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Article

Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li

by
Caixia Liu
1,2,
Lingyu Liang
1,
Huimin Wang
1,
Zheng Wang
3 and
Quan Lu
1,4,*
1
Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Chinese Academy of Forestry, Ecology and Nature Conservation Institute, Beijing 100091, China
2
Institute of Plant Protection, Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China
3
College of Plant Protection, Shandong Agricultural University, Tai’an 271018, China
4
School of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China
*
Author to whom correspondence should be addressed.
Forests 2025, 16(10), 1584; https://doi.org/10.3390/f16101584
Submission received: 16 September 2025 / Revised: 10 October 2025 / Accepted: 14 October 2025 / Published: 15 October 2025
(This article belongs to the Special Issue Biological Control and Management of Tree Diseases and Insect Pests in Forests)
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Abstract

Dendroctonus armandi is a native bark beetle that infests healthy Pinus armandii Franch. in western China. The complex symbiotic relationships with diverse microbes are critical to hosts for survival and outbreak dynamics. Understanding the potential functions and assembly metabolisms of these symbiotic microbes to host colonization are therefore crucial. Metagenomic analysis revealed that gut microbial communities differed from cuticular ones significantly. The cuticle exhibited greater fungal diversity, while the gut supported a significantly higher bacterial diversity. Our findings indicated that gut unclassified Burkholderiales, Escherichia, Bacteroides and Prevotella may play a crucial role in degrading terpenes, phenols and polysaccharides rather than cuticular microbes. Stochastic processes appeared to be served as the primary drivers shaping the core microbial community structures. Cuticular dominant and functional microbial community assemblies except for Escherichia may be primarily driven by stochasticity to adapt the unstable habitats. The direct comparison of gut and cuticular microbiomes may provide valuable insights into the specific functions of symbiotic microbes, and offer critical molecular data for broader understanding of symbiotic relationship between bark beetles and microbes.

1. Introduction

Bark beetles represent one of the most species-rich groups within the Coleoptera, with over 7500 species recorded globally, which poses a threat to the stability of forest ecosystems [1]. They mainly feed on phloem of coniferous trees. However, the bark contains abundant terpenoids and phenolic compounds, which are toxic to bark beetles at high concentrations [2,3,4,5]. Symbiotic microbes can assist bark beetles in detoxifying these complex compounds [6,7]. Additionally, these microbes can also cooperate with hosts to degrade cellulose, hemicellulose, and other polysaccharides, which are crucial carbon sources for bark beetle growth and development [8,9], or neutralize these defensive capabilities to facilitate colonization. Therefore, the microbes frequently maintain symbiotic relationships with bark beetles [10,11]. Studies have revealed that the primary microbial habitats of insects are the gut and cuticle [12]. Gut microbes exhibit remarkable diversity in acidic environments and nutrient-rich conditions, creating a suitable niche for bacterial growth [13]. Gut harbors significantly greater bacterial diversity [14,15]. They play crucial roles in facilitating the digestion, nutrient absorption, and metabolic processes for bark beetles [8,9]. It can also modulate the interactions and resist the pathogens’ invasion, which are closely associated with the onset of host diseases [2,16,17,18].
Conversely, the cuticular microbiota exhibits relatively lower diversity than the gut, which primarily colonizes various areas, such as the oral cavity and mycangia [19,20]. The cuticular environment differs markedly from the gut, harboring distinct microbial communities that can protect and maintain microecological balance, inhibit the proliferation of detrimental microbes, and enhance host survival [21]. While cuticular microbes may be involved in metabolism and immune regulation [2,22], their roles are relatively less understood than those of gut microbes. To date, studies have explored cuticular fungal diversity and pathogenicity [23,24,25], gut microbial community composition [26,27,28,29], microbial interaction, and metabolic abilities of microbes associated with bark beetles [30,31,32,33,34,35] with cultured, high-sequencing, and metagenomic methods [33]. However, it was quite poor in terms of genes used to annotate the degradation of complex compounds. And direct comparisons of microbial functional profiles between gut and cuticular habitats remain limited, hindering an understanding of the microbial-specific functions of Dendroctonus armandi.
Furthermore, the mechanisms underlying microbial community assembly have emerged as pivotal elements to understand microbial diversity and forest ecosystem stability [34,35]. Gut microbial communities are mainly shaped by stochastic processes [36,37,38], and non-intestinal microbial communities are mainly driven by deterministic processes [38]. However, microbial community assembly may not be dominated by one mechanism; the combined effects of both mechanisms may be more conducive to driving the microbial assemblies [39]. To date, the main driving forces of the microbial community assembly process for D. armandi remain unexplored, decelerating insights into its symbiotic relationship between D. armandi and associated microbes.
In this study, metagenomic sequencing was employed to analyze gut and cuticular microbes associated with D. armandi. Microbial community structures and functional characteristics of both habitats were directly compared. Further, we screened core microbes to assess the primary drivers of gut and cuticular microbial community assemblies. Our findings will provide molecular data on the role of gut and cuticular microbes in assisting hosts to colonize the trees, and lay a scientific basis for future microbial-based control of forest pests and diseases.

2. Materials and Methods

2.1. Pine Logs and Bark Beetle Collection

Pine cut-logs (diameter 27–35 cm, length 40–50 cm), approximately 45 years old, were collected from Shanxi Province, China, in May 2023 (Table 1). Mature second-generation adults were removed from different galleries within a debarked log. Species were identified according to the morphological descriptions by Six [40]. A total of 210 adults were collected and assigned to three groups. The guts of 70 individuals were pooled (minimizing the differences among individuals), and the remaining tissues, cuticle, oral cavity, glandular reservoirs, antennal segments, etc. (cuticle accounts for most as cuticular samples). These tissues for each adult were separately placed into 2 mL sterile tubes. All of the above operations were conducted on the ice to minimize pollution and reduce DNA contamination. Six samples were snap–frozen in liquid nitrogen and stored in the laboratory at –80 °C until total DNA extraction and subsequent metagenomic sequencing.

2.2. Metagenomic Data Acquiring and Uploading

DNA extraction, library construction, quality inspection, and metagenomic sequencing were conducted by Beijing Biomarker Biotechnology Company (Beijing, China) using Illumina NovaSeq6000 (NovaSeq 6000 S4 Reagent Kit, San Diego, CA, USA). Sequence alignment, assembly (filtering contigs less than 300 bp), and annotation were performed using Dendroctonus valens LeConte as the reference genome (GenBank accession number: GCA_024550625.1). Gene redundancy was conducted with a 95% similarity and 90% coverage threshold [41]. The original metagenomic data were uploaded to NCBI, with detailed information provided in Table 2.

2.3. Gut and Cuticular Microbial Composition Analyses

Gut and cuticular microbial community compositions were primarily analyzed at the phylum and genus levels. Alpha diversity (α-diversity) was assessed using the Shannon, Simpson, Chao1, and the observed species indices based on Student’s t-test. Differences in fungal and bacterial communities for both samples were calculated using a t-test in SPSS R26.0.0.0. Linear discriminant analysis Effect Size (LEfSe) analysis was performed to assess differences in microbial diversity between gut and cuticular samples.

2.4. Gut and Cuticular Microbial Functional Analyses

Taxonomic annotation of microbes associated with D. armandi was performed using the non-redundant (NR) protein sequence database. Unigenes and enzymes involved in complex compounds degradation were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGGs) and Carbohydrate-Active enZYmes (CAZy) databases. Microbial functional differences were examined in the gut and cuticular samples. Gene relative abundances of all pathways were assessed using STAMP (R version 4.1.3) analysis (https://www.omicstudio.cn/tool/84, accessed on 19 March 2025) based on the Wilcoxon test to determine the difference in both samples.

2.5. Gut and Cuticular Microbial Community Assembly Analyses

The dominant taxa, including Erysiphe, Rhizophagus, Enterospora, ophiostomatoid fungi, Bacteria unclassified, Thiobacillus, Enterobacter, Wolbachia, Microbacterium were screened across microbial diversity analysis, and functional taxa fungi unclassified, Rhizopus, Escherichia, Prevotella, Bacteroides, Clostridium, and Ruminococcus were screened as core taxa to assess the crucial drivers of gut and cuticular community assemblies. Gene-related sequences of each microbial taxon were aligned using MEGA 7.0 [42] or MAFFT (https://mafft.cbrc.jp/alignment/server/, accessed on 13 October 2025). PhyloSuite version 1.2.3 was employed to convert the formats and build maximum likelihood (ML) phylogenetic trees, with 5000 bootstraps and 1000 replicates in SH–aLRT branch tests [43]. Gene abundance and corresponding phylogenetic tree files (selected for higher abundance at the top 1000 in a file of >10,000 genes) related to different core microbes were jointly used for acquiring the weighted beta-nearest taxon index (βNTI) in null model analyses.
A null model was applied to evaluate the dominant drivers of microbial community assembly processes [34]. The R packages “picante 1.8.2” (https://cran.rstudio.com/bin/windows/contrib/4.2/picante_1.8.2.zip, accessed on 13 October 2025) [44] and “ape 5.8” (https://cran.rstudio.com/bin/windows/contrib/4.2/ape_5.8.zip, accessed on 13 October 2025) [45] were mainly used to calculate the βNTI, with reference to Zhao et al. [46]. |βNTI| was greater than 2 (βNTI > 2 and βNTI < −2); heterogeneous selection (HS) and homogeneous selection (HOS), indicative of deterministic processes, were considered as important driving forces. |βNTI| was less than 2, and stochastic processes governed the microbial assembly [34,47].
All data analyses were conducted using the GenesCloud (https://www.genescloud.cn/, accessed on 13 October 2025) and Omicstudio Cloud platform (https://www.omicstudio.cn/, accessed on 13 October 2025).

3. Results

3.1. Metagenome Sequencing of Microbes

The results of rarefaction curves showed that species and KOs were saturated for gut and cuticular samples, indicating that sequencing depth was sufficient for all samples (Figure S1a,b). Six metagenomes generated consisted of 37.14 to 37.14 Mbp using Illumina sequencing. The largest length of contigs was between 150,314 and 209,561. The maximum value of N50 can reach 10,011 bp. The percentage of assembled contigs (assembled contigs/sequenced reads) was from 74.75% to 97.80%. The number of genes was from 88,527 to 770,418, with the maximum length of genes ranging from 13,719 to 19,893 (Table S1).

3.2. Gut and Cuticle-Symbionts Community Structures

A total of 661 fungi were identified from the gut of D. armandi, spanning eight phyla and 365 genera, while 749 fungi were detected in the cuticle, including eight phyla and 384 genera. Both communities comprised Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Cryptomycota, Microsporidia, Mucoromycota, Zoopagomycota, and other unclassified taxa (Figure 1a). At the genus level, unclassified fungi, Spizellomyces, Basidiobolus, and Rhizopus exhibited relatively higher abundance in the cuticular samples than in the gut (Figure 1c).
For bacterial communities, 14,774 species were obtained from 149 phyla and 2479 genera in the gut, and 4091 species from 109 phyla and 2584 genera in the cuticular samples. Proteobacteria were the most abundant phylum, accounting for 26.22% in the gut and 41.87% in the cuticular samples. Bacteroidetes had 15.67% relative abundances in the gut samples and 6.11% in the cuticular samples (Figure 1b). At the genus level, the relative abundances of Escherichia and Prevotella were higher in the gut than in the cuticular samples (Figure 1d).
The Shannon, Simpson, Chao1, and Observed species indices showed the differences were not statistically significant. However, it was observed that higher fungal diversity in the cuticular samples than in the gut (Figure 2a). LEfSe analysis presented that Catenaria, Lichtheimia, Phycomyces, and other fungi were significantly more abundant in the cuticular samples (Figure 2c).
Conversely, gut bacterial associates showed higher diversity than cuticular bacteria as reflected by the four diversity indices. And Shannon and Simpson indices indicated distinct differences between the gut and cuticular bacteria (Figure 2b). LEfSe analysis revealed that gut bacteria were more important than cuticular ones, while fungal symbionts were more prevalent in the cuticular samples than gut samples.

3.3. Gut and Cuticular Microbial Functional Characteristics

Functional pathways comparisons showed that gut and cuticular symbiotic microbes only had a slight difference in the galactose metabolism pathway (map00052) (p = 0.0495) (Figure 3a). A total of 4807 unigenes were annotated in this pathway, including 19 and 33 fungal unigenes, 4771 and 135 bacterial unigenes in the gut and cuticular samples, respectively. These unigenes were predominantly associated with the gut Prevotella, unclassified Firmicutes, Bacteroides, and Clostridium (Figure 3b–e).
The results showed that there were no differences for degrading terpenoids, phenols, and polysaccharides in the gut and cuticular samples. Six KEGG Orthologies (KOs) and six enzymes associated with terpenoid degradation were found in the gut samples. Only three KOs and three enzymes were present in the cuticular samples (lacking K14731, K10533, and K01825) (Figure 4a). A total of 215 unigenes were annotated, of which 28 were shared, and 172 were unique bacterial unigenes in the gut samples. The cuticular samples contained four unique fungal unigenes and 11 unique bacterial unigenes (Figure 4b). It indicated that gut unigenes may play more important roles in degrading terpenes. These unigenes were mainly distributed in Burkholderiales unclassified, Chloroflexi unclassified, Firmicutes unclassified, and bacteria unclassified (Figure 4c). Cuticular fungal unigenes were mainly annotated in Rhizopus, Rozella, Verruconis, and Syncephalastrum (Figure 4d).
A total of 20 unigenes corresponding to 12 KOs and six enzymes involved in the degradation of phenolic compounds were found in the gut samples. Two unigenes matching two KOs and enzymes were annotated in the cuticular samples (Figure 4e). The gut unigenes were primarily affiliated with Alicycliphilus, Escherichia, Limosilactobacillus, and Serratia (Figure 4f). This finding showed that gut microbes may assist D. armandi to detoxify the trees defense.
A total of 20 enzymes related to the degradation of polysaccharides, including cellulose, xylan, xyloglucan, galactomannan, pectin, lignin, and chitin, were identified (Figure 5a,b). It included 1652 unigenes in the gut samples, 58 unigenes in the cuticular samples to digest pectin. There were 1335 and 58 unigenes related to cellulose degradation presented in the gut and cuticular samples. For xylan degradation, 256 unigenes were found in the gut associates, while only one unigene was detected in the cuticular samples. Additionally, 1585 unigenes related to xyloglucan degradation were found in the gut samples and 46 in the cuticular samples. It contained 562 unigenes related to galactomannan degradation in the gut samples and 16 unigenes in the cuticular samples. Thirty unigenes related to lignin degradation were in the gut tracts, and 20 were in the cuticular samples. And 99 unigenes were presented in the gut and 18 in the cuticular samples, both of which were involved in chitin degradation. Overall, the results suggested that the number of unigenes related to polysaccharide degradation was higher in the gut than in the cuticular samples. These unigenes were principally associated with gut Prevotella, Bacteroides, Ruminococcus, and Clostridium (Figure 5c).

3.4. Crucial Drivers of Gut and Cuticular Microbial Assemblies

Based on the gut and cuticular microbial community structures and functional characteristics analyses, six fungal (Table 3) and nine bacterial (Table 4) taxa were screened to serve as the core microbes. Null model analyses revealed that deterministic ecological processes (heterogeneous selection) may be the main driving forces for community assemblies of gut fungi unclassified (βNTI: 2.50), Rhizophagus (βNTI: 6.15), Enterobacter (βNTI: 16.14), and Wolbachia (βNTI: 9.86). However, these microbes in the cuticular samples may be primarily driven by stochastic processes (Table 3 and Table 4). The assemblies of Erysiphe (Gut, βNTI: 0.62; Cuticle, βNTI: −0.47), Enterospora (Gut, βNTI: 0.003; Cuticle, βNTI: 0), Rhizopus (Gut, βNTI: −0.10; Cuticle, βNTI: −0.19), unclassified bacteria (Gut, βNTI: 0.70; Cuticle, βNTI: −0.31), Prevotella (Gut, βNTI: 0; Cuticle, βNTI: 0.54) and Ruminococcus (Gut, βNTI: 0; Cuticle, βNTI:0.13) may be dominated by stochasticity in the gut and cuticular samples. Cuticular Escherichia assembly may tend to be governed by heterogeneous selection. It was hypothesized that the gut and cuticular microbes may interact with each other to maintain the adaptability to the environment for D. armandi.

4. Discussion

Microbial community structures are often influenced by different developmental stages of insects, host trees, and geographical conditions, which affect the ecological functions of host insects [48,49,50,51,52]. These microbes assisted bark beetles in neutralizing coniferous compounds that would otherwise impede the ability to infest trees, facilitating successful colonization [53,54]. In this study, we compared the symbiotic microbial community structures and functional characteristics of gut and cuticular samples. Our findings suggested that gut bacteria might play a more important role in assisting the bark beetles to degrade terpenoids, phenolic compounds, and polysaccharides. The results of crucial microbial community assemblies showed that unclassified fungi, Rhizophagus, Enterobacter, and Wolbachia, with relatively high abundance, were mainly driven by deterministic processes in the gut samples. Conversely, cuticular microbes were more likely to be driven by stochastic processes. Notably, Bacteroides, Clostridium, and Ruminococcus, which are critical for specific functions, appear to be involved in the stochastic processes in the gut samples.

4.1. The Higher Gut Bacterial Community Diversity

Gut and cuticular fungi and bacteria are crucial microbes for host insects, with distinct community structures that influence their ability to attack and colonize trees. Due to the differences among individual bark beetles, they showed distinct relative abundance in both gut and cuticular samples. However, gut and cuticular fungi exhibited congruent compositions by Ascomycota and Basidiomycota (Figure 1a). This is consistent with the results in the cuticular mycangium of Dendroctonus frontalis Zimmerman species complex [55]. The intricate symbiotic and antagonistic relationships exist between Dendroctonus spp., Ascomycetes (yeast and filamentous mycelia), and Basidiomycetes, as determined using culturable and PCR-denaturing gradient gel electrophoresis (DGGE) methods [26,56]. In this study, abundant yeasts were detected in both gut and cuticular samples, suggesting a specific relationship between yeasts and D. armandi. Previous studies have demonstrated that yeasts could provide abundant nutrition for larval development, pupation, egg viability, and reproduction of bark beetles [26].
The bacterial communities of D. armandi in the phylum are similar to the findings in the gut bacterial communities of D. valens and Dendroctonus mexicanus Hopkins. Enterobacter, known for hydrolyzing carbohydrates, provides nutrients for bark beetle larvae growth [9,57]. This study found that relatively high abundances of this genus in both the gut and cuticular samples, which may also play an important role in the development of D. armandi. Notably, bacterial diversity was higher in the gut than in cuticular samples, while cuticular fungal diversity was higher than that of the gut (Figure 2). It was also observed that fungal diversity was relatively lower in the tunnels and gut fungal communities of Dendroctonus ponderosae Hopkins and D. armandi at various developmental stages [24,56]. Gut bacterial diversity was higher than that of cuticular bacteria in D. armandi, which aligns with previous findings about the high diversity of gut bacteria associated with D. valens [58]. However, gut microbial community composition was similar to that of the cuticle. Host insects, stages of development, and geographical regions affected the microbial community structures.

4.2. Crucial Gut Bacteria in Degrading Complex Compounds

Cuticular symbiotic microbes play a significant role in terpenoid metabolism. Ophiostomatoid fungi, an important symbiotic microbial community in the cuticular samples, are often carried and spread to the host trees by bark beetles, promoting the detoxification of defense compounds. For instance, Grosmannia clavigera (Robinson-Jeffrey & R.W. Davidson) Zipfel, Z.W. de Beer & M.J. Wingf., a pathogenic fungus, detoxifies oleoresin terpenoids, assisting D. ponderosae to colonize the pines [3]. Gut symbiotic microbes also play a crucial role in enabling hosts to colonize successfully. Studies have shown that gut bacteria Sphingomonas associated with D. valens larvae can catabolize α-pinene, mitigating the adverse effects of complex compounds in the inner bark [58]. Unigenes of Sphingomonas related to terpenoid degradation were annotated in the gut samples in this study. Additionally, symbionts, unclassified Burkholderiales, and unclassified bacteria may also degrade terpenoids. Noticeably, gut symbionts associated with D. armandi may be involved in degrading terpenoids compared to those associated with Ips bark beetles in the terpenoid backbone biosynthesis pathway (Figure 6a). This may suggest that D. armandi infests healthy conifers, potentially due to the gut bacteria in detoxifying defensive compounds.
Additionally, ophiostomatoid fungi play an indispensable role in degrading phenolic compounds. For example, following the infection of Endoconidiophora polonica (Siemaszko) Z.W. de Beer, T.A. Duong & M.J. Wingf., the concentration of phenolic compounds in phloem decreased significantly, making D. armandi more capable of attacking and colonizing host trees [59]. Although ophiostomatoid fungi involved in phenolic compounds degradation were not annotated in this study, various gut bacterial symbionts, Alicycliphilus, Escherichia, and Serratia were found, and they may play key roles in detoxifying these compounds. Additionally, we found that the unigenes related to phenolic compounds degradation were absolutely absent in the DAC1 and DA1 samples. We speculated that it may present differences among the individual bark beetles, which may affect the ability of colonizing host trees. By contrast, the unigenes related to these complex compounds were frequently discovered in the gut samples, which indicated gut microbes may have a greater ability to degrade phenolic compounds than cuticular samples. Gut bacterial symbionts can provide nutritional resources for bark beetle growth and development by degrading polysaccharides (e.g., cellulose and hemicellulose). Previous studies have proved that gut Acinetobacter spp., Pseudomonas putida Trevisan, Rahnella aquatilis Izard, Gavini, Trinel & Leclerc associated with Dendroctonus rhizophagus Thomas and Bright can degrade cellulose, xylan, and pectin as carbon and nitrogen sources for the growth and development [9,60]. In this study, gut Prevotella, Bacteroides, Ruminococcus and Clostridium may be involved in degrading cellulose, xyloglucan, galactomannan, and pectin. Additionally, Prevotella, Bacteroides, and Clostridium may degrade xylan. Bacteroides, Clostridium, and Ruminococcus may degrade chitin (Figure 6b). Thus, gut bacteria may play a prominent role in the degradation of complex compounds [23,61]. Future studies may utilize the interrelationship between microbes and bark beetles to control and manage the occurrence of pests and diseases.

4.3. Stochasticity for Driving Core Bacterial Community Assemblies

Interactions between symbiotic microbes and bark beetles have multifaceted effects on the host insects. Some microbes establish long-term stable mutualistic relationships with the bark beetles. These microbes can provide nutrition [62,63], protect hosts from hazards [64], enhance host population invasions [58,65], and degrade complex compounds [66]. However, specific microbial community assembly processes can influence microbial interactions. Therefore, understanding the drivers of ecological processes is crucial. Gut-specific bacterial communities may be shaped by stochasticity, serving as a heterogeneous microenvironmental habitat [57]. Previous studies have shown that the gut bacterial community assembly of bees is driven by stochastic processes, especially drift [67]. In this study, gut Prevotella and Ruminococcus community assemblies are dominated by stochasticity. And these taxa may be involved in degrading polysaccharides, indicating that microbes may help bark beetles adapt to the complex environments of plants through processes like dispersal, weak selection, and drift. Additionally, it may be driven by stochasticity for cuticular core fungi and bacteria except for Escherichia. This is inconsistent with community assemblies of crucial non-intestinal microbes associated with Ips bark beetles [38]. Cuticular Escherichia had higher relative abundances and was taken as a functional taxon of degrading phenolics, and this community assembly may be driven by deterministic processes without stable community structure and function. All in all, the two processes may be combined to maintain the gut and cuticular microbial diversity and function. It may also be related to the adaptability to the environment for bark beetles. However, it was controversial for microbial community assembly mechanisms in ecology.

5. Conclusions

A direct comparison of gut and cuticular microbial community structures and functional characteristics revealed significant variations in fungal and bacterial diversity. Cuticular fungi exhibited higher diversity than gut fungi, whereas gut bacteria displayed greater diversity than cuticular bacteria. Gut microbes may metabolize complex compounds, which may be shaped by stochastic processes adapting to the dynamic gut environment. These findings highlight the importance of microbial diversity and offer insights into the symbiosis between the bark beetles and their microbes. In the future, it may be possible to use microbes or interactions among the microbes to control the development of pests and diseases.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16101584/s1.

Author Contributions

Conceptualization, Q.L. and H.W.; methodology, Q.L. and C.L.; software, C.L.; validation, Q.L. and H.W.; formal analysis, C.L.; investigation, C.L. and L.L.; resources, Q.L. and H.W.; data curation, C.L.; writing—original draft preparation, C.L. and H.W.; writing—review and editing, C.L., H.W. and Z.W.; visualization, Q.L. and H.W.; supervision, Q.L. and H.W.; project administration, Q.L. and H.W.; funding acquisition, Q.L. and H.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 32201569 and No. 32230071).

Data Availability Statement

The raw metagenomic data have been uploaded on the NCBI Bioproject: PRJNA1251992. DNA sequences with SRAs are available at https://submit.ncbi.nlm.nih.gov/subs/sra/SUB15265100/overview, 18 April 2025.

Acknowledgments

We thank Haifeng Zhang from Longcaoping Forestry Bureau of Shanxi Province for assisting in sample collection.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
LEfSeLinear discriminant analysis Effect Size
NRNon-redundant
KEGGKyoto Encyclopedia of Genes and Genomes
KOsKEGG Orthologies
CAZyCarbohydrate-Active enZYmes
HSheterogeneous selection
HOShomogeneous selection
βNTIbeta-nearest taxon index
MLmaximum likelihood

References

  1. Farrell, B.D.; Sequeira, A.S.; O’Meara, B.C.; Normark, B.B.; Chung, J.H.; Jordal, B.H. The evolution of agriculture in beetles (Curculionidae: Scolytinae and Platypodinae). Evolution 2001, 55, 2011–2027. [Google Scholar] [CrossRef] [PubMed]
  2. Zhao, T.; Kandasamy, D.; Krokene, P.; Chen, J.; Gershenzon, J.; Hammerbacher, A. Fungal associates of the tree-killing bark beetle, Ips typographus, vary in virulence, ability to degrade conifer phenolics and influence bark beetle tunneling behavior. Fungal Ecol. 2019, 38, 71–79. [Google Scholar] [CrossRef]
  3. DiGuistini, S.; Wang, Y.; Liao, N.Y.; Taylor, G.; Tanguay, P.; Feau, N.; Henrissat, B.; Chan, S.K.; Hesse-Orce, U.; Alamouti, S.M.; et al. Genome and transcriptome analyses of the mountain pine beetle-fungal symbiont Grosmannia clavigera, a lodgepole pine pathogen. Proc. Nat. Acad. Sci. USA 2011, 108, 2504–2509. [Google Scholar] [CrossRef] [PubMed]
  4. Huang, J.; Kautz, M.; Trowbridge, A.M.; Hammerbacher, A.; Raffa, K.F.; Adams, H.D.; Goodsman, D.W.; Xu, C.; Meddens, A.J.H.; Kandasamy, D.; et al. Tree defence and bark beetles in a drying world: Carbon partitioning, functioning and modelling. New Phytol. 2020, 225, 26–36. [Google Scholar] [CrossRef]
  5. Hammerbacher, A.; Paetz, C.; Wright, L.P.; Fischer, T.C.; Bohlmann, J.; Davis, A.J.; Fenning, T.M.; Gershenzon, J.; Schmidt, A. Flavan-3-ols in Norway spruce: Biosynthesis, accumulation, and function in response to attack by the bark beetle-associated fungus Ceratocystis polonica. Plant Physiol. 2014, 164, 2107–2122. [Google Scholar] [CrossRef]
  6. Kaltenpoth, M. Actinobacteria as mutualists: General healthcare for insects. Trends Microbiol. 2009, 17, 529–535. [Google Scholar] [CrossRef]
  7. Glass, N.L.; Schmoll, M.; Cate, J.H.D.; Coradetti, S. Plant cell wall deconstruction by Ascomycete fungi. Annu. Rev. Microbiol. 2013, 67, 477–498. [Google Scholar] [CrossRef]
  8. Morales-Jiménez, J.; Zúñiga, G.; Villa-Tanaca, L.; Hernández-Rodríguez, C. Bacterial community and nitrogen fixation in the red turpentine beetle, Dendroctonus valens LeConte (Coleoptera: Curculionidae: Scolytinae). Microb. Ecol. 2009, 58, 879–891. [Google Scholar] [CrossRef]
  9. Morales-Jiménez, J.; Zúñiga, G.; Ramírez-Saad, H.C.; Hernández-Rodríguez, C. Gut associated bacteria throughout the life cycle of the bark beetle Dendroctonus rhizophagus Thomas and Bright (Curculionidae: Scolytinae) and their cellulolytic activities. Microb. Ecol. 2012, 64, 268–278. [Google Scholar] [CrossRef]
  10. Six, D.L. The bark beetle holobiont: Why microbes matter. J. Chem. Ecol. 2013, 39, 989–1002. [Google Scholar] [CrossRef]
  11. García-Fraile, P. Roles of bacteria in the bark beetle holobiont—How do they shape this forest pest. Ann. Appl. Biol. 2018, 172, 111–125. [Google Scholar] [CrossRef]
  12. Douglas, A.E. Multiorganismal insects: Diversity and function of resident Microorganisms. Annu. Rev. Entomol. 2015, 60, 17–34. [Google Scholar] [CrossRef]
  13. Cao, Q.; Zhao, Y.; Koski, T.M.; Li, H.; Sun, J. Effects of simulated gut pH environment on bacterial composition and pheromone production of Dendroctonus valens. Insect Sci. 2024, 31, 225–235. [Google Scholar] [CrossRef] [PubMed]
  14. Engel, P.; Moran, N.A. The gut microbiota of insects–diversity in structure and function. FEMS Microb. Rev. 2013, 37, 699–735. [Google Scholar] [CrossRef] [PubMed]
  15. Mohammed, W.S.; Ziganshina, E.E.; Shagimardanova, E.I.; Gogoleva, N.E.; Ziganshin, A.M. Comparison of intestinal bacterial and fungal communities across various xylophagous beetle larvae (Coleoptera: Cerambycidae). Sci. Rep. 2018, 8, 10073. [Google Scholar] [CrossRef] [PubMed]
  16. Xu, L.; Deng, J.; Zhou, F.; Cheng, C.; Zhang, L.; Zhang, J.; Lu, M. Gut microbiota in an invasive bark beetle infected by a pathogenic fungus accelerates beetle mortality. J. Pest Sci. 2019, 92, 343–351. [Google Scholar] [CrossRef]
  17. Torres-Banda, V.; Obregón-Molina, G.; Soto-Robles, L.V.; Albores-Medina, A.; López, M.F.; Zúñiga, G. Gut transcriptome of two bark beetle species stimulated with the same kairomones reveals molecular differences in detoxification pathways. Comput Struct Biotec. 2022, 20, 3080–3095. [Google Scholar] [CrossRef]
  18. Gupta, S.; Chakraborty, A.; Roy, A. Prospects for deploying microbes against tree-killing beetles (Coleoptera) in Anthropocene. Front. For. Glob. Change 2023, 6, 1182834. [Google Scholar] [CrossRef]
  19. Kostovcik, M.; Bateman, C.C.; Kolarik, M.; Stelinski, L.L.; Jordal, B.H.; Hulcr, J. The ambrosia symbiosis is specific in some species and promiscuous in others: Evidence from community pyrosequencing. ISME J. 2015, 9, 126–138. [Google Scholar] [CrossRef]
  20. Hulcr, J.; Rountree, N.R.; Diamond, S.E.; Stelinski, L.L.; Fierer, N.; Dunn, R.R. Mycangia of ambrosia beetles host communities of bacteria. Microb. Ecol. 2012, 64, 784–793. [Google Scholar] [CrossRef]
  21. Cardoza, Y.J.; Klepzig, K.D.; Raffa, K.F. Bacteria in oral secretions of an endophytic insect inhibit antagonistic fungi. Ecol. Entomol. 2006, 31, 636–645. [Google Scholar] [CrossRef]
  22. Xu, L.; Zhang, Y.; Zhang, S.; Deng, J.; Lu, M.; Zhang, L.; Zhang, J. Comparative analysis of the immune system of an invasive bark beetle, Dendroctonus valens, infected by an entomopathogenic fungus. Dev. Comp. Immunol. 2018, 88, 65–69. [Google Scholar] [CrossRef]
  23. Wang, T.T. Study on Diversity and Pathogenicity of Ophiostomatoid Fungi Associated with the Dendroctonus armandi in Pinus armandii; Chinese Academy of Forestry: Beijing, China, 2020. [Google Scholar]
  24. Wang, Z.; Zhou, Q.; Zheng, G.; Fang, J.; Han, F.; Zhang, X.; Lu, Q. Abundance and diversity of Ophiostomatoid fungi associated with the Great Spruce Bark Beetle (Dendroctonus micans) in the Northeastern Qinghai-Tibet Plateau. Front. Microbiol. 2021, 12, 721395. [Google Scholar] [CrossRef]
  25. Wang, Z.; Liang, L.; Wang, H.; Decock, C.; Lu, Q. Ophiostomatoid fungi associated with Ips bark beetles in China. Fungal Divers. 2024, 129, 283–364. [Google Scholar] [CrossRef]
  26. Hu, X.; Li, M.; Chen, H. Community structure of gut fungi during different developmental stages of the Chinese white pine beetle (Dendroctonus armandi). Sci. Rep. 2015, 5, 8411. [Google Scholar] [CrossRef] [PubMed]
  27. Hu, X.; Li, M.; Zhang, F.; Chen, H. Influence of starvation on the structure of gut-associated bacterial communities in the Chinese white pine beetle (Dendroctonus armandi). Forests 2016, 7, 126. [Google Scholar] [CrossRef]
  28. Wang, J.; Chen, H.; Tang, M. Community structure of gut bacteria of Dendroctonus armandi (Coleoptera: Curculionidae: Scolytinae) larvae during overwintering stage. Sci. Rep. 2017, 7, 14242. [Google Scholar] [CrossRef]
  29. Cheng, T.; Veselská, T.; Křížková, B.; Švec, K.; Havlíček, V.; Stadler, M.; Kolařík, M. Insight into the genomes of dominant yeast symbionts of European spruce bark beetle, Ips typographus. Front. Microbiol. 2023, 14, 1108975. [Google Scholar] [CrossRef]
  30. Hu, X.; Yu, J.M.; Wang, C.Y.; Chen, H. Cellulolytic bacteria associated with the gut of Dendroctonus armandi larvae (Coleoptera: Curculionidae: Scolytinae). Forests 2014, 5, 455–465. [Google Scholar] [CrossRef]
  31. Wang, H.; Liu, Y.; Wang, T.; Liu, D.; Lu, Q. Pathophysiology and transcriptomic responses of Pinus armandii defenses to ophiostomatoid fungi. Tree Physiol. 2024, 44, tpae056. [Google Scholar] [CrossRef]
  32. Liu, F.; Ye, F.; Cheng, C.; Kang, Z.; Kou, H.; Sun, J. Symbiotic microbes aid host adaptation by metabolizing a deterrent host pine carbohydrate d-pinitol in a beetle-fungus invasive complex. Sci. Adv. 2022, 8, eadd5051. [Google Scholar] [CrossRef] [PubMed]
  33. Khara, A.; Chakraborty, A.; Modlinger, R.; Synek, J.; Roy, A. Comparative metagenomic study unveils new insights on bacterial communities in two pine-feeding Ips beetles (Coleoptera: Curculionidae: Scolytinae). Front. Microbiol. 2024, 15, 1400894. [Google Scholar] [CrossRef] [PubMed]
  34. Stegen, J.C.; Lin, X.; Fredrickson, J.K.; Chen, X.; Kennedy, D.W.; Murray, C.J.; Rockhold, M.L.; Konopka, A. Quantifying community assembly processes and identifying features that impose them. ISME J. 2013, 7, 2069–2079. [Google Scholar] [CrossRef] [PubMed]
  35. Feng, Y.; Chen, R.; Stegen, J.C.; Guo, Z.; Zhang, J.; Li, Z.; Lin, X. Two key features influencing community assembly processes at regional scale: Initial state and degree of change in environmental conditions. Mol. Ecol. 2018, 27, 5238–5251. [Google Scholar] [CrossRef]
  36. Zhu, Y.X.; Yang, R.; Wang, X.Y.; Wen, T.; Gong, M.H.; Shen, Y.; Xu, J.Y.; Zhao, D.S.; Du, Y.Z. Gut microbiota composition in the sympatric and diet-sharing Drosophila simulans and Dicranocephalus wallichii bowringi shaped largely by community assembly processes rather than regional species pool. iMeta 2022, 1, e57. [Google Scholar] [CrossRef]
  37. Zhu, Y.X.; Yang, T.Y.; Deng, J.H.; Yin, Y.; Song, Z.R.; Du, Y.Z. Stochastic processes drive divergence of bacterial and fungal communities in sympatric wild insect species despite sharing a common diet. mSphere 2024, 9, e00386-24. [Google Scholar] [CrossRef]
  38. Liu, C.; Wang, H.; Wang, Z.; Liang, L.; Li, Y.; Liu, D.; Lu, Q. Distinct assembly processes of intestinal and non-intestinal microbes of bark beetles from clues of metagenomic insights. Sci. Rep. 2025, 15, 7910. [Google Scholar] [CrossRef]
  39. Niederdorfer, R.; Fragner, L.; Yuan, L.; Hausherr, D.; Wei, J.; Magyar, P.; Joss, A.; Lehmann, M.F.; Ju, F.; Bürgmann, H. Distinct growth stages controlled by the interplay of deterministic and stochastic processes in functional anammox biofilms. Water Res. 2021, 200, 117225. [Google Scholar] [CrossRef]
  40. Six, D.L.; Bracewell, R. Dendroctonus. Chapter 8. In Bark Beetles; Academic Press: Cambridge, MA, USA, 2015; pp. 305–350. [Google Scholar]
  41. Steinegger, M.; Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. biotechn. 2017, 35, 1026–1028. [Google Scholar]
  42. Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar]
  43. Zhang, D.; Gao, F.; Jakovlić, I.; Zou, H.; Zhang, J.; Li, W.X.; Wang, G.T. PhyloSuite: An integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies. Mol. Ecol. Res. 2020, 20, 348–355. [Google Scholar] [CrossRef]
  44. Kembel, S.W.; Cowan, P.D.; Helmus, M.R.; Cornwell, W.K.; Morlon, H.; Ackerly, D.D.; Blomberg, S.P.; Webb, C.O. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 2010, 26, 1463–1464. [Google Scholar] [CrossRef] [PubMed]
  45. Paradis, E.; Claude, J.; Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 2004, 20, 289–290. [Google Scholar] [CrossRef] [PubMed]
  46. Zhao, W.; Wang, X.B.; Shi, L.Y.; Zhu, W.Y.; Ma, L.; Wang, J.J.; Xu, S.; Yang, R.; Zhang, X.X.; Han, Y.F.; et al. Calculation method for stochastic and deterministic assembly processes of prokaryotic communities. Bioprotocol 2021, 101, e2003400. (In Chinese) [Google Scholar]
  47. Tripathi, B.M.; Stegen, J.C.; Kim, M.; Dong, K.; Adams, J.M.; Lee, Y.K. Soil pH mediates the balance between stochastic and deterministic assembly of bacteria. ISME J. 2018, 12, 1072–1083. [Google Scholar] [CrossRef]
  48. Zhou, F.; Lou, Q.; Wang, B.; Xu, L.; Cheng, C.; Lu, M.; Sun, J. Altered carbohydrates allocation by associated bacteria-fungi interactions in a bark beetle-microbe symbiosis. Sci. Rep. 2016, 6, 20135. [Google Scholar]
  49. Chakraborty, A.; Ashraf, M.Z.; Modlinger, R.; Synek, J.; Schlyter, F.; Roy, A. Unravelling the gut bacteriome of Ips (Coleoptera: Curculionidae: Scolytinae): Identifying core bacterial assemblage and their ecological relevance. Sci. Rep. 2020, 10, 18572. [Google Scholar] [CrossRef]
  50. Chakraborty, A.; Modlinger, R.; Ashraf, M.Z.; Synek, J.; Schlyter, F.; Roy, A. Core mycobiome and their ecological relevance in the gut of five Ips bark beetles (Coleoptera: Curculionidae: Scolytinae). Front. Microbiol. 2020, 11, 568853. [Google Scholar] [CrossRef]
  51. Vega, F.E.; Biedermann, P.H.W. On interactions, associations, mycetangia, mutualists and symbiotes in insect-fungus symbioses. Fungal Ecol. 2020, 44, 100909. [Google Scholar] [CrossRef]
  52. Baños-Quintana, A.P.; Gershenzon, J.; Kaltenpoth, M. The Eurasian spruce bark beetle Ips typographus shapes the microbial communities of its offspring and the gallery environment. Front. Microbiol. 2024, 15, 1367127. [Google Scholar] [CrossRef]
  53. Paine, T.D.; Raffa, K.F.; Harrington, T.C. Interactions among scolytid bark beetles, their associated fungi, and live host conifers. Annu. Rev. Entomol. 1997, 42, 179–206. [Google Scholar] [CrossRef] [PubMed]
  54. Fossdal, C.G.; Nagy, N.E.; Johnsen, O.; Dalen, L.S. Local and systemic stress responses in Norway spruce: Similarities in gene expression between a compatible pathogen interaction and drought stress. Physiol. Mol. Plant P. 2007, 70, 161–173. [Google Scholar] [CrossRef]
  55. Vazquez-Ortiz, K.; Pineda-Mendoza, R.M.; González-Escobedo, R.; Davis, T.S.; Salazar, K.F.; Rivera-Orduña, F.N.; Zúñiga, G. Metabarcoding of mycetangia from the Dendroctonus frontalis species complex (Curculionidae: Scolytinae) reveals diverse and functionally redundant fungal assemblages. Front. Microbiol. 2022, 13, 969230. [Google Scholar] [CrossRef] [PubMed]
  56. Lim, Y.W.; Kim, J.J.; Lu, M.; Breuil, C. Determining fungal diversity on Dendroctonus ponderosae and Ips pini affecting lodgepole pine using cultural and molecular methods. Fungal Divers. 2006, 19, 79–94. [Google Scholar]
  57. Hernández-García, J.A.; Gonzalez-Escobedo, R.; Briones-Roblero, C.I.; Cano-Ramírez, C.; Rivera-Orduña, F.N.; Zúñiga, G. Gut bacterial communities of Dendroctonus valens and D. mexicanus (Curculionidae: Scolytinae): A metagenomic analysis across different geographical locations in Mexico. Int. J. Mol. Sci. 2018, 19, 2578. [Google Scholar] [CrossRef]
  58. Xu, L.; Shi, Z.; Wang, B.; Lu, M.; Sun, J. Pine defensive monoterpene α-Pinene influences the feeding behavior of Dendroctonus valens and its gut bacterial community structure. Int. J. Mol. Sci. 2016, 17, 1734. [Google Scholar] [CrossRef]
  59. Li, S.H.; Nagy, N.E.; Hammerbacher, A.; Krokene, P.; Niu, X.M.; Gershenzon, J.; Schneider, B. Localization of phenolics in phloem parenchyma cells of Norway spruce (Picea abies). ChemBioChem 2012, 13, 2707–2713. [Google Scholar] [CrossRef]
  60. Briones-Roblero, C.I.; Rodríguez-Díaz, R.; Santiago-Cruz, J.A.; Zúñiga, G.; Rivera-Orduña, F.N. Degradation capacities of bacteria and yeasts isolated from the gut of Dendroctonus rhizophagus (Curculionidae: Scolytinae). Folia Microbiol. 2017, 62, 1–9. [Google Scholar] [CrossRef]
  61. Adams, A.S.; Boone, C.K.; Bohlmann, J.; Raffa, K.F. Responses of bark beetle-associated bacteria to host monoterpenes and their relationship to insect life histories. J. Chem. Ecol. 2011, 37, 808–817. [Google Scholar] [CrossRef]
  62. Bracewell, R.R.; Six, D.L. Experimental evidence of bark beetle adaptation to a fungal symbiont. Ecol. Evol. 2015, 5, 5109–5119. [Google Scholar] [CrossRef]
  63. Guevara-Rozo, S.; Hussain, A.; Cale, J.A.; Klutsch, J.G.; Rajabzadeh, R.; Erbilgin, N. Nitrogen and ergosterol concentrations varied in live jack pine phloem following inoculations with fungal associates of mountain pine beetle. Front. Microbiol. 2020, 11, 1703. [Google Scholar] [CrossRef]
  64. Scott, J.J.; Oh, D.C.; Yuceer, M.C.; Klepzig, K.D.; Clardy, J.; Currie, C.R. Bacterial protection of beetle-fungus mutualism. Science 2008, 322, 63. [Google Scholar] [CrossRef]
  65. Kandasamy, D.; Gershenzon, J.; Andersson, M.N.; Hammerbacher, A. Volatile organic compounds influence the interaction of the Eurasian spruce bark beetle (Ips typographus) with its fungal symbionts. ISME J. 2019, 13, 1788–1800. [Google Scholar] [CrossRef]
  66. Ceja-Navarro, J.A.; Vega, F.E.; Karaoz, U.; Hao, Z.; Jenkins, S.; Lim, H.C.; Kosina, P.; Infante, F.; Northen, T.R.; Brodie, E.L. Gut microbiota mediate caffeine detoxification in the primary insect pest of coffee. Nat. Commun. 2015, 6, 7618. [Google Scholar] [CrossRef]
  67. Ge, Y.; Jing, Z.; Diao, Q.; He, J.Z.; Liu, Y.J. Host species and geography differentiate honeybee gut bacterial communities by changing the relative contribution of community assembly processes. mBio 2021, 12, e0075-21. [Google Scholar] [CrossRef]
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Figure 1. Gut and cuticular microbial composition for Dendroctonus armandi. (a,b) Relative abundances of fungal community composition in the gut and cuticular samples at the phylum and genus levels. (c,d) Relative abundances of bacterial community composition in the gut and cuticular samples at the phylum and genus (top 12 genera) levels.
Figure 1. Gut and cuticular microbial composition for Dendroctonus armandi. (a,b) Relative abundances of fungal community composition in the gut and cuticular samples at the phylum and genus levels. (c,d) Relative abundances of bacterial community composition in the gut and cuticular samples at the phylum and genus (top 12 genera) levels.
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Figure 2. Gut and cuticular microbial diversity in Dendroctonus armandi. α-diversity analysis of fungi (a) and bacteria (b) based on Student t-test (* p < 0.05) in the gut and cuticular samples; Evolution diagram of biomarker for associated microbes in the gut (c) and cuticular (d) samples. The different dots on the evolutionary branch represent different taxonomic levels. This was at the phylum, class, order, family, genus, and species levels from the inside to the outside in an orderly manner. Each node represents a microbe, and the larger the node, the greater the relative abundance of microbes. Blue dots indicate a more significant difference and the higher abundance of microbes in the cuticular samples than in the gut samples. Red dots represent a more significant difference and higher abundance of microbes in the gut than in the cuticular samples.
Figure 2. Gut and cuticular microbial diversity in Dendroctonus armandi. α-diversity analysis of fungi (a) and bacteria (b) based on Student t-test (* p < 0.05) in the gut and cuticular samples; Evolution diagram of biomarker for associated microbes in the gut (c) and cuticular (d) samples. The different dots on the evolutionary branch represent different taxonomic levels. This was at the phylum, class, order, family, genus, and species levels from the inside to the outside in an orderly manner. Each node represents a microbe, and the larger the node, the greater the relative abundance of microbes. Blue dots indicate a more significant difference and the higher abundance of microbes in the cuticular samples than in the gut samples. Red dots represent a more significant difference and higher abundance of microbes in the gut than in the cuticular samples.
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Forests 16 01584 g003
Figure 3. Gene relative abundance and distribution in the galactose metabolic pathway. (a) Gene relative abundance based on the Wilcoxon test (* p < 0.05) in the gut and cuticular microbes. Fungal unigenes in the gut (b) and cuticular (d) samples; bacterial unigenes in the gut (c) and cuticular (e) samples.
Figure 3. Gene relative abundance and distribution in the galactose metabolic pathway. (a) Gene relative abundance based on the Wilcoxon test (* p < 0.05) in the gut and cuticular microbes. Fungal unigenes in the gut (b) and cuticular (d) samples; bacterial unigenes in the gut (c) and cuticular (e) samples.
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Figure 4. Important enzymes and genes related to terpenoids and phenolic compounds degradation for gut and cuticular symbiotic microbes associated with Dendroctonus armandi. (a) Gene relative abundances related to terpenoid degradation in the gut and cuticular symbiotic microbes. (b) Unique and shared unigenes of degrading terpenoids in the gut and cuticular samples. (c,d) Distribution characteristics of unigenes related to terpenoid degradation in the gut and cuticular samples. (e) The number of genes related to six enzymes in the gut and cuticular samples. (f) Relative abundance of unigenes related to the dominant microbes in the gut and cuticular samples.
Figure 4. Important enzymes and genes related to terpenoids and phenolic compounds degradation for gut and cuticular symbiotic microbes associated with Dendroctonus armandi. (a) Gene relative abundances related to terpenoid degradation in the gut and cuticular symbiotic microbes. (b) Unique and shared unigenes of degrading terpenoids in the gut and cuticular samples. (c,d) Distribution characteristics of unigenes related to terpenoid degradation in the gut and cuticular samples. (e) The number of genes related to six enzymes in the gut and cuticular samples. (f) Relative abundance of unigenes related to the dominant microbes in the gut and cuticular samples.
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Figure 5. Enzymes and unigenes related to polysaccharide degradation in the gut and cuticular samples for Dendroctonus armandi. (a) representing KOs related to polysaccharides (cellulose, xylan, xyloglucan, galactomannan, pectin, lignin, and chitin) degradation in the gut and cuticular samples. The red represents the number of unigenes corresponding to KOs in the gut samples, the blue the number of unigenes corresponding to KOs in the cuticular samples. The larger the dot, the higher the number of unigenes corresponding to Kos. (b) Relative abundance of genes for 22 enzymes in the gut and cuticular samples. Z-score for data scaling, clustering, and distance calculation method using “Complete” and “Euclidean”, respectively. Each color block represents a kind of enzyme in a sample, the color block ranging from blue to red, indicating that higher relative abundance of the unigene for this enzyme. (c) Distribution characteristics of unigenes related to polysaccharide degradation in the gut and cuticular samples. The dark blue represents the highest unigenes corresponding to xyloglucan and pectin degradation in Prevotella associated with D. armandi; the red represents crucial taxa in the legend for degrading polysaccharides.
Figure 5. Enzymes and unigenes related to polysaccharide degradation in the gut and cuticular samples for Dendroctonus armandi. (a) representing KOs related to polysaccharides (cellulose, xylan, xyloglucan, galactomannan, pectin, lignin, and chitin) degradation in the gut and cuticular samples. The red represents the number of unigenes corresponding to KOs in the gut samples, the blue the number of unigenes corresponding to KOs in the cuticular samples. The larger the dot, the higher the number of unigenes corresponding to Kos. (b) Relative abundance of genes for 22 enzymes in the gut and cuticular samples. Z-score for data scaling, clustering, and distance calculation method using “Complete” and “Euclidean”, respectively. Each color block represents a kind of enzyme in a sample, the color block ranging from blue to red, indicating that higher relative abundance of the unigene for this enzyme. (c) Distribution characteristics of unigenes related to polysaccharide degradation in the gut and cuticular samples. The dark blue represents the highest unigenes corresponding to xyloglucan and pectin degradation in Prevotella associated with D. armandi; the red represents crucial taxa in the legend for degrading polysaccharides.
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Figure 6. Genetic encoding products for bark beetles in terpenoid backbone biosynthesis and important microbes related to polysaccharide degradation. (a) Genetic encoding products of Ips bark beetles and Dendroctonus armandi. with microbial collaboration in terpenoid backbone biosynthesis. Yellow rectangles represent the shared metabolic products in Dendroctonus armandi and Ips bark beetles; the green represents unique metabolic products for D. armandi; the red represents unique metabolic products for Ips bark beetles. (b) The shared and unique complex compounds degradation for four important microbial communities.
Figure 6. Genetic encoding products for bark beetles in terpenoid backbone biosynthesis and important microbes related to polysaccharide degradation. (a) Genetic encoding products of Ips bark beetles and Dendroctonus armandi. with microbial collaboration in terpenoid backbone biosynthesis. Yellow rectangles represent the shared metabolic products in Dendroctonus armandi and Ips bark beetles; the green represents unique metabolic products for D. armandi; the red represents unique metabolic products for Ips bark beetles. (b) The shared and unique complex compounds degradation for four important microbial communities.
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Table 1. Sample collection information of Dendroctonus armandi.
Table 1. Sample collection information of Dendroctonus armandi.
Sample TypeSample IDHost
Tree		Latitude
Longitude		Elevation/mLocation
GutDAC1Pinus armandii33.6891° N, 107.8966° E1701.70 ± 4.62Foping, Hanzhong City in Shanxi Province, China
DAC2
DAC3
CuticleDA1
DA2
DA3
Table 2. Sequencing information for metagenomic raw data of Dendroctonus armandi.
Table 2. Sequencing information for metagenomic raw data of Dendroctonus armandi.
Sample NameBioproject IDBiosample IDSequence Read Archive
(SRA)
DAC1PRJNA1251992SAMN48028048SRR33208850
DAC2SAMN48028049SRR33208849
DAC3SAMN48028050SRR33208848
DA1SAMN48028045SRR33208853
DA2SAMN48028046SRR33208852
DA3SAMN48028047SRR33208851
Table 3. The βNTI value for gut and cuticular fungal symbiont community assembly processes for Dendroctonus armandi.
Table 3. The βNTI value for gut and cuticular fungal symbiont community assembly processes for Dendroctonus armandi.
Sample TypeFungi UnclassifiedErysipheRhizophagusEnterosporaRhizopusOphiostomatoid Fungi
Gut2.500.626.150.00−0.10NA
Cuticle0.00−0.471.540.00−0.190.11
Table 4. The βNTI value for gut and cuticular bacterial associate community assembly processes for Dendroctonus armandi.
Table 4. The βNTI value for gut and cuticular bacterial associate community assembly processes for Dendroctonus armandi.
Sample TypeBacteria UnclassifiedThiobacillusEnterobacterEscherichiaWolbachia
Gut0.70NA16.14NA9.86
Cuticle−0.310.000.212.05−0.21
Sample TypePrevotellaMircobacteriumBacteroidesClostridiumRuminococcus
Gut0.00NANANA0.00
Cuticle0.540.110.620.520.13
NA: no βNTI value.
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Liu, C.; Liang, L.; Wang, H.; Wang, Z.; Lu, Q. Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li. Forests 2025, 16, 1584. https://doi.org/10.3390/f16101584

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Liu C, Liang L, Wang H, Wang Z, Lu Q. Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li. Forests. 2025; 16(10):1584. https://doi.org/10.3390/f16101584

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Liu, Caixia, Lingyu Liang, Huimin Wang, Zheng Wang, and Quan Lu. 2025. "Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li" Forests 16, no. 10: 1584. https://doi.org/10.3390/f16101584

APA Style

Liu, C., Liang, L., Wang, H., Wang, Z., & Lu, Q. (2025). Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li. Forests, 16(10), 1584. https://doi.org/10.3390/f16101584

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