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. 2026 Jan 31;89(1):54. doi: 10.1007/s00248-025-02641-x

Microbial Mediators of Pine Defense Resistance: Stage-Specific Gut Symbionts Enable Acantholyda posticalis to Overcome Terpenoid Barriers

Yao Wang 1,#, Shipeng Han 1,#, Wenlong Zhang 1, Weixing Shen 2, Bin Dong 2, Ningxin Wang 1,✉
PMCID: PMC12909442  PMID: 41620541

Abstract

Acantholyda posticalis (Matsumura) is a globally significant forest pest that inflicts substantial economic losses through its feeding activity on Pinus species. As an oligophagous insect, A. posticalis relies critically on its gut microbiota to overcome the defensive secondary metabolites of pine needles, particularly α- and β-pinene terpenoids. This study investigated the dynamic compositional changes of gut bacterial communities across different developmental stages of A. posticalis and characterized their functional roles in host adaptation. Through traditional culturing methods, two pinene-degrading bacterial strains—Klebsiella variicola and Enterobacter hormaechei—were isolated from the larval gut. In vitro assays demonstrated their significant capacity to degrade the two pinenes. High-throughput 16S rRNA sequencing revealed stage-specific bacterial enrichment patterns. Functional prediction suggested these microbial communities participate in critical metabolic processes, including phosphotransferase systems, GST activity, and detoxification pathways. This work advances understanding of insect-microbe symbiosis in oligophagous systems and proposes novel strategies for ecologically sustainable A. posticalis control through manipulation of its gut microbiota.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00248-025-02641-x.

Keywords: Acantholyda posticalis, Gut bacteria, Pinene degradation, 16S rRNA sequencing, Microbial diversity

Introduction

Acantholyda posticalis (Matsumura), a devastating oligophagous sawfly, has emerged as a major forestry pest across Europe and East Asia. This species exhibits strong host specificity, primarily infesting Pinus species including P. tabuliformis, P. densiflora, P. thunbergii, P. sylvestris, and P. koraiensis [1]. The larval stage causes particularly severe damage by feeding at the base of pine shoots, while adults contribute to defoliation through needle consumption [1]. With the development of the larvae, the energy metabolism demand is also increasing, and the food intake is also significantly increased [1]. Such feeding behavior not only stunts tree growth but also compromises the ecological and aesthetic value of forest ecosystems.

Pine needles employ sophisticated chemical defenses against herbivory, predominantly through terpenoid compounds, primary terpenes, such as α-pinene and β-pinene [2]. These terpenoids are almost insoluble in water but soluble in organic solvents like ethanol, ether, chloroform, and acetonitrile. The terpenes exhibit high chemical activity due to unsaturated double bonds [3]. They are volatile oils that are difficult to degrade and exert a negative influence on insects. For example, gossypol in cotton inhibits the growth of Helicoverpa armigera [4]. Nitrophenol disrupts the intestinal microbial homeostasis and inhibits the growth and reproduction of Plutella xylostella by destroying the structure of the intestinal perifeeding membrane [5]. Cucurbitacin in the leaves of cucurbitaceae plants acts as an antagonist of ecdyhormone and can cause molting defects and death in Drosophila melanogaster and B. mori [6]. However, for certain pine-eating beetles, they can resist terpenes by relying on their own detoxification enzymes, such as cytochrome P450 enzymes. Moreover, they rely on terpenes to find hosts [7]. In particular, the diterpenoid acids in spruce have no obvious toxicity to Hylobius abietis. On the contrary, H. abietis can degrade diterpenoid acids and improve its reproductive ability through its own gut microbiota [8].

Most insects have abundant bacteria in their guts, and the bacteria play beneficial roles in nutrition acquisition, growth and development, detoxification, and pathogen resistance of insects [9–15]. Insect symbionts can be divided into obligate and facultative symbionts. Obligate symbiont and host have a mutualistic symbiosis during the long co-evolution process. Obligate symbionts generally live in cells and spread vertically, while facultative symbionts can be transmitted horizontally or vertically [16]. The diversity and function of gut microorganisms vary in different insects [17]. Oligophagous insects have evolved specialized gut microbial communities to overcome plant defenses [18, 19]. Wood-feeding Coptotermes formosanus possesses a potent lignocellulose degradation system, and the efficient degradation of lignocellulose by termites depends on the assistance of gut symbiotic microorganisms [20]. Treatment of Spodoptera frugiperda larvae with antibiotics results in decreased food consumption and loss of body weight [21]. Enterococcus (HcM7), a strain isolated from the intestinal tract of Hyphantria cunea larvae, is capable of pre-activating the expression of antimicrobial peptide HcGlv1 to inhibit virus replication in the host gut and hemolymph, thereby reducing the pathogenic effect of nuclear polyhedrosis virus on insects [22]. The structure and abundance of insect symbiotic bacteria are influenced by the growth and development stage as well as the diet of the host [23–25].

While previous studies have established fundamental knowledge of A. posticalis’ biological characteristics and conventional control methods [1, 26, 27], three critical research gaps remain unresolved: (i) the dynamic succession patterns of gut microbiota across developmental stages, (ii) the mechanistic basis of microbial-mediated terpene detoxification, and (iii) the translational potential of microbiome manipulation for sustainable pest management. To address these gaps, our study pioneers an integrated approach, synergizing traditional culture-dependent techniques with next-generation sequencing (16S rRNA V3-V4 profiling) and HPLC-based functional validation of pinene degradation. By elucidating how gut microbiota enable A. posticalis to exploit pine defenses, this work provides mechanistic insights into host-microbe coadaptation while laying the groundwork for novel biological control approaches that could reduce reliance on chemical pesticides in forest ecosystems.

Materials and Methods

Insect Collection and Sample Preparation

Acantholyda posticalis occurs once a year and can not be artificially reared in the laboratory. Field collections of A. posticalis were conducted during May 2022 and 2023 from Pinus tabuliformis stands at Mount Tai, China (36.25°N, 117.11°E), including 250 eggs, 433 first–second instar larvae, 1022 third-forth instar larvae, 302 fifth instar larvae, 235 sixth instar larvae, and 120 adults.

For bacterial isolation, gut tissues from third-fourth and fifth instar larvae (n = 30 per stage, 10 individuals per replicate in triplicate) were aseptically dissected after 24-h starvation to clear gut contents. The remaining specimens were processed for microbiome analysis by pooling gut tissues (20 individuals per tube) in a sterile 1.5-mL centrifuge tube, and collecting every 25 eggs as a sample in a 1.5-mL centrifuge tube. All samples were immediately flash-frozen in liquid nitrogen and stored at − 80 ℃ until DNA extraction, with strict quality control measures including sterile workspace maintenance (UV-treated laminar flow hood) and RNase/DNase-free consumables.

Isolation, Culture, and Sequencing Verification of Intestinal Symbiotic Bacteria of A. posticalis

For bacterial isolation, fresh gut tissues from third-fourth and fifth instar larvae were homogenized using sterile glass grinding rods, followed by preparation of serial dilutions (10−4 to 10−6) from the initial 10 µL gut homogenate. Aliquots (40 µL) of each dilution were aseptically plated onto four distinct culture media—LB agar, glucose agar, nutrient agar (NA), and blood agar—using the spread plate technique, followed by incubation at 28 ℃ for 72 h under aerobic conditions. Following incubation, morphologically distinct colonies were selected based on visual characteristics (size, color, edge morphology) and subjected to five rounds of purification via streak plating on their respective media. Genomic DNA was extracted from bacterial cultures (Omega, Magen Inc., NY, USA) and used as a template for PCR amplification of the 16S rRNA gene using universal primers 27 F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-TACGACTTAACCCCAATCGC-3′) under the following optimized conditions: initial denaturation at 94 ℃ for 3 min; 30 cycles of denaturation (94 ℃, 30 s), annealing (55 ℃, 30 s), and extension (72 ℃, 30 s); followed by final extension at 72 ℃ for 5 min. PCR products were verified through 1.2% agarose gel electrophoresis before commercial sequencing (Beijing Qingke Biotechnology Co., Ltd.). The resulting sequences were analyzed using NCBI BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi) with a 97% identity threshold for species-level identification, and phylogenetic relationships were reconstructed using MEGA 10 software (neighbor-joining method with 1000 bootstrap replicates) to confirm bacterial taxonomy.

Determination of Pinene Degradation Ability by Culturable Bacteria

The isolated bacteria were cultured in LB liquid medium to an OD600 value of 1. Then, 50 mL of isolated bacteria were inoculated into 1000-mL MM medium (minimal medium, which contains only the minimum nutrients required to maintain the basic growth of microorganisms) containing α-pinene or β-pinene as the sole carbon source (25 ℃, 160 r/min), with pinene concentrations set at 100, 200, and 300 mg/L, respectively. Uninoculated medium was used as a blank control. Bacterial growth was monitored by measuring OD600 every 8 h, with higher OD600 values indicating greater pinene degradation capability.

The degradation rate of pinene by potential bacteria was determined through high-performance liquid chromatography (HPLC). Optimal culture conditions were first determined for each strain. At 8-h intervals, 20 mL aliquots of minimal medium culture containing α-pinene or β-pinene were collected and subjected to liquid–liquid microextraction using ethyl acetate, followed by 2 min of sonication. After phase separation, the supernatant was collected, concentrated by rotary evaporation, and redissolved in methanol. The processed samples were filtered through 0.22 µm membranes prior to HPLC injection. Uninoculated minimal medium served as the blank control, with three biological replicates per treatment. Standard curves were generated using α-pinene and β-pinene solutions at concentrations of 0, 10, 50, 100, 200, and 300 mg/L. HPLC analysis was conducted using an Agilent 1200 system equipped with an Agilent C18 column (mobile phase: methanol:water = 70:30, v/v; column temperature: 30 °C; detection wavelength: 205 nm; flow rate: 1 mL/min; injection volume: 20 µL). Statistical analysis was performed using IBM SPSS Statistics 24 (IBM, USA), while figures were generated using GraphPad Prism 9 (GraphPad Software, USA).

DNA Extraction and High Throughput Sequencing

Total microbial DNA was extracted from samples using the OMEGA-D5625-01 Soil DNA Kit (Omega, Magen Inc., NY, USA), followed by quantification with a UV spectrophotometer (Eppendorf, Germany). The hypervariable V3-V4 region of the 16S rRNA gene sequence was amplified with the universal primers 338 F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGGTWTCTAAT-3′) in a 20 µL PCR reaction system. The PCR products were pooled and detected using 2% agarose gel electrophoresis, and purified by AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, USA). NEXTFLEX Rapid DNASeq Kit was used to construct the sequencing libraries, which were sequenced using Illumina Miseq PE300 by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

Data Processing and Bioinformatics Analysis

Paired-end data were merged using Flash (version 1.2.11) software. High-quality clean reads were obtained using the Quantitative Insight into Microbial Ecology (QIIME) (version 1.9.0) package under filtering conditions to remove chloroplast and mitochondrial gene sequences. OTUs were clustered based on 97% similarity using Usearch software (version 11) to generate the OTU table. Shannon diversity index, Simpson index, Chao 1 index, Ace index, and Coverage species coverage index were calculated using QIIME software, while rarefaction curves were plotted using R software (version 3.3.1). Beta diversity distance matrices were calculated using Qiime (2020.2.0), and dendrograms were plotted using R software (version 3.3.1). Community bar plots were also plotted using R software, and the vegan package in R was used to cluster according to the similarity of species or sample abundances to create community Heatmap plots.

The non-parametric Kruskal–Wallis (KW) sum-rank test was used to detect differences in species abundance across groups, identifying significantly different species. Significant taxa were further validated using Wilcoxon rank-sum tests (with Benjamini–Hochberg FDR correction) to assess consistency between subgroup pairs. The effect size of discriminative taxa was quantified through Linear Discriminant Analysis (LDA), with an LDA score threshold of > 2.0 considered biologically significant. Visualization was implemented using R (v3.3.1) (stats package for KW/Wilcoxon tests, ggplot2 for LDA bar plots) and Python (scipy v1.5.4) for effect size calculations.

The NetworkX network analysis toolkit was used for correlation network analysis by calculating the degree distribution of network nodes. Finally, graph theory was applied to analyze the established biological correlation network and construct the species correlation network. Functional prediction was performed using PICRUSt2, which normalized the OTU abundance table and predicted metagenomic functions by mapping 16S rRNA sequences to the KEGG database, with metabolic pathways (Level 3) quantified based on OTU abundance to infer potential ecological roles of the microbial community.

Results

Isolation and Screening of Pinene-Degrading Bacterial Strains​

Nine culturable bacterial species were isolated from the gut microbiota of third-fourth and fifth instar larvae using four media types, including Enterococcus casseliflavus, Klebsiella variicola, K. pneumoniae, K. quasivariicola, Enterobacter hormaechei, E. ludwigii, Priestia megaterium, P. aryabhattai, and Bacillus safensis. These isolates spanned two phyla (Proteobacteria and Firmicutes), three families (Enterobacteriaceae, Bacillaceae, and Enterococcaceae), and five genera (Klebsiella, Enterobacter, Enterococcus, Priestia, and Bacillus) (Table S1). Growth curve analysis under varying pinene concentrations (100–300 mg/L) identified K. variicola L13 and E. hormaechei L16 as the most robust strains (Fig. S1), suggesting their potential for pinene degradation (Fig. 1).

Fig. 1.

Fig. 1

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Growth curves of Klebsiella variicola and Enterobacter hormaechei in minimal medium with various concentrations of pinene. Growth curves of K. variicola in MM medium containing α-pinene (a) and β-pinene (b). Growth curves of E. hormaechei in MM medium containing α-pinene (c) and β-pinene (d). Three replicates were set at each time point. The minimal medium without pinene was used as the control group.

Degradation of Two Pinene Compounds by Klebsiella variicola and Enterobacter hormaechei

The degradation curve showed that the concentration of pinene in the treatment group added with Klebsiella variicola and Enterobacter hormaechei was significantly lower than that in the control group over time (Fig. 2). At the final determination time point, K. variicola degraded 60.8% of α-pinene and 60.5% of β-pinene, while E. hormaechei achieved 62.3% and 61% degradation for respective isomers. Natural degradation controls showed significantly lower rates (37% for α-pinene, 49.5% for β-pinene) (Fig. 2). These results demonstrate that both gut bacterial strains actively participate in pinene compound breakdown, potentially facilitating host adaptation to pine needle digestion through microbial-assisted detoxification.

Fig. 2.

Fig. 2

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Degradation efficiency of two terpenoid compounds by Klebsiella variicola and Enterobacter hormaechei. a Structural formula of α-pinene. b Structural formula of β-pinene. c Degradation curve of α-pinene by K. variicola and E. hormaechei. d Degradation curve of β-pinene by K. variicola and E. hormaechei. The data in the figures are means ± SE

General Profile of 16S rRNA Sequencing Data

The gut microbiota of A. posticalis across developmental stages was characterized using Illumina MiSeq PE300 sequencing, yielding 1,845,620 high-quality sequences (772,643,874 total bases, average length = 420 bp). Cluster analysis identified 340 operational taxonomic units (OTUs) spanning 1 kingdom, 17 phyla, 25 classes, 59 orders, 100 families, 185 genera, and 246 species. Rarefaction curves plateaued (Fig. S2), confirming adequate sequencing depth, while significant inter-group versus intra-group variation (p < 0.001) validated sample stratification. OTU richness peaked in first–second instar larval guts, followed by eggs. All samples exhibited > 99% good’s coverage (Table S2), demonstrating comprehensive representation of bacterial diversity throughout the host’s life cycle.

Comparison of the Bacterial Communities of A. posticalis at Different Developmental Stages

Alpha diversity analysis revealed significant developmental stage–specific variations in the gut microbiota of A. posticalis (p < 0.05). The Sobs, Chao, Ace, Shannon, and Simpson indices collectively demonstrated that eggs and first–second instar larvae harbored significantly richer and more diverse bacterial communities compared to other developmental stages (Fig. S3).

The composition of the bacterial community in different developmental stages of A. posticalis presented distinct stage-specific patterns at the genus level. Wolbachia dominated in eggs (86%) and first-second instar larvae (73.9%). Klebsiella was predominant in third-fourth (46.5%) and fifth instar larvae (52.7%). Raoultella showed peak abundance in sixth instar larvae (54.4%) while Bacillus (42.9%) and Acinetobacter (42.4%) were most abundant in adults (Fig. 3a). Notably, the microbiota profiles of eggs and early instar larvae showed remarkable similarity, as did those of mid-to-late instar larvae. In contrast, adult gut microbiota displayed a distinct composition compared to other developmental stages (Fig. 3b). Some core bacterial genera exhibited stage-specific distribution patterns. Wolbachia was ubiquitous but most prevalent in eggs (44% of total) and first-second instar larvae (38%). Klebsiella accumulated predominantly in third-fourth (45%) and fifth instar larvae (51%). Raoultella showed exclusive enrichment in sixth instar larvae (80%). Bacillus (80%) and Acinetobacter (83%) were almost exclusively associated with adult stages (Fig. 3c).

Fig. 3.

Fig. 3

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Taxonomic profiling of gut microbiota in A. posticalis across developmental stages (genus-level resolution)

A total of nine culturable bacterial species were successfully isolated and purified from the gut microbiota of third-fourth and fifth instar larvae, representing five distinct genera. Notably, all isolated genera were detected in the high-throughput sequencing data of corresponding developmental stages, with the exception of Priestia. Among these, Klebsiella and Enterococcus emerged as the most abundant genera. The pinene-degrading strain K. variicola L13, isolated through culture-based methods, was phylogenetically matched to OTU427 in the sequencing dataset. This OTU demonstrated stage-specific abundance patterns, constituting 35.8% of the microbial community in third-fourth instar larvae and increasing to 60.1% in fifth instar larvae. While E. hormaechei L16 was not directly identified in the sequencing data, its corresponding Enterobacter genus was annotated, albeit at relatively low abundance levels.

Furthermore, hierarchical clustering analysis revealed stage-specific grouping patterns, with samples from the same developmental stage exhibiting greater similarity. Notably, adult and sixth instar larval samples formed distinct clusters, while egg and first–second instar larval communities showed close association. Similarly, third-fourth and fifth instar larval microbiota clustered together (Fig. 4a). The analysis demonstrated a positive correlation between developmental stage divergence and bacterial community dissimilarity, with greater temporal distance between stages corresponding to more pronounced microbial composition differences (Fig. 4b). Consistent with these findings, both PCoA and NMDS analyses confirmed the close phylogenetic relationship between egg and early instar (first–second) larval microbiota, as well as the strong similarity between mid-late instar (third-fourth and fifth) larval gut communities (Fig.4c, d).

Fig. 4.

Fig. 4

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Beta diversity analysis of gut microbiota across developmental stages

Screening ofKey Bacteria for the Growth and Development of A. posticalis

Network analysis revealed stage-specific microbial interactions, with first–second instar larvae exhibiting the highest network coefficient (2.069372), followed by eggs (1.750615), indicating their central ecological importance. Thirty-nine genera demonstrated significant network coefficients, including five core taxa: Bacillus, Enterobacter, Wolbachia, Klebsiella, and Serratia, suggesting their crucial roles in host development (Fig. 5a). Univariate analysis showed limited species connections in third-fourth instar larvae, where Wolbachia and Serratia emerged as keystone genera (Fig. 5b). The fifth instar larval gut microbiota was dominated by Klebsiella (total centrality coefficient = 0.69533), demonstrating its structural importance (Fig. 5c). Eggs displayed a distinct network pattern where Wolbachia, represented by the largest node with numerous connections, served as the primary hub genus (total centrality = 0.52916) (Fig. 5d).

Fig. 5.

Fig. 5

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Microbial co-occurrence network analysis across key developmental stages. a Global network of bacterial interactions. b Stage-specific network for 3rd-4th instar larvae. c Stage-specific network for 5th instar larvae. d Stage-specific network for egg microbiota

At the genus level, six bacterial taxa—Wolbachia, Klebsiella, Raoultella, Bacillus, Acinetobacter, and Serratia—showed highly significant stage-specific enrichment patterns (p < 0.001), suggesting their potential as developmental stage–specific keystone taxa (Fig. S4). Notably, Wolbachia demonstrated predominant abundance in both eggs and first–second instar larval guts (Fig. 6b). Klebsiella exhibited marked proliferation in mid-developmental stages, particularly in third-fourth and fifth instar larvae, while Raoultella showed exclusive dominance in sixth instar larvae (Fig. S4).

Fig. 6.

Fig. 6

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LEfSe multilevel discriminant analysis of species differences

LEfSe analysis was performed to identify the main bacterial communities of different taxa at various taxonomic levels among groups (LDA score threshold set at 3) (Fig. 6, Fig. S5). The results revealed distinct microbial signatures across developmental stages. At the OTU level, 20 OTUs were identified as significant, with OTU427 being classified as K. variicola. This particular OTU emerged as a key bacterium in the gut of both third-fourth and fifth instar larvae, and was additionally confirmed as a degrading bacterium through in vitro culture experiments.

Functional Prediction of Bacterial Communities of A. posticalis

The functional analysis revealed that symbiotic bacteria across different developmental stages of A. posticalis were primarily involved in core metabolic pathways. Notably, the egg and first–second instar larval gut samples exhibited greater functional enrichment in environmental information processing–related genes compared to other developmental stages (Fig. 7a). In contrast, the gut bacterial communities of third-fourth and fifth instar larvae showed stronger enrichment in predicted phosphotransferase system functions (Fig. 7b, c). Additionally, the fifth instar larval gut demonstrated significantly higher bacterial functional abundance of glutathione S-transferase than all other developmental stages (Fig. 7d).

Fig. 7.

Fig. 7

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Functional prediction of bacterial communities in A. posticalis. a Clustering heatmap of primary metabolic pathways. b Clustering heatmap of secondary metabolic pathways. c Clustering heatmap of tertiary metabolic pathways. d Clustering heatmap of enzyme abundance.

Discussion

Oligotrophic pests typically maintain specialized feeding habits and harbor unique gut bacteria that facilitate host digestion, nutrient absorption, detoxification, and metabolic processes [19, 28]. For instance, when B. mori feeds on Cudrania tricuspidata leaves, its gut-associated B. subtilis assists in metabolizing the plant’s secondary metabolite isopentenyl isoflavones [19]. Similarly, the gut microbiota composition of C. medinalis shows significant diet-dependent variations [18]. In our study, two bacterial strains (K. variicola L13 and E. hormaechei L16) capable of degrading both α-pinene and β-pinene were successfully isolated. Both strains belong to the Enterobacteriaceae family, which has been reported to perform multiple ecological functions including chitin degradation [29], phosphate solubilization [30], pathogen colonization resistance [31], and potential α-pinene degradation [32]. Notably, the cultured K. variicola strain showed perfect correspondence with OTU427 in our high-throughput sequencing data. This OTU represented the dominant bacterial species in third-fourth and fifth instar larval guts and was identified among the 20 key OTUs through screening. These findings highlight the crucial role of K. variicola in A. posticalis physiology, and also indicate its potential role in the metabolism of terpenes present in pine needles in early larval stages. Supporting this, whole genome sequencing of K. variicola DX120E identified 39 genes involved in polyamine metabolism, transport, and secretion. Furthermore, K. variicola exhibits lipase activity and may contribute to agarwood resin formation in the gut of Neurozerra confera walker [33]. Compared to K. variicola L13, E. hormaechei L16 demonstrated superior pinene degradation capability in vitro assays. Previous studies have established E. hormaechei as a beneficial gut symbiont for housefly larvae, promoting host growth and development by enhancing gut microbiota diversity and humoral immunity [34]. A related strain (E. hormaechei KA3) isolated from Hypomeces squamosus gut achieved 32.05% lignin degradation with high lignin peroxidase activity [35], further demonstrating its metabolic versatility in insect systems. These collective findings confirm the significant positive effects of E. hormaechei on insect growth and development.

Our results revealed that Klebsiella dominated the gut microbiota of third-fourth and fifth instar larvae, representing approximately 50% of the total bacteria, with the K. variicola L13 successfully isolated in vitro. Klebsiella has been shown to participate in the digestive processes of various hosts including C. formosanus, Hermetia illucens, Eyprepocnemis alacris, and Harmonia axyridis, facilitating the decomposition of refractory dietary components. Wolbachia was the dominant genus during egg and first–second instar larval stages, accounting for over 70% of the total number of bacteria and was present throughout all developmental phases. This pattern has also been observed in the distantly related Nilaparvata lugens [36]. As a widely distributed α-proteobacterial endosymbiont, Wolbachia undergoes vertical transmission via host eggs and influences insect reproduction [37]. Raoultella dominated sixth instar larval guts. Studies demonstrate that native Raoultella can degrade quercetin, alleviating its growth inhibition in Thitarodes xiaojinensis and promoting heavier pupal weights [38], suggesting its potential role in A. posticalis pupation. Contrastingly, in Coleopteran Anoplophora glabripennis, Raoultella predominates in first instar larvae [39], highlighting interspecific variation in commensal bacterial composition. Bacillus and Acinetobacter became dominant in adult stages, collectively exceeding 40% of the total bacteria. This aligns with observations in Leptocybe invasa, where Bacillus abundance peaks during pupal and adult stages [40]. In the Hymenoptera leaf-cutter ants, Acinetobacter is also significantly enriched in adults. Studies have shown that Acinetobacter can promote carbon and nitrogen metabolism [41].

Cytochromes P450 (P450s) genes play an important role in the host adaptation of pine-feeding insects. Extensive research has demonstrated that bark beetles employ CYP450 genes to perform multiple functions: detoxifying tree-derived terpenes for pheromone biosynthesis, as well as oxidizing and eliminating terpenoid compounds in their antennae [42, 43]. Specifically, bark beetle larvae utilize the CYP6DE1 gene to hydroxylate α-pinene into three alcohol derivatives (trans-verbenol, cis-verbenol, and trans-myrtanol), which are subsequently esterified with oleic or palmitic acid and stored in fat bodies [42]. The CYP6DE1 enzyme in Dendroctonus ponderosae demonstrates substrate specificity for bicyclic monoterpenes, particularly α-pinene and β-pinene, catalyzing their hydroxylation [44]. Meanwhile, CYP345E2 exhibits broader catalytic capabilities, epoxidizing both α-pinene and limonene while also hydroxylating β-pinene [45]. Our functional prediction analysis of A. posticalis bacterial communities revealed significant enrichment in detoxification metabolic pathways. We successfully isolated and characterized two pinene-degrading bacterial strains (K. variicola and E. hormaechei) from A. posticalis. We hypothesize that K. variicola and E. hormaechei strains in A. posticalis may harbor detoxification-related genes, including cytochrome P450 variants. Chen et al. found that Klebsiella variicola B2 strain can effectively decompose pesticides in soil through its own cytochrome P450 oxygenase system [46]. These microbial enzymes may facilitate host adaptation by catalyzing the hydroxylation or epoxidation of pine needle terpenes, thereby reducing phytochemical toxicity, improving nutritional assimilation, and supporting developmental homeostasis. Such symbiotic detoxification mechanisms likely constitute a critical evolutionary adaptation enabling pine-feeding insects to overcome plant defensive compounds. In the future, it can be used as a target for biological control of A. posticalis through the transformation of engineered bacteria or the search for antagonistic bacteria.

Functional prediction analysis of bacterial communities revealed significantly higher abundance of glutathione S-transferase–related functions in fifth instar larval guts compared to other developmental stages. This finding parallels observations in Pieris rapae, where four specific GST genes (PrGSTe2, PrGSTo4, PrGSTs4, and PrGSTt1) showed predominant expression in fourth instar larvae [47]. Similar developmental stage–specific expression patterns of GST genes have been documented in Mythimna separata [48]. Comparative analysis of termite gut microbiota evolution demonstrated remarkable functional conservation across species, with different dietary groups maintaining similar microbial compositions and functional gene repertoires. Notably, dietary variations primarily influenced gene abundance rather than introducing novel genetic pathways [11, 14]. In the oligophagous insect C. medinalis, functional prediction of gut bacteria revealed enrichment of carbohydrate metabolism–related enzymes, and antibiotic-mediated gut microbiota disruption significantly impaired host digestive capacity [18]. These findings suggest that bacterial communities in A. posticalis fifth instar larval guts may contribute to host detoxification metabolism through their enzymatic capabilities. Furthermore, functional profiling showed greater enrichment of metabolic pathways in third-fourth and fifth instar larvae compared to other developmental stages. We hypothesize that these functionally specialized gut bacteria facilitate A. posticalis’ nutrient acquisition and assimilation from its food sources. A common method for studying the functions of intestinal bacteria is to create germ-free insects, usually by using antibiotics, and then by adding specific bacterial strains to the gut to determine their functions. However, in this study, we were severely constrained by the fact that A. posticalis is an annual species and cannot be reared under artificial laboratory conditions, so we verified the functions of the bacteria in vitro.

In this study, we systematically investigated the gut microbial ecology of the oligophagous pest A. posticalis through integrated approaches. Using traditional culture methods, we successfully isolated and characterized two pinene-degrading bacterial strains (K. variicola and E. hormaechei) from A. posticalis, with in vitro assays confirming their significant terpenoid degradation capabilities. Complementing these findings, high-throughput 16S rRNA gene sequencing revealed stage-specific gut microbiota profiles across the insect’s life cycle. Functional prediction analysis demonstrates particular enrichment of detoxification metabolic pathways in larval gut microbiomes, suggesting their crucial role in host adaptation to pine needle phytochemicals. Our results demonstrate how A. posticalis’s gut microbiota facilitates pine needle detoxification and nutrient extraction, redefining the physiological basis for its host adaptation and enabling precision manipulation of its symbiotic microbiome for population control.

Supplementary Information

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Acknowledgements

We sincerely thank the anonymous reviewers of this paper for their valuable comments and constructive suggestions, which significantly improved the manuscript. We are also grateful to the Mount Tai Scenic Area Administration Committee for their generous support in sample collection during this research.

Author Contribution

Ningxin Wang and Weixing Shen contributed to the study conception and design. Material preparation, data collection and analysis were performed by Wenlong Zhang, Yao Wang, Bin Dong and Ningxin Wang. The first draft of the manuscript was written by Yao Wang, Shipeng Han and Ningxin Wang. All authors read and approved the final manuscript.

Funding

This work was supported by the Shandong Province Modern Agricultural Technology System (SDAIT-24), Natural Science Foundation of Shandong Province (ZR2022MC198), the Science and Technology of Small and Medium Enterprises Innovation Ability Enhancement in Shandong Province (2023TSGC0345), and the Mount Tai Scenic Area Science and Technology Project.

Data Availability

The raw 16S rRNA (V3-V4 region) amplicon sequencing data of *Acantholyda posticalis* from 33 samples have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession number PRJNA1293151. The associated BioSample metadata are available under accession numbers SAMN50015291 to SAMN50015323 (33 samples in total). The raw sequence reads can be retrieved using SRA accession numbers SRR34580271 to SRR34580303 (corresponding to each sample).

Declarations

Ethics Approval

Ethical approval was not applicable to this study.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yao Wang and Shipeng Han contribute equally to this work.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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(DOCX. 731 KB)

Data Availability Statement

The raw 16S rRNA (V3-V4 region) amplicon sequencing data of *Acantholyda posticalis* from 33 samples have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession number PRJNA1293151. The associated BioSample metadata are available under accession numbers SAMN50015291 to SAMN50015323 (33 samples in total). The raw sequence reads can be retrieved using SRA accession numbers SRR34580271 to SRR34580303 (corresponding to each sample).

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