed in insecticide-resistant strains\u003csup\u003e41\u003c/sup\u003e. Similarly, \u003cem\u003eCYP337B3v2\u003c/em\u003e is prevalent in pyrethroid-resistant \u003cem\u003eHelicoverpa. armigera\u0026nbsp;\u003c/em\u003epopulations but scarce in susceptible populations\u003csup\u003e42\u003c/sup\u003e. Overexpression of \u003cem\u003eCYP12A4\u003c/em\u003e in the midgut and Malpighian tubules confers resistance to lufenuron in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e\u003csup\u003e43\u003c/sup\u003e. In this study, through comparative transcriptomic analysis across generations during the adaptation of two fruit borers to quercetin\u003csup\u003e28\u003c/sup\u003e, we observed that in \u003cem\u003eG. molesta\u003c/em\u003e, both during the adaptation process and in fully adapted populations, transcript levels of several P450 members from the traditionally detoxification-related CYP3 and CYP4 clans were significantly upregulated. Conversely, \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003ealso activated a cohort of CYP3 and CYP4 clan P450s during adaptation, but in its fully adapted population, two additional P450s from the mitochondrial clan, \u003cem\u003eCYP333B118\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;CYP333B119\u003c/em\u003e, were recruited. This suggest that the canonical detoxification-associated P450 genes belonging CYP3 and CYP4 clans, are insufficient to ensure\u003cem\u003e\u0026nbsp;C. pomonella\u003c/em\u003e\u0026apos;s complete mitigation of quercetin pressures in newly invaded habitats. Consequently, there is a requirement for the temporary recruitment of mitochondrial P450 genes. This finding corroborates the viewpoint posited by Heidel-Fischer and Vogel (2015) that gene recruitment and neofunctionalization represent a pivotal molecular strategy by which insects evolve adaptations to PSMs\u003csup\u003e44\u003c/sup\u003e. For instance, neofunctionalization of duplicated \u003cem\u003eCYP337B28\u003c/em\u003e and \u003cem\u003eCYP337B29\u003c/em\u003e led to the evolution of pyrethroid resistance in African lineage, \u003cem\u003eH. a. armigera\u003c/em\u003e\u003csup\u003e45\u003c/sup\u003e. Similarly, duplication and neofunctionalization of \u003cem\u003eCYP6ER1\u003c/em\u003e led to the evolution of imidacloprid resistance in \u003cem\u003eNilaparvata lugens\u003c/em\u003e\u003csup\u003e46\u003c/sup\u003e. Nonetheless, the detoxification capacity of these \u0026quot;temporarily recruited\u0026quot; mitochondrial P450 enzymes appears comparatively weaker than that of CYP3 and CYP4 clan enzymes, consistent with previous reports indicating lower catalytic activity of mitochondrial CYP339A1 toward esfenvalerate relative to CYP6 and CYP9 families in \u003cem\u003eH. armigera\u003c/em\u003e\u003csup\u003e47,48\u003c/sup\u003e. These findings suggest that invasive species like \u003cem\u003eC. pomonella\u003c/em\u003e may induce mitochondrial P450s to detoxify quercetin during host adaptation, while Clan 3 members, especially CYP6 and CYP9 families\u003csup\u003e35,36\u003c/sup\u003e, maintain broad conversation and detoxification functions against other PSMs and insecticides, potentially facilitating rapid invasion success (Figure 6).\u003c/p\u003e\n\u003cp\u003eDetoxification is a complex, multisystem biochemical process involving various enzymatic pathways and regulatory factors\u003csup\u003e49\u003c/sup\u003e. For instance, \u003cem\u003eZygaena filipendulae\u0026nbsp;\u003c/em\u003eemploys two P450 and a UGT to mitigate cyanide toxicity\u003csup\u003e17\u003c/sup\u003e. In this study, we observed that, regardless of \u003cem\u003eG. molesta\u003c/em\u003e or \u003cem\u003eC. pomonella\u003c/em\u003e, the QA population exhibits lower levels of quercetin accumulation across tissues compared to the QNA population, indicating an enhanced metabolic adaptation to quercetin. Moreover, functional assays involving RNAi targeting key P450 genes identified through proteomic and transcriptomic correlation analyses revealed that silencing \u003cem\u003eCYP6AB364\u003c/em\u003e and \u003cem\u003eCYP341Q10\u003c/em\u003e in \u003cem\u003eG. molesta\u003c/em\u003eresulted in greater increases in midgut quercetin accumulation than the gene suppression efficiencies would predict. Conversely, in the QA population of \u003cem\u003eC. pomonella\u003c/em\u003e, gene knockdowns of \u003cem\u003eCYP333B118\u003c/em\u003e and \u003cem\u003eCYP333B119\u003c/em\u003e at efficiencies of approximately 40% and 63%, respectively, corresponded to quercetin accumulation proportions of approximately 82% and 40%, showing no direct positive correlation between gene silencing efficacy and metabolite accumulation. These findings imply that the current screening may not encompass all relevant P450 isoforms or other biotransformation enzymes involved in \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003edetoxification. Besides, this disparity could stem from the fact that quercetin detoxification in \u003cem\u003eC. pomonella\u003c/em\u003e involves multiple parallel pathways, whereas our focus was limited to a single pathway. Future research should aim at an integrated characterization of differentially expressed detoxification enzymes, such as ABC and GST, which have been implicated in quercetin metabolism\u003csup\u003e28\u003c/sup\u003e. Understanding the substrate specificities and their roles within PSM metabolic networks will facilitate a more systematic understanding of the mechanisms underpinning adaptation in invasive versus native species to their host plants. Moreover, this study initially explored the adaptive mechanisms of both fruit borers under quercetin selection pressure. Future investigations should examine the influence of additional PSMs on these fruit borers host adaptation and assess whether PSMs adaptation influences their susceptibility to insecticides.\u0026nbsp;Additionally, combined analysis of binding energy derived from traditional molecular docking and structural simulations using AlphaFold3 reveals that the P450 proteins of \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e possess strong binding affinity for quercetin. These insights serve as a critical foundation for the rational design of P450-specific inhibitors, facilitating the advancement of targeted pest management strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eInsect species and populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e strains were maintained in the laboratory conditions without exposure to quercetin for over 50 generations. Larval rearing was performed on an artificial diet within a MLR-352H-PC growth chamber (Panasonic, Ehime Prefecture, Japan), maintained at 26 \u0026plusmn; 1 \u003csup\u003eo\u003c/sup\u003eC, 60 \u0026plusmn; 5% relative humidity, with a 16:8 h (L:D) photoperiod. Adults were supplied with a 10% honey solution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA quercetin-adapted population (QA) of \u003cem\u003eC. pomonella\u003c/em\u003e is defined as a population continuously exposed to 70 \u0026mu;g/g quercetin across four generations, originating from a quercetin-non-adapted population (QNA). Similarly, a quercetin-adapted\u0026nbsp;\u003cem\u003eG. molesta\u003c/em\u003e population (QA) is defined as one subjected to the same quercetin concentraation across three generations\u003csup\u003e28\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analysis of transcriptomic and proteomic data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptome and proteome analyses were conducted on fourth instar larvae of both species, comparing QNA and QA groups. Transcriptome datasets have been published previously\u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;Proteomic samples comprised 60 individuals per \u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand \u003cem\u003eC. pomonella\u0026nbsp;\u003c/em\u003egroup, each with three biological replicates, conducted at Novogene Company (Tianjin, China).\u0026nbsp;Quantitative proteomics employed Data Independent Acquisition (DIA) based on the GCA_0226743251.1 (\u003cem\u003eG. molesta\u003c/em\u003e) and GCA_033807575.1 (\u003cem\u003eC. pomonella\u003c/em\u003e) databases. Functional annotation was performed using InterProScan for Gene Ontology (GO) classification, including cellular components, molecular functions, and biological processes. Further pathways and proteins function analyses involved COG and KEGG databases.\u003c/p\u003e\n\u003cp\u003eAn integrated multi-omics approach was employed to elucidate regulatory mechanisms from transcription to translation, matching differentially expressed genes (DEGs) and proteins (DEPs) via common gene identifiers to generate paired mRNA and protein expression profiles. Given that protein levels more directly reflect functional gene output, and that transcript-protein correlation can be variable, key P450 genes involved in quercetin adaptation were identified using threshold criteria of |FC| \u0026gt; 1 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 on the proteomic dataset, corroborated by corresponding mRNA expression profiles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentify of P450 candidates associated with quercetin adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOmics analysis was employed to identify P450 candidates associated with quercetin adaptation in \u003cem\u003eG. molesta\u003c/em\u003e and \u003cem\u003eC. pomonella\u003c/em\u003e. Candidate P450 genes were cloned using genespecific primers (Table S1), designed via Primer 5, synthesized by Suzhou Genewiz Biotechnology Co. Ltd. (Suzhou, China). PCR amplification conditions included an initial denaturation at 94 \u0026deg;C for 3 min, followed by 39 cycles of 30 seconds at 94\u0026nbsp;\u0026deg;C, 30 seconds at 56\u0026nbsp;\u0026deg;C, 1 min at 72\u0026nbsp;\u0026deg;C, with a final extension at 72\u0026nbsp;\u0026deg;C for 10 min. PCR products were gel-purified with TIANgel Midi Purification Kit (DP219, TIANGEN BIOTECH, Beijing, China), cloned into the pMD 19-T vector (TaKaRa, Dalian, China), transformed into \u003cem\u003eEscherichia coli\u003c/em\u003e DH5ɑ (TaKaRa), and finally sequenced at Suzhou Genewiz Biotechnology Co. Ltd. Sequence similarities were assessed via DNAMAN 5.2.2 alignment .\u003c/p\u003e\n\u003cp\u003ePhylogenetic analyses utilized P450 amino acid sequences from \u003cem\u003eBombyx mori\u003c/em\u003e, \u003cem\u003ePlutella xylostella\u003c/em\u003e, \u003cem\u003eManduca sexta, H._armigera, Z._filipendulae\u003c/em\u003e, \u003cem\u003eSpodoptera_exigua\u003c/em\u003e, \u003cem\u003eSpodoptera_frugiperda\u003c/em\u003e, and \u003cem\u003eSpodoptera_litura\u003c/em\u003e as reference sequences. Phylogenetic trees were constructed using MEGA 11 employing the neighbor-joining method with 1000 bootstrap repeats. Protein domains were determined via the NCBI (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA extraction and cDNA synthesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from whole insects following the instructions provided by the manufacturer using Trizol Reagent (TaKaRa, Dalian, China). RNA purity and concentration were evaluated via NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA). For each sample, 1 \u0026mu;g of total RNA was reverse-transcribed into first-strand cDNA using PrimeScript\u0026trade; RT reagent Kit with gDNA Eraser (TaKaRa). The cDNA samples were stored at -20 \u0026deg;C until further analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTranscript analysis of quercetin adaptation-related P450 genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of fifty eggs, thirty larvae of the first (1L), second (2L) and third (3L) instar stages, ten larvae of the fourth (4L) and fifth (5L) instar stages, as well as ten female pupae (P♀), male pupae (P♂), female adults (A♀), and male adults (A♂), along with various tissues from fourth-instar larvae (head, cuticle, fat body, midgut, and Malpighian tubules), were collected with three replicates each.\u003c/p\u003e\n\u003cp\u003eExpression profiles of genes associated with quercetin adaptation\u0026nbsp;were analyzed via real-time qPCR (RT-qPCR) on a Bio-Rad CFX96 system (Bio-Rad, Hercules, CA, USA). Each 20 \u0026mu;L qPCR reaction comprised 10 \u0026mu;L of TB Premix Ex Taq, 1 \u0026mu;L of cDNA, 1 \u0026mu;L each of forward and reverse primers, and 7 \u0026mu;L of nuclease-free water. \u003cem\u003eEF-1\u0026alpha;\u003c/em\u003e and \u003cem\u003eActin\u003c/em\u003e genes were employed as internal controls for \u003cem\u003eC. pomonella\u003c/em\u003e\u003csup\u003e50\u003c/sup\u003e and\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003eG. molesta\u003c/em\u003e\u003csup\u003e51\u003c/sup\u003e. Primers sequences for RT-qPCR analysis of P450 genes were designed using Primer5 (Table S2). Three biological replicates each with three technical replicates were performed. Negative controls, including non-template controls (NTC) and non-reverse transcription controls (NRC), were incorporated to prevent potential genomic DNA contamination. Cycling conditions consisted of 95\u0026nbsp;\u0026deg;C for 30 seconds, followed by 40 cycles of 95\u0026nbsp;\u0026deg;C for 5 seconds, 50-60\u0026nbsp;\u0026deg;C for 30 seconds, and 72\u0026nbsp;\u0026deg;C for 30 seconds. Relative expression levels were calculated using the 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;\u003c/sup\u003e\u003csup\u003eCT\u003c/sup\u003e method\u003csup\u003e52\u003c/sup\u003e and visualized with GraphPad Prism software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHeterologous expression of recombinant P450 proteins\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe open reading frame (ORF) of \u003cem\u003eCYP341Q10\u003c/em\u003e, \u003cem\u003eCYP6AB364\u003c/em\u003e, \u003cem\u003eCYP333B119\u003c/em\u003e, \u003cem\u003eCYP333B118\u003c/em\u003e, \u003cem\u003eCYP337B19\u003c/em\u003e, and a NADPH-dependent cytochrome P450 reductase (CPR) was synthesized by Tsingke Science (Beijing, China) following the method described in Li \u003cem\u003eet al.\u003c/em\u003e (2023)\u003csup\u003e53\u003c/sup\u003e. These sequences were cloned into the pFastBac1 vector via restriction enzyme digestion, and the recombinant plasmids were verified through PCR and sequencing before storage at -20\u003csup\u003eo\u003c/sup\u003eC. To generate the recombinant bacmid DNA, the pFastBac1 constructs were transformed into the MAX Efficiency DH10Bac chemically competent cells (Thermo Fisher Scientific, Langenselbold, Germany). Positive clones containing recombinant bacmid DNA were confirmed via PCR using M13 forward and reverse primers. The recombinant bacmid DNA was isolated, quantified, aliquoted, and stored at -20\u003csup\u003eo\u003c/sup\u003eC in TE buffer at approximately 500 ng/\u0026mu;L.\u003c/p\u003e\n\u003cp\u003eRecombinant P450 proteins were expressed in Sf9 cells. Bacmids haboring CYP341Q10, CYP6AB364, CYP333B119, CYP333B118, and CYP337B19 were transfected into Sf9 cells using the Bac-to-Bac baculovirus expression system (Thermo Fisher Scientific, Langenselbold, Germany), following manufacturer instructions. The viral titers was determined as per protocol. Sf9 cells were co-infected with recombinant baculoviruses expressing P450 and CPR at \u0026nbsp; multiplicities of infection (MOI) of 1 and 0.1, respectively. Cells were maintained at 27\u003csup\u003eo\u003c/sup\u003eC in Sf-900 II SFM medium (LifeTechnologies, Carlsbad, CA, USA), supplemented with 2.5 \u0026mu;g/mL hemin and 0.3% (\u003cem\u003ev/v\u003c/em\u003e) fetal bovine serum. After 72 h, cells were harvested to isolate microsomal fraction, which were aliquoted and stored at -80\u003csup\u003eo\u003c/sup\u003eC after protein quantification via the Bradford assay (Beyotime, Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting analysis of quercetin adaptation-related P450 genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMicrosomal fractions containing recombinant P450 enzymes and CPR were denatured at 100 \u003csup\u003eo\u003c/sup\u003eC for 10 min, then separated using 10 % SDS-PAGE. Proteins were blotted transferred onto polyvinylidene difluoride (PVDF) membrane (Merck Millipore, Darmstadt, Germany) using a Bio-Rad blotting system. Membranes were blocked with a 5% (\u003cem\u003ew/v\u003c/em\u003e) non-fat dry milk in TBST buffer for 2 h, followed by overnight incubation at 4\u003csup\u003eo\u003c/sup\u003eC primary antibody (1:1000; ProbeGene, Jiangsu, China). After washing, membranes were incubated with HRP-conjugated goat anti-rabbit secondary antibody (1:10000; Bio-Platform, China) for 1h. Detection was performed \u0026nbsp;with Omni-ECL\u0026trade; Femto Light Chemiluminescence Kit (Yamei, Shanghai, China) and chemiluminescent images were captured with a Tanon 5200 imaging system (Tanon, Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular docking analysis of the interaction between P450 and quercetin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structures of P450 proteins were predicted using AlphaFold2. The three-dimensional (3D) structure of quercetin was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/). Active pockets of P450 enzymes were predicted using Proteins Plus. Molecular docking simulations between proteins and quercetin were conducted with AutoDock Vina 1.1.2, and results were analyzed using Discovery Studio and visualized with PyMOL 2.4.1. Lower docking free energies indicate stronger binding affinity. Furthermore, AlphaFold3 was employed to directly predict the structures of protein-ligand complexes. The Predicted Template Modeling (pTM) and Interface Predicted Template Modeling (iPTM) scores, derived from the Predicted Aligned Error (PAE) matrix through AlphaFold\u0026apos;s internal algorithm, were employed to assess the structural confidence and interface accuracy of the modeled complexes, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional analysis of P450 gene via RNA interference (RNAi)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDouble-stranded RNA (dsRNA) synthesis was performed following the instructions provided by the T7 RiboMAXTM Express RNAi System (Promega, USA). The resulting dsRNA solution was diluted to a concentration of 3000 ng/\u0026mu;L. Prior to microinjection, fourth instar larvae of QNA and QA populations of\u0026nbsp;\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eC. pomonella\u003c/em\u003e were starved for 12 h. A volume of 1\u0026nbsp;\u0026mu;L of dsRNA was microinjected into the third-to-fifth abdominal segment at the posterior end of each larva, with dsGFP serve as a control.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePost-injection, fourth instar larvae of QNA and QA populations of\u0026nbsp;\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eC. pomonella\u003c/em\u003e were fed on quercetin-free artificial diets. Whole insect samples were collected at 6 h, 12 h, 24 h, and 48 h, with 10 larvae per group and 3 replicates per group. The RNAi efficiency of the target gene was detected using RT-qPCR.\u003c/p\u003e\n\u003cp\u003eMoreover, fourth instar larvae of QNA and QA populations of\u0026nbsp;\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eC. pomonella\u003c/em\u003e were fed on 70 \u0026mu;g/g quercetin artificial diets for 2 h. Subsequently, the feed was removed. Tissue samples from the midgut, fat body, and Malpighian tubules were collected at 2 h and 5 h, with 20 larvae per group and 3 replicates per group. The RNAi efficiency of gene within these tissues was assessed via RT-qPCR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of nutritional parameters of two fruit borers following RNAi\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePost-injection of dsRNA, larvae were fed artificial diets containing either 0 \u0026mu;g/g or 70 \u0026mu;g/g quercetin. Nutritional parameters such as the efficiency of conversion of digested food (ECD), efficiency of conversion of ingested food (ECI) and relative growth rate (GR), were quantified at 6 h, 12 h, 24 h, and 48 h, according to previous documented method.\u003csup\u003e27\u003c/sup\u003e Weight of diet before feeding (WBF), weight of diet after feeding (WAF), weight of larvae feces (WLF) and weight growth (WG) were recorded according to previous documented\u003csup\u003e54\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn vivo\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;metabolism of quercetin in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFurther experiments involved feeding QA and QNA populations with diets containing 70 \u0026mu;g/g quercetin post-starvation, with tissue and fecal sample collection at 2 h, 5 h, and 8 h intervals. Samples were rinsed with phosphate buffer (pH 7.4) and stored at -80\u0026deg;C for subsequent high-performance liquid chromatography (HPLC) analysis to quantify quercetin levels (Figure 4a).\u003c/p\u003e\n\u003cp\u003eTo assess the metabolic impact of P450 gene expression on quercetin biotransformation, larvae from the same populations underwent feeding with quercetin-enriched diets for 2 hours following starvation, with tissue and feces harvested at 2 h and 5 h post-feeding (Figure 4a). Quercetin was extracted and quantified following previously described protocols\u003csup\u003e28\u003c/sup\u003e with slight modifications. Frozen frass and tissue samples were homogenized in a 2:1 (v/w) ratio of methanol at 4\u0026deg;C. Post-centrifugation at 20, 000 \u0026times; g for 10 min, the pellet was re-extracted with methanol, and the supernatants were combined. This extraction step was repeated to ensure comprehensive recovery. The pooled extracts were then diluted to a predetermined volume with methanol, filtered, and the final supernatant was subjected to HPLC analysis. Briefly, 20 \u0026mu;L of the prepared sample was injected into an Agilent 1260 HPLC system and separated on a reverse-phase XDB-C18 column (AG120, 5 \u0026mu;m, 4.6 \u0026times; 150 mm) at a flow rate of 1.0 mL/min. The mobile phase comprised water with 0.1% phosphoric acid (70%) and acetonitrile (30%). Quercetin was detected at 372 nm using a Waters 996 photodiode array detector. All measurements were conducted in triplicate. A standard curve was prepared by serially diluting quercetin in methanol to concentrations of 2.5, 5, 10, 20, 40, 80, and 160 \u0026mu;g/mL for quantification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn vitro\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;metabolism of quercetin in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eG. molesta\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eC. pomonella\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe metabolic activity assay was conducted following the protocol outlined by Zhang et al. (2024)\u003csup\u003e27\u003c/sup\u003e. The enzyme incubation mixtures included 20 pmol of recombinant cytochrome P450 isoforms, 5 \u0026mu;L of a 5 mM quercetin substrate solution, 0.5 mg of D-glucose-6-phosphate, 0.5 \u0026mu;L of glucose-6-phosphate dehydrogenase, and 50 \u0026mu;L of NADPH (1 mg/mL in 0.1 M phosphate buffer, pH 7.8), or 50 \u0026mu;L of phosphate buffer as a control lacking NADPH. The total reaction volume was adjusted to 500 \u0026mu;L with 0.1 M phosphate buffer (pH 7.8). Reactions were incubated at 30 \u003csup\u003eo\u003c/sup\u003eC for 90 minutes with gentle agitation in a water bath. Post-incubation, each reaction mixture was combined with an equal volume of acetone, vortexed, and subjected to centrifugation at 10,000 \u0026times; g for 10 minutes at room temperature to separate metabolites. The resulting supernatants were analyzed via HPLC. The analyses for quercetin metabolism were repeated three times, and the depletion rate was calculated using the formula: depletion (%) = (peak area without NADPH - peak area with NADPH) / peak area without NADPH \u0026times; 100%.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Key R\u0026amp;D Program of China (2021YFD1400200), Liaoning Distinguished Youth Scholars Science Foundation (2024JH3/50100027), and the Shenyang Special Project for Cultivating Young Scientific and Technological Innovation Talents U40 (RC230879). We express our gratitude to the Agricultural Invasive Species Control and Surveillance Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, for generously providing the susceptible strain (SS) of \u003cem\u003eC. pomonella\u003c/em\u003e. Additionally, we extend our thanks to Professor Yanqiong Guo (College of Plant Protection, Shanxi Agricultural University) for providing the sensitive strains of \u003cem\u003eG. molesta\u003c/em\u003e that were utilized in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. B:\u003c/strong\u003e Conceived and designed the experiments, Performed the experiments, Analyzed the data, Wrote the paper. \u003cstrong\u003eX.-Q.Y.:\u003c/strong\u003e Conceived and designed the experiments, Contributed materials/analysis tools, Wrote the paper. All authors read and approved the manuscript. \u003cstrong\u003eN.-X.F.\u003c/strong\u003e: Contributed materials/analysis tools. \u003cstrong\u003eB.-K.W., T.-T.W. and X.-F.L:\u003c/strong\u003e Analyzed the data.\u0026nbsp;\u003cstrong\u003eY.\u003c/strong\u003e-\u003cstrong\u003eH.L.\u003c/strong\u003e, \u003cstrong\u003eY.-T.L.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eY.-T.L., P. G. and J. L.:\u003c/strong\u003e Wrote the paper. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCheng, Y.N., Wen, P., Tan, K. \u0026amp; Darrouzet, E. .Designing a sex pheromone blend for attracting the yellow-legged hornet (Vespa velutina), a pest in its native and invasive ranges worldwide. \u003cem\u003eEntomol. 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Physiol.\u003c/em\u003e\u003cstrong\u003e205\u003c/strong\u003e, 106110 (2024).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Plant-insect interactions, adaptive mechanism, P450 enzyme, neofunctionalization","lastPublishedDoi":"10.21203/rs.3.rs-9176885/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9176885/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The coevolutionary arms race between plants and herbivores is a key driver of insect adaptation. While the global invasive fruit borer Cydia pomonella shows slower adaptation to the plant secondary metabolite quercetin compared to native species Grapholita molesta, the molecular basis remains unclear. Here, we clarify the divergent evolutionary mechanisms governing the adaptation of these two species to quercetin. Results revealed enhanced quercetin metabolic capacity in adapted populations of both species relative to their non-adapted counterparts. G. molesta relies on the canonical detoxification-associated P450 genes CYP6AB364 and CYP341Q10 belonging to the CYP3 and CYP4 clans, respectively, showing positive correlation with adaptation. In contrast, C. pomonella employs a member of the CYP3 clan (CYP337B19) and specific mitochondrial P450 genes (CYP333B119 and CYP333B118). Artificial intelligence (AI)-based molecular docking assay confirmed strong binding interactions between these P450 enzymes and quercetin. Knockdown of these genes reduced metabolic adaptation, and in vitro assays showed decreased metabolic efficiency post-silencing. Notably, recombinant P450 enzymes from C. pomonella (with the exception of CYP337B19) exhibited lower quercetin metabolic capability than G. molesta's. These findings suggest divergent adaptive strategies between species, with the invasive C. pomonella potentially employing neofunctionalized mitochondrial P450s for quercetin detoxification and facilitate adaption. G. molesta's superior quercetin metabolism likely drives its greater adaptability, advancing our understanding of host adaptation and interspecific interactions in pest species.","manuscriptTitle":"Cytochrome P450 drives divergent adaptation to quercetin in invasive and native fruit borers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-31 04:31:04","doi":"10.21203/rs.3.rs-9176885/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10d72bc5-6d01-46be-a3fa-cd08292c54eb","owner":[],"postedDate":"March 31st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64844144,"name":"Biological sciences/Evolution/Coevolution"},{"id":64844145,"name":"Biological sciences/Evolution/Molecular evolution"}],"tags":[],"updatedAt":"2026-04-19T03:15:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-31 04:31:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9176885","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9176885","identity":"rs-9176885","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}