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Article

Effects of Antheraea pernyi on Parasitization of Kriechbaumerella dendrolimi by Using Immunology and Metabolomics

1
Forestry College, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
Forestry College, Najing Forestry University, Nanjing 210037, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Forests 2024, 15(5), 851; https://doi.org/10.3390/f15050851
Submission received: 30 March 2024 / Revised: 5 May 2024 / Accepted: 8 May 2024 / Published: 13 May 2024
(This article belongs to the Special Issue Advances in Biological Control of Forest Diseases and Pests)

Abstract

:
Kriechbaumerella dendrolimi (Hymenoptera, Chalcididae) is a dominant pupal parasitoid species of various significant pine caterpillars, including Dendrolimus houi Lajonquiere (Lepidoptera, Lasiocampidae), with great potential for utilization. So far, the mass rearing of K. dendrolimi has been successfully established using Antheraea pernyi (Lepidoptera, Saturniidae) pupae as alternative hosts and released in the forest to suppress D. houi populations. However, the outcome is still expected to be improved due to lower parasitism rates, which might be related to the autonomous immune function of A. pernyi pupae. In our study, we investigated the effects of K. dendrolimi parasitization on the immune responses of A. pernyi pupae by measuring the expression of key immune factors: superoxide dismutase (SOD), polyphenol oxidases (PPOs), Attacin, Lysozymes (LYSs), and serine proteases (PRSSs). Our results show that parasitization significantly upregulated these immune factors, with distinct temporal patterns observable between 4 and 48 h post-parasitization. This upregulation highlights a robust immune response, adapting over time to the parasitic challenge. These findings suggest that specific immune mechanisms in A. pernyi pupae are activated in response to K. dendrolimi, shedding light on potential targets for enhancing host resistance. Metabolomic analyses complemented these findings by illustrating the broader metabolic shifts associated with the immune response. Specifically, Attacin was significantly upregulated twice, hypothesizing that the parasitoid’s venom contains at least two parasitic factors. Metabolomics analysis revealed a significant metabolite difference within parasitized A. pernyi pupae. The highest number of differential expression metabolites (DEMs) was observed at 16 h post-parasitism (1184 metabolites), with fewer DEMs at 8 h (568 metabolites) and 32 h (693 metabolites), suggesting a close relationship between parasitism duration and the number of DEMs. These fluctuations reflected the fundamental process of immune interaction. KEGG enrichment results showed that the DEMs were mainly enriched in energy metabolism and immune-related pathways, indicating that parasitism is a process of continuous consumption and immune interaction in the host. These DEMs could also become future targets for regulating the immune functions of A. pernyi pupae and could provide reference data for optimizing mass-rearing techniques.

1. Introduction

The Dendrolimus houi Lajonquiere (Lepidoptera, Lasiocampidae) is a major defoliator in the southern forest regions of China, often causing widespread dieback and severe economic and ecological losses from larvae feeding on needles and tender branches of pine trees [1,2,3,4,5]. Previous research indicates that Kriechbaumerella dendrolimi Sheng and Zhong (Hymenoptera, Chalcididae), a parasitoid wasp, exhibits high natural parasitism rates, short life cycles, and high offspring production. It effectively controls D. houi [6,7] and is a crucial natural enemy of various Lepidopteran pests such as D. punctatus Walker and D. kikuchii Matsumura, thus holding great developmental potential [8,9]. In the artificial mass-rearing system of K. dendrolimi, Antheraea pernyi is the most suitable alternative host for mass rearing. However, the parasitism rate of A. pernyi pupae remains low [8], which is one of the main factors limiting the efficiency and cost of mass rearing. Based on the melanization phenomenon observed within the parasitized A. pernyi pupae, it is hypothesized that the low parasitism rate is related to the autonomous immune function of A. pernyi pupae.
Insects lack adaptive immunity but possess an efficient innate immune system capable of successfully defending against exogenous pathogenic infections [10]. The main forms of immunity are cellular and humoral [11,12]. Humoral immunity refers to immune reactions involving soluble effector molecules such as antimicrobial peptides (AMPs), complement-like proteins, and enzymes involved in melanin cascades [13,14]. When insects are attacked, serine proteases (PRSSs) initiate cascade reactions affecting the Toll pathway [15]. The AMPs, as vital effectors of insect humoral immunity, are subsequently controlled by pathways such as Toll and participate in eliminating foreign pathogens [16,17]. Moreover, Lysozymes (LYSs) are another type of lytic protein that could cleave the β-1,4 glycosidic linkages between N-acetylglucosamine and N-acetylmuramic acid in peptidoglycans, one component of the bacterial cell wall, activating melanin-based pathways and causing melanization [18,19,20]. Meanwhile, various enzymes and metabolites in insects, such as hemolymph proteins, polyphenol oxidases (PPOs), and superoxide dismutase (SOD), also respond rapidly and participate in defense reactions [21,22]. These immune factors play a crucial role in protecting insects from foreign biological invasions, and their changes can reveal the immune interaction process between the parasitoid and the host to some extent.
Furthermore, insect metabolic products play a crucial role in regulating their physiology, behavior, and adaptation [23], and changes in metabolic products can often be identified using metabolomics techniques [24]. Recently, these techniques have been widely applied to explore insect immune mechanisms [25,26]. Therefore, this study aims to reveal the immune mechanism of A. pernyi pupae against K. dendrolimi by measuring the expression of five immune factors: SOD, PPOs, Attacin, LYSs, and PRSSs before and after parasitism and combining metabolomic analyses. This will provide a theoretical basis for the mass rearing of K. dendrolimi.

2. Materials and Methods

2.1. Rearing of Test Insects and Sample Preparation

2.1.1. Rearing of Test Insects

The test parasitoids K. dendrolimi and fertilized eggs of A. pernyi were sourced from the indoor population at the Provincial Key Laboratory of Integrated Pest Management in Ecological Forests, Fujian Agriculture and Forestry University (26°05′06.0″ N 119°14′07.0″ E). K. dendrolimi was propagated indoors using A.pernyi pupae as hosts. The environmental conditions were meticulously controlled, maintaining a temperature of 24 ± 2 °C and a relative humidity of 60 ± 10%. Upon emergence, the parasitoids were fed with 100% honey applied to rayon balls. A 1:1 male-to-female ratio was maintained for mating, allowing the parasitoids to mate freely within rearing boxes (14.1 cm × 6.3 cm × 8.5 cm) over a period of 24 h. Each rearing cage contained ten males and ten females. After this period, female wasps were selected as experimental insects [8]. After hatching, A. pernyi larvae were reared on Quercus aliena leaves under controlled conditions with a temperature of 24 ± 2 °C and relative humidity of 60 ± 10%. The larvae were housed in specified rearing cages (40 cm × 30 cm × 40 cm) until they pupated. Post-pupation, the pupae were stored at 4 °C in a refrigerator for further use [8,27]. Pupae of A. pernyi that were healthy, active, and free of external injuries, all uniformly sized with a body length of 5 cm ± 0.2 cm and a width of 2 cm ± 0.1 cm, were then selected as the test hosts.

2.1.2. Collection of Hemolymph Samples from Host Insects

Parasitism was conducted in a one-to-one ratio of wasp to A. pernyi pupa. Hemolymph samples were collected from non-parasitized (CK) and parasitized A. pernyi pupae at intervals of 4 h from 4 to 48 h post-parasitism. The surface of each pupa was rinsed with sterile water, disinfected with 75% alcohol spray, and then allowed to air dry. The lower abdomen of each pupa was dissected with a sterile scalpel to collect the hemolymph into sterile centrifuge tubes [28,29]. The samples were immediately flash-frozen in liquid nitrogen for 15 min and then stored at −80 °C for further analysis. Each sample consisted of hemolymph collected from six pupae.

2.2. Determination of Immune Factors in Host Insect Hemolymph

2.2.1. SOD Activity Assay

A 20× concentrated wash buffer was prepared by diluting with distilled water. Hemolymph samples from A. pernyi pupae were allowed to clot at room temperature for 15 min, followed by centrifugation at 2000 rpm for 20 min to collect the supernatant. This extraction process was repeated twice to ensure consistency. Using the Insect SOD Assay Kit (YJ403841, Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China), 50 μL of standards at concentrations of 200, 100, 50, 25, 12.5, and 0 U/mL were added sequentially to six standard wells. For each sample well, 40 μL of sample diluent and 10 μL of the sample were added, followed by gentle shaking to mix. Subsequently, 100 μL of the enzyme-label reagent was added to each well. The plate was covered with a sealing film and incubated in a 37 °C water bath for 60 min. After incubation, the sealing film was removed, the liquid discarded, and the wells flicked dry. Each well was filled with wash buffer, left to stand for 30 s, and emptied. This washing step was repeated five times before flicking dry. Then, 50 μL of chromogen solution A and 50 μL of chromogen solution B were added to each well, gently shaken to mix, and incubated in the dark at 37 °C for 15 min for color development. Finally, 50 μL of stop solution was added to each well, and each well’s optical density (OD value) was sequentially measured at 450 nm wavelength using an ELISA reader (SpectraMax iD5, Molecular Devices, San Jose, CA, USA). Each sample was tested eight times, and the average value was taken. The standard curve’s linear regression equation was calculated using the concentrations and OD values of the standards. The enzyme activity of the samples was calculated by substituting the sample OD values into the standard curve equation [30].

2.2.2. PPO Activity Assay

The insect PPO activity was measured using the Polyphenol Oxidase Assay Kit (YJ480715, Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China). Except for adding standard solutions to six standard wells at concentrations of 2000, 1000, 500, 250, 125, and 0 U/mL, the other steps were consistent with Section 2.2.1.

2.2.3. Attacin Activity Assay

The activity of the insect Attacin was determined using the Attacin Assay Kit (YJ217054, Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China). Except for adding standard solutions to six standard wells at concentrations of 800, 400, 200, 100, 50, and 0 pg/mL, the other steps were consistent with Section 2.2.1.

2.2.4. LYS Activity Assay

The activity of insect LYSs was measured using the Lysozyme Assay Kit (YJ409903, Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China). Except for adding standard solutions to six standard wells at concentrations of 20, 10, 5, 2.5, 1.25, and 0 U/L, the other steps were consistent with Section 2.2.1.

2.2.5. PRSS Activity Assay

The activity of insect PRSSs was determined using the Serine Protease Assay Kit (YJ440300, Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China). Except for adding standard solutions to six standard wells at concentrations of 64, 32, 16, 8, 4, and 0 U/L, the other steps were consistent with Section 2.2.1.

2.3. Sample Preparation for HPLC-Mass

Hemolymph samples from A. pernyi pupae were selected as metabolomic experiment samples at various stages: non-parasitized (CK), 8 h after parasitization (AP8h), 16 h after parasitization (AP16h), and 32 h after parasitization (AP32h). For each sample, 100 μL was measured and mixed with 500 μL of extraction solvent (methanol–acetonitrile–water, v/v, 2/2/1 with an internal standard concentration of 2 mg/L) at a ratio of 1000:2. The mixture was vortexed for 30 s and ultrasonicated for 10 min in an ice-water bath. After ultrasonication, the samples were left to stand at −20 °C for 1 h and then centrifuged at 4 °C for 15 min at 12,000 rpm. Subsequently, 500 μL of the supernatant was transferred into an Eppendorf tube and dried in a vacuum concentrator. The dried metabolites were then reconstituted with 160 μL of acetonitrile–water (v/v, 1/1), vortexed for 30 s, ultrasonicated in an ice-water bath for 10 min, and finally centrifuged at 4 °C for 15 min at 12,000 rpm. After this, 120 μL of the supernatant was transferred to a sample vial for analysis [31]. Each sample was analyzed with a 10 μL injection volume.

2.4. Metabolite Profiling

Metabolomic analysis was performed using a liquid–mass system consisting of an ultra-high-performance liquid phase (Waters Acquity I-Class PLUS, Waters, Framingham, MA, USA) tandem high-resolution mass spectrometer (Waters Xevo G2-XS QTof, Waters, Framingham, MA, USA). The column model used was an AcquityUPLC HSS T3 column (1.8 μm × 2.1 mm × 100 mm). The liquid phase separation condition was mobile phase A (0.1% formic acid aqueous solution) and mobile phase B (0.1% formic acid acetonitrile) gradient elution [32]. The elution process started with 2% mobile phase B and was maintained for 0.25 min. The mobile phase B increased uniformly from 0.25 to 10 min to 98% and maintained for 3 min. It was then returned to the initial condition of 2% mobile phase B and held for 2 min, then was analyzed in the next sample. The flow rate was 0.4 mL/min, and the sample volume was 1 μL. The mass spectrometer detection conditions were as follows: capillary voltage: 2000 V (positive ion modes) or −1500 V (negative ion modes), cone hole voltage: 30 V, ion source temperature: 150 °C, desolvation temperature: 500 °C, flow rate of back blowing: 50 L/h, and desolvent gas flow rate: 800 L/h [33].

2.5. Qualitative and Quantitative Analyses of Metabolites

The metabolites were identified and quantified based on the online METLIN database of Progenesis QI software (v3.0) and the self-built database of Beijing BioMaker Technologies Co. (Beijing, China). Theoretical fragmentation identification was also conducted with a parent ion mass deviation within 100 ppm and fragment ion mass deviation within 50 ppm. R software (v4.1.3, https://www.r-project.org/, accessed on 5 May 2023) was employed for principal component analysis (PCA) [34]. An OPLS-DA (orthogonal partial least squares discriminant analysis) model was employed with the first principal component of VIP (variable importance in the projection) ≥ 1, combined with Student’ s t-test (p < 0.05) and FC (fold change) > 1.5, to identify the differential expression metabolites (DEMs) [35]. Additionally, the DEMs were functionally annotated, and metabolic pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [36].

2.6. Enzymatic Activity Data Analysis

Experimental results are presented as mean ± standard deviation (SD). Data were analyzed using SPSS 25.0 software. After testing for normal distribution and homogeneity of variances, statistical analyses were conducted using Fisher’s LSD for group comparisons [37]. A p-value of less than 0.05 was considered statistically significant.

3. Results

3.1. Impact of K. dendrolimi Parasitization on the Hemolymph Immune Factors of A. pernyi Pupae

After parasitization by K. dendrolimi, the activity of five immune factors in A. pernyi pupae was significantly higher than in the control, indicating that the parasitism activated the host’s immune response and enhanced its immunity level. Specifically, the activity of SOD showed a clear upward trend starting from AP8h. It was significantly higher than CK (p < 0.05) from AP12h (12 h after parasitization), with more minor fluctuations after that (Figure 1a). The activity of PPOs gradually increased from the onset of parasitism, becoming significantly higher than CK from AP16h (p < 0.05) and then stabilizing, reaching a peak at AP32h (Figure 1b). The activity of Attacin significantly increased at AP4h (4 h after parasitization) and AP20h (20 h after parasitization) (p < 0.05), subsequently maintaining stability (Figure 1c). Within 48 h of parasitism, the LYS activity in the A. pernyi pupae was significantly higher than CK (p < 0.05), with the highest activity at AP32h, then beginning to decline (Figure 1d). PRSSs showed some increase before AP16h but did not reach significance (p > 0.05); it became significantly higher than CK from AP20h (p < 0.05) and reached its peak at AP32h, followed by a decrease (Figure 1e).
Overall, AP8h and AP16h are critical turning points when early- to mid-stage immune factors change significantly, indicating that the immune response of A. pernyi entered a new phase. At the same time, AP32h is the peak point for multiple immune factors such as PPOs and LYSs, indicating the highest level of immune response of A. pernyi pupae to the parasitoid. These nodes reflect the physiological response time differences of the host at different stages to the parasitoid. Interestingly, the activity of Attacin significantly increased at AP4h but then decreased to levels similar to the control during the subsequent period (8–16 h) before significantly increasing again, indicating two stress responses in the Attacin during the immune process. This suggests that the venom of K. dendrolimi might contain multiple parasitic factors.

3.2. Impact of K. dendrolimi on the Hemolymph Metabolites of A. pernyi Pupae

The results of PCA analysis indicated that PC1 and PC2 accounted for 28.46% and 18.29% of the variation between different treatment groups, respectively (Figure 2). The samples parasitized by K. dendrolimi were distant from the CK group, suggesting significant differences in metabolite expression induced by parasitism in A. pernyi pupae.
In OPLS-DA analysis, the CK-AP8h model explained 63.7% of the variance for the predictor variable X and 99.7% for the response variable Y and had a predictive ability of 80.5% for the sample variables (Figure 3a). The CK-AP16h model explained 64% of the variance for X and 100% for Y and had a predictive ability of 87.9% for the sample variables (Figure 3b). The CK-AP32h model explained 69.1% of the variance for X and 99.9% for Y and had a predictive ability of 89.5% for the sample variables (Figure 3c). The R2Y values in all three comparison combinations were close to 1, and the Q2Y values were all greater than 0.5, indicating suitable data quality and effective models suitable for subsequent analysis.
Analysis of the number of DEMs revealed that 568 DEMs were produced at AP8h compared to CK, with 268 upregulated and 300 downregulated. The notably upregulated DEMs included 2-Hydroxybutyric acid and 2-(L-Menthoxy) ethanol, while significantly downregulated ones included 2-Oxoarginine and Uridine triphosphate (Figure 4a). At AP16h compared to CK, 1184 DEMs were identified, with 748 upregulated and 436 downregulated. Notable upregulated DEMs included Prolyl-Histidine, Cyanidin-3-o-beta-glucopyranoside, and (2S,4S)-Monatin, while significantly downregulated ones included Hexadecadienylcarnitine (Figure 4b). At AP32h compared to CK, 693 DEMs were identified, with 293 upregulated and 400 downregulated. Notably, upregulated DEMs included 2′-Deamino-2′-hydroxyparomamine and 4′-Hydroxy-5,6,7,8-tetramethoxyflavone, while significantly downregulated ones included Pyrrolysin and Ureidoacrylate (Figure 4c). These DEMs might play an essential role in the immune process of A. pernyi pupae against the parasitoid. The number of DEMs was highest at AP16h. It decreased at AP32h, approaching the levels at AP8h, indicating significant differences in the immune response of A. pernyi pupae to parasitism by K. dendrolimi at different times, with the immune reaction being most intense at AP16h.
KEGG enrichment results showed that the DEMs produced at AP8h compared to CK were mainly enriched in amino acid metabolism (29), followed by nucleotide metabolism (12) and membrane transport (11) (Figure 5a). At AP16h compared to CK, the DEMs were also primarily enriched in amino acid metabolism (33), followed by the digestive system (24) and metabolism of cofactors and vitamins (20) (Figure 5b). At AP32h compared to CK, the DEMs were mainly enriched in amino acid metabolism (23), followed by nucleotide metabolism (19) and digestive system (10) (Figure 5c). These metabolic changes in these pathways might be related to the immune process. The consistent enrichment of amino acid metabolic pathways in all three periods indicates that parasitism by the K. dendrolimi has a sustained and significant impact on the amino acid metabolism of A. pernyi pupae.

4. Discussion

Previous research indicated that rapid and efficient immune responses were triggered to antagonize parasitic invasions within insects [38,39,40,41], characterized by swift activation of immune factors engaged in immune resistance activities such as metabolism of toxic substances [42,43,44], encapsulation of external pathogens [45,46], hemolymph agglutination [47], and wound healing processes [48]. Our study also revealed that upon parasitism, A. pernyi pupae show a significant increase in various immune factors from their hemolymph, indicating an intense immune response to the parasitization by K. dendrolimi. Among the immune effectors within insects, the AMPs played a dominant role, primarily by hydrolyzing bacterial cell walls and cell membrane permeability, inhibiting microbial division, and neutralizing metabolic toxins [49,50]. These peptides effectively disinfect bacteria, fungi, viruses, protozoa, and cancer cells [51,52,53,54]. We observed a rapid increase in the activity of Attacin, a major group of insect AMPs, within 4 h of parasitism by K. dendrolimi, followed by a rapid decrease between 8 and 16 h, before maintaining a consistently higher level [55,56,57,58], indicating at least two parasitic factors from the venom of K. dendrolimi, producing two times of intense change due to different response reactions from the immune system of A. pernyi pupae.
The innate immunity of host insects is critical to detect and eliminate external parasites, encompassing complex physiological, biochemical, and genetic interactions [38,40,59]. However, the metabolic adaptation to external invasions is another key factor influencing immune functions [60,61,62]. Following parasitism by K. dendrolimi, significant metabolic changes in A. pernyi pupae led to the production of specific DEMs directly related to insect immunity. For instance, 2-Hydroxybutyric acid, a biomarker linked to impaired cellular function and increased oxidative stress, participates in intracellular lipid oxidation and oxidative stress [63,64]. Furthermore, metabolites like 2′-Deamino-2′-hydroxyparomamine and Cyanidin-3-o-beta-glucopyranoside, involved in antibiotic biosynthesis and antioxidative activities, respectively [65,66,67,68], played a vital role in the immune process of A. pernyi pupae against K. dendrolimi. Additionally, the significant upregulation of 4′-Hydroxy-5,6,7,8-tetramethoxyflavone, known for its strong antiviral activity [69], at 32 h post-parasitism suggested the presence of viral elements in K. dendrolimi’s parasitic factors, regulating the host immune process.
KEGG enrichment analysis revealed that the DEMs produced in A. pernyi pupae post-parasitism mainly focused on pathways such as amino acid metabolism, nucleotide metabolism, membrane transport, and cofactors and vitamins metabolism, all closely related to energy metabolism [70,71]. Similar to the response of Drosophila melanogaster to microbial infections, the activation of immune functions in A. pernyi pupae increased the body’s energy metabolic rate, with the additional energy consumption closely related to the synthesis of immune factors like AMPs [72,73,74,75,76]. Changes in membrane transport pathways affected energy metabolism and directly or indirectly influenced immune functions, such as nutrient intake, waste degradation and excretion, hormone release, and cell signaling [77,78]. Numerous studies indicate that key metabolites produced in hosts due to parasitization by parasitoid wasps can significantly affect the survival and reproduction of the parasitoids [79,80,81]. For instance, in their study, Liu et al. utilized metabolomics analysis to identify key metabolites, including lipids and amino acids, which can reduce the immune response of Drosophila hosts. Certain specific lipids and amino acids, such as L-histidine, L-proline, and L-glutamate, were crucial in this process [82]. These pathway alterations reflected the host insect’s metabolic adaptation to parasitization. In summary, significant immune reactions and immune metabolites generated in parasitized A. pernyi pupae by K. dendrolimi may rapidly neutralize or resolve the parasitoid eggs during the early stages of parasitization, leading to lower parasitism. Therefore, the synthesis of these substances could be targeted for molecular modifications aimed at enhancing the reproductive efficiency of K. dendrolimi.

5. Conclusions

In the artificial rearing of K. dendrolimi, the alternative host A. pernyi pupae exhibited significant immune responses upon parasitism, specifically manifested as short-term significant upregulation of various immune factors and the DEMs related to energy metabolism and immune function. These are the primary causes of the lower parasitism rate of K. dendrolimi. The synthesis of these substances may serve as a molecular modification target to enhance the mass-rearing efficiency of K. dendrolimi.

Author Contributions

Conceptualization, Y.Q., X.F., C.L., Z.Z. and G.L.; data curation, Y.Q., X.F., Z.Z. and Q.Z.; investigation, Y.Q., X.F., Z.C. and C.L.; writing—original draft preparation, Y.Q., X.F., Z.C., Q.Z., J.T. and G.L., writing—review and editing, Y.Q., C.L., X.F., Z.Z., J.T., F.Z. and G.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the introductory project of the Fujian Provincial Science and Technology Department (No. 2021N002), the Fuzhou Forestry Science and Technology Research Project (No. 2021FZLY01), the Forestry Science and Technology Research Project of Fuzhou City (No. 2022-81), the Fujian Province Forestry Science and Technology Promotion Project (No. 2023TG16), the National Natural Science Fund of China (No. 31870641).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

In this study, we extend our gratitude to the Provincial Key Laboratory of Integrated Pest Management in Ecological Forests, Fujian Agriculture and Forestry University for providing the insect sources and experimental platform. We also thank the Forestry Bureau of Xiapu County and Minqing State-owned Forest Farm for their assistance in field collection and investigation.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Changes in immune factors of A. pernyi pupae after parasitization by K. dendrolimi. (a) SOD activity in A. pernyi pupae after parasitization by K. dendrolimi; (b) PPO activity in A. pernyi pupae after parasitization by K. dendrolimi; (c) Attacin activity in A. pernyi pupae after parasitization by K. dendrolimi; (d) LYS activity in A. pernyi pupae after parasitization by K. dendrolimi; (e) PRSS activity in A. pernyi pupae after parasitization by K. dendrolimi. Note: different lowercase letters indicate significant differences (p < 0.05).
Figure 1. Changes in immune factors of A. pernyi pupae after parasitization by K. dendrolimi. (a) SOD activity in A. pernyi pupae after parasitization by K. dendrolimi; (b) PPO activity in A. pernyi pupae after parasitization by K. dendrolimi; (c) Attacin activity in A. pernyi pupae after parasitization by K. dendrolimi; (d) LYS activity in A. pernyi pupae after parasitization by K. dendrolimi; (e) PRSS activity in A. pernyi pupae after parasitization by K. dendrolimi. Note: different lowercase letters indicate significant differences (p < 0.05).
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Figure 2. Score of PCA of metabolites of A. pernyi. Note: pupae non-parasitized (CK), 8 h after parasitization (AP8h), 16 h after parasitization (AP16h), and 32 h after parasitization (AP32h).
Figure 2. Score of PCA of metabolites of A. pernyi. Note: pupae non-parasitized (CK), 8 h after parasitization (AP8h), 16 h after parasitization (AP16h), and 32 h after parasitization (AP32h).
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Figure 3. (a) Score of orthogonal projections to OPLS-DA score chart of CK-AP8h; (b) score of orthogonal projections to OPLS-DA score chart of CK-AP16h; (c) score of orthogonal projections to OPLS-DA score chart of CK-AP32h.
Figure 3. (a) Score of orthogonal projections to OPLS-DA score chart of CK-AP8h; (b) score of orthogonal projections to OPLS-DA score chart of CK-AP16h; (c) score of orthogonal projections to OPLS-DA score chart of CK-AP32h.
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Figure 4. (a) Volcano plots of DEMs of CK-AP8h; (b) volcano plots of DEMs of CK-AP16h; (c) volcano plots of DEMs of CK-AP32h. Note: In the volcano plot, each point represents a metabolite. The x-axis represents the fold change of each substance in the comparison group (logarithm base 2); the y-axis represents the p-value from the t-test (logarithm base 10); the size of the dot indicates the variable importance in the projection (VIP) value from the OPLS-DA model. Blue dots represent downregulated DEMs; red dots represent upregulated DEMs; gray describes detected but not significant DEMs.
Figure 4. (a) Volcano plots of DEMs of CK-AP8h; (b) volcano plots of DEMs of CK-AP16h; (c) volcano plots of DEMs of CK-AP32h. Note: In the volcano plot, each point represents a metabolite. The x-axis represents the fold change of each substance in the comparison group (logarithm base 2); the y-axis represents the p-value from the t-test (logarithm base 10); the size of the dot indicates the variable importance in the projection (VIP) value from the OPLS-DA model. Blue dots represent downregulated DEMs; red dots represent upregulated DEMs; gray describes detected but not significant DEMs.
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Figure 5. (a) KEGG enrichment analysis of DEMs between CK and AP8h; (b) KEGG enrichment analysis of DEMs between CK and AP16h; (c) KEGG enrichment analysis of DEMs between CK and AP32h. Note: The numbers in the figure represent the quantities of DEMs.
Figure 5. (a) KEGG enrichment analysis of DEMs between CK and AP8h; (b) KEGG enrichment analysis of DEMs between CK and AP16h; (c) KEGG enrichment analysis of DEMs between CK and AP32h. Note: The numbers in the figure represent the quantities of DEMs.
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Que, Y.; Fang, X.; Zhao, Z.; Chen, Z.; Lu, C.; Zheng, Q.; Tan, J.; Zhang, F.; Liang, G. Effects of Antheraea pernyi on Parasitization of Kriechbaumerella dendrolimi by Using Immunology and Metabolomics. Forests 2024, 15, 851. https://doi.org/10.3390/f15050851

AMA Style

Que Y, Fang X, Zhao Z, Chen Z, Lu C, Zheng Q, Tan J, Zhang F, Liang G. Effects of Antheraea pernyi on Parasitization of Kriechbaumerella dendrolimi by Using Immunology and Metabolomics. Forests. 2024; 15(5):851. https://doi.org/10.3390/f15050851

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Que, Yuwen, Xinyuan Fang, Zhenhui Zhao, Zhenhong Chen, Ciding Lu, Qiufang Zheng, Jiajin Tan, Feiping Zhang, and Guanghong Liang. 2024. "Effects of Antheraea pernyi on Parasitization of Kriechbaumerella dendrolimi by Using Immunology and Metabolomics" Forests 15, no. 5: 851. https://doi.org/10.3390/f15050851

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