Physiological Adaptation Strategies of the Interaction Defense Between Larvae of Megastigmus sabinae and the Host Juniperus przewalskii

1. Introduction

Within forest ecosystems, the interaction between host plants and phytophagous insects remains a central theme in forest protection research. Juniperus przewalskii Komarov, an endemic alpine conifer on the northeastern margin of the Qinghai-Tibet Plateau [1], exhibits a geographically restricted distribution confined to high-altitude mountains (2,600 ~ 4,300 m) ranging from the northeastern Qinghai-Tibet Plateau to the western edge of the Loess Plateau [2]. This species adapts to extreme drought and low-temperature environments through traits such as a deep root system, scaly leaf structure, and the accumulation of secondary metabolites (e.g., flavonoids) [3,4]. It serves as a dominant constructive species within the montane forest-steppe ecotone [5,6]. Its cones provide the exclusive reproductive substrate for the juniper seed pest, Megastigmus sabinae Xu et He (Hymenoptera: Torymidae), establishing a highly specialized parasitic relationship. This interaction system offers an ideal model for investigating plant-insect interaction and deciphering the spatiotemporal dynamics of host plant defenses versus insect counter-adaptations [7]. Recent studies demonstrate that plants employ secondary metabolites as a key strategy in constructing chemical defense systems against seed and cone pests [8,9], while insects develop detoxification mechanisms, often involving metabolic plasticity, to overcome these plant defenses [10]. However, our understanding of high-altitude juniper-pest systems remains limited. Specifically, the spatiotemporal coupling between dynamic defense strategies during cone development and insect counter-defense mechanisms remains unclear, as does the interaction between the dynamics of secondary metabolites in high-altitude Cupressaceae plants and the diverse enzyme activities of their insect pests.

Megastigmus sabinae and Juniperus przewalskii exhibit a highly specific synergistic developmental relationship. Adults oviposit into healthy cones, and the larval stage, comprising five instars, extends from late August of the current year to late June of the following year. The majority of larvae overwinter predominantly as 2nd instar (with a minority overwintering as 1st or 3rd instars) [11]. Larvae from the 1st to 4th instars bore into the endosperm, their development synchronizes with that of the host cones, culminating in the pupal stage, coinciding with the complete depletion of endosperm nutrients, resulting in hollow and abortion of cones [12]. This protracted developmental period and synchrony render the larvae entirely dependent on cone resources throughout their development. However, it also exacerbates seed abortion in J. przewalskii due to the barrier to natural regeneration. Current research primarily focuses on the biological characteristics and control techniques of M. sabinae [13]. Nevertheless, the physiological adaptation mechanisms underlying its interaction with the host plant remain unclear.

Plant secondary metabolites, such as flavonoids, coumarins, and steroidal compounds, play crucial roles in defending against feeding by herbivorous insects. Flavonoids exert insecticidal effects by inducing cytotoxicity or forming complexes with various enzymes, thereby impairing insect behavior and growth [14,15]. Picea spp. defend against Pissodes strobi larvae by activating terpene-rich oleoresin chemical defenses and increasing the abundance of stone cells [16]. This synergistic physical and chemical defense mechanism is prevalent in conifer cone defense mechanisms. However, systematic investigation into the temporal dynamics of secondary metabolites in Cupressaceae plants, particularly their correspondence with insect stages, remains lacking.

Research on insect adaptation strategies to plant defenses shows a multidimensional trend. Biochemically, insects rely on detoxifying enzyme systems, such as cytochrome P450 monooxygenases (CYP450), glutathione S-transferases (GST), and carboxylesterases (CarE), to degrade plant antiherbivore chemical defenses [17,18]. Physiologically, they dynamically regulate digestive enzymes to cope with host nutrient limitations, enhancing physiological plasticity [19]. From a genetic evolutionary perspective, certain oligophagous groups develop specific adaptation mechanisms through key gene mutations—for instance, oligophagous species within the noctuid genus Spodoptera cannot feed on Poaceae plants containing the toxin DIMBOA (2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one) due to mutations of UGT genes (UDP-glycosyltransferases) [20]. However, current research predominantly focuses on polyphagous Lepidoptera species [20,21,22], with a paucity of systematic analysis on defense mechanisms in oligophagous Hymenoptera species. For example, M. sabinae larvae complete their entire larval stage within the cones of J. przewalskii, likely evolving unique physiological adaptation mechanisms and detoxification metabolic pathways. The molecular basis and ecological significance of these adaptations warrant further exploration.

Based on this background, our study for the first time establishes a multi-level interaction system between a typical high-altitude tree species (J. przewalskii) and its oligophagous pest (M. sabinae), integrating nutrient content analysis, metabolomic analysis, and multi-category enzyme activity profiling. Primarily, we analyzed dynamic nutrient content and protective enzyme activities in cones following parasitism by M. sabinae larvae. Subsequently, based on liquid chromatography-mass spectrometry (LC-MS) technology, we analyzed differential secondary metabolites in infested cones in response to larvae feeding. Finally, we determined the digestive and detoxifying enzyme activities of larvae during their synergistic development within the cones. This study aims to address the following scientific questions: (1) How do infested cones establish multi-layered defense through nutrient content remodeling, responsive regulation of protective enzyme activities, and temporal accumulation of secondary metabolites? (2) How do larvae achieve metabolic adaptation through dynamic modulation of digestive and detoxifying enzymes? (3) What are the quantitative coupling relationships between cone defense strategies and larval adaptation mechanisms? This work lays the foundation for elucidating the physiological adaptation strategies underpinning nutritional and chemical defense interactions formed during the long-term coevolutionary process between J. przewalskii and M. sabinae.

2. Materials and Methods

2.1. Insect Material and Host Plant Cones

Mature cones of J. przewalskii were collected from the forest stand in Toutan, Sunan Yugur Autonomous County, Zhangye City, Gansu Province (altitude: 2,920 m; 38°32′N, 100°14′E). Megastigmus sabinae insects were collected on six dates: August 25, 2021(i.e., egg stage); December 18, 2021(i.e., 1st instar); April 5, 2022(i.e., 2nd instar); May 10, 2022(i.e., 3rd instar); June 12, 2022(i.e., 4th instar) and July 3, 2022(i.e., 5th instar). For each collection, 1,000 cones were collected, transported to the laboratory, longitudinally bisected, and examined to distinguish healthy cones from infested cones. Both cone material and larvae from each stage were immediately frozen and stored at -80°C for subsequent analysis.

2.2. Nutrient Contents Analysis in Juniperus przewalskii Cones

2.2.1. Protein Content

Protein content in healthy and infested J. przewalskii cones across developmental stages was quantified using the BCA Protein Assay Kit (Beijing Bairuiji Biotechnology Co., Ltd., Beijing, China), according to the manufacturer’s instructions. Each experimental group included three biological replicates. Finally, using the function formula of the standard curve to calculate the protein concentration of each sample.

2.2.2. Starch Content

Starch content in healthy and infested J. przewalskii cone tissues across developmental stages was quantified using the Plant Starch Content Kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China), according to the manufacturer’s instructions. Each experimental group included three biological replicates. Starch content was calculated using the following formula:

$$\mathrm{S}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{c}\mathrm{h} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}={\displaystyle \frac{{\mathrm{A}}_{\mathrm{d}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}-{\mathrm{A}}_{\mathrm{b}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{k}}}{{\mathrm{A}}_{\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{a}\mathrm{r}\mathrm{d}}-{\mathrm{A}}_{\mathrm{b}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{k}}}}\times {\mathrm{C}}_{\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{a}\mathrm{r}\mathrm{d}}\times {\mathrm{V}}_{\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}\times {\displaystyle \frac{\mathrm{N}}{\mathrm{W}}}$$

(1)

Where C _standard refers to the concentration of the Standard Solution, V _sample is the total volume of the sample, N is the dilution factor of the supernate, and W is the fresh weight of the sample.

2.2.3. Crude Fat Content

Crude fat content of J.przewalskii cone was determined by Soxhlet extractor method, which was invented by German scientist Franz Ritter von Soxhlet in 1879. First, about 1 g of healthy or infested cone was weighed and placed on the filter paper, wrapped, and fixed with cotton thread before marking. Then, the filter paper was put into the extraction bag, and the various parts of the instrument were assembled. Two-thirds of petroleum ether was added to the receiver, and heated under the condition of 60 ~ 75 ℃ water bath, so that the petroleum ether was continuously refluxed and extracted 8 times h^-1 for 6 ~ 8 h. Next, the receiving bottle was taken off, and the petroleum ether was recovered. When the residual petroleum ether in the receiving bottle was left only 1 ~ 2 mL, it was evaporated in a water bath, and then dried in an oven at 105 ± 5 ℃ for 2 h, until the drying device was cooled and weighed. Each experimental group included three biological replicates. Finally, crude fat contents of each sample were calculated by the formula following:

$$\mathrm{C}\mathrm{r}\mathrm{u}\mathrm{d}\mathrm{e} \mathrm{f}\mathrm{a}\mathrm{t} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}={\displaystyle \frac{{m_1-m}_0}{m_2}}\times 100$$

(2)

Where m₁ refers to the quality of the receiving bottle and crude fat, m₀ is the quality of the receiving bottle, and m₂ is the quality of each sample.

2.3. Protective Enzyme Activity Analysis in Juniperus przewalskii Cone

2.3.1. Peroxidase Activity

Peroxidase activity in healthy and infested J. przewalskii cone tissues across stages was quantified using the Peroxidase Assay Kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China), according to the manufacturer’s instructions. Each experimental group included three biological replicates. Peroxidase activity was calculated using the following formula, the activity of an enzyme was shown as U per g of fresh weight:

$$\mathrm{P}\mathrm{O}\mathrm{D} \mathrm{A}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}={\displaystyle \frac{{\mathrm{A}}_{\mathrm{d}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}+{\mathrm{A}}_{\mathrm{b}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{k}}}{12\times \mathrm{d}}}\times {\displaystyle \frac{{\mathrm{V}}_{\mathrm{R}\mathrm{S}}}{{\mathrm{V}}_{\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e} \mathrm{q}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}}}}÷\mathrm{T}÷{\displaystyle \frac{\mathrm{W}}{{\mathrm{V}}_{\mathrm{S}}}}\times 1000$$

(3)

Where V_RS refers to the total volume of the reaction system, V _{Sample quality} is the quality of the sample; T is the response time (i.e., 20 min), W is the fresh weight of the tissue, V_S is the total volume of the sample.

2.3.2. Phenylalamine Ammonia Lyase Activity

Phenylalanine ammonia lyase activity in healthy and infested J. przewalskii cone tissues across stages was quantified using the Phenylalamine ammonia lyase Kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China), according to the manufacturer’s instructions. Each experimental group included three biological replicates. Phenylalanine ammonia lyase activity was calculated using the following formula, the activity of an enzyme was shown as U per g of fresh weight:

$$\mathrm{P}\mathrm{A}\mathrm{L} \mathrm{A}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}={\displaystyle \frac{△\mathrm{A}}{0.1}}÷({\displaystyle \frac{\mathrm{W}}{{\mathrm{V}}_{\mathrm{C}\mathrm{E}}}}\times \mathrm{V}\mathrm{S})\times {\displaystyle \frac{{\mathrm{V}}_{\mathrm{R}\mathrm{S}}}{1}}÷\mathrm{T}$$

(4)

Where W refers to the weight of the sample, V_CE is the total volume of the crude extract, V_S is the loading amount of the crude extract during determination, V_RS is the total volume of the reaction system, T is the response time, △A=A _{determination} − A _blank.

2.4. LC-MS-Based Untargeted Metabolomics and Differential Metabolite Screening in Juniperus przewalskii Cones

Metabolites in healthy and infested J. przewalskii cone seeds were analyzed using liquid chromatography-mass spectrometry (LC-MS; Thermo Scientific Q Exactive HF-X) in two batches due to prolonged intervals between larval stages. Cones collected on December 18, 2021 (i.e., 2nd instar), April 5, 2022 (i.e., 3rd instar), and May 10, 2022 (i.e., 4th instar) were longitudinally dissected to separate healthy and infested seeds. Samples were flash-frozen in liquid nitrogen and homogenized, with specific procedures as follows. Briefly, 0.1 g of the J. przewalskii tissue is weighed and transferred into a 2 mL Eppendorf tube. Methanol containing L-2-chlorophenylalanine (4 mg kg^-1; pre-cooled to −20°C) (Merck KGaA; Germany) was added for 30s vortex oscillation. After fully mixing, add 100 mg of glass beads to each centrifuge tube, then place them all in the tissue grinder (Thermo Fisher Scientific Inc.; United States) and grind for 90 s at 60 Hz. Subsequently, ultrasonic treatment was performed at room temperature for 15 min, and centrifuged at 4 °C and 12000 rpm for 10 min, the supernate was filtered with a 0.22 μm membrane and detected by LC-MS, with three replicates performed.

In addition, some of the extracted samples to be tested were mixed into quality control (QC) samples to evaluate the stability and repeatability of the experimental method, and the QC inspection was performed on more than 10 experimental samples. The samples were eluted and determined by reference to the method of Want et al. [23].

Raw LC-MS data were converted to mzXML format using ProteoWizard version 3.0.8789 and processed via XCMS for peak alignment and normalization. Metabolites were annotated using the Human Metabolome Database (HMDB, v5.0, https://hmdb.ca), MassBank (v2023.12, https://massbank.eu), Kyoto Encyclopedia of Genes and Genomes (KEGG, Release 107.0, https://www.kegg.jp), and LipidMaps (2024Q1 update, https://www.lipidmaps.org), accessed on March 20, 2023. Only metabolites with QC showing relative standard deviation (RSD) < 30% across technical replicates and detection rates > 80% in biological samples were retained. Subsequently, differential metabolites between healthy and infested cones were identified based on statistical significance (p-value), fold change, and the Variable Importance in Projection (VIP) score. Metabolites with a p-value < 0.05 and a VIP score > 1 were considered statistically significant.

2.5. Detoxication Enzyme Activity Analysis in Megastigmus Sabinae Larvae

First, prepare the tissue homogenate of the larvae. Every 10 larvae of the 2nd, 3rd, 4th and 5th instars in each treatment were divided into a group, with 5 replicates in each group. Then, the pre-cooled sample was homogenized in a homogenizer, and the supernatant was taken for subsequent determination. In this study, the activities of cytochrome P450 (CYP450), glutathione S-transferase (GST) and carboxylesterase (CarE) were determined to measure the detoxication enzyme activity in the larvae of M. Sabinae. Enzyme-linked immunosorbent assay (ELISA) was used in the determination, and the specific steps are taken as the example of the determination of GST activity.

The Insect Glutathione S-transferase ELISA Kit (Jingmei Biotechnology Co., Ltd., Nanjing, China) was used to determine the GST activity in the larvae of M. Sabinae. According to the manufacturer’s instructions, samples, standard and Horseradish Peroxidase (HRP) detection antibody were added to the micropores pre-covered with GST antibody, incubated at 37 °C for 1 h, and fully cleaned. Subsequently, under the action of TMB, the samples were first converted to blue with the catalyst of peroxidase, and last turned yellow, the color was shaded with the GST activity in the samples. Finally, the stopping solution was added, and the absorbance (OD value) was determined by a microplate reader at 450 nm. The linear regression curve was drawn with the standard concentration as the abscissa and the OD value as the ordinate, and the concentration of each sample was quantified according to the curvilinear equation.

2.6. Digestive Enzyme Activity Analysis in Megastigmus Sabinae Larvae

The protease activity, amylase activity and lipase activity of the larvae were determined to measure the digestive enzyme activity in this study, also based on the ELISA. The specific procedures were the same as the detoxication enzyme activity determination method above.

2.7. Statistical Analysis

All statistical analyses were performed using IBM SPSS Statistics version 23.0 (IBM Corp., Armonk, NY, USA). One-way analysis of variance (One-way ANOVA) was employed to analyze the differences in nutrient contents of J. przewalskii cones and the activities of protective enzymes. For the detoxication and digestive enzyme activities of M. sabinae larvae, a two-way analysis of variance (Two-way ANOVA) was applied. Tukey’s honestly significant difference (HSD) post hoc test was used for multiple comparisons among different treatments to determine significant differences at the P < 0.05 level. Figures were generated using GraphPad Prism version 10.1.2 (GraphPad Software, San Diego, CA, USA).

3. Results

3.1. Nutrient Contents of Juniperus przewalskii Cones

The principal nutrient contents (protein, starch, and crude fat content) of healthy and infested cones of J. przewalskii across larval stages was determined (Figure 1). Overall, protein content was significantly higher than that of starch and crude fat, and all three nutrient contents exhibited a progressive decline in both healthy and infested cones over the developmental period. Infested cones consistently displayed higher protein content but lower starch content compared to healthy cones at all sampled stages, indicating larval feeding-induced alterations in internal nutrient composition. Specifically, infested seeds exhibited significantly higher protein content than healthy seeds during the earlier larvae instars (2nd~3rd instar; P < 0.001; Figure 1a), while this difference diminished during later instars (4th~5th instar), showing only marginal (P < 0.05) or no significant differences (P > 0.05). Conversely, infested cones demonstrated significantly reduced starch content compared to healthy cones at every larval stage (P < 0.001; Figure 1b). For crude fat content, no significant differences (P > 0.05) were generally observed between infested and healthy seeds, except for a slight decrease in infested seeds during the 4th instar (Figure 1c).

3.2. Protective Enzyme Activity of Juniperus przewalskii Cones

Larvae feeding by M. sabinae significantly altered the protective enzyme activities in J. przewalskii cones compared to healthy cones, with both peroxidase (POD) and phenylalanine ammonia lyase (PAL) activities exhibiting varying degrees of increase in infested cones (Figure 2). POD activity in healthy cones remained relatively stable throughout the developmental stages, ranging from 2811.12 to 3520.67 U/g. In contrast, POD activity in infested cones was significantly higher than in healthy cones during the earlier instars (2nd~3rd instar). The most pronounced increase occurred during the 2nd instar, reaching 6280.39 U/g in infested cones, a 71.10% increase compared to healthy cones at the same stage (P < 0.001). Similarly, POD activity during the 3rd instar was 26.23% higher in infested cones (P < 0.01). PAL activity in healthy cones also remained stable across developmental stages, ranging from 2.86 to 3.43 U/g. Infested cones showed marginally higher PAL activity than healthy cones during the 2nd instar (P < 0.05). Subsequently, PAL activity in infested cones became highly significantly elevated during the 3rd to 5th instar larvae feeding periods, showing increases of 51.57% (P < 0.001), 57.34% (P < 0.001), and 42.37% (P < 0.001) compared to healthy cones, respectively.

3.3. Metabolomic Analysis Reveals Differential Metabolites in Juniperus przewalskii Cones

Untargeted LC-MS-based metabolomic analysis was employed to profile secondary metabolites in healthy and infested J. przewalskii cones during the 2nd to 4th instar. A total of 437, 513, and 513 secondary metabolites were identified in healthy and infested cones during the 2nd, 3rd, and 4th instar, respectively (Figure 3).

Differential metabolite analysis between infested and healthy cones within each larval stage was performed. As shown in Figure 3, 73 differentially metabolites (DMs) were identified during the 2nd instar (48 upregulated, 25 downregulated). Similarly, 73 DMs were identified during the 3rd instar (46 upregulated, 27 downregulated). In contrast, the number of DMs decreased to 36 during the 4th instar (25 upregulated, 11 downregulated). Comparative analysis of DMs across larval stages identified three key classes of defense-related secondary metabolites consistently enriched (high cumulative VIP scores) in multiple instars: carboxylic acids and derivatives, benzene and substituted derivatives, and flavonoids (Table 1, Table 2 and Table 3). Notably, several identified DMs are known insect-resistance compounds. This finding indicates that feeding by M. sabinae significantly activates chemical defense responses in J. przewalskii, which persist across larval developmental stages. For instance, the enrichment of flavonoids suggests potential impairment of larval nutrient absorption efficiency via the flavonoid biosynthesis pathway. Furthermore, stage-specific DM enrichment was observed: coumarin (VIP = 6.2) and cinnamaldehyde derivatives (VIP = 5.8) were specifically enriched during the 2nd instar. Novel enrichment of steroid derivatives occurred during the 3rd and 4th instar larvae feeding periods; these compounds may enhance cone defense by disrupting insect hormonal balances.

Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis (Figure 3d–f) revealed that DAMs in infested cones were significantly enriched in pathways including Phenylpropanoid biosynthesis, ABC transporters, and hormone signaling pathways (Sphingolipid signaling pathway; Retinol metabolism) compared to healthy cones. This integrated multi-pathway defense network suggests that J. przewalskii cones primarily counteract M. sabinae larvae feeding by modulating the biosynthesis of secondary metabolites, transmembrane transport of nutrients, and hormone signaling-mediated physiological responses.

3.4. Digestive Enzyme Activity of Megastigmus Sabinae Larvae

To assess larvae digestive adaptation to host plant nutrients, we measured protease, amylase, and lipase activities in M. sabinae larvae across the 2nd to 5th instars (Figure 4). Overall, larvae in later instars (4th~5th) exhibited significantly higher activities for all three digestive enzymes compared to those in earlier instars (2nd~3rd; Figure 4; P < 0.05). Protease activity showed the most pronounced increase (62.96%), with enzyme activity generally increasing with larval stage. Lipase activity demonstrated only a slight increase during the 5th instar.

3.5. Detoxication Enzyme Activity of Megastigmus Sabinae larvae

To investigate larvae detoxification mechanisms in response to plant secondary metabolites in J. przewalskii cones, we measured the activities of cytochrome P450 (CYP450), glutathione-S-transferase (GST), and carboxylesterase (CarE) in M. sabinae larvae across the 2nd to 5th instars (Figure 5). The results revealed a consistent overall trend in the activity of all three enzymes during larvae development. Significantly higher activities were observed in larvae of earlier instars (2nd~3rd) compared to those in later instars (4th~5th; P < 0.05). Generally, detoxification enzyme activity decreased with the increase in larval stage, except for CarE, which showed a slight increase during the 5th instar.

4. Discussion

The interaction between phytophagous insects and their host plants represents a central theme in ecological interaction research [9]. Herbivory activates complex defense response networks in host plants [9], while insects counter these defenses through adaptive adjustments in developmental strategies and detoxification metabolic systems [24]. This study focuses on the unique interaction system between Megastigmus sabinae larvae and Juniperus przewalskii cones. Elucidating their multi-layered interaction mechanisms and physiological adaptation strategies provides novel insights into plant-insect co-defensive and adaptive evolutionary processes within high-altitude ecosystems.

This study reveals, for the first time, that J. przewalskii cones resist M. sabinae larvae feeding through the synergistic action of dynamically regulated nutrient composition and a multi-layered chemical defense network. Concurrently, shifts in multiple enzyme activities in M. sabinae larvae reflect their adaptive evolutionary responses to host plant defenses. Firstly, the protein content in infested cones was significantly higher than that in healthy cones, particularly during the early larvae instars (2nd~3rd). This likely results from J. przewalskii inducing the synthesis and accumulation of specific proteins to interfere with larvae’s overwintering survival and post-diapause digestion. For instance, infested cones exhibited significantly higher levels of defensive protective enzymes (e.g., peroxidases, polyphenol oxidases). These enzymes likely inhibit insect digestive enzymes, reducing herbivore digestive efficiency (as evidenced by lower digestive enzyme activity in early instars) [25], and increasing larval metabolic costs. Additionally, J. przewalskii may produce protease inhibitors (PIs), and other defense-related proteins (e.g., pathogenesis-related proteins (PRs), chitinases) [26,27], further compromising larvae’s physiological processes. In response, larvae significantly downregulated protease activity, potentially to minimize these costs, demonstrating an adaptation to host defenses [28]. Secondly, starch content decreased significantly in infested cones. This decline may reflect its conversion to soluble sugars to compensate for carbohydrate depletion following larval feeding, aligning with a “nutrient limitation” strategy [29]. Compared to healthy cones, the reduced starch content in infested cones coincided with larvae amylase activity being significantly higher than protease and lipase activity. This suggests larvae may upregulate amylase activity to enhance the utilization efficiency of cone starch, preferentially consuming readily metabolizable starch while significantly downregulating lipase activity to conserve energy reserves for overwintering. This strategy is highly consistent with the “carbon-prioritizing and lipid-conserving strategy” observed in gall-inducing insects during overwintering [30]. Analogous adaptations are seen in oligophagous seed pests like Callosobruchus maculatus and Plodia interpunctella [31,32], indicating oligophagous insects may overcome host nutrient limitations through metabolic plasticity. For example, Eriogyna pyretorum enhances trypsin activity when feeding on hosts low in soluble protein content to acquire more protein [19,33]. Thirdly, the decrease in crude fat content in infested cones, coupled with significantly elevated larvae lipase activity during the 4th instar and the enrichment of novel steroid derivatives during the 3rd~4th instar feeding period, suggests J. przewalskii may interfere with insect lipid metabolism (e.g., potentially inhibiting juvenile hormone synthesis). This could reduce available lipid nutrients for larvae, thereby delaying larval development [34]. This phenomenon also highlights the larvae’s adaptive feedback to such liposoluble toxins.

Furthermore, the temporal pattern of protective enzyme activity in cones indicates a “stage-specific division of labor” strategy. During the overwintering period (2nd instar), peroxidase (POD) activity was significantly elevated in infested cones. This likely serves to scavenge reactive oxygen species (ROS) accumulated prior to overwintering, induced by mechanical damage and insect saliva, thereby maintaining cellular homeostasis [35,36]. Analogously, Bemisia tabaci (Gennadius) feeding significantly induces enhanced POD activity in Vigna mungo (L.) Hepper. As larval development progressed (3rd~5th instars), phenylalanine ammonia-lyase (PAL) activity significantly increased. This likely drives the sustained activation of the phenylpropanoid pathway [37], promoting the accumulation of flavonoids and coumarins.

Detoxification enzyme activity data reveal a biphasic detoxification strategy in the larvae: the three major detoxification enzymes (CYP450, GST, CarE) exhibited peak activity during the early instar (2nd), followed by a significant decline as development advanced to later instars (4th~5th). This closely correlates with changes in secondary metabolites within infested cones: Early instar larvae (2nd) require elevated detoxification enzyme activity to counteract the host’s diverse array of secondary metabolites (e.g., coumarins and cinnamaldehyde derivatives). By the later instar (4th), larvae have largely adapted to the host cone environment, shifting focus towards accelerated growth and development. Concurrently, the variety of secondary metabolites upregulated by the host cones during the later larval stage was markedly reduced (25 types). The phenomenon of significantly higher digestive enzyme activities in later instar larvae (4th ~ 5th) compared to earlier instars (2nd~3rd) aligns with this adaptive shift. Additionally, winter low-temperature stress triggers a ROS burst and membrane lipid peroxidation within J. przewalskii, leading to the accumulation of lipid peroxidation end-products (e.g., MDA) in the cones [38]. This may compel M. sabinae larvae to preemptively activate glutathione-S-transferase (GST) during the prolonged overwintering period (~200 days in the 2nd instar) as an antioxidant defense system. This activation counters ROS generated during environmental exposure, preventing oxidative damage to cellular components [28,39]. Collectively, these findings demonstrate larval adaptation to J. przewalskii ’s multi-layered defenses through enzyme specialization strategies.

Leveraging LC-MS-based untargeted metabolomics, this study deciphered the multi-pathway coordinated defense network in infested J. przewalskii cones. Analysis revealed that differentially abundant metabolites in infested cones were significantly enriched in the phenylpropanoid biosynthesis pathway, providing molecular-level corroboration for the observed PAL activity enhancement [37]. The sustained accumulation of flavonoids confers potent defensive functions. Flavonoid accumulation causes midgut damage in Helicoverpa zea larvae and disrupts the expression of key genes essential for maintaining gut health [40]. It also influences the oviposition behavior of Papilio xuthus on citrus juvenile leaves [41]. Coumarins, specifically enriched during the 2nd instar in this study, can stimulate plant defense responses by triggering ROS generation and activating immune-related genes and signaling pathways (e.g., the salicylic acid-dependent pathway). These compounds possess multifaceted anti-insect activities, including inhibiting various insect processes and hindering nucleic acid synthesis. This aligns with the high levels of detoxification enzymes like GST maintained in early instar larvae (2nd) [42]. Such synchronized responses represent a key interactive mechanism ensuring synchronized development between the plant and insect. Furthermore, significant activation of the ABC transporter pathway unveils a spatial regulation mechanism in plant defense. For instance, transmembrane transport of secondary metabolites like terpenoids may be enhanced [43]. The novel enrichment of steroid derivatives during the 3rd~4th instar feeding period further supports this hypothesis, potentially facilitating the targeted accumulation of toxins at larval feeding sites [44]. Moreover, the abnormal activation of the retinol metabolism pathway suggests J. przewalskii may implement defense by potentially disrupting insect molting hormone signaling [45].

In summary, this study systematically deciphers the intricate and sophisticated physiological interaction mechanisms between J. przewalskii and its specialist herbivore, M. sabinae. Juniperus przewalskii employs a comprehensive defense strategy involving the dynamic modulation of cone nutrient composition, the temporal activation of protective enzymes, and the construction of a multi-layered chemical defense network. Conversely, M. sabinae larvae exhibit remarkable adaptive capabilities, effectively countering host-imposed nutritional constraints and chemical challenges through the precise regulation and strategic division of labor among digestive and detoxification enzymes. This tight coupling of plant defense and insect counter-defense across temporal and metabolic dimensions represents a core manifestation of their long-term coevolution within the high-altitude habitat. This study not only provides novel perspectives for understanding the interaction mechanisms between oligophagous insects and their specific hosts but also contributes significant physiological and molecular evidence to the theory of plant-insect coevolution in alpine ecosystems. However, it is important to note that this study was conducted under controlled laboratory conditions, omitting the influence of complex field variables such as temperature fluctuations and natural enemy interactions. Future research will integrate field experiments to validate the ecological applicability of these findings and delve deeper into the functional differentiation of detoxification enzyme genes and the interference mechanism of the host retinol pathway on insect hormone signaling. These insights will furnish new evidence for the coevolutionary dynamics and bidirectional physiological adaptation mechanisms within plant-oligophagous pest systems in high-altitude ecosystems, laying a crucial foundation for developing ecologically sound pest management strategies based on host chemical defenses.