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The effect of white grub (Maladera Verticalis) larvae feeding on rhizosphere microbial characterization of aerobic rice (Oryza sativa L.) in Puer City, Yunnan Province, China

BMC Microbiology volume 24, Article number: 123 (2024) Cite this article

Abstract

Background

Rhizosphere microorganisms are vital in plants’ growth and development and these beneficial microbes are recruited to the root-zone soil when experiencing various environmental stresses. However, the effect of white grub (Maladera verticalis) larvae feeding on the structure and function of rhizosphere microbial communities of aerobic rice (Oryza sativa L.) is unclear.

Results

In this study, we compared physicochemical properties, enzyme activities, and microbial communities using 18 samples under healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils at the Yunnan of China. 16 S rRNA and ITS amplicons were sequenced using Illumina high throughput sequencing. M. verticalis larvae feeding on aerobic rice can influence rhizosphere soil physicochemical properties and enzyme activities, which also change rhizosphere microbial communities. The healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soil microorganisms had distinct genus signatures, such as possible_genus_04 and Knoellia genera in healthy aerobic rice rhizosphere soils and norank_f__SC − I−84 and norank_f__Roseiflexaceae genera in M. verticalis larvae-feeding aerobic rice rhizosphere soils. The pathway of the metabolism of terpenoids and polyketides and carbohydrate metabolism in rhizosphere bacteria were significantly decreased after M. verticalis larvae feeding. Fungal parasite–wood saprotroph and fungal parasites were significantly decreased after M. verticalis larvae feeding, and plant pathogen–wood saprotroph and animal pathogen–undefined saprotroph were increased after larvae feeding. Additionally, the relative abundance of Bradyrhizobium and Talaromyces genera gradually increased with the elevation of the larvae density. Bacterial and fungal communities significantly correlated with soil physicochemical properties and enzyme activities, respectively.

Conclusions

Based on the results we provide new insight for understanding the adaptation of aerobic rice to M. verticalis larvae feeding via regulating the rhizosphere environment, which would allow us to facilitate translation to more effective measures.

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Background

Rice (Oryza sativa L.) is one of the major staple food crops with respect to area under cultivation and total production. It is widely cultivated in Asia and is significant in ensuring global food security. Rice cultivation requires a huge amount of water [1, 2]. In Asia, approximately 50% of irrigation water is consumed by rice cultivation, which accounts for 24–30% of the withdrawal of the world’s total freshwater [1, 2]. In addition, aerobic rice is a method of rice where seeds are sowed directly in well-tilled and leveled fields [3]. Aerobic rice is developed to tackle the water shortage as a sustainable method to enhance rice production [3]. However, aerobic rice cultivation not only faces overground insects damage, such as yellow stem borer (Scirpophaga incertulas), rice leaf folder (Cnophalocrosis medinalis), brown planthopper (Nilaparvata lugens), white-backed planthopper (Sogatella turcifera), and green paddy leafhopper (Nephotetticx virescens), but also increases the risk of damage caused by root-feeding insects, such as white grubs [4, 5]. The white grub is a destructive root-feeding insect that feeds on corn [6], potato [7], peanut [8], which may also become one of the pests that harm rice with aerobic cultivation. Such as white grubs were a major production constraint in upland rice production in North-Western Himalayas [9], Madagascar [10], Philippines [11]. The larvae usually damage young seedlings and roots of plants, sometimes resulting in significant yield losses [12, 13] and cost input [11]. However, the damage caused by root-feeding insects is a serious problem in aerobic rice cultivation and will remain so for a long time. Therefore, it is important to investigate the effects of white grub on aerobic rice and microenvironment.

After herbivorous insect’s attack plants, plants rely on direct defense mechanisms and recruit pest antagonists mainly via the release of volatile organic compounds [14, 15]. Accumulating evidence shows that changes in other rhizosphere organisms after root-feeding insects are strongly associated with other rhizosphere organisms [16], such as beneficial plant microbes, antagonists/pathogens of root herbivores, competitors, symbiotic microbes, and detritivores. The root-feeding insect Elateridae larvae (wireworms) was reported to change the structure, functional diversity, and tolerance of soil fungi and bacteria [17]. Holotrichia parallela larvae (white grub) infestation was reported to change the rhizosphere microbiome of peanuts [18]. In addition, there have been many reports on the dynamic responses of conventional rice rhizosphere microorganisms to biotic and abiotic stresses [19,20,21], and root-feeding insects feeding on plant root changed rhizosphere microorganisms’ structure and functional diversity. However, the effects of white grub on rhizosphere microorganisms of aerobic rice are not completely understood. Therefore, this study investigates the effects of white grub on aerobic rice rhizosphere microorganisms.

Plants can recruit soil microorganisms into the rhizosphere when experiencing various biotic (insects) and abiotic (heavy metal pollution, droughts, floods, and salinity) stresses [22]. Rhizosphere microorganisms play critical roles in enhancing plant growth and development by promoting nutrient acquisition and assimilation, improving soil texture, and secreting and modulating extracellular molecules [23]. A root-feeding insect infestation can recruit some microorganisms into a plant’s rhizosphere, such as bacterial genera Pseudomonas, Bryobacter, Chryseobacterium, and Roseiarcus and fungal species Candida palmioleophila and Coniochaeta fasciculata [18, 24, 25]. The Pseudomonas genus, as a plant-growth-promoting rhizobacteria (PGPR), improves plant growth and health [23]. Notably, rhizosphere microorganisms also promote plant defense against herbivores both above- and belowground by providing feeding deterrence or antibiosis [26]. In addition, Bryobacter was positively correlated with the content of bioactive compounds and promoted the biosynthesis and accumulation of 1,8-cineole, cypressene, limonene, and α-terpineol [27]. However, the effects of altered rhizosphere microorganisms on the surrounding soil environment are still unclear.

Therefore, the purpose of this study was to investigate the effects of white grub feeding on soil physicochemical properties, soil enzyme activities, and microbial characterizations of the aerobic rice rhizosphere.

Materials and methods

Plants

The rice cultivar (Oryza sativa L.), Dianheyou615, was grown at the Puer experimental station, Puer City, Yunnan Province, China. Since January 2022, these experimental sites have been planting Dianheyou615 rice and conducting the same agricultural operations. The rhizosphere soil was collected from three distinct sites (Haguoma, Haozhiba, and Nuoguo) in July 2023.

Soil collection

The damage of white grubs was investigated during the tillering stage by digging out the root soil. When a white grub found in the field was identified as Maladera verticalis larvae, the rhizosphere soil of the aerobic rice plant was collected. The loose soil around the M. verticalis larvae-feeding (Mv group) plants and the healthy (CK group) aerobic rice plants was shaken off, and the attached soil was brushed gently and collected [28]. Three biological replicates were maintained for each group, with each replicate collected from 15 plants. Then, the samples were quickly stored in ice boxes and returned to the laboratory. The soil samples were used for soil microbiological analysis, and the other collected material was air-dried for soil properties and enzyme activity for detection analysis. The basic information on sampling location, longitude, insect population density, temperature, humidity, latitude, and altitude are shown in Table 1.

Table 1 The basic conditions of the sampling sites
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Analysis of soil physicochemical properties

A pH meter (FE28, METTLER-TOLEDO, USA) was used to determine soil pH in a soil–water suspension (1:2.5, air-dried soil/distilled water for removing CO2) after shaking for 30 min. Soil physiochemical properties were measured using the following methods: organic matter—potassium dichromate oxidation spectrophotometric method; total nitrogen—sulfuric acid digestion method + Kjeldahl method; total phosphorus—alkali fusion-Mo-Sb anti spectrophotometric method; available phosphorus—sodium hydrogen carbonate solution-Mo-Sb anti spectrophotometric method; total potassium—NaOH digestion method + flame photometric method; available potassium—ammonium acetate extraction + flame photometric method; and NH4-N—KCl2 extraction + indophenol blue spectrophotometric method.

Determination of soil enzyme activities

Urease activity, acid phosphatase activity, catalase activity, β-glucosidase, polyphenol oxidase, and acid invertase in rhizosphere soil were determined using commercially available kits (MolFarming, Nanjing, China). Briefly, fresh soil samples were naturally air-dried and sieved through a 30–50 mesh sieve.

Urease activity

(1) Add 100 µL of toluene to 0.1 g of soil and let sit at room temperature for 15 min. (2) Add 500 µL of reagent I and 1,000 µL of reagent II to (1) the sample. Then, incubate the mixture at 37℃ for 24 h and centrifuge at 10,000 rpm for 10 min. Add 80 µL of reagent III and 60 µL of reagent IV to 200 µL of (2) the supernatant. Then, incubate the mixture at room temperature for 20 min and add 660 µL of distilled water. The absorbance value was measured at 630 nm.

Acid phosphatase activity

(1) Add 50 µL of toluene to 0.1 g of soil and let sit at room temperature for 15 min. (2) Add 250 µL of reagent I and 250 µL of reagent II to (1) the sample. Then, incubate the mixture at 37℃ for 24 h. (3) Add reagent III (500 µL) to (2) the sample and centrifuge at 10,000 rpm for 10 min. (4) Add 700 µL of reagent IV, 100 µL of reagent V, and 100 µL of reagent VI to 100 µL of (3) the supernatant and allow a standing reaction time of 10 min. The absorbance value was measured at 630 nm.

Catalase activity

(1) Add 1,000 µL of reagent I to 0.05 g of soil and incubate for 30 min. Then, add 200 µL of reagent II and centrifuge at 10,000 rpm for 10 min. (2) Mix 100 µL of (1) the supernatant and 1,000 µL of reagent III and allow the mixture to stand for 5 min. The absorbance value was measured at 405 nm.

β-glucosidase

(1) Add 50 µL of toluene to 0.1 g of soil and allow the mixture to sit at room temperature for 15 min. (2) Add 500 µL of reagent I and 100 µL of reagent II to (1) the sample. Then, incubate at 37℃ for 3 h and then boil for 5 min. (3) Add 900 µL of reagent IV to 100 µL of (2) the supernatant and allow the mixture to stand for 15 min. The absorbance value was measured at 400 nm.

Polyphenol oxidase

(1) Add 500 µL of reagent I to 0.1 g of soil and incubate at 30℃ for 2 h. Add 200 µL of reagent II and 2,000 µL of ether and allow the mixture to stand at room temperature for 30 min. The absorbance value was measured at 430 nm.

Acid invertase

(1) Add 50 µL of toluene to 0.1 g of soil and allow the mixture to stand at room temperature for 15 min. (2) Add 250 µL of reagent I and 750 µL of reagent II to (1) the sample and incubate at 37℃ for 24 h. Then, centrifuge at 10,000 rpm for 10 min. (2) Add 300 µL of reagent III to (1) the supernatant and then boil for 5 min. (3) Add 1,000 µL of distilled water to (2) the sample. The absorbance value was measured at 540 nm.

Determine bacterial and fungal densities

The rhizosphere soil (10 g) was suspended in 90 mL of sterile saline (10% w/v) and agitated at 150 rpm for 30 min. The suspension was diluted serially to 10-1-10-6. Aliquots of 100 µL of suspension (10-4-10-6) were spread on Luria–Bertani (LB) plates to cultivate bacteria and 100 µL of suspension (10-1-10-3) was spread on Thayer–Martin medium (hopebio, Qingdao, China) with rose Bengal and 0.003% streptomycin sulfate on plates to cultivate fungi. The plates were incubated at 25 ± 1℃ for 3 days. After incubation, the colony-forming units (CFU/g) of bacteria and fungi were counted.

DNA extraction and MiSeq sequencing

Rhizosphere microorganism genomic DNA isolation, 16 S rDNA, and ITS gene sequencing were completed with the help of Majorbio Co. Ltd., Shanghai. Isolation of microbial DNA from the rhizosphere soil was performed using a Qiagen E. Z.N. A.® Soil DNA Kit (Omega Bio-Tek, USA). The 16 S rRNA-encoding gene and ITS rDNA were amplified from extracted DNA using bacterial primers, 338 F/806R [29], and fungal primers, ITS1F/ITS2R, respectively [30]. The PCR product was identified via 2% gel electrophoresis, purified using AxyPrep DNA Gel Extraction Kit (AXYGEN, Union, CA), and quantified via QuantiFluor™-ST (Promega, Wisconsin, USA). The pooled amplicon library was then sequenced on the Illumina MiSeq platform using the TruSeqTM DNA Sample Prep Kit (Illumina, USA) according to the manufacturer’s instructions. Flash and Trimmomatic programs were used to screen and trim the raw sequences, including quality trimming, chimera detection, and removal. The Silva database (Release 138) was used to align the sequences for 16 S rRNA gene data [31], and the Unite database (version 8.0) was used to align ITS gene data [32]. The operational taxonomic unit (OTU) was aligned using the Silva and Unite databases to obtain species taxonomic information for each OTU. The OTU table was manually filtered, i.e., chloroplast sequences in all samples were removed.

Bacterial and fungal functional analyses

The software Tax4Fun (Version 0.3.1) and FUNGuild (Version 1.0) were used for the functional prediction of 16 S and ITS amplicon sequencing results, respectively. Tax4Fun was used to obtain three levels of metabolic pathway information and pathway abundance [33]. FUNGuild was used to obtain fungal functional guild data [34].

Statistical analysis

The alpha diversity index of Shannon–Wiener was calculated using Mothur (Version 1.30.1). The number of reads of species was also used for principal component analysis (PCA) based on the Euclidean distance using Qiime (Version 1.9.1). Species with significant differences in sample classification were identified using linear discriminant analysis (LDA ≥ 2). The correlation analyses were conducted using R software (Version 4.1.1) and visualized using the pheatmap package in R software. An unpaired, two-sided Student’s t-test was used when two groups were compared. Differences were considered to be statistically significant if P < 0.05.

Results

M. verticalis larvae feeding influenced soil physicochemical properties

The irrigated rice Dianheyou 615 can be grown in mountainous areas in the Yunnan-Guizhou plateau in China, where below 1900 m above sea level and the rainfall exceeds 1000 millimeters. Aerobic rice cultivation model will increase the risk of damage caused by M. verticalis larvae (Fig. 1). Next, we examined the changes in the physicochemical properties of rhizosphere soil after the harm of M. verticalis larvae. As shown in Table 2, M. verticalis larvae feeding on aerobic rice plants significantly increased the pH, organic matter, total K, and available K contents of the HGM-Mv group and significantly decreased the total N content compared with the HGM-CK group. M. verticalis larvae feeding significantly raised the pH of the HZB-Mv group, while M. verticalis larvae feeding significantly reduced the total N, total P, available P, and available K contents compared with the HZB-CK group. In addition, the total P, available P, and available K contents were markedly elevated in the NG-Mv group compared with the NG-CK group, and the pH and organic matter contents were inhibited. However, the content of NH4+-N was not affected by M. verticalis larvae feeding in the three regions.

Fig. 1
figure 1

An image of a white grub (Maladera verticalis larvae) in the field, which harms aerobic rice roots

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Table 2 Physicochemical characteristics of healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils within different regions
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M. Verticalis larvae feeding influenced soil enzyme activities

As shown in Table 3, M. verticalis larvae feeding significantly increased the activity of urease, phosphatase, β-glucosidase, polyphenol oxidase, and acid invertase in the HGM samples. In the HZB samples, M. verticalis larvae feeding significantly increased urease, catalase, and β-glucosidase activities and significantly decreased phosphatase and acid invertase activities. M. verticalis larvae feeding markedly decreased urease and phosphatase activities in the NG samples.

Table 3 Soil enzyme activities of healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils within different regions
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Sequencing data statistics

The OTU number of bacteria in each sample was at least 24.32 (Table S1). The coverage of bacteria in all samples were > 98%. The rarefaction curves of these sequences tend to be flat in bacteria, indicating a sufficient depth for the sequencing depth. In addition, the OTU number of fungi in each sample was at least 672. The coverage of bacteria in all samples were > 99%. The rarefaction curves of these sequences tend to be flat in fungi, indicating a sufficient depth for the sequencing (Figure F1).

The diversity and composition of rhizosphere bacteria after M. verticalis larvae feeding

We next explored the effects of M. verticalis larvae feeding on aerobic rice rhizosphere bacteria. M. verticalis larvae feeding increased bacterial density in the three regions compared with the CK group (Fig. 2A). PCA was used to determine whether there were significant differences in the bacterial composition of M. verticalis larvae-feeding aerobic rice soil samples between the three regions. As shown in Figure S2, the samples were divided into three groups by region (Figure S2A). These samples were divided into two groups according to the Mv and CK groups in the HGM (Figure S2B), HZB (Figure S2C), and NG (Figure S2D) regions. The results suggest that M. verticalis larvae feeding was the main factor leading to differences in rhizosphere bacteria in a plot. However, the Shannon index (Fig. 2B) and the relative abundance of the top 10 phyla (Fig. 2C) showed no significant differences in the Mv and CK groups in same experimental area. In addition, the top 20 genera were displayed using a heatmap. The 9 healthy and 9 M. verticalis larvae-feeding aerobic rice rhizosphere bacteria formed three distinct groups with three regions (Fig. 3D). Bradyrhizobim was elevated in the M. verticalis larvae-feeding aerobic rice rhizosphere soils. Then, the top 50 bacterial genera that distinguish the M. verticalis larvae-feeding aerobic rice rhizosphere bacteria and the healthy aerobic rice rhizosphere bacteria were recorded by log10FC levels. The relative abundances of 26, 37, and 24 genera were increased after M. verticalis larvae feeding in the HGM-Mv, HZB-Mv, and NG-Mv groups, respectively (Fig. 2D, Table S2). On the contrary, M. verticalis larvae feeding decreased the relative abundances of 24, 13, and 26 genera in the samples from the HGM, HZB, and NG sites (Fig. 2D, Table S2).

Fig. 2
figure 2

The diversity and composition of rhizosphere bacteria after M. verticalis larvae feeding. (A) The colony-forming units of bacteria in the LB medium. (B) Alpha diversity of the Shannon index at the bacterial genus level. (C) Phylum-level relative frequency in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere bacteria. (D) Heatmap of genus-level in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere bacteria. (E) Genus-level relative frequency in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere bacteria. The relative frequency of log10 fold change (log10FC) was included in the plot. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice; HGM, Haguoma; HZB, Haoziba; and NG, Nuoguo

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Fig. 3
figure 3

The diversity and composition of rhizosphere fungi after M. verticalis larvae feeding. (A) The colony-forming units of fungi in Thayer–Martin medium with rose bengal and 0.003% streptomycin sulfate. (B) Alpha diversity of Shannon index at the fungal genus level. (C) Phylum-level relative frequency in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere fungi. (D) Heatmap of genus-level in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere fungi. (E) Genus-level relative frequency in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere fungi. The relative frequency of log10 fold change (log10FC) was included in the plot. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice; HGM, Haguoma; HZB, Haoziba; and NG, Nuoguo

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The diversity and composition of rhizosphere fungi after M. Verticalis larvae feeding

M. verticalis larvae feeding did not significantly change fungal density in the rhizosphere soil of three regions (Fig. 3A). PCA was used to determine whether there were significant differences in the fungal composition of M. verticalis larvae-feeding soil samples between the tested regions. As shown in Figure S2, the samples were divided into three groups by region (Figure S3A). These samples were then divided into two groups according to the Mv and CK groups in the HGM (Figure S3B), HZB (Figure S3C), and NG (Figure S3D) regions. The results suggest that M. verticalis larvae feeding was the main factor leading to differences in rhizosphere fungi in a plot. However, M. verticalis larvae feeding did not significantly change the Shannon index (Fig. 3B) and relative abundance of the top five phyla (Fig. 3C) in same experimental area. In addition, the top 20 genera were displayed using a heatmap. The 9 healthy and 9 M. verticalis larvae-feeding aerobic rice rhizosphere bacteria formed three distinct groups with three regions (Fig. 3D). Papulaspora was decreased in the M. verticalis larvae-feeding aerobic rice rhizosphere soils. Then, the top 50 fungal genera that distinguish the Mv and CK were recorded by log10FC. The relative abundances of 19, 24, and 24 genera were increased in the HGM-Mv, HZB-Mv, and NG-Mv groups, respectively (Fig. 3D, Table S3). On the contrary, M. verticalis larvae feeding decreased the relative abundances of 27, 25, and 21 genera in the HGM, HZB, and NG samples (Fig. 3D, Table S3).

LDA revealed the most featured microbial genera in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere microorganisms

To identify the featured genus associated with M. verticalis larvae feeding, we performed LDA on microbial abundance profiles at the genus level. After comprehensive analysis and screening with the Venn diagram tool (Figure S4), at the bacterial level, seven featured genera were identified in the healthy aerobic rice rhizosphere (Figure S4A), five genera were shared among the two regions, and possible_genus_04 and Knoellia genera were shared among the three regions (Fig. 4A). M. verticalis larvae-feeding aerobic rice rhizosphere bacteria featured 22 genera (Figure S4B), 20 genera were shared among the two regions, and norank_f_SC-I-84 and norank_f_Roseiflexaceae genera were shared among the three regions (Fig. 4A). At the fungal level, 8 and 13 featured genera were identified in the healthy and M. verticalis larvae-feeding aerobic rice rhizosphere, respectively (Figure S4C and S4D), but no featured genera were shared among the three regions (Fig. 4B). Our results further confirm that the healthy and M. verticalis larvae-feeding aerobic rice rhizosphere microorganisms have distinct taxonomical signatures.

Fig. 4
figure 4

Significant differences in genus abundance that discriminate healthy and M. verticalis larvae-feeding aerobic rice rhizosphere microorganisms. LDA (LDA value > 2.0 and P value ≤ 0.05) scores of top featured bacterial (A) and fungal (B) genera in healthy and M. verticalis larvae-feeding aerobic rice rhizosphere. The square and circle represent the CK and Mv groups, respectively. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice; HGM, Haguoma; HZB, Haoziba; and NG, Nuoguo

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M. verticalis larvae-feeding induced changed aerobic rice rhizosphere soil microbial community and composition

To further investigate the effects of M. verticalis larvae feeding on aerobic rice rhizosphere soil microorganisms, we merged all CK and Mv groups, separately. In the bacterial level, M. verticalis larvae-feeding significantly reduced the relative abundances of Fibrobacterota and Cyanobacteria phyla (Fig. 5A). With respect to soil bacterial composition, M. verticalis larvae-feeding significantly increased the genera of Bradyrhizobium, Ramlibacter, Rhodoplanes, and unclassified_f__Oxalobacteraceae, but decreased the genera of norank_f__norank_o__Chloroplast, Knoellia, norank_f__norank_o__norank_c__Sericytochromatia, Acidipila, Asticcacaulis, and possible_genus_04 (Fig. 5B). Besides, M. verticalis larvae-feeding changed aerobic rice rhizosphere soil bacterial community (Fig. 5C). The network was assigned to 4 modules with healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils. The modularity decreased from 0.355 in healthy aerobic rice rhizosphere soils to 0.277 in M. verticalis larvae-feeding aerobic rice rhizosphere soils (Table S4). Modules I, III, and IV displayed more proportion in the Mv group (49%, 12.5%, and 6%) than CK group (48.5%, 5.55%, and 1%) (Fig. 5C and Table S6). However, the module I was decreased from 45% in healthy aerobic rice rhizosphere soils to 32.5% in M. verticalis larvae-feeding aerobic rice rhizosphere soils. The network was assigned to 11 and 12 phyla within healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils, respectively. Among them, nodes in the CK network were mostly from Acidobacteriota (25%), Proteobacteria (22.55%), and Chloroflexi (22%) and in the Mv network mostly from Proteobacteria (25%), Acidobacteriota (22.5%), and Chloroflexi (20%) (Table S5).

Fig. 5
figure 5

M. verticalis larvae-feeding induced changed aerobic rice rhizosphere soil microbial community and composition. Histogram showing significantly different phyla (A) and genera (B). (C) Aerobic rice rhizosphere soil bacterial community. (D) Histogram showing significantly different genera. (E) Aerobic rice rhizosphere soil fungi community. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice

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In the fungi level, M. verticalis larvae feeding did not significantly change any soil fungal phyla in the aerobic rice rhizosphere soils. M. verticalis larvae-feeding significantly increased the genera of Talaromyces, Poaceascoma, unclassified_o__Xylariales, Coniochaeta, and Dichotomopilus but decreased the genus of Psathyrella (Fig. 5D). Besides, M. verticalis larvae-feeding changed aerobic rice rhizosphere soil fungal community (Fig. 5E). The network was assigned to 3 modules with healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils. The modularity increased from 0.207 in healthy aerobic rice rhizosphere soils to 0.255 in M. verticalis larvae-feeding aerobic rice rhizosphere soils (Table S4). Modules I and II displayed more proportion in the Mv group (54% and 44.67%) than CK group (40.44% and 35.9%) (Fig. 5E and Table S4). However, the module III was decreased from 23.66% in healthy aerobic rice rhizosphere soils to 1.02% in M. verticalis larvae-feeding aerobic rice rhizosphere soils. The network was assigned to 6 phyla within healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils. Among them, nodes in the CK network were mostly from Ascomycota (80.81%) and in the Mv network mostly from Ascomycota (77.16%) (Table S5). Notably, the change of bacterial community and composition were greater than fungal community and composition with M. verticalis larvae-feeding stress.

Rhizosphere microbial community functional prediction

The bacterial communities’ functional prediction results showed (Fig. 6A, Table S6) that at level 2, we identified 1 (HGM), 4 (HZB), and 10 (NG) pathways significantly enriched in the M. verticalis larvae-feeding aerobic rice rhizosphere bacteria, while 4 (HGM), 8 (HZB), and 9 (NG) pathways were significantly depleted. The pathways of the metabolism of terpenoids and polyketides, carbohydrate metabolism, and immune system were shared among the three regions, and they were significantly more abundant in the healthy aerobic rice rhizosphere. To further study the functional information of rhizosphere bacteria, the metabolism of terpenoids and polyketides, carbohydrate metabolism, and the immune system of each experimental group were compared at KEGG level 3. As shown in Fig. 6B and Table S7, we detected 3 (HGM), 3 (HZB), and 12 (NG) pathways significantly enriched in the M. verticalis larvae-feeding aerobic rice rhizosphere bacteria, and 6 (HGM), 8 (HZB), and 9 (NG) pathways significantly enriched in the healthy aerobic rice rhizosphere bacteria. Compared with the healthy aerobic rice rhizosphere, M. verticalis larvae feeding significantly depleted the enrichment of galactose metabolism and amino sugar and nucleotide sugar metabolism in the three regions.

Fig. 6
figure 6

Rhizosphere microbial community functional prediction. (A) Statistical differences in predicated bacterial functional characteristics between CK and Mv rhizosphere soil at KEGG level 2 (A) and KEGG level 3 (B). (C) Statistical differences in predicated fungal functional characteristics between CK and Mv rhizosphere soil. The relative abundance of log10 fold change (log10FC) was included in the plot. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice; HGM, Haguoma; HZB, Haoziba; and NG, Nuoguo

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The fungal communities’ functional prediction results showed that 10 (HGM), 15 (HZB), and 11 (NG) different ecological guilds were present among the communities of the aerobic rice rhizospheres, in addition to unidentified guilds (Fig. 6C, Table S8). Fungal parasite–wood saprotroph and fungal parasite abundance at the HGM and HZB regions were significantly decreased with M. verticalis larvae feeding. In addition, the abundance of plant pathogen–wood saprotroph (a type of fungi that obtains nutrients by damaging host plant cells and degrading wood cells to obtain nutrients) and animal pathogen–undefined saprotroph (a type of fungi that obtains nutrients by damaging host animal cells and degrading unknown substances to obtain nutrients) in samples from the HZB and NG regions notably increased after M. verticalis larvae feeding.

Relationships between soil properties and rhizosphere microbial community structures

We identified the correlation among pest density, soil physicochemical properties, soil enzyme activities, and bacterial and fungal alpha diversity in the three regions with M. verticalis larvae feeding. In the healthy aerobic rice rhizosphere soils (Fig. 7A), total N, total P, available P, and available K negatively correlated with soil enzyme activities. Bacterial number, bacterial Shannon index, and fungal Shannon index significantly positively correlated with soil physicochemical properties, whereas they significantly negatively correlated with phosphatase, β-glucosidase, and acid invertase. Fungal number significantly positively correlated with urease, β-glucosidase, polyphenol oxidase, and acid invertase. In the M. verticalis larvae-feeding aerobic rice rhizosphere soils (Fig. 7B), pest density significantly positively correlated with pH, organic matter, total P, catalase, and bacterial number and Shannon index but significantly negatively with available P, urease, phosphatase, β-glucosidase, and acid invertase. M. verticalis larvae-feeding changed many correlations, including reversed the correlation of organic matter and available P, total K and urease, and available P and fungal Shannon index, disrupted the correlation of pH with organic matter, available P, and fungal Shannon index, organic matter with total P, total N, available K, phosphatase, and et al., and generated new correlation of organic matter and total K, total P and fungal number, and acid invertase and bacterial number. Interestingly, M. verticalis larvae-feeding greatly reduced the correlation of fungi with soil physicochemical properties, soil enzyme activities, and bacterial community.

Fig. 7
figure 7

Relationship between soil properties and rhizosphere microbial community structures. (A) Relationship between healthy aerobic rice rhizosphere soils properties and rhizosphere microbial community structures. (B) Relationship between M. verticalis larvae-feeding aerobic rice rhizosphere soils properties and rhizosphere microbial community structures. *, **, and *** indicate significant differences at P < 0.05, P < 0.01, and P < 0.001

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Relationships between M. verticalis larvae density and aerobic rice rhizosphere soil microbial composition

The Bradyrhizobium and Talaromyces were the genera with the greatest difference between bacteria and fungi, respectively, after M. verticalis larvae-feeding. Therefore, we illustrated the relationships the relative abundance of Bradyrhizobium and Talaromyces and larvae density by using linear fitting. The fitting line in Fig. 8A showed that the relative abundance of Bradyrhizobium gradually increases with the elevation of the larvae density. The R2 of the fitting was 0.46, indicating a moderate correlation. The relative abundance of Talaromyces increases with the increases in larvae density (Fig. 8B). The high R2 of 0.52 suggested that the Talaromyces genus had a good correlation with larvae density.

Fig. 8
figure 8

Relationships between M. verticalis larvae density and aerobic rice rhizosphere soil microbial composition. Relationships between M. verticalis larvae density and the relative abundance of Bradyrhizobium (A) and Talaromyces (B) genera. CK, healthy aerobic rice; Mv, M. verticalis larvae-feeding aerobic rice

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Discussion

Underground insects are closely related to soil’s physicochemical properties [35,36,37]. In this study, M. verticalis larvae feeding significantly changed soil pH and available K content in the three studied regions. The content of organic matter, total N, and available P were remarkably changed between two regions. Waste cricket chitin (Acheta domesticus) reduced the germination of Lepidium sativum and stimulated root elongation [36], which was closely related to soil physicochemical properties [38], suggesting that underground insects mediated changes in soil physicochemical properties that are critical for regulating plant’s growth and development. Furthermore, insect abundance of Oulema spp. larvae were negatively correlated with dehydrogenases, catalase, and peroxidases in soil [39]. Accumulating evidence shows that the expression of host-specific genes had a regulatory effect on soil enzyme activity [39,40,41]. Our results also showed that M. verticalis larvae density negatively correlated with soil enzyme (urease, phosphatase, β-glucosidase, and acid invertase) activities, suggesting that M. verticalis larvae-feeding stress mediated soil enzyme activities by regulating host‐specific genes expression.

Biotic and abiotic stresses can sculpt rhizosphere microbiota assembly and modulate the growth of root commensals that bolster stress tolerance [42]. Previous studies have shown that soil bacterial networks were less stable under biotic and abiotic stress than fungal networks [43,44,45]. In this study, we observed that the change of bacterial community was greater than fungal community with M. verticalis larvae-feeding stress, but M. verticalis larvae-feeding maintained the correlation of bacterial community with soil physicochemical properties and enzyme activities, suggesting that aerobic rice adapted to M. verticalis larvae-feeding stress by changing bacterial community. Increasingly more studies suggest that plant-mediated timely reshaping of the microbiota could also confer benefits in responding to certain biotic and abiotic stresses [46]. We observed that M. verticalis larvae-feeding significantly enriched Bradyrhizobium (bacterial genus) and Talaromyces (fungal genus), and the relative abundance of Bradyrhizobium and Talaromyces gradually increased with the elevation of the larvae density. Notably, Bradyrhizobium is one of the most cosmopolitan and diverse bacterial group modulating a variety of host legumes, which can promote growth, increase yield, and improve abiotic stresses resistance [47, 48] in various plants, including rice [49] peanuts [50], and maize [51]. In addition, Talaromyces can promote plant growth and inhibit pathogenic fungi and insects [52,53,54], such as Talaromyces apiculatus reduced linear mycelial growth of Ganoderma boninense, elevated area and bole girth of oil-palm seedlings, and increased shoot and root biomass, and nutrient contents in seedlings [52]. Combined with the results of this study, we speculate that aerobic rice may adapt to M. verticalis larvae-feeding stress by recruiting beneficial microorganisms.

Our experimental site is in Puer, Yunnan Province, China, where there is rich biodiversity [55, 56]. M. verticalis larvae-feeding will enrich many functional microorganisms compared to other places. Such as white grub (H. parallela) larvae infestation decreased the genus of Rhodoplanes and Ramlibacter [18], but they were increased in our study. Notably, M. verticalis larvae-feeding increased the genus of Bradyrhizobium and Talaromyces in this study, which were functional microorganisms that were beneficial for plants to adapt to stress [47, 48, 52,53,54], suggesting that they can be made into biological agents for use. However, specific species had not been isolated and identified.

We observed that seven featured genera were identified in the healthy aerobic rice rhizosphere, including the PGPR Mucilaginibacter [57] and Dyella [58] genera. M. verticalis larvae-feeding aerobic rice rhizosphere bacteria featured 22 genera, including the PGPR Terrimonas [59] and Bradyrhizobium [60, 61] genera. PGPR can successfully colonize insects and use them as a means of dispersal to the rhizosphere of new host plants [62], suggesting that M. verticalis larvae may have brought over these 22 featured genera. M. verticalis larvae feeding significantly depleted the enrichment of the pathway of metabolism of carbohydrate metabolism at KEGG level 2. Carbohydrate metabolism is the dominant bacterial function in halophytes rhizosphere bacteria and light-exposure rhizosphere bacteria [63, 64]. Notably, rhizosphere bacteria were significantly affected by soil physicochemical characteristics [65, 66]. In our study, bacterial number and Shannon index correlated significantly positively with pH, total N, total P, available K, and NH4+-N. These results indicate that 22 featured bacterial genera from M. verticalis larvae-feeding aerobic rice rhizosphere are strongly associated with soil physicochemical properties.

Many rhizosphere fungi belong to the arbuscular mycorrhizal fungi (AMF) and dark septate fungi (DSE). By forming symbiotic relationships with most plants, AMF and DSE can improve salt tolerance, disease resistance, and water stress [67,68,69,70]. In this study, eight featured genera were identified in the healthy aerobic rice rhizosphere, including the AMF Penicillium genus [71]. M. verticalis larvae-feeding aerobic rice rhizosphere bacteria featured 13 genera, including one DSE Exophiala genus [72], three AMF Acremonium, Mortierella, and Lecythophora genera [71, 73], and P solubilization fungi Talaromyces genus [74]. Notably, we found that M. verticalis larvae feeding significantly decreased the abundance of fungal parasite–wood saprotroph and fungal parasite, possibly because insect ectomicrobiomes produce antimicrobial peptides or antibiotic compounds [75]. The reduction in such fungi reduces the degradation of soil organisms, leading to a decrease in the nutrients obtained by aerobic rice plants from the soil. M. verticalis larvae feeding significantly increased the abundance of plant pathogen–wood saprotroph and animal pathogen–undefined saprotroph. Their increase may be carried out by plant pathogens and animal pathogens via M. verticalis larvae [76, 77]. Here, we found that rhizosphere fungal number and Shannon index strongly correlated with soil physicochemical properties and soil enzyme activities. Rhizosphere fungal community structures were primarily shaped by the total N, available N, and available P of soil [78], which increased the activity of chitinase, leucine-aminopeptidase, acid phosphatase, and β-glucosidase [79]. However, we did not determine if the high correlation between fungal activity and soil enzyme activity is due to fungal secretion. Finally, the relationship between soil physicochemical properties, soil enzyme activities, and rhizosphere fungi should be investigated in the future.

However, this study also raises some issues that must be clarified in future investigations. Firstly, the isolation and identification of Bradyrhizobium and Talaromyces species is important for subsequent functional research. Further studies would need to focus on the application of key functional microorganisms. Secondly, this study doesn’t have a good way to eliminate the potential confounding factors, such as environmental variations, other pest interactions, and agronomic practices, and a long-term testing experiment was necessary. Finally, the mechanism by which M. verticalis larvae feeding drives changes in aerobic rice rhizosphere soil microbial communities is still unclear.

Conclusions

This study demonstrates that M. verticalis larvae feeding can influence soil physicochemical properties and soil enzyme activities, which also changed the rhizosphere microbial communities and increased the featured microbial genera of the aerobic rice rhizosphere. In addition, the pathway of the metabolism of terpenoids and polyketides, carbohydrate metabolism, and immune system at KEGG level 2 and the pathway of galactose metabolism and amino sugar and nucleotide sugar metabolism at KEGG level 3 were significantly increased after M. verticalis larvae feeding. Fungal parasite–wood saprotroph and fungal parasite were significantly decreased after M. verticalis larvae feeding, and plant pathogen–wood saprotroph and animal pathogen–undefined saprotroph were increased. Pest density was most closely associated with the relative abundance of Bradyrhizobium and Talaromyces. These results provide new insights for understanding the adaptation of aerobic rice to M. verticalis larvae feeding via regulating the rhizosphere environment.

Data availability

Rhizosphere bacteria and fungi raw data have been deposited in the NCBI Sequence Read Archive (https://submit.ncbi.nlm.nih.gov/subs/sra/) under the accession number of PRJNA1052402 and PRJNA1053271, respectively.

Abbreviations

PGPR:

plant-growth-promoting rhizobacteria

CK:

healthy aerobic rice

Mv:

M. verticalis larvae-feeding aerobic rice

HGM:

Haguoma

HZB:

Haoziba

NG:

Nuoguo

CFU:

colony-forming units

PCR:

polymerase chain reaction

OUT:

operational taxonomic unit

PCA:

principal component analysis

LDA:

linear discriminant analysis

KEGG:

Kyoto Encyclopedia of Genes and Genomes

AMF:

arbuscular mycorrhizal fungi

DSE:

dark septate fungi

References

  1. Barker R, Dawe D, Tuong TP, Bhuiyan SI, Guerra L. The outlook for water resources in the year 2020: Challenges for research on water management in rice production. Proceedings of 19th Session of the International Rice Commission 1999:96–109.

  2. Bouman B, Lampayan R, Tuong TP. Water management in irrigated rice. Coping with water scarcity; 2007.

  3. Meena RK, Bhusal N, Kumar K, Jain R, Jain S. Intervention of molecular breeding in water saving rice production system: aerobic rice. 3 Biotech. 2019;9(4):133.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hugar S, Naik M, Munishamappa M. Comparative Biology of Yellow Stem Borer, Scirpophaga incertulas Walker in Aerobic and Transplanted Rice.

  5. Kr R, Nath, Deka S. Insect pests of citrus and their management ARITCLE INFO a CASE STUDY. 2020, 12:188–96.

  6. Tamayo-Sánchez F, Tamayo-Mejía F, Marín-Jarrillo A, Santillán-Galicia T, Pérez-Valdez A, Guzmán-Franco A. Dynamics of natural infection of white grub larvae by Beauveria and Metarhizium in maize crops from Mexico. Biocontrol Sci Technol. 2022;32:1–17.

    Article  Google Scholar 

  7. Sravani D, Bhattacharyya B, Elangbam B. Biocontrol-based management module provided maximum protection in potato against white grub, lepidiota mansueta Burmeister in Assam, India. Egypt J Biol Pest Control 2023, 33.

  8. Li X, Liu X, Nong X, Wang G, McNeill M, Ullah H, Wang Q, Henderson H, Zhang Z. Peanut early flowering stage is beneficial to Metarhizium anisopliae survival and control of white grub larvae. 3 Biotech 2020, 10.

  9. Mohapatra SD, Mishra P, Singh M. Management of white grub, Holotrichia Longipennis Blanch through post- sown soil application of insecticides in upland rice. ORYZA- Int J Rice. 2013;50:419–21.

    Google Scholar 

  10. Ratnadass A, Randriamanantsoa R, Rajaonera T, Rabearisoa M, Rafamatanantsoa E, Moussa N, Michellon R. Interaction between cropping systems and white grub (Coleoptera: Scarabeoidea) status (pest or beneficial) on upland rice. Cahiers Agricultures. 2013;22:432–41.

    Article  Google Scholar 

  11. Litsinger JA, Apostol RF, Obusan MB. White Grub, Leucopholis Irrorata (Coleoptera: Scarabaeidae): Pest Status, Population Dynamics, and Chemical Control in a Rice-Maize Cropping Pattern in the Philippines1. J Econ Entomol. 1983;76(5):1133–8.

    Article  Google Scholar 

  12. Abudulai M, Dzomeku I, Opare-Atakora D, Nutsugah S, Salifu A, Brandenburg R, Jordan D. Survey of Soil Arthropod pests and Assessment of Yield loss in peanut in Northern Ghana. Peanut Sci. 2012;39:113–20.

    Article  Google Scholar 

  13. Youngman R, Midgarden D, Herbert D, Nixon K, Brann D. Evaluation of a Preplant Method for detecting damage to germinating Corn seeds by multiple species of insects. Environ Entomol. 1993;22:1251–9.

    Article  Google Scholar 

  14. Pearse I, LoPresti E, Schaeffer R, Wetzel W, Mooney K, Ali J, Ode P, Eubanks M, Bronstein J, Weber M. Generalising indirect defence and resistance of plants. Ecol Lett 2020, 23.

  15. Boter M, Diaz I. Cyanogenesis, a Plant Defence Strategy against herbivores. Int J Mol Sci. 2023;24:6982.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Johnson S, Rasmann S. Root-Feeding insects and their interactions with organisms in the Rhizosphere. Ann Rev Entomol. 2015;60:517–35.

    Article  CAS  Google Scholar 

  17. Samoylova E, Kostina N, Striganova B. Effects of the vital activity of soil insect larvae on microbial processes in the Soil. Biology Bull. 2015;42:563–9.

    Article  Google Scholar 

  18. Geng L, Shao G-X, Raymond B, Wang M-L, Sun X-X, Shu C, Zhang J. Subterranean infestation by Holotrichia parallela larvae is associated with changes in the peanut (Arachis hypogaea L.) rhizosphere microbiome. Microbiol Res 2018, 211.

  19. Shi Z, Yang Y, Fan Y, He Y, Li T. Dynamic responses of Rhizosphere microorganisms to Biogas Slurry combined with Chemical Fertilizer Application during the whole life cycle of Rice Growth. Microorganisms. 2023;11:1755.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zang Y, Zhao J, Chen W, Lu L, Chen J, Lin Z, Qiao Y, Lin H, Tian S. Sulfur and water management mediated iron plaque and rhizosphere microorganisms reduced cadmium accumulation in rice. J Soils Sediments. 2023;23:1–14.

    Article  Google Scholar 

  21. Yasuda M, Dastogeer KMG, Sarkodee Addo E, Tokiwa C, Isawa T, Shinozaki S, Okazaki S. Impact of Azospirillum sp. B510 on the Rhizosphere Microbiome of Rice under Field conditions. Agronomy. 2022;12:1367.

    Article  CAS  Google Scholar 

  22. Ge J, Li D, Ding J, Xiao X, Liang Y. Microbial coexistence in the rhizosphere and the promotion of plant stress resistance: a review. Environ Res. 2023;222:115298.

    Article  CAS  PubMed  Google Scholar 

  23. Bhat BA, Tariq L, Nissar S, Islam ST, Islam SU, Mangral Z, Ilyas N, Sayyed RZ, Muthusamy G, Kim W, et al. The role of plant-associated rhizobacteria in plant growth, biocontrol and abiotic stress management. J Appl Microbiol. 2022;133(5):2717–41.

    Article  CAS  PubMed  Google Scholar 

  24. Friman J, Karssemeijer PN, Haller J, de Kreek K, van Loon JJA, Dicke M. Shoot and root insect herbivory change the plant rhizosphere microbiome and affects cabbage-insect interactions through plant-soil feedback. New Phytol. 2021;232(6):2475–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Geng LL, Shao GX, Raymond B, Wang ML, Sun XX, Shu CL, Zhang J. Subterranean infestation by Holotrichia parallela larvae is associated with changes in the peanut (Arachis hypogaea L.) rhizosphere microbiome. Microbiol Res. 2018;211:13–20.

    Article  PubMed  Google Scholar 

  26. Francis F, Jacquemyn H, Delvigne F, Lievens B. From Diverse origins to specific targets: role of microorganisms in Indirect Pest Biological Control. Insects 2020, 11(8).

  27. Li L, Yang X, Tong B, Wang D, Tian X, Liu J, Chen J, Xiao X, Wang S. Rhizobacterial compositions and their relationships with soil properties and medicinal bioactive ingredients in Cinnamomum migao. Front Microbiol. 2023;14:1078886.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Zhang J, Lu J, Zhu Y, Huang Q, Qin L, Zhu B. Rhizosphere microorganisms of Crocus sativus as antagonists against pathogenic Fusarium oxysporum. Front Plant Sci. 2022;13:1045147.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lee CK, Barbier BA, Bottos EM, McDonald IR, Cary SC. The inter-valley soil comparative survey: the ecology of Dry Valley edaphic microbial communities. ISME J. 2012;6(5):1046–57.

    Article  CAS  PubMed  Google Scholar 

  30. Degnan PH, Ochman H. Illumina-based analysis of microbial community diversity. ISME J. 2012;6(1):183–94.

    Article  CAS  PubMed  Google Scholar 

  31. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glöckner FO. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007;35(21):7188–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AF, Bahram M, Bates ST, Bruns TD, Bengtsson-Palme J, Callaghan TM, et al. Towards a unified paradigm for sequence-based identification of fungi. Mol Ecol. 2013;22(21):5271–7.

    Article  PubMed  Google Scholar 

  33. Aßhauer KP, Wemheuer B, Daniel R, Meinicke P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinf (Oxford England). 2015;31(17):2882–4.

    Google Scholar 

  34. Nguyen N, Song Z, Bates S, Branco S, Tedersoo L, Menke J, Schilling J, Kennedy P. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol 2015, 20.

  35. Zhao L, Gao R, Liu J, Liu L, Li R, Men L, Zhang Z. Effects of Environmental factors on the spatial distribution pattern and Diversity of Insect Communities along Altitude gradients in Guandi Mountain, China. Insects 2023, 14(3).

  36. Różyło K, Jędruchniewicz K, Krasucka P, Biszczak W, Oleszczuk P. Physicochemical Characteristics of Biochar from Waste Cricket Chitin (Acheta domesticus). Molecules 2022, 27(22).

  37. Vivero RJ, Torres-Gutierrez C, Bejarano EE, Peña HC, Estrada LG, Florez F, Ortega E, Aparicio Y, Muskus CE. Study on natural breeding sites of sand flies (Diptera: Phlebotominae) in areas of Leishmania transmission in Colombia. Parasites Vectors. 2015;8:116.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Lyu Q, Liu J, Liu J, Luo Y, Chen L, Chen G, Zhao K, Chen Y, Fan C, Li X. Response of plant diversity and soil physicochemical properties to different gap sizes in a Pinus massoniana plantation. PeerJ. 2021;9:e12222.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Pobereżny J, Wszelaczyńska E, Lamparski R, Lemanowicz J, Bartkowiak A, Szczepanek M, Gościnna K. The impact of spring wheat species and sowing density on soil biochemical properties, content of secondary plant metabolites and the presence of Oulema Ssp. PeerJ. 2023;11:e14916.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Liu Q, Cheng L, Nian H, Jin J, Lian T. Linking plant functional genes to rhizosphere microbes: a review. Plant Biotechnol J. 2023;21(5):902–17.

    Article  PubMed  Google Scholar 

  41. Shah T, Ali A, Haider G, Asad M, Munsif F. Microplastics alter soil enzyme activities and microbial community structure without negatively affecting plant growth in an agroecosystem. Chemosphere. 2023;322:138188.

    Article  CAS  PubMed  Google Scholar 

  42. Hou S, Wolinska KW, Hacquard S. Microbiota-root-shoot-environment axis and stress tolerance in plants. Curr Opin Plant Biol. 2021;62:102028.

    Article  CAS  PubMed  Google Scholar 

  43. de Vries FT, Griffiths RI, Bailey M, Craig H, Girlanda M, Gweon HS, Hallin S, Kaisermann A, Keith AM, Kretzschmar M, et al. Soil bacterial networks are less stable under drought than fungal networks. Nat Commun. 2018;9(1):3033.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Chang Y, Xia X, Sui L, Kang Q, Lu Y, Li L, Liu W, Li Q, Zhang Z. Endophytic colonization of entomopathogenic fungi increases plant disease resistance by changing the endophytic bacterial community. J Basic Microbiol. 2021;61(12):1098–112.

    Article  CAS  PubMed  Google Scholar 

  45. Wang R, Cao B, Sun Q, Song L. Response of grass interplanting on bacterial and fungal communities in a jujube orchard in Ningxia, northwest China. Heliyon. 2020;6(3):e03489.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Jiao S, Chu H, Zhang B, Wei X, Chen W, Wei G. Linking soil fungi to bacterial community assembly in arid ecosystems. iMeta 2022, 1.

  47. Wülser J, Ernst C, Vetsch D, Emmenegger B, Michel A, Lutz S, Ahrens CH, Vorholt JA, Ledermann R, Fischer HM. Salt- and osmo-responsive sensor histidine kinases activate the Bradyrhizobium diazoefficiens general stress response to initiate functional symbiosis. Mol plant-microbe Interactions: MPMI. 2022;35(7):604–15.

    Article  PubMed  Google Scholar 

  48. Ledermann R, Emmenegger B, Couzigou JM, Zamboni N, Kiefer P, Vorholt JA, Fischer HM. Bradyrhizobium diazoefficiens requires Chemical chaperones to cope with osmotic stress during soybean infection. mBio 2021, 12(2).

  49. Padukkage D, Geekiyanage S, Reparaz JM, Bezus R, Balatti PA, Degrassi G. Bradyrhizobium japonicum, B. Elkanii and B. diazoefficiens interact with Rice (Oryza sativa), promote growth and increase yield. Curr Microbiol. 2021;78(1):417–28.

    Article  CAS  PubMed  Google Scholar 

  50. Gericó TG, Tavanti RFR, de Oliveira SC, Lourenzani A, de Lima JP, Ribeiro RP, Dos Santos LCC. Dos Reis AR: Bradyrhizobium sp. enhance ureide metabolism increasing peanuts yield. Arch Microbiol. 2020;202(3):645–56.

    Article  PubMed  Google Scholar 

  51. Dong Q, Zhao X, Zhou D, Liu Z, Shi X, Yuan Y, Jia P, Liu Y, Song P, Wang X, et al. Maize and peanut intercropping improves the nitrogen accumulation and yield per plant of maize by promoting the secretion of flavonoids and abundance of Bradyrhizobium in Rhizosphere. Front Plant Sci. 2022;13:957336.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Goh YK, Marzuki NF, Tuan Pa TNF, Goh TK, Kee ZS, Goh YK, Yusof MT, Vujanovic V, Goh KJ. Biocontrol and Plant-Growth-promoting traits of Talaromyces Apiculatus and Clonostachys Rosea Consortium against Ganoderma Basal Stem Rot Disease of Oil Palm. Microorganisms 2020, 8(8).

  53. Nicoletti R, Becchimanzi A. Talaromyces-Insect relationships. Microorganisms 2021, 10(1).

  54. Abbas A, Fu Y, Qu Z, Zhao H, Sun Y, Lin Y, Xie J, Cheng J, Jiang D. Isolation and evaluation of the biocontrol potential of Talaromyces spp. against rice sheath blight guided by soil microbiome. Environ Microbiol. 2021;23(10):5946–61.

    Article  CAS  PubMed  Google Scholar 

  55. Yu TT, Chang Z, Dong ZW, Li KQ, Ma FZ, Wang W, Li XY. A glimpse into the biodiversity of insects in Yunnan: an updated and annotated checklist of butterflies (Lepidoptera, Papilionoidea). Zoological Res. 2022;43(6):1009–10.

    Article  Google Scholar 

  56. Zhu M, Ding Y, Li X, Xiao Y, Zhao Z, Li T. Biodiversity of Root Endophytic Fungi from Oxyria sinensis grown in metal-polluted and unpolluted soils in Yunnan Province, Southwestern China. Plants (Basel Switzerland) 2021, 10(12).

  57. Lyu D, Backer R, Berrué F, Martinez-Farina C, Hui JPM, Smith DL. Plant growth-promoting Rhizobacteria (PGPR) with Microbial Growth Broth improve Biomass and secondary Metabolite Accumulation of Cannabis sativa L. J Agric Food Chem. 2023;71(19):7268–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Monteiro JM, Vollú RE, Coelho MR, Alviano CS, Blank AF, Seldin L. Comparison of the bacterial community and characterization of plant growth-promoting rhizobacteria from different genotypes of Chrysopogon zizanioides (L.) Roberty (vetiver) rhizospheres. J Microbiol. 2009;47(4):363–70.

    Article  CAS  PubMed  Google Scholar 

  59. Świątczak J, Kalwasińska A, Szabó A, Brzezinska MS. The effect of seed bacterization with Bacillus paralicheniformis 2R5 on bacterial and fungal communities in the canola rhizosphere. Microbiol Res. 2023;275:127448.

    Article  PubMed  Google Scholar 

  60. Seraj MF, Rahman T, Lawrie AC, Reichman SM. Assessing the plant growth promoting and Arsenic Tolerance potential of Bradyrhizobium japonicum CB1809. Environ Manage. 2020;66(5):930–9.

    Article  PubMed  Google Scholar 

  61. Zeffa DM, Fantin LH, Koltun A, de Oliveira ALM, Nunes M, Canteri MG, Gonçalves LSA. Effects of plant growth-promoting rhizobacteria on co-inoculation with Bradyrhizobium in soybean crop: a meta-analysis of studies from 1987 to 2018. PeerJ. 2020;8:e7905.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Pronk LJU, Bakker P, Keel C, Maurhofer M, Flury P. The secret life of plant-beneficial rhizosphere bacteria: insects as alternative hosts. Environ Microbiol. 2022;24(8):3273–89.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Staley C, Ferrieri AP, Tfaily MM, Cui Y, Chu RK, Wang P, Shaw JB, Ansong CK, Brewer H, Norbeck AD, et al. Diurnal cycling of rhizosphere bacterial communities is associated with shifts in carbon metabolism. Microbiome. 2017;5(1):65.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Yin F, Zhang F, Wang H. Rhizosphere bacteria community and functions under typical natural halophyte communities in North China salinized areas. PLoS ONE. 2021;16(11):e0259515.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Onyango LA, Ngonga FA, Karanja EN, Kuja JO, Boga HI, Cowan DA, Mwangi KW, Maghenda MW, Marinho Lebre PBN, Kambura AK. The soil microbiomes of forest ecosystems in Kenya: their diversity and environmental drivers. Sci Rep. 2023;13(1):7156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Jamil FN, Hashim AM, Yusof MT, Saidi NB. Analysis of soil bacterial communities and physicochemical properties associated with Fusarium wilt disease of banana in Malaysia. Sci Rep. 2022;12(1):999.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Giard-Laliberté C, Azarbad H, Tremblay J, Bainard L, Yergeau É. A water stress-adapted inoculum affects rhizosphere fungi, but not bacteria nor wheat. FEMS Microbiol Ecol 2019, 95(7).

  68. Ji C, Chen Z, Kong X, Xin Z, Sun F, Xing J, Li C, Li K, Liang Z, Cao H. Biocontrol and plant growth promotion by combined Bacillus spp. inoculation affecting pathogen and AMF communities in the wheat rhizosphere at low salt stress conditions. Front Plant Sci. 2022;13:1043171.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Liu S, Tao C, Zhang L, Wang Z, Xiong W, Xiang D, Sheng O, Wang J, Li R, Shen Z, et al. Plant pathogen resistance is mediated by recruitment of specific rhizosphere fungi. ISME J. 2023;17(6):931–42.

    Article  CAS  PubMed  Google Scholar 

  70. Berthelot C, Blaudez D, Leyval C. Differential growth promotion of poplar and birch inoculated with three dark septate endophytes in two trace element-contaminated soils. Int J Phytoremediation. 2017;19(12):1118–25.

    Article  CAS  PubMed  Google Scholar 

  71. Toju H, Sato H. Root-Associated Fungi Shared between Arbuscular Mycorrhizal and Ectomycorrhizal conifers in a Temperate Forest. Front Microbiol. 2018;9:433.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Gong M, Bai N, Wang P, Su J, Chang Q, Zhang Q. Co-inoculation with Arbuscular Mycorrhizal Fungi and Dark Septate endophytes under Drought stress: synergistic or competitive effects on Maize Growth, Photosynthesis, Root Hydraulic properties and aquaporins? Plants (Basel Switzerland) 2023, 12(14).

  73. Fu L, Zhang L, Dong P, Wang J, Shi L, Lian C, Shen Z, Chen Y. Remediation of copper-contaminated soils using Tagetes patula L., earthworms and arbuscular mycorrhizal fungi. Int J Phytoremediation. 2022;24(10):1107–19.

    Article  CAS  PubMed  Google Scholar 

  74. Della Mónica IF, Godeas AM, Scervino JM. In vivo modulation of Arbuscular Mycorrhizal Symbiosis and Soil Quality by Fungal P Solubilizers. Microb Ecol. 2020;79(1):21–9.

    Article  PubMed  Google Scholar 

  75. Hong S, Sun Y, Chen H, Zhao P, Wang C. Fungus-insect interactions beyond bilateral regimes: the importance and strategy to outcompete host ectomicrobiomes by fungal parasites. Curr Opin Microbiol. 2023;74:102336.

    Article  CAS  PubMed  Google Scholar 

  76. Trębicki P, Dáder B, Vassiliadis S, Fereres A. Insect-plant-pathogen interactions as shaped by future climate: effects on biology, distribution, and implications for agriculture. Insect Sci. 2017;24(6):975–89.

    Article  PubMed  Google Scholar 

  77. Vodovar N, Vallenet D, Cruveiller S, Rouy Z, Barbe V, Acosta C, Cattolico L, Jubin C, Lajus A, Segurens B, et al. Complete genome sequence of the entomopathogenic and metabolically versatile soil bacterium Pseudomonas Entomophila. Nat Biotechnol. 2006;24(6):673–9.

    Article  CAS  PubMed  Google Scholar 

  78. Sui X, Zeng X, Li M, Weng X, Frey B, Yang L, Li M. Influence of different vegetation types on Soil Physicochemical parameters and Fungal communities. Microorganisms 2022, 10(4).

  79. Zhou J, Gube M, Holz M, Song B, Shan I, Shi L, Kuzyakov Y, Dippold MA, Pausch J. Ectomycorrhizal and non-mycorrhizal rhizosphere fungi increase root-derived C input to soil and modify enzyme activities: A (14) C pulse labelling of Picea abies seedlings. Plant Cell Environ. 2022;45(10):3122–33.

    Article  CAS  PubMed  Google Scholar 

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Funding

This research was funded by the Major Science and Technology Project of Yunnan and Kunming, grant number 202202AE090036, and the China Academy of Engineering Local Cooperation Project, grand number 2023-DZ-02.

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Author notes

  1. Guang Wang and Zhengfei Li contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Conservation and Utilization of Biological Resources of Yunnan, College of Plant Protection, Yunnan Agricultural University, Kunming, 650201, China

    Guang Wang, Zhengfei Li, Baoyun Yang, Huquan Yang, Yujie Zhang, Qingping Zeng, Chaojianping Yan, Yanyan He, Yuejin Peng, Wenqian Wang, Bin Chen & Guangzu Du

  2. School of Agriculture, Yunnan University, Kunming, 650500, China

    Yanyan He

Authors
  1. Guang Wang
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  2. Zhengfei Li
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  3. Baoyun Yang
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  4. Huquan Yang
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  5. Yujie Zhang
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  10. Wenqian Wang
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  11. Bin Chen
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  12. Guangzu Du
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Contributions

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

Corresponding author

Correspondence to Guangzu Du.

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Ethics approval and consent to participate

This study was conducted at Puer experimental station, College of Plant Protection, Yunnan Agricultural University, Coimbatore and all comply with relevant institutional, national, and international guidelines and legislation. The plant material Dianheyou615 involved in this study is allowed to be used in any ordinary experiments. All the methods were carried out in accordance with relevant guidelines and regulations.

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Not appliable.

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The authors declare no competing interests.

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Wang, G., Li, Z., Yang, B. et al. The effect of white grub (Maladera Verticalis) larvae feeding on rhizosphere microbial characterization of aerobic rice (Oryza sativa L.) in Puer City, Yunnan Province, China. BMC Microbiol 24, 123 (2024). https://doi.org/10.1186/s12866-024-03265-w

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  • DOI: https://doi.org/10.1186/s12866-024-03265-w

Keywords

BMC Microbiology

ISSN: 1471-2180

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