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Article

Functional Role of Intestinal Symbiotic Microorganisms in Improving the Adaptability of Anoplophora glabripennis to Resistant Host Plants

by
Qi Gu
1,
Ruofeng Jia
1,
Shuai Guo
1,
Han Li
1,
Enhua Hao
1,
Xi Yang
1,
Pengfei Lu
1,* and
Haili Qiao
2,*
1
The Key Laboratory for Silviculture and Conservation of the Ministry of Education, School of Forestry, Beijing Forestry University, Beijing 100083, China
2
Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China
*
Authors to whom correspondence should be addressed.
Forests 2023, 14(8), 1573; https://doi.org/10.3390/f14081573
Submission received: 17 June 2023 / Revised: 24 July 2023 / Accepted: 30 July 2023 / Published: 1 August 2023
(This article belongs to the Special Issue Applied Chemical Ecology of Forest Insects)
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Abstract

:
To investigate the adaptation mechanism of Anoplophora glabripennis to traditional resistant Fraxinus, we used metabolomics, enzyme activity detection, and 16SrRNA sequencing technology to analyze the correlation among plants, insects, and symbiotic microorganisms. The results show that a total of 19 classes and 108 different resistant metabolites were screened from xylem of Fraxinus pennsylvanica and Fraxinus chinensis. Except iridoids, lignin, alkaloids, and derivatives; amines, cinnamic acids, and derivatives; and amino acids and derivatives, the rest of them were abundant in F. chinensis. The activity of digestive enzymes and detoxifying enzymes in the intestinal of F. pennsylvanica feeder was significantly higher than that of F. chinensis feeder. After feeding on two hosts, there were significant differences in the intestinal bacterial community of A. glabripennis. At the phylum level, the dominant phyla of intestinal bacteria after feeding on F. pennsylvanica and F. chinensis were Proteobacteria and Firmicutes, respectively. At the genus level, Raoultella (55.79%) and Lactococcus (57.52%) were the most dominant bacteria, respectively. The correlation analysis shows that β-glucosidase, exo-β-1,4-glucanase, lipase, carboxylesterase, and cytochrome P450 had a significant negative correlation with sesquiterpenoids, amino acids, and derivatives, and a significant positive correlation with lignin and amines. Raoultella, unclassified Enterobactriaceae, and Enterobacter in the gut community were negatively correlated with sesquiterpenes and amino acid derivatives and significantly positively correlated with lignin and amines. The correlations with defensive substances for Lactococcus, Enterococcus, and Gibbsiella were the exact opposite of those for these gut communities. This can provide a new idea for the prevention and control of A. glabripennis by studying the interaction among plants, insects and intestinal symbiotic microorganisms.

1. Introduction

Anoplophora glabripennis is a kind of burrowing insect that mainly feeds on the tissues under the bark of plants. In the face of phloem and xylem, where lignin is the main carbohydrate source and contains a lot of secondary metabolites [1], insects have formed special coping strategies. However, facing such a severe living environment, insects are not alone. Large studies have shown that there is a three-phase interaction between plants, insects, and intestinal microorganisms [2,3]. Insects have also used this relationship to develop different types of survival strategies [4]. Plants, as the media linking insects and microorganisms, have a certain cascade effect on the interaction between them [5].
In the evolutionary relationship between insects and plants feeding and being fed, plants achieve the purpose of self-protection by changing their morphological and physiological states to reduce the harm degree of insects [1,6,7,8]. With the feeding of insects, the damaged parts of plants stimulate the synthesis of secondary defense substances under the action of insect-inducible factors and enter the insect together with nutrients. The constant feeding of insects causes toxic substances to keep accumulating. When the concentration reaches a certain extent, it has a negative impact on the growth of insects [9]. In addition, some plant proteins, such as amino acid-degrading enzymes [10], can also participate in the defense process of plants against insects [11]. Since plants are the only food source for insects, the types and contents of defensive substances contained in plants have a great impact on the survival status of insects [12].
However, for the challenging environment created by food sources, insects can adapt to the host plants by changing their physiological and biochemical status. The ability to use cellulose efficiently and obtain enough energy from plant tissues composed of cellulose is crucial for xylophagous insects. Most xylophagous insects have relatively mature systems for decomposing cellulose [13,14,15]. There are also some other enzymes, such as lipase, protease, amylase, etc., that are important participants in the process of insect energy acquisition and help insects meet their own growth and development needs [15]. Secondly, in order to survive in the difficult environment and keep the internal environment relatively stable, burrowing pests express various detoxifying enzymes [16], including carboxylesterase [17], glutathione s-transferase [18], and cytochrome P450 [19]. It has been proven that excess expression of detoxifying enzymes can significantly enhance the detoxification metabolism’s ability and adaptability [19,20].
Due to the rich variety and content of toxic secondary metabolites in plants, it is not easy for insects to fully decompose and metabolize the ingested secondary metabolites of the toxic plant. The microbial community in the intestine plays an indispensable role in helping the xylophore beetle to face these challenges [2,21]. There are two ways for microbial communities to enter insects; one is through feeding activities, and the other is through vertical transmission from parents [22]. No matter how it enters the insect intestine, as long as it can stably reproduce in an insect, it may play a principal role in its survival and closely link host and wood breeders [22,23,24]. Some specific microorganisms also have the ability to degrade plant chemicals and even use secondary metabolites to remove the nutritional restriction of plants on insects [25]. For example, tannin, which can reduce the utilization of protein in food, is a ubiquitous substance in plants, and many microorganisms inhabiting insect intestines can produce tannase, which increases the potential of insect birth canal microorganisms to metabolize plant tannin [26,27]. Sphingomonas detected in the guts of some insects can synthesize a variety of oxygenases and glycoside hydrolases, which may be responsible for the degradation of various refractory aromatic compounds and polysaccharides [28]. In addition, the midgut flora also play a crucial role in the production of insect pheromones, the degradation of plant secondary metabolites, and the protection of insects from virus infection [28,29,30]. It is worth noting that when some microorganisms are lost in the intestine of insects, the normal growth and development of the host is also affected, and in serious cases, the survival rate declines [31]. These cases not only provide evidence that intestinal microbiota play a role in the metabolism of plant defense substances but also imply that they are crucial to insect life activity.
With the development of economic globalization, the circulation of materials around the world is becoming more and more frequent [32]. A. glabripennis has caused significant economic losses in many parts of the world due to its wide host range, which gradually expands the scope of damage [33]. However, with the field survey conducted by our research team in recent years, it was found that Fraxinus [34], which was considered to be the resistant species of A. glabripennis in the past, has caused extremely serious damage in Ningxia, China, but not in Cixi, Zhejiang. This shows that the host spectrum of A. glabripennis has been further expanded, which also brings new challenges to the prevention and control of A. glabripennis. In order to explore the key factors affecting the selection and adaptation of A. glabripennis, LC-MS was used to analyze the difference of secondary metabolites between Fraxinus chinensis and Fraxinus pennsylvanica. The larvae of longicorn beetles feeding on different hosts were systematically sampled, and the changes in intestinal enzyme activity were detected. The influence of different hosts on the structure and composition of the insect intestinal symbiotic microbial community was determined by sequencing. Finally, the correlation of the insects, plants, and microorganisms was analyzed to explore the adaptive strategies of A. glabripennis to traditional resistant species.

2. Materials and Methods

2.1. Acquisition of Plants and Maintaining Condition of Anoplophora glabripennis

The perennial branches of Fraxinus pennsylvanica and Fraxinus chinensis were picked from June to July in Cixi, Zhejiang (30°10′ N, 121°14′ E), and Guyuan, Ningxia (36°01′ N, 106°28′ E), respectively. Then, the samples were sent to the Forest Protection Laboratory of Beijing Forestry University in dry ice. Some of the plant branches were washed and the xylem was collected at low temperature. Eventually the xylem was ground into fragments for subsequent metabolomics detection. The rest was stored in −80 °C.
A. glabripennis larvae originated from a damaged tree in Baoding, Hebei (38°87′ N, 115°47′ E). The damaged wood was sealed by paraffin and mailed to the Forest Protection Laboratory of Beijing Forestry University. Larvae were acquired from the block. After that, instars of larvae were identified by measuring the head capsule width, and three-instar larvae that had the same size and health status as the experimental materials (2.40 mm–3.16 mm) were selected. The food source of the insects was branches 4–5 cm in diameter that were naturally thawed at 4 °C. Then, the branches were washed and the phloem was removed, cut to 5 cm, and transferred to a sterile 5 mL centrifuge tube. Before the feeding test, all larvae went hungry for 24 h, and then they were randomly divided into two groups and put in a centrifuge tube. The larvae were cultured in a constant temperature and humidity incubator, and the plant branches were replaced every two days for one month. Rearing temperature was 27–30 °C, humidity was 40%–60%, and illumination condition was black. All the tested larvae were starved for 24 h to empty the midgut food residue so as to facilitate the detection and analysis of physiological indicators and microorganisms.

2.2. Plant Metabolomics Analysis

Plant samples were kept at 4 °C throughout the analysis. Firstly, 20 mg of F. pennsylvanica and F. chinensis xylem were weighed and put in centrifuge tubes. Then, 500 μL methanol (containing 5 μg/mL 2-chloro-L-phenylalanine) was added, followed by homogenization at 50 Hz for 4 min and shaking for 2 min. Subsequently, the mixture was centrifuged at 12,000 rpm at 4 °C for 10 min. Supernatant was transferred to sampler vials for detection. An in-house quality control (QC) was prepared by mixing an equal amount of each sample. Extracted plant samples were analyzed using an Agilent 1290 Infinity IIUHPLC system coupled to an Agilent 6545 UHD and Accurate-Mass Q-TOF/MS. The chromatographic column was performed with a Waters XSelect ○R HSS T3 (2.5 μm 100 × 2.1 mm) maintained at 40 °C, and 1 μL was injected in positive and negative mode. The mobile phase was aqueous solution with 0.1% formic acid (A) and acetonitrile solution with 0.1% formic acid (B). The flow rate was 0.35 mL/min. Post time was set as 5 min for system balance. The optimized elution gradient was as follows: 0 to 2 min, 95% A:5% B; from 2 to 10 min, 95% A:5% B to 5% A:95% B; and from 10 to 15 min, 5% A:95% B for equilibrating the systems. Mass spectrometry was operated in both positive and negative ion modes.

2.3. Preparation and Determination of Anoplophora glabripennis Enzyme Activity

A. glabripennis larvae were dissected on ice, and the midgut was taken out and weighed. Pre-cooled phosphate buffer (pH = 7.4) was used to homogenize at low temperature according to the ratio of the midgut mass (g): phosphate buffer volume (mL) 1:9. After homogenization, the samples were centrifuged at 4 °C at 8000 rpm for 10 min, and the supernatant was stored at 4 °C until it was used as an enzyme source. The kits from Suzhou Keming Biotechnology Co., Ltd. (Suzhou Keming Biotechnology, Suzhou, China) were used to detect the enzyme activity of β-glucosidase, exo-β-1,4-glucanase, endo-β-1,4-glucanase, lipase activity, and the total protein concentration. The kit from Shanghai Enzymatic Biotechnology Co., Ltd. (Shanghai Enzymatic Biotechnology, Shanghai, China) was used to detect the enzyme activity of carboxylesterase, glutathione S-transferase, and cytochrome P450. Test procedures were in accordance with the manufacturer instructions.

2.4. DNA Extraction and PCR Amplification

A. glabripennis was starved for 24 h and surface disinfected for 1 min with 70% ethanol. Then, it was rinsed twice with sterile water before dissection. Insects were dissected under sterile petri dishes containing PBS and low temperature to obtain the midgut. The midgut was shifted to a sterile centrifuge tube containing 1 mL PBS buffer and grinded quickly to obtain intestinal homogenate. The tubes were then centrifuged at low speed (1000 rpm), and the supernatants were collected for bacterial DNA extraction. Five larvae were used in each group, and the procedure was repeated for each group three times. Individual larvae from different host species were collected and transferred to the same centrifuge tube; thus, larvae from F. pennsylvanica were designated as FP, and larvae from F. chinensis were designated as FC.
Midgut bacterial DNA was extracted using the E.Z.N.A.® soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to the manufacturer’s instructions. The DNA extract was detected by 1% agarose gel electrophoresis. DNA concentration and purity were detected by a NanoDrop 2000 UV-Vis spectrophotometer (Thermo Fisher Scientific, Wilmington, NC, USA). The hypervariable region V3–V4 of the bacterial 16S rRNA gene was amplified using an ABI GeneAmp R 9700 PCR thermocycler (ABI GeneAmp, CA, USA). PCR amplification of the 16S rRNA gene was performed as follows: initial denaturation at 95 °C for 3 min, followed by 27 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 45 s, single extension at 72 °C for 10 min, and ending at 4 °C. The PCR mixtures contained 5× TransStart FastPfu buffer 4 μL, 2 μL 2.5 mM dNTPs, 0.8 μL 5 μM forward primer, 0.8 μL 5 μM reverse primer, 0.4 μL TransStart FastPfu DNA polymerase, 10 ng template DNA, and finally, up to 20 μL ddH2O. PCR reactions were performed in triplicate. The PCR product was extracted from 2% agarose gel and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions and quantified using a Quantus™ Fluorometer (Promega, WI, USA). The amplicons were merged and purified on the Illumina MiSeq PE300 platform (Illumina, San Diego, CA, USA), and paired terminal sequencing was performed.

2.5. Analysis of Metabonomics, Enzyme Activity, and Sequence Processing Data

Raw data were converted into the common (mz.data) format by Agilent Masshunter Qualitative Analysis (Agilent Technologies, CA, USA). In the R software (4.1.2) platform, the XCMS (4.1.2) program was used for peak identification, retention time correction, and automatic integration pretreatment. Then, the data were subjected to internal standard normalization and weight normalization. After editing, the data matrices were imported into SIMCA-P (Umetrics, Umea, Sweden), mean-centered, and scaled to Pareto variance. Then, multivariate analysis was conducted.
The enzyme activity differences among the different hosts groups were analyzed by one-way analysis, and the treatment means were compared using the least significant difference (Duncan) test at the 5% significance level. To avoid false duplication, each experimental group had three sets of replicates. Data were analyzed statistically using the software SPSS 20.0, and the Origin software (2021) was used for charting.
Raw 16S rRNA gene sequencing reads were demultiplexed, quality-filtered by fastp version 0.20, and merged by FLASH version 1.2.7. Operational taxonomic units (OTUs) with a 97% similarity cutoff were clustered using UPARSE version 7.1, and chimeric sequences were identified and removed. The taxonomy of each OTU representative sequence was analyzed for taxonomic annotation by RDP Classifier version 2.2 against the 16S rRNA database using a confidence threshold of 0.7. Based on the species taxonomic information, a Venn map and a community histogram were drawn with R software (4.1.2), and statistical analysis was completed.

2.6. Correlation Analysis of Differential Metabolites with Intestinal Enzyme Activity and Intestinal Microorganisms

Different plant secondary metabolites affect the enzyme activity in insects and also cause changes in the composition of insect intestinal communities. Pearson correlation analysis between insect digestive enzymes and detoxifying enzymes fed by different hosts with plant defensive compound concentrations was conducted. Pearson correlation analysis between the highly rich microbial community in each group of host tree species feeders with plant defensive compounds was also presented. The Pearson test method of the spss20.0 software was used for the correlation analysis.

3. Results

3.1. Principal Component Analysis and System Stability

To verify the difference and stability of the metabolomics model, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS−DA) were used to analyze F. pennsylvanica and F. chinensis. A clear degree of separation of F. pennsylvanica and F. chinensis was shown for both positive and negative ion mode, indicating that the difference between the two groups was significant (Figure 1). Then, OPLS−DA, an effective supervised method for identifying ion peaks and sample classification, was used for subsequent analysis. The results show that the main parameters R2 and Q2 under positive and negative ion modes were greater than 0.4 (R2 = 0.993, Q2 = 0.984 under positive ion mode (Figure 2); R2 = 0.997, Q2 = 0.988 under negative ion mode (Figure 2)). Thus, the OPLS−DA model possessed very high reliability and predictability. In the PCA and OPLS−DA plots, two sets of samples showed a great separation extent, which indicates that there was a remarkable distinction in the metabolites between the two groups of Fraxinus.

3.2. Screening of Differential Metabolites of Insect Resistance

Plant defense compounds comprise many categories, mainly including terpenoids, phenolic compounds, and nitrogenous defense compounds (alkaloids, cyanogenic glycosides, mustard oil glycosides, etc.). According to the above three kinds of compounds, the differential metabolites in F. pennsylvanica and F. chinensis were screened (screening condition: VIP value > 1 and p < 0.05). The differential compound name was determined by comparing the accurate molecular weight with the HMDB online database. The results show that 19 categories and 108 kinds of differential metabolites were finally obtained (Table 1). Among them, organic heterocyclic compounds, flavonoids, and amino acids and derivatives were the most abundant compounds, containing 21, 20, and 17 compounds, respectively. According to the cumulative statistics of VIP values of differential metabolites, the top five categories were organic heterocyclic compounds, amino acids and derivatives, coumarins and derivatives, flavonoids, and polyphenols. By analyzing the relative content ratio of the two samples, it was found that the relative content of iridoids, polyphenols, alkaloids and derivatives, amines, fatty acyls, and cinnamic acid and derivatives in the F. pennsylvanica group was higher than those in the F. chinensis group, and the relative content of other substances in the F. pennsylvanica group was lower than that in the F. chinensis group. It can be seen that the species and content of insect-resistant metabolites in F. chinensis were higher than those in F. pennsylvanica.

3.3. Changes in Digestive Enzyme and Detoxifying Enzyme Activity in Larval Gut

The changes in digestive enzyme and detoxifying enzyme activity in the intestine after intake of F. pennsylvanica and F. chinensis are shown in Figure 3. The results indicate that the gut digestive enzyme activity of β-glucosidase (F = 7.944, p < 0.05), exo-β-1,4-glucanase (F = 16.685, p < 0.05), and lipase of F. pennsylvanica feeder was significantly higher than that of F. chinensis feeder, whereas there was no significant difference in the activity of exo-β-1,4-glucanase (F = 2.505, p = 0.145) (Figure 3A). The changes in detoxifying enzyme activity demonstrate that carboxylesterase (F = 62.433, p < 0.05) and cytochrome P450 (F = 101.458, p < 0.05) fed on F. pennsylvanica were significantly higher than those fed on F. chinensis, whereas there was no significant difference in the activity of glutathione s-transferase (F = 0.733, p = 0.408) (Figure 3B). It is worth noting that the expressions of different digestive enzymes and detoxification enzymes in insects showed the same trend despite feeding on different plants. Among digestive enzymes, β-glucosidase was the highest, followed by exonuclease β-1,4-glucanase and lipase, and the content of endo-β-1,4-glucanase was the lowest. Similarly, a similar situation existed for detoxifying enzymes. The content of carboxylate esterase was the highest, followed by cytochrome P450, and glutathione S transferase was the lowest.

3.4. OTU Annotation and Venn Diagram Analysis

In total, 48,551 and 39,649 high-quality and filtered sequences were obtained, from which 44 OTUs were obtained from F. pennsylvanica and F. chinensis larval midgut samples, respectively. There were 17 OTUs shared between the two samples, indicating that the two groups had certain similarity in species taxonomy. In addition, 11 and 16 unique OTUs were identified from larvae feeding on F. pennsylvanica and F. chinensis, respectively (Figure 4).

3.5. Analysis of Midgut Bacterial Community

A total of 6 phyla, 7 classes, 20 orders, 31 families, and 40 genera were detected in 44 OTUs. The community composition of each group was analyzed at the phylum and genus levels. The phyla Proteobacteria and Firmicutes were the dominant bacteria in both midgut samples fed on either host (Figure 5, Supplementary Table S1).
At the genus level, the bacteria from A. glabripennis midguts showed different distribution based on the host tree species. The top three dominant genera of F. pennsylvanica feeder were Raoultella (55.79%), unclassified Enterobacteriaceae (27.09%), and Enterobacter (16.1%). Similar to F. pennsylvanica feeders, high-abundance intestinal communities of larvae feeding on F. chinensis were mostly consistent within species but with differences in relative abundance; the relative abundance was Lactococcus (57.52%), Raoultella (35.6%), and Enterococcus (4.48%). What is noteworthy is that only Lactococcus had a higher relative abundance and was unique in larval midgut fed on F. chinensis among the common dominant genera (Figure 6, Supplementary Table S2).

3.6. Correlation between Differential Metabolites of Insect Resistance and Intestinal Enzyme Activity

The Person correlation analysis method was used to analyze the correlation between the differentially resistant substances in the two types of Fraxinus and their feeder midgut enzyme activity. The correlation coefficient is shown in Figure 7A. From the results, it can be seen that different kinds of intestinal enzymes showed different correlations with plant differential metabolites. Exo-β-1,4-glucanase, lipase, carboxylesterase, and cytochrome P450 showed significant negative correlations with most compounds and only showed significant positive correlations with iridoids, lignins, and amines. β-glucosidase showed a strong negative correlation with sesquiterpenes, schizolene ether, organic heterocyclic compounds, and amino acids and derivatives, and a strong positive correlation with lignin and amines. The activity of exo-β-1,4-glucanase and glutathione S transferase was almost unaffected by plant secondary metabolites (Supplementary Table S3).

3.7. Correlation between Differential Metabolites of Insect Resistance and Intestinal Bacteria

Correlation analysis was conducted between the differentially resistant substances in the two kinds of Fraxinus and intestinal bacteria (relative abundance greater than 1%), and the correlation coefficient is shown in Figure 7B. It can be seen from the results that the intestinal bacteria of insects showed a strong correlation with the differential metabolites of plants. Lactococcus, Enterococcus, and Gibbsiella had a very significant positive correlation with sesquiterpenes, diterpenes, schicycloene ether, coumarin and derivatives, flavonoids, isoflavones, neoflavones, organic heterocyclic compounds, benzenoids, arylsulfates, and amino acids and derivatives, whereas they showed a very significant negative correlation with iridoids, lignin, and amines. Raoultella and Enterobacter showed opposite correlations with Lactococcus. Unclassified Enterobacteriaceae showed a significant negative correlation with sesquiterpenes, flavonoids, arylsulfates, and amino acids and derivatives and a significant positive correlation with lignin and amines (Supplementary Table S4).

4. Discussion

In the process of co-evolution between plants and insects, different plants have different defense mechanisms to regulate the synthesis and release of resistant substances through their own metabolism so as to reduce the stress effect of insects. Insects digest and decompose these metabolites through physiological and biochemical reactions in vivo. Meanwhile, the microorganisms established in the intestine of insects play an important role. In this study, we combined the types of host plant metabolites, the changes in insect physiology and biochemistry, and the microbial community structure of the insect midgut in A. glabripennis for the first time to reveal the potential interaction mechanisms.

4.1. Host Metabolites Affect Intestinal Physiological and Biochemical Status of Anoplophora glabripennis Larvae

The physiological and biochemical status of insect intestine is largely affected by the host species. Observing the change trend in insect digestive enzymes and detoxification enzymes feeding on different hosts can reflect the ability of insects to absorb nutrition and detoxification efficiency to a certain extent.
In our correlation research results, exo-β-1,4-glucanase and lipase showed a significant negative correlation with most plant defense substances. However, β-glucosidase and endo-β-1,4-glucanase were hardly affected by secondary metabolites. We suspect that β-glucosidase and endo-β-1,4-glucanase are the main enzymes of cellulose decomposition in insects, which are the main channels of energy acquisition for A. glabripennis [35]. Ensuring that these two kinds of enzyme activity have complete function is very important. However, the functions of exo-β-1,4-glucanase and lipase in insects can be replaced by certain intestinal symbioses, which are easily affected by environmental factors [36]. The decreased activity of these digestive enzymes may be related to the nitrogen content in plants. Meanwhile, metabolomics results show that amino acids and their derivatives were significantly higher in F. chinensis than in F. pennsylvanica, indicating that nitrogen nutrients were more abundant in F. chinensis. As nitrogen nutrition is crucial for A. glabripennis, the larvae need to enhance the activity of digestive enzymes to obtain basic energy expenditure in the face of relative deficiencies in F. pennsylvanica [37,38,39]. In other words, the nutrients in the host are easier to use and transform, and the low activity of cellulolytic enzymes and lipolytic enzymes can obtain enough energy for the normal growth and development of insects. In contrast, relatively few nutrients are available for F. pennsylvanica, so to maximize the utilization of resistant hosts, it is necessary to enhance the activity of digestive enzymes to reduce the effects of low nutrition.
With the feeding process, insects are not only faced with how to efficiently use the nutrients of the host but also need to deal with a large number of plant defense substances [40]. Detoxification enzymes, as proteases that decompose toxic compounds in insect species, play an indispensable role in the process of insect adaptation to different host plants [41]. Because plants contain different allelopathic substances, feeding on different hosts can induce changes in the activity of various detoxifying enzymes in insects, change the toxicity of natural synthetic toxins to insects, and enhance the adaptation of insects to hosts [42,43]. However, using biosynthesis and detoxifying enzymes to maintain the energy budget implies a lot of demand for insects [44,45]. Due to the available energy being limited, therefore, insects need an energy trade−off between growth and detoxification. The results of the metabolomics and enzyme activity changes show that F. chinensis was rich in isoprenoid compounds, phenolic compounds, and nitrogen−containing organic compounds. At the same time, the detoxification enzyme activity in insects showed different degrees of reduction after feeding on F. chinensis. These results indicate that compared with F. pennsylvanica, exposure to the chemical defense compounds in F. chinensis had a certain inhibitory effect on the detoxification enzymes produced by A. glabripennis, which indirectly affected the energy trade−off between the metabolic decomposition and biosynthesis of insects [45,46]. Surprisingly, exposure to a much wider range and level of chemicals did not prevent A. glabripennis from continuing to harm F. chinensis. Therefore, we hypothesize that there is another way to help insects share environmental stress; that is, the gut microbiome plays an important role in alleviating allelopathic toxicity. In addition, in the correlation study, there was no obvious correlation between GSH S-transferase and any chemical, and there was no significant difference in the results of enzyme activity changes, which indicates that the large amount of GSH S−transferase expression could not be induced in F. chinensis or F. pennsylvanica. This suggests that insects can selectively respond to resistant substances in host plants [47].

4.2. Effects of Host Metabolites on Symbiotic Community

Because of the interaction of various internal and external factors, the intestinal microflora of insects show significant differences, even if the larvae feed on similar hosts [48]. In this study, the microbial communities in the intestine of the two host larvae showed consistency at the phylum level. Proteobacteria and Firmicutes are the dominant bacteria in the gut, accounting for more than 90% of the total intestinal flora, which is consistent with previous research results in other insects [49,50,51,52]. These microbial communities are also often reported as the main phyla in the intestines of the main pests [50]. The high abundance level of these phyla may be due to the active supplementation of insects or because the taxa of these phyla are more likely to invade and colonize insect hosts than other bacterial communities [53]. However, at the genus level, the high-abundance microbial community structure in the intestine of A. glabripennis was obviously changed due to the host plant species. In F. pennsylvanica feeder, Raoultella, Enterobacteriaceae, and unidentified Enterobacteriaceae were the dominant genera, whereas in F. chinensis feeder, the main microorganisms were Lacticoccus, Raoultella, and Enterococcus.
At the classification level, the differences in intestinal bacteria species feeding on host plants reflect the different metabolite characteristics of the host plant. At the same time, these differences are ultimately reflected in the role and function of gut microbiota, including the decomposition of refractory dietary compounds, the production of specific nutrients, and the provision of amino acids and cofactors. Our metabolic outcome data indicate that the concentrations of many compounds in the xylem of the two species of Fraxinus were significantly different, implying that larvae of different host species face different metabolite environments, which may amplify differences in gut bacteria between host species [54]. Although the composition of microbial communities in the insect intestinal tract is variable, the diversity of microbial communities in their gut is not random [55], and the presence of these frequently occurring symbiotic microorganisms in the breeder may be beneficial for better adaptation to the environment. Raoultella, Enterococcus, and unidentified Enterobacteriaceae are the representatives of such intestinal bacteria. These typical taxonomic communities belong to Enterobacteriaceae. Most members of Enterobacteriaceae have nitrogen fixation functions. Therefore, the colonization of such bacteria is often associated with the removal of nitrogen nutrition restrictions of stem borers. In addition, it has been reported that Raoultella can independently complete heterotrophic nitrification and aerobic denitrification, as well as decompose carbendazim [56], which may play a beneficial role for larvae facing various plant defensive compounds. Some strains of Enterobacteriaceae also play an important role in the production of insect pheromones and the degradation of plant secondary substances [27,28]. The results of the correlation analysis show that the dominant bacteria genera Lactobacillus, Gibbsiella, and Enterococcus showed a more significant positive correlation with a large number of phenolic substances, whereas the dominant bacteria genera Raoulella and Enterobacter showed a strong positive correlation with lignin, iridoids, and amines. This may be the reason why these intestinal microorganisms, which are predicted to have a strong metabolism of corresponding compounds, are abundant in the insect gut.

4.3. Potential Role of Microbial Community Structure Changes in Host Adaptation

It is worth noting that the relative abundance of Lactococcus, the dominant bacterium in F. chinensis, reached 57.52% but was not detected in F. pennsylvanica. Lactococcus can produce superoxide dismutase under anaerobic conditions, and metabolomics results show that the defensive substances in F. chinensis contained a large number of phenolic compounds. These compounds produce a large amount of reactive oxygen during the decomposition process. Stable colonization of Lactococcus in the intestine of A. glabripennis can protect the gut from free radical toxicity. Lactococcus is not only an important part of the lignin metabolism of termites but also can participate in the process of saccharide fermentation [57]. For A. glabripennis, which also feeds on plant xylem as termites, we inferred that such bacteria can provide nutrition supplementation for the host at a limited level. Enterococcus, another dominant bacterium in F. chinensis, is a common microbiota in the intestine of insects. It is generally regarded as an important digestive bacterium [58] that assists the host in the metabolism and decomposition of nutrient substances [59]. In addition, Lactococcus and Enterococcus have an inhibitory effect on the growth and development of pathogenic fungi in the intestine [60], which plays an important role in consolidating the stability of the internal environment and inhibiting the infection of pathogenic bacteria [61] and has the ability to improve host metabolic regulation and immunity [62]. Studies have shown that most Enterococcus produce acetate, reduce intestinal PH, resist the invasion of pathogenic bacteria, and may participate in the degradation of toxic substances in food [63,64,65]. The presence of Enterococcus in the larvae of Chilo suppressalis and Spodoptera litura reduces the insecticidal activity of pesticides [63]. Lactococcus and Enterococcus showed a strong positive correlation with some terpenoids and nitrogenous compounds, which also suggests that the dominant symbiotic community had a strong ability to metabolize toxic compounds in F. chinensis. However, no corresponding intestinal bacteria showed any correlation with terpenes, fatty acyls, or cinnamic acids and derivatives. Therefore, we hypothesized that the dominant bacteria that colonize the insect gut are not fully efficient in the catabolism of toxic compounds that enter the insect gut.
In addition to the above bacteria with high relative abundance, some specific bacteria with low relative abundance were present in both host plants (Supplementary Table S2). The presence of these specific bacteria can also biotransform and decompose the plant secondary substances that cannot be directly metabolized and digested by living organisms after entering the intestine [66]. For example, Enterococcus casei can ferment the flavonol in flavonoid compounds into glycosides [67]. Acinetobacter can degrade phenolic glycosides and reduce cytotoxicity [68]. Bifidobacterium can degrade some phenols into coumaric acid and caffeic acid [69]. Pseudomonas can efficiently decompose alkaloids [70], and the degradation efficiency can even reach 100% [71]. Lactobacillus secretes β-glucosidase under anaerobic conditions, which can assist in the completion of the deglycosylation of flavonoids and promote the metabolic transformation process of flavonoids [72]. Glutamicibacter has the ability to fix nitrogen, hydrolyze phosphorus, hydrolyze potassium, and produce ACC deaminase, and it has a strong ability to decompose cellulose [73,74]. Although the relative content of these bacteria is not very rich in the insect intestine, it could be an important part of assisting the host to enhance its adaptability.
There is no doubt that a single bacterium can achieve the transformation of secondary substances, but in most cases it is the result of a variety of intestinal microorganisms working together. For example, during the conversion of daidzein to estrol, it is subject to the synergistic effect of a variety of bacteria, such as Bacteroides ovatus, Ruminococcus, Streptococcus, Lactobacillus mucosa, Enterococcus faecalis, and Gordonia [75]. Therefore, it is particularly important to study the potential interaction of various intestinal microorganisms in A. glabripennis. Moreover, the dominant bacteria in the insect intestine can only metabolize some toxic compounds and cannot completely eliminate all of the negative effects of host plants on insects [54]. In addition to bacteria, fungi are an important member of the insect gut microbiota. The colonization of these intestinal fungi also has a significant impact on the host’s material metabolism. It is still unknown which strategy insects adopt to deal with insect resistant secondary metabolites that have not yet been metabolized to further eliminate the negative effects of plants on insects. Therefore, our subsequent research will focus on the dynamic collaboration between microbial communities, including bacteria and fungi, and further clarify the role of intestinal microbial pathways in the process of host adaptation to host plants.

5. Conclusions

In summary, our studies demonstrated that there are significant differences in the categories and contents of secondary metabolites between F. chinensis. and F. pennsylvanica, which significantly affects the activity of enzymes in the insect intestine and relative abundance of gut bacterial communities. The differences in intestinal bacteria species ultimately reflected in the role and function of gut microbiota. Our correlation analysis results indicate that gut bacteria predicted to be able to metabolize specific compounds exhibit strong positive correlations with these compounds, including dominant bacterium and specific bacterium. However, some metabolites are not associated with any kind of bacteria, which may be due to limitations in the metabolic capacity of the gut microbiota. Collectively, the intestinal community may have a powerful function in helping Anoplophora glabripennis adapt to different host plants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14081573/s1, Table S1. Relative abundance of intestinal bacteria in A. glabripennis at the phylum level after feeding on two hosts. Table S2. Relative abundance of intestinal bacteria in A. glabripennis at the genus level after feeding on two hosts. Table S3. Correlation coefficient between secondary metabolites and intestinal enzyme activity in the Fraxinus group. Table S4. Correlation coefficient between secondary metabolites and intestinal bacteria in the Fraxinus group.

Author Contributions

Majority of the bioinformatics studies and experiments, Q.G.; sample collection, R.J. and S.G.; sample pretreatment, R.J., S.G. and H.L.; data curation, H.L., E.H. and X.Y.; writing—original draft preparation, Q.G.; project proposal, design of the whole study, writing and revision of the manuscript, P.L. and H.Q. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Alashan League Science and Technology Program Project (AMYY2022-14), the National Key R&D Program of China 377 (2021YFD1400900), and the National Natural Science Foundation of China (grant No. 31570643, 81774015). The funders had no role in the design of the study, the data collection and analysis, the decision to publish, or the preparation of the manuscript.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. PCA positive (a) and negative (b) ion mode scores of xylem samples from F. pennsylvanica and F. chinensis.
Figure 1. PCA positive (a) and negative (b) ion mode scores of xylem samples from F. pennsylvanica and F. chinensis.
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Figure 2. OPLS−DA positive (a) and negative (b) ion mode scores of xylem samples from F. pennsylvanica and F. chinensis.
Figure 2. OPLS−DA positive (a) and negative (b) ion mode scores of xylem samples from F. pennsylvanica and F. chinensis.
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Figure 3. Comparison of digestive enzyme (A) and detoxification enzyme (B) activity of larvae fed on two kinds of Fraxinus. Statistical analysis was performed using ANOVA. Different superscripts were considered significantly different (p < 0.05).
Figure 3. Comparison of digestive enzyme (A) and detoxification enzyme (B) activity of larvae fed on two kinds of Fraxinus. Statistical analysis was performed using ANOVA. Different superscripts were considered significantly different (p < 0.05).
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Figure 4. Venn diagram of OTU distribution of gut microorganisms of A. glabripennis in two hosts.
Figure 4. Venn diagram of OTU distribution of gut microorganisms of A. glabripennis in two hosts.
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Figure 5. Relative abundance of intestinal bacteria in A. glabripennis at the phylum level after feeding on two hosts. Note: FC means F. chinensis; FP means F. pennsylvanica.
Figure 5. Relative abundance of intestinal bacteria in A. glabripennis at the phylum level after feeding on two hosts. Note: FC means F. chinensis; FP means F. pennsylvanica.
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Figure 6. Relative abundance of intestinal bacteria in A. glabripennis at the genus level after feeding on two hosts. Note: FC means F. chinensis; FP means F. pennsylvanica.
Figure 6. Relative abundance of intestinal bacteria in A. glabripennis at the genus level after feeding on two hosts. Note: FC means F. chinensis; FP means F. pennsylvanica.
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Figure 7. Correlation coefficient thermogram. (A) Thermogram of correlation analysis between plant metabolite content and insect intestinal enzyme activity. (B) Thermogram of correlation analysis between plant metabolite content and relative content of insect intestinal microorganisms. * p < 0.05 and ** p < 0.01 for the indicated significance.
Figure 7. Correlation coefficient thermogram. (A) Thermogram of correlation analysis between plant metabolite content and insect intestinal enzyme activity. (B) Thermogram of correlation analysis between plant metabolite content and relative content of insect intestinal microorganisms. * p < 0.05 and ** p < 0.01 for the indicated significance.
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Table 1. Classification of metabolites related to insect resistance.
Table 1. Classification of metabolites related to insect resistance.
CategoryNameNumberVIPFold Change
Isoprenoid derivativeSesquiterpene312.262380.12282105
Diterpenoid34.211440.27948403
Triterpene610.374810.60262061
Iridoids11.178932.01966533
Schicycloene ether16.373680.08465611
PhenolsFlavonoid2020.972690.43348063
Coumarin and derivatives1323.139150.48444245
Polyphenol1016.270280.39015662
Lignin13.485713.79855115
Isoflavone57.918470.43254758
Neoflavone12.132210.12592673
Phenolic acid515.176830.62583462
Nitrogenous compoundAlkaloids and derivatives58.331851.19046171
Organic heterocyclic compounds2150.013670.40141739
Amines12.880293.77167077
Benzenoids34.227630.2577388
Arylsulfates11.393720.08986068
Fatty acyls68.985491.16805049
Cinnamic acids and derivatives23.001781.14433432
Amino acids and derivatives1729.69490.071145
Note: VIP means the contribution rate of substance in the difference groups. The higher the VIP is, the higher the contribution rate is. Fold change means the ratio of the contents of all compounds in F. pennsylvanica and F. chinensis.
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Gu, Q.; Jia, R.; Guo, S.; Li, H.; Hao, E.; Yang, X.; Lu, P.; Qiao, H. Functional Role of Intestinal Symbiotic Microorganisms in Improving the Adaptability of Anoplophora glabripennis to Resistant Host Plants. Forests 2023, 14, 1573. https://doi.org/10.3390/f14081573

AMA Style

Gu Q, Jia R, Guo S, Li H, Hao E, Yang X, Lu P, Qiao H. Functional Role of Intestinal Symbiotic Microorganisms in Improving the Adaptability of Anoplophora glabripennis to Resistant Host Plants. Forests. 2023; 14(8):1573. https://doi.org/10.3390/f14081573

Chicago/Turabian Style

Gu, Qi, Ruofeng Jia, Shuai Guo, Han Li, Enhua Hao, Xi Yang, Pengfei Lu, and Haili Qiao. 2023. "Functional Role of Intestinal Symbiotic Microorganisms in Improving the Adaptability of Anoplophora glabripennis to Resistant Host Plants" Forests 14, no. 8: 1573. https://doi.org/10.3390/f14081573

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