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Article

Diversity of Gut Microbes in Adult Vespa velutina (Asian Hornet) Carcasses Killed by Natural Causes

by
Meiling Pang
1,2,
Ji Luo
1,
Zhende Yang
2,3 and
Xuejian Jiang
1,*
1
Guangxi Engineering Research Centre of Natural Enemy Breeding of Forestry Pests, Nanning 530002, China
2
College of Forestry, Guangxi University, Nanning 530004, China
3
Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Nanning 530004, China
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(12), 1162; https://doi.org/10.3390/d15121162
Submission received: 12 September 2023 / Revised: 8 November 2023 / Accepted: 14 November 2023 / Published: 22 November 2023
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Abstract

:
[Objective] This study’s objective was to investigate the diversity of intestinal microorganisms in adult Vespa velutina (Asian hornet) killed by natural causes. This study investigates the composition of intestinal fungi and bacteria and predicts the pathogenic pathogen in adult Vespa velutina (Asian hornet). [Methods] We determined the ITS1 sequence of fungi and the V3–V4 variant region of 16S rRNA of bacteria using Illumina MiSeq technology. Operational taxonomic units (OTU) of gut symbiotic microorganisms were quantified, and the resulting data were subjected to analysis of species abundance, composition, and alpha diversity. OTU function was predicted using PICRUSt2/FUNGuild. In addition, cultured microorganisms from the gut microbiota of adult Vespa velutina were isolated and identified. A number of 3610 (fungi) and 8373 (bacteria) were identified via cluster analysis. A total of 13 strains, 51 classes, 126 orders, 285 families, and 586 genera were identified for fungi and 44 strains, 113 classes, 319 orders, 662 families, and 1394 genera were identified for bacteria. E. shigella, Herbaspirillum, and Aaaia were the most abundant classes of bacteria, and Fusarium, Mortierella, and Starmerella were the most abundant classes of fungi. In addition, 16 community genera of fungi and 11 of bacteria were outlined as core taxa. Species diversity and richness for the gut fungal and bacterial communities with VN were found to be higher than those with VA. Furthermore, bacterial species diversity and richness were found to be higher than those of fungi in VA and VN. Functional analysis revealed that Vespa velutina gut bacteria exhibited 20 functions, while fungi were classified into three types of nutrient modes. Cultivable bacteria were obtained from two phyla and two classes, but no fungi could be cultivated. [Conclusion] Variations in the species diversity and abundance of both fungi and bacteria in the gut were observed between the VA and the VN. The involvement of bacteria in the death of adult Vespa velutina was found to be significant. In addition, VA1 (the self-named strain) may be a pathogenic bacterium derived from the gut of the VA that exhibits virulence.

1. Introduction

Vespa velutina, also known as a red wasp, tiger bee, or yellow wasp, is an arthropod of Hymenoptera and the family Vespidae and is considered one of the most serious invasive insects in Japan, South Korea, and most of Europe [1]. Vespa velutina, an omnivorous insect, is mainly distributed in agriculture and forestry. Young wasps feed on the larvae of other insects. Vespa velutina feeds on fruit and trees. It is worth noting that there are reports that its melittin polypeptides are a cause of allergy and even death in humans and animals [2,3]. In addition, due to its high toxicity [4] and wide range of activities, it has caused serious damage to agroforestry ecology [5,6]. There is an urgent need to control the number of Vespa velutina and reduce its range of activities in order to protect the ecological balance of agriculture and forestry and to reduce harm to humans. Controlling V. velutina mainly depends on physically removing and eradicating them [2,3,4]. However, this method is extremely dangerous. It requires a lot of labour and material resources. Therefore, controlling V. velutina is very difficult. Biological agents can promote or inhibit the quantitative development of certain organisms under the condition of protecting the ecological balance. It is necessary to use appropriate biological control agents to improve the efficiency of V. velutina control. In addition, microbial insecticides have received a lot of attention worldwide. However, there are no reports on the control of wasps.
In order to study the intestinal pathogen V. velutina and to develop suitable microbial insecticides for its control, this study investigated the diversity of fungi and bacteria that are present in the adult stages of this insect species. The insect gut is a critical organ that serves as a habitat for numerous microorganisms [7] and plays a vital role in host metabolism, the degradation of toxic substances, and immune response [8,9]. The insect gut is also an important site for the colonisation of pathogens [10,11,12] given the high adaptability and utility of the wasp, as well as the close relationship between insect gut microorganisms. By studying the diversity of the microbial community, the function of the microbial community can be explored [13]. Traditional methods to study microbial community diversity include pure culture, physical and chemical identification, etc. However, most microorganisms in the natural environment are not culturable and difficult to identify [14,15]. With the development of the metagenomic concept and the rapid development of sequencing technology, 16S rRNA/ITS1 gene sequencing has been widely used in the study of microbial community diversity [16,17,18]. Zhang conducted a study on the diversity of the gut microbial community in V. velutina using high-throughput sequencing [19]. It was shown that Proteus and Lactobacillus (especially Lactobacillus and other lactic acid bacteria) could potentially have a significant impact on the gut of V. velutina. However, the study did not reveal any differences in the gut microbiota between naturally dying (VA) and typical (VN) adult V. velutina. A Cini [20] used targeted meta-genomics to describe the yeasts and bacteria gut communities of individuals of different reproductive phenotypes (workers and future queens), life stages (larvae, newly emerged individuals, and adults), and colony non-living samples (nest paper and larval faeces). Bacilli, Gammaproteobacteria, Actinobacteria, and Alphaproteobacteria were the most abundant classes of bacteria, and Saccharomycetes Dothideomycetes, Tremellomycetes, and Eurotiomycetes were the most represented yeast classes. But the result only provides the resource of the microbiome of V. velutina in Europe. Our aim is to determine the differences in species diversity and abundance of gut fungi and bacteria between VA and VN using PICRUSt2/FUNGuild in order to make functional predictions. Furthermore, our research provides data that can be used to investigate the functionality of the adult V. velutina gut microbiome. This will be valuable for the development of biocontrol agents for V. velutina control. In addition, our results provide the first metagenomic resource of the gut microbiome of V. velutina in China.

2. Materials and Methods

2.1. Materials Used

2.1.1. Adult Vespa velutina Sampling Method

In June 2022, both naturally decaying (VA) and healthy (VN) adult bodies of V. velutina were collected from a wasp farm in Nanning 530004, China. The bodies were surface disinfected with 70% alcohol prior to storage at 4 °C.

2.1.2. Gut Dissection

The worms were aseptically dissected, the intestines were isolated, and the intestines were placed separately in a 5 mL centrifuge tube with 2 mL of sterile water, according to Tu [21]. Then, the intestines were pulverised separately and mixed with a sterile blender. Finally, the intestines were ground separately and mixed using a sterilised blender.

2.2. DNA Extraction, PCR and Data Analysis

According to Jia [22], the total DNA was extracted from the intestine of adult V. velutina using a DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany). The extraction steps are described in the manual. The ITS2 (fungal) and 16S rRNA V3–V4 regions (bacterial) were then amplified using universal primers FITS7/RITS4 (fungal) and 333F/806R (bacterial), and our study refers to Jia [22] and Zhang [23]. PCR amplification steps and conditions were adapted from Jia [22], and the combined PCR amplification products were detected by 1% agarose gel electrophoresis. Paired-end sequencing was performed using the Illumina MiSeqPE300 sequencing platform. Finally, the high-throughput sequencing data were processed and analysed using the BMKCloud platform. The SPSS (26.0) analysis system (LSD) was then used to analyse the significance of the differences between treatments. In our study, sequencing data was analysed according to Zeng [24] using the Operational Taxonomic Units (OTU) marker method. To analyse the diversity of the gut microbiota in adult V. velutina, Shannon, Simpson, Ace, Chao, and coverage were selected. Ace and Chao reflect sample community richness, and the higher the index values, the higher the sample community richness. Shannon and Simpson reflect on sample species diversity. In addition, the higher the Shannon values and the lower the Simpson values, the higher the species diversity in the sample. The depth of sequencing is reflected in the coverage index. The closer the coverage index is to 1, the more likely it is that all species in the sample are covered by the sequencing depth. The closer the coverage index is to 1, the more reasonable the depth of sequencing is, and the depth of sequencing has basically covered all the species in the sample. Finally, PICRUSt2/FUNGuild was used to predict the function of ITS and 16S gene data and infer the functional gene composition of the sequenced samples, according to Zhang [23] and Kou [25]. Univariate analysis and multiple comparisons were performed using SPSS (26.0).

2.3. Isolation, Purification, and Identification of Cultural Microorganisms

The gut microorganisms of adult Vespa velutina were isolated and purified, according to Tu [21]. Simultaneously, the observation and recording of the culture characteristics of the strains were carried out. Preliminary strains were identified according to R.E. Buchanan [26] and Wei [27]. Then, the molecular identification of the strains by the ITS/16S rDNA amplification method and the phylogenetic tree were constructed by MEGA (5.1) according to Li [28].

3. Analysis of Results

3.1. Sequence Mosaic Assembly and OTU Clustering Analysis

Cluster analysis of the gut microbiota of adult Vespa velutina yielded a total of 3610 (fungi) and 8373 (bacteria). In addition, the number of gut fungal and bacterial OTUs was higher in VN than in VA. The number of bacterial OTUs was higher in VN or VA than in fungi separately (Table 1).

3.2. Alpha and Beta Diversity Analysis of Gut Bacteria and Fungi

Alpha diversity analysis showed that the sequencing depth covered all species in the sample. The flat curve indicates sufficient sampling for data analysis (Figure 1A,B). Both species diversity and richness were higher in VN than in VA for the gut fungal and bacterial communities. In addition, the species diversity and richness of the bacteria in both the VN and the VA were greater than those of the fungi (Table 2). Among the gut bacteria of adult Vespa velutina, the species composition of VA1 and VN1 is more similar, with Enterobacteriaceae dominating in VN1 and Asaia dominating in VA1; the species composition of VA2 and VA3 is more similar, with Herbaspirillum and Enterobacteriaceae dominating in VA2 and Herbaspirillum dominating in VA3; and the species composition of VN2 and VN3 is more similar, with Herbaspirillum dominating (Figure 1C). Among the gut fungi of adult Vespa velutina, the species composition of VA1, VA2, and VA3 is more similar, with Starmerella dominating in VA1, VA2, and VA3. The species composition of VN1, VN2, and VN3 is more similar, with Mortierella and Fusarium dominating in VN1, VN2, and VN3 (Figure 1D).

3.3. Identification of Fungi and Bacteria in the Gut of Adult V. velutina

Sequence alignment (Figure 2) identified the gut microbiota and bacteria of adult V. velutina. For the bacterial community, 44 phylum, 113 classes, 319 orders, 662 families, and 1394 genera could be determined. The microbial community composition of the gut samples of adult V. velutina is mainly Bacteroidot, Firmicute, and Proteobacteria at the phylum level (Figure 2A); mainly Bacteroida, Alphaproteobacteria, and Gammaproteobacteria at the class level (Figure 2B); mainly Enterobacterales, Burkholderiales, and Acetobacterales at the order level (Figure 2C); at the family level, mainly Oxalobacteraceae, Acetobacteraceay, and Enterobacteriaceae (Figure 2D); and at the genus level, mainly E. shigella, Herbaspirillum, and Aaaia (Figure 2E). For fungi, 13 phylum, 51 classes, 126 orders, 285 families, and 586 genera were identified. The microbial community composition of adult V. velutina gut samples is mainly Asomycota, Basidiomycota, and Chytridiomycota at the phylum level (Figure 2F), Saccharomycetes, Sodarmycetes, and Mortierellomycetes at the class level (Figure 2G); at the order level, mostly Saccharomycetales, Hypocreales, and Mortierellales (Figure 2H); at the family level, mostly Saccharomycetaceae, Mortierellaceae, and Plectosphaerellaceae (Figure 2I); and at the genus level, mostly Fusarium, Mortierella, and Starmerella (Figure 2J).

3.4. Differences in Gut Bacteria and Fungi between VN and VA

There were differences in gut bacteria and fungi composition between VN and VA adults. In addition, nine genera of fungi and 186 genera of bacteria were endemic to VA1; five genera of fungi and three genera of bacteria were endemic to VA2; four genera of fungi and six genera of bacteria were endemic to VA3; 73 genera of fungi and one genus of bacteria were endemic to VN1; 63 genera of fungi and 268 genera of bacteria were endemic to VN2; and 134 genera of fungi and 239 genera of bacteria were endemic to VN3. The core flora especially included 16 genera of fungi and 11 genera of bacteria in groups of samples (Figure 3); the common fungi included Cladosporium, Cladosporium, Fusarium, Trichocladium, Mortierella, Aspergillus, Talaromyces, Starmerella, Zygosaccharomyces, etc.; the common bacteria included Pseudomonas, Comamonadaceae, Lactobacillus, Bacillus, Muribaculaceae, Brevundimonas, etc. It is worth mentioning that there was a certain correlation between VN and VA via Source Tracker.

3.5. Function Prediction

A total of 20 functions were obtained via COG function prediction (Figure 4A), and the functions of bacteria in VN were similar to VA at the genus level (Table 3). Simultaneously, 364 bacterial metabolic pathways were annotated via KEGG metabolic pathway analysis. In addition, nine phenotypes were predicted by Bugbase phenotypes, such as Aerobic, Anaerobic, Gram-Negative, etc. (Figure 4B). There are three types of nutrition (Pathotroph, Saprotroph, and Symbiotroph; Figure 4C), which, in the gut fungi of V. velutina, were obtained via FUNGuild’s function prediction. In particular, Pathotroph could be subdivided into nine types, including Plant Pathogen, Wood Saprotroph, Fungal Parasite, etc. (Figure 4D).

3.6. Isolation and Identification of Culturable Microorganisms

The isolation and purification of gut microbes from adult Vespa velutina lepeletier yielded two genera and two classes of bacteria. However, no culturable fungi were obtained. Figure 5 shows the cultivation characteristics of VN1-VN6 and VA1-VA9. Two groups of culturable bacteria in the gut of adult V. velutina were identified in a phylogenetic tree (Figure 5). The first group consisted of Proteobacteria, including Escherichia, Raoultella, Shigella, Serratia, Cedecea, Acinetobacter, Klebsiella, and Erwinia. The second group consisted of Firmicutes, including only Bacillus. In addition, VA5, VN2, and VN5 are Serratia.;VA1 and VN1 are Escherichia; and VN4 and VN5 are Bacillus.

4. Discussion

4.1. The Gut Bacteria over Fungi in Adult V. velutina

The number of fungal and bacterial operational taxonomic units (OTUs) in the gut was higher in VN compared to VA, based on the OTU counts obtained. This result can be attributed to the diverse interactions between the insect’s gut immune system and the gut microorganisms [29,30,31]. Consequently, the natural mortality of V. velutina gradually eliminated pathogens from other gut microbial groups. Finally, the number of operational taxonomic units (OTUs) of the VA was lower than that of the VN. Furthermore, the number of bacterial OTUs in either VN or VA was higher than that of fungi alone, suggesting that bacteria were the primary beneficial flora in adult V. velutina. To further confirm the role of bacteria as beneficial flora, an alpha diversity analysis of the gut microbiota was performed. The gut microbiota of adult V. velutina were subjected to alpha diversity analysis. The results of the study showed that the gut fungi and bacteria of adult Vespa velutina Lepeletier in VA exhibited both diversity and uniformity. It was observed that the gut bacteria of adult V. velutina were the dominant flora compared to Chrysomya [32], megacephala, and Copris incertus [33].

4.2. The VA1 Is a Potential Pathogenic Bacteria of Adult V. velutina

In our study, 16 genera of fungi, such as Cladosporium, Cladosporium, and Fusarium, and 11 genera of bacteria, such as Pseudomonas, Comamonadaceae, and Lactobacillus, were present in different samples from both groups (three replicates in each group). In addition, the results were similar to those of Zhang [19]. In particular, Firmicutes, Bacteroidetes and Actinobacteria in gut microorganisms of adult V. velutina and Lactobacillus were reported to be the dominant genus. Simultaneously, the core flora of our study did not include Tenericutes and Sphingomonas, as reported by Zhang. Incidentally, Pseudomonas bacteria are characterised by their ability to immobilise perforation into tissues, elastin production, and adhesion activity. Pseudomonas bacteria are often considered potential pathogenic bacteria [34,35,36], indicating that under certain conditions, Pseudomonas bacteria may play a role in adult V. velutina disease. However, whether Pseudomonas bacteria form a symbiotic relationship with adult V. velutina requires further study. In addition, there are 11 phylum and 21 classes of fungi in our study, but no relevant reports have been found. Aspergillus in Fungi is a common pathogen, and most species of Fusarium are plant pathogenic pathogens [37,38].
In our study, we categorised fungi into three groups using FUNGuild, namely Symbiotroph, Pathotroph, and Saprotroph. It is noteworthy that symbiotrophs had the highest abundance across the different samples, whereas undefined saprotrophs and plant pathotrophs had significant numbers in the pathotroph group. The results indicate that fungi are not the main pathogen in mature V. velutina. However, they may be important in disease progression. Furthermore, the comparison of bacteria with PICRUSt2 in our study showed that there is a greater diversity of gut bacterial species between different samples. However, the function of the gut bacteria remains consistent, so we can speculate that this function belongs to a specific group of bacteria in the Vietnamese and American guts, which is the result of the long-term evolution of the microorganisms and their respective hosts. A total of nine types of bacteria were identified according to the Bugbase phenotype prediction. Incidentally, the pathogenic potential of VA was found to be higher than that of VN. For the village, the alpha diversity analysis showed that intestinal bacteria were the dominant flora. Therefore, it can be hypothesised that the pathogenic bacteria in adult V. velutina are bacterial in nature. To clarify the origin of these bacteria, a source tracker analysis was performed. The results indicate that the pathogenic bacteria could originate from either the gut or the environment, although the latter is more likely. To obtain culturable pathogens, gut microorganisms were isolated and identified. Two phylum and two classes of bacteria were obtained. No fungi were found. Furthermore, Escherichia and Serratia, which are common pathogenic bacteria [34,35,36], were detected in the gut of both adult VN and VA. The presence of Escherichia bacteria in VA and VN, however, differed significantly. VA1 was found to be more abundant than VN1 in the digestive tracts of adult V. velutina. It has been suggested that VA1 may be the causative agent of V. velutina in adults, but further authentication is required.

5. Conclusions

There were discrepancies in species diversity and prevalence of gut fungi and bacteria between VA and VN. In particular, both species diversity and frequency of VN were greater than VA alone. In addition, both species diversity and abundance of bacteria exceeded that of fungi in both VN and VA. The results indicate that bacteria are a critical component of the decomposition process. Furthermore, microbial isolation and identification revealed a potentially virulent bacterial strain (VA1), which is believed to be the pathogen causing infestation in adult V. velutina.

Author Contributions

M.P., Z.Y. and X.J.: Writing—original draft, preparation, Investigation, Conceptualization, and Methodology. J.L., M.P., Z.Y. and X.J.: Supervision, Conceptualization, and Project Administration. M.P. and Z.Y.: Conceptualization and Writing—review and editing, Supervision, Funding acquisition, and Resources. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financed by the National Natural Science Foundation of Guangxi (2017GXNSFAA198142).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

All data included in this study are available upon request by contact with the corresponding author.

Conflicts of Interest

The authors state that they have no known competing financial interests or personal relationships that may have influenced the work reported in this paper.

References

  1. Chi, L.; Li, Q.; Ma, L. Bionomics of Vespa velutina Lepeletier (Hymenoptera: Vespidae). J. Yunnan Agric. Univ. 2019, 34, 933–941. (In Chinese) [Google Scholar]
  2. Ueno, T. Flower-Visiting by the Invasive Hornet Vespa velutina nigrithorax (Hymenoptera: Vespidae). Int. J. Chem. Environ. Biol. Sci. 2015, 3, 444–448. [Google Scholar]
  3. Yang, Q.; Zhao, R.; Liu, X.; Guo, M.; Chen, X. Inhibitory Effects of Vespa velutina Extract on HepG2 Human Hepatoma Cells. J. Dali Univ. 2021, 6, 34–38. (In Chinese) [Google Scholar]
  4. Zhao, P.; Chang, M.; Luo, J.; Jiang, X. Approach-avoidance response of Vespa velutina workers to different plant extracts. J. For. Environ. 2021, 41, 76–81. (In Chinese) [Google Scholar]
  5. Bertolino, S.; Lioy, S.; Laurino, D.; Manino, A.; Porporato, M. Spread of the invasive yellow-legged hornet Vespa velutina (Hymenoptera: Vespidae) in Italy. Appl. Entomol. Zool. 2016, 51, 589–597. [Google Scholar] [CrossRef]
  6. Kishi, S.; Goka, K. Review of the invasive yellow-legged hornet, Vespa velutina nigrithorax (Hymenoptera: Vespidae), in Japan and its possible chemical control. Appl. Entomol. Zool. 2017, 52, 361–368. [Google Scholar] [CrossRef]
  7. Kamada, N.; Chen, G.Y.; Inohara, N.; Núñez, G. Control of pathogens and pathobionts by the gut microbiota. Nat. Immunol. 2013, 14, 685–690. [Google Scholar] [CrossRef]
  8. Ayres, J.S.; Schneider, D.S. Two ways to survive an infection: What resistance and tolerance can teach us about treatments for infectious diseases. Nat. Rev. Immunol. 2008, 8, 889. [Google Scholar]
  9. Zhong, Y.; Zou, D.; Liao, W.; Huang, N.; Luo, J. Comparison and Analysis of Diversified Intestinal Flora of Buzura suppressaria Larvae and Endophytes in Eucalyptus Leaves. J. For. Environ. 2021, 34, 10. (In Chinese) [Google Scholar]
  10. Fogarty, C.; Burgess, C.M.; Cotter, P.D.; Cabrera-Rubio, R.; Whyte, P.; Smyth, C.; Bolton, D.J. Diversity and composition of the gut microbiota of Atlantic salmon (Salmo salar) farmed in Irish waters. J. Appl. Microbiol. 2019, 127, 648–657. [Google Scholar] [CrossRef]
  11. Polenogova, O.V.; Kabilov, M.R.; Tyurin, M.V.; Rotskaya, U.N.; Krivopalov, A.V.; Morozova, V.V.; Mozhaitseva, K.; Kryukova, N.A.; Alikina, T.; Kryukov, V.Y.; et al. Parasitoid envenomation alters the Galleria mellonella midgut microbiota and immunity, thereby promoting fungal infection. Sci. Rep. 2019, 9, 4012. [Google Scholar] [CrossRef] [PubMed]
  12. Thong-On, A.; Suzuki, K.; Noda, S.; Inoue, J.I.; Kajiwara, S.; Ohkuma, M. Isolation and characterization of anaerobic bacteria for symbiotic recycling of uric acid nitrogen in the gut of various termites. Microbes Environ. 2012, 27, 186–192. [Google Scholar] [CrossRef]
  13. Huang, Z.; Qiu, J.; Li, J.; Xu, D.; Liu, Q. Exploration of microbial diversity based on 16S rRNA gene sequence analysis. Acta Microbiol. Sin. 2021, 61, 1044–1063. [Google Scholar]
  14. Amann, R.I.; Ludwig, W.; Schleifer, K.H. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 1995, 59, 143–169. [Google Scholar] [CrossRef] [PubMed]
  15. Steen, A.D.; Crits-Christoph, A.; Carini, P.; DeAngelis, K.M.; Fierer, N.; Lloyd, K.G.; Thrash, J.C. High proportions of bacteria and archaea across most biomes remain uncultured. ISME J. 2019, 13, 3126–3130. [Google Scholar] [CrossRef]
  16. The Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 2012, 486, 207–214. [Google Scholar] [CrossRef]
  17. The Integrative HMP (iHMP) Research Network Consortium. The integrative human microbiome project. Nature 2019, 569, 641–648. [Google Scholar] [CrossRef]
  18. Turnbaugh, P.J.; Ley, R.E.; Hamady, M.; Fraser-Liggett, C.M.; Knight, R.; Gordon, J.I. The human microbiome project. Nature 2007, 449, 804–810. [Google Scholar] [CrossRef]
  19. Zhang, L.; Liu, F.; Wang, X.-L.; Wang, P.H.; Ma, S.L.; Yang, Y.; Ye, W.-G.; Diao, Q.-Y.; Dai, P.-L. Midgut Bacterial Communities of Vespa velutina Lepeletier (Hymenoptera: Vespidae). Front. Ecol. Evol. 2022, 10, 934054. [Google Scholar] [CrossRef]
  20. Cini, A.; Meriggi, N.; Bacci, G.; Cappa, F.; Vitali, F.; Cavalieri, D.; Cervo, R. Gut microbial composition in different castes and developmental stages of the invasive hornet Vespa velutina nigrithorax. Sci. Total Environ. 2020, 745, 140873. [Google Scholar] [CrossRef]
  21. Tu, Y.; Lu, B.; Zhang, Y.; Jiang, D.; Qi, K. Preliminary identification and functional analysis of larval gut bacteria in Opisina arenosella Walker. J. Biosaf. 2020, 29, 258–263. (In Chinese) [Google Scholar]
  22. Jia, F.; Zhou, Z.; Zhao, W.; Sun, H.; Yao, Y. Diversity of Gut Microorganisms in Natural Population of Agrilus mali (Coleoptera: Buprestidae). Sci. Silvae Sin. 2022, 58, 86–96. (In Chinese) [Google Scholar]
  23. Zhang, J.; Zhu, B.; Xu, C.; Ding, X.; Li, J.F.; Zhang, X.G.; Lu, Z.H. Strategy of selecting 16S rRNA hypervariable regions for matagenome-phylogenetic marker genes based analysis. Chin. J. Appl. Ecol. 2015, 26, 3545–3553. (In Chinese) [Google Scholar] [CrossRef]
  24. Zeng, W.; Cheng, X.; Bi, L.; Lu, Y.; Chen, X.; Zhao, Z.; Zhang, Z. Analysis of Endophytic Bacteria Species in Cinnamon Leaves and Twigs under Different Pretreatment Methods. J. Southwest For. Univ. 2022, 42, 23–29. (In Chinese) [Google Scholar]
  25. Kou, R.; Dou, F.; Li, H.; Zhou, Z.; Long, J.; Huang, D. Gut bacterial divergence between different larval instars of Andrena camellia Wu (Hymenoptera: Andrenidae). J. Environ. Entomol. 2022, 44, 402–413. (In Chinese) [Google Scholar]
  26. Buchanan, R.E.; Gibbons, N.E. Berger’s Handbook for Bacterial Identification, 8th ed.; Science Press: Beijing, China, 1984. (In Chinese) [Google Scholar]
  27. Wei, J. Fungal Identification Handbook; Shanghai Science and Technology Press: Shanghai, China, 1979. (In Chinese) [Google Scholar]
  28. Li, X.; Wang, J.; Sha, J. Screening and identification of a cellulose degrading fungus. Feed Res. 2019, 42, 83–86. (In Chinese) [Google Scholar]
  29. Douglas, A.E. The molecular basis of bacterial–insect symbiosis. J. Mol. Biol. 2014, 426, 3830–3837. [Google Scholar] [CrossRef]
  30. Engel, P.; Moran, N.A. The gut microbiota of insects–diversity in structure and function. FEMS Microbiol. Rev. 2013, 37, 699–735. [Google Scholar] [CrossRef]
  31. Stecher, B.; Hardt, W.-D. Mechanisms controlling pathogen colonization of the gut. Curr. Opin. Microbiol. 2011, 14, 82–91. [Google Scholar] [CrossRef]
  32. Suárez-Moo, P.; Cruz-Rosales, M.; Ibarra-Laclette, E.; Desgarennes, D.; Huerta, C.; Lamelas, A. Diversity and Composition of the Gut Microbiota in the Developmental Stages of the Dung Beetle Copris incertus Say (Coleoptera, Scarabaeidae). Front. Microbiol. 2020, 11, 1698. [Google Scholar] [CrossRef]
  33. Wang, X.; Gao, Q.; Wang, W.; Wang, X.; Lei, C.; Zhu, F. The gut bacteria across life stages in the synanthropic fly Chrysomya megacephala. BMC Microbiol. 2018, 18, 131. [Google Scholar] [CrossRef] [PubMed]
  34. Ewers, C.; Janssen, T.; Wieler, L.H. Avian pathogenic Escherichia coli (APEC). Berl. Und Munch. Tierarztl. Wochenschr. 2003, 116, 381–395. [Google Scholar]
  35. Jeong, H.U.; Mun, H.Y.; Oh, H.K.; Kim, S.B.; Yang, K.Y.; Kim, I.; Lee, H.B. Evaluation of insecticidal activity of a bacterial strain, Serratia sp. EML-SE1 against diamondback moth. J. Microbiol. 2010, 48, 541–545. [Google Scholar] [CrossRef] [PubMed]
  36. Mohan, M.; Selvakumar, G.; Sushil, S.N.; Bhatt, J.C.; Gupta, H.S. Entomopathogenicity of endophytic Serratia marcescens strain SRM against larvae of Helicoverpa armigera (Noctuidae: Lepidoptera). World J. Microbiol. Biotechnol. 2011, 27, 2545–2551. [Google Scholar] [CrossRef]
  37. Cheng, Y.; Zhao, W.; Lin, R.; Yao, Y.; Yu, S.; Zhou, Z.; Zhang, X.; Gao, Y.; Huai, W. Fusarium species in declining wild apple forests on the northern slope of the Tian Shan Mountains in north-western China. For. Pathol. 2019, 49, e12542. [Google Scholar] [CrossRef]
  38. Yang, W.; Chen, Y.; Chen, X.; Yao, Y.; Zhou, Y. A New Disease of Tea Plant Caused by Phoma adianticola. J. Tea Sci. 2016, 36, 59–67. [Google Scholar]
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Figure 1. Alpha and Beta Diversity Analysis of Gut Bacteria and Fungi. (A): The species accumulation curves of the gut bacteria; (B): the species accumulation curves of the gut fungi (at the level of the genus); (C): the UPGMA analysis of the gut bacteria; (D): the UPGMA analysis of the gut fungi (at the level of the genus).
Figure 1. Alpha and Beta Diversity Analysis of Gut Bacteria and Fungi. (A): The species accumulation curves of the gut bacteria; (B): the species accumulation curves of the gut fungi (at the level of the genus); (C): the UPGMA analysis of the gut bacteria; (D): the UPGMA analysis of the gut fungi (at the level of the genus).
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Figure 2. Composition of the top ten gut microbiota of Locusta migratoria manilensis Meyen in different geographical populations. (A,F): Phylum. (B,G): Class. (C,H): Order. (D,I): Family. (E,J): Genus.
Figure 2. Composition of the top ten gut microbiota of Locusta migratoria manilensis Meyen in different geographical populations. (A,F): Phylum. (B,G): Class. (C,H): Order. (D,I): Family. (E,J): Genus.
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Figure 3. Venn diagram of gut bacteria (A) and fungi (B).
Figure 3. Venn diagram of gut bacteria (A) and fungi (B).
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Figure 4. Predicting COG functional genes in gut bacteria (A), predicting Bugbase phenotypes in gut bacteria (B), and predicting FUNGuild in gut fungi (C,D).
Figure 4. Predicting COG functional genes in gut bacteria (A), predicting Bugbase phenotypes in gut bacteria (B), and predicting FUNGuild in gut fungi (C,D).
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Figure 5. Phylogenetic tree in gut bacteria.
Figure 5. Phylogenetic tree in gut bacteria.
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Table 1. Basic information for the high-throughput sequencing of ITS1 of intestinal fungi and of 16S rRNA of bacteria in the VN and VA.
Table 1. Basic information for the high-throughput sequencing of ITS1 of intestinal fungi and of 16S rRNA of bacteria in the VN and VA.
Sample NumberGeneNumber of Raw TagsNumber of Valid TagsNumber of OTUsNumber of Taxa of Different Taxonomic Categories
PhylumClassOrdersFamilyGenus
VA1ITS179,89279,63395820334654
16S rRNA80,15779,9931131522476987
VA2ITS179,96779,798120718344663
16S rRNA80,13780,006299214097145186
VA3ITS180,06079,87084715274051
16S rRNA79,95379,80318963682218375688
VN1ITS180,22179,90813021344274051
16S rRNA80,32380,162731115303744
VN2ITS180,02179,65513021345100197345
16S rRNA79,93979,765325439101303744
VN3ITS180,00679,66914251351109234406
16S rRNA79,94779,764318341113261504886
Table 2. Diversity indices of fungi and bacteria in the gut of Vespa velutina Lepeletier in different hosts and at different stages of development.
Table 2. Diversity indices of fungi and bacteria in the gut of Vespa velutina Lepeletier in different hosts and at different stages of development.
GroupsSample CodeDiversity Index
AceChao1ShannonSimpsonCoverage
FungiVA196.4495.192.050.690.9999
VA2120.62120.040.540.111.0000
VA384.8784.161.810.571.0000
VN11326.431326.138.530.991.0000
VN31302.411302.168.620.991.0000
VN31426.061425.108.360.990.9999
BacteriaVA1113.00113.001.510.441.0000
VA2303.32299.722.670.710.9998
VA31896.171896.008.150.981.0000
VN173.7173.041.310.511.0000
VN33254.323254.0010.081.001.0000
VN33183.233183.0010.261.001.0000
Table 3. Diversity indices of fungi and bacteria in the gut of Vespa velutina lepeletier at different hosts and stages.
Table 3. Diversity indices of fungi and bacteria in the gut of Vespa velutina lepeletier at different hosts and stages.
CategoryDescriptionSample (%)
VA1VA2VA3VN1VN2VN3
RGenus function prediction only0.11070.11490.11480.10840.11230.1112
EAmino acid transport and metabolism0.10920.09350.09370.08950.10660.0986
SFunction unknown0.08870.07500.07330.08710.09340.0749
GCarbohydrate transport and metabolism0.10500.06150.06120.08410.07200.0677
CEnergy production and conversion0.06610.06420.06470.06520.06260.0648
MCell wall/membrane/envelope biogenesis0.05490.06490.06590.06830.06180.0639
KTranscription0.06710.06430.06420.05810.06460.0632
JTranslation, ribosomal structure, and biogenesis0.04560.07330.07440.05980.05100.0710
PInorganic ion transport and metabolism0.07350.05070.05020.05460.06490.0553
HCoenzyme transport and metabolism0.04480.04820.04860.04860.04660.0497
LReplication, recombination, and repair0.03920.04850.04890.04810.03350.0466
TSignal transduction mechanisms0.03470.04190.04120.03500.04490.0400
OPosttranslational modification, protein turnover, and chaperones0.03350.03960.03960.04160.03410.0394
ILipid transport and metabolism0.02400.03600.03610.02590.03380.0331
FNucleotide transport and metabolism0.02420.03000.03030.02870.02250.0299
UIntracellular trafficking, secretion, and vesicular transport0.02220.02560.02550.03210.02560.0251
NCell motility0.01190.01850.01800.02240.02630.0193
QSecondary metabolites biosynthesis, transport, and catabolism0.02170.01870.01860.01840.02220.0184
VDefence mechanisms0.01360.01900.01930.01390.01220.0166
DCell cycle control, cell division, and chromosome partitioning0.00860.01090.01090.00990.00820.0107
OtherOther0.00050.00060.00060.00030.00090.0006
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Pang, M.; Luo, J.; Yang, Z.; Jiang, X. Diversity of Gut Microbes in Adult Vespa velutina (Asian Hornet) Carcasses Killed by Natural Causes. Diversity 2023, 15, 1162. https://doi.org/10.3390/d15121162

AMA Style

Pang M, Luo J, Yang Z, Jiang X. Diversity of Gut Microbes in Adult Vespa velutina (Asian Hornet) Carcasses Killed by Natural Causes. Diversity. 2023; 15(12):1162. https://doi.org/10.3390/d15121162

Chicago/Turabian Style

Pang, Meiling, Ji Luo, Zhende Yang, and Xuejian Jiang. 2023. "Diversity of Gut Microbes in Adult Vespa velutina (Asian Hornet) Carcasses Killed by Natural Causes" Diversity 15, no. 12: 1162. https://doi.org/10.3390/d15121162

APA Style

Pang, M., Luo, J., Yang, Z., & Jiang, X. (2023). Diversity of Gut Microbes in Adult Vespa velutina (Asian Hornet) Carcasses Killed by Natural Causes. Diversity, 15(12), 1162. https://doi.org/10.3390/d15121162

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