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Article

Field Inoculation of Pleurotus tuoliensis in Natural Habitat Promotes Microbial Communities That Enhance Its Growth

by
Ying Luo
1,2,†,
Hanbing Liu
1,†,
Wenjie Jia
1,
Nuerziya Yalimaimaiti
1,
Qi Zhu
1,
Peisong Jia
1,*,
Yilin Huang
3,
Wenting Shi
2,
Chunhua Sun
4 and
Jianhua Guan
4
1
Key Laboratory of Integrated Pest Management on Crops in Northwestern Oasis, Ministry of Agriculture and Rural Affairs, National Plant Protection Scientific Observation and Experiment Station of Korla, Xinjiang Key Laboratory of Agricultural Biosafety, Institute of Plant Protection, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830091, China
2
College of Horticulture, Xinjiang Agricultural University, Urumqi 830052, China
3
College of Agronomy, Xinjiang Agricultural University, Urumqi 830052, China
4
Qinghe County Agricultural Technology Extension Center, Altay 836299, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(5), 1136; https://doi.org/10.3390/agronomy15051136
Submission received: 21 March 2025 / Revised: 20 April 2025 / Accepted: 3 May 2025 / Published: 6 May 2025
(This article belongs to the Section Horticultural and Floricultural Crops)
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Versions Notes

Abstract

:
Pleurotus tuoliensis is a valuable edible mushroom native to Xinjiang in northwest China. It colonizes the roots and stems of Ferula plants. Field inoculation in its natural habitat has been shown to significantly enhance the colonization rate of P. tuoliensis hyphae in Ferula plants. However, the effects of field inoculation on P. tuoliensis hyphal colonization, soil properties, and microbial communities remain underexplored. In this study, we examined the characteristics of rhizosphere soil and microbial communities under four conditions: natural environments with and without hyphal colonization, and field inoculation with and without colonization. High-throughput sequencing results revealed that field inoculation markedly increased the relative abundance of Pleurotus species (57.98%) compared to natural colonization (14.11%). However, field inoculation also resulted in a reduction in microbial community diversity compared to hyphal colonization. Concurrently, the relative abundance of Pseudomonadota, Bacteroidota, and Bacillota significantly increased following field inoculation. LEfSe analysis suggested that the identified potential biomarkers were most likely associated with the Bacillus genus within Bacillota. Furthermore, mushroom growth-promoting bacteria were successfully isolated and identified as members of the Bacillus cereus group (L5) and Bacillus safensis (S16). This finding suggests that field inoculation with P. tuoliensis in its natural habitat promotes microbial communities that enhance its growth. This study offers new insights into conserving wild edible fungi and their interactions with soil microbiota.

1. Introduction

The oyster mushroom (Pleurotus spp.) is one of the most widely cultivated species worldwide [1,2,3]. Among these, Pleurotus tuoliensis, commercially known as Bailinggu [4], is a unique species. It is only found in Xinjiang, China and Iran [4,5] and has high nutritional and medicinal value. This species was previously identified as P. nebrodensis [6] and P. eryngii var. tuoliensis [7]. P. tuoliensis is a valuable source of nutrients, including amino acids, vitamins, and trace elements. Moreover, its fruiting body is rich in polysaccharides and some biological components that are of benefit to human health [8,9,10,11,12]. Due to its delicious taste and nutritional value, P. tuoliensis has been commercially cultivated on a large scale since 1997 [7]. Nevertheless, its commercial cultivation is limited by low yield, extended cultivation periods, inconsistency in fruiting body development, and susceptibility to diseases compared to other oyster mushrooms [13,14]. According to the China Association of Edible Fungi data, the total yield of P. tuoliensis in 2010 reached 323,713 tons [13] but declined significantly to 34,300 tons in 2022. In addition to developing new cultivars and optimizing cultivation environments, the application of biological agents to enhance mushroom growth represents a novel and essential approach in mushroom cultivation.
In its natural habitat, wild P. tuoliensis is reported to grow saprophytically or as a weak parasite on the rhizomes of Ferula plants in the Gobi Desert of Xinjiang [5,6]. Capable of thriving in high salinity and a high pH underground, P. tuoliensis obtains nutrients from Ferula plants and biomass decomposed by soil microbes. Consequently, understanding the interactions between soil microbes and P. tuoliensis is essential. However, to date, no studies have explored the microbial community in the native habitats of P. tuoliensis.
Numerous studies have investigated the interactions between bacteria and fungi, including Pleurotus spp. and Agaricus bisporus. However, most of these studies were conducted under artificial conditions, such as by using pasteurized or sterilized substrates for Pleurotus spp., or non-axenic substrates for A. bisporus, rather than in situ soil. These interact with various beneficial bacteria by forming a selective substrate, providing nutrients, stimulating growth and mushroom formation, and preventing pathogen contamination [15,16]. Mushroom growth-promoting bacteria (MGPB) are typically isolated from composts, casings, fruiting bodies, and the rhizosphere soil of some crops [15,16,17]. Several Pseudomonas species have been reported to increase the mycelial growth of A. bisporus [18,19], P. ostreatus [20,21], and P. eryngii [22]. The genus Bacillus can not only act as MGPB [23] but also as biocontrol bacteria to effectively control fungal diseases by secreting antimicrobial peptides [24,25]. Notably, there are no reports on MGPB application in P. tuoliensis cultivation.
Soil, a complex ecosystem, serves as a vital medium for diverse biological processes. It harbors a rich community of microorganisms that play crucial roles in nutrient cycling [26]. For instance, it has long been established that microorganisms in the casing layer are essential for the fruiting of A. bisporus; without the casing layer, few or no sporophores are produced [15,27].
Against this backdrop, a systematic investigation of wild P. tuoliensis conducted by our group in Xinjiang revealed a concerning trend from 2013 to 2023 (Table S1, see Supplementary Materials for detailed data). The results indicated a sharp decline in the number of wild P. tuoliensis strains, with a decrease of 69.66% since 2019; the distribution areas had been reduced from seven to five. Potential contributing factors to this decline may include habitat degradation, over-harvesting, and changes in the local micro-ecological environment. Consequently, the artificial conservation of P. tuoliensis has become essential.
In edible mushrooms, artificial conservation involves human intervention to boost the mycelial biomass of wild edible mushrooms within their natural habitats, thereby improving their reproductive capacity and yield. Studies have demonstrated that habitat conservation, the inoculation of fungal strains, nutrient supplementation, pest and disease control, and ecosystem regulation can significantly improve the natural reproductive capacity and yield of wild edible mushrooms [28]. In our previous study, on-site field inoculation of P. tuoliensis increased the mycelial colonization rate in the Ferula plants’ rhizosphere from 18% to 80%. In the process, changes in the structure of the soil microbial communities may play a critical role [29].
Traditional culture-dependent methods have been widely used to isolate environmental bacteria; however, these are highly media- and condition-dependent. In contrast, high-throughput sequencing technology enables the comprehensive profiling of biological community characteristics [30,31]. Combining culture-dependent and culture-independent methods offers a more thorough understanding of microbial community composition. In the present study, we aimed to better understand the interactions between soil microbes and P. tuoliensis, as well as to identify some of the beneficial bacteria that can enhance mycelial growth. Our approach involved examining rhizosphere soil physicochemical changes after field inoculation, analyzing microbial community shifts, and isolating and evaluating bacteria from Ferula plants’ rhizosphere soil for their effects on P. tuoliensis proliferation.

2. Materials and Methods

2.1. Experimental Sites

The experiment was carried out in the Bailinggu Conservation Area (Figure 1A) of Qinghe County, Altay Prefecture (46°59′82″ N, 89°87′20″ E) in Xinjiang, northwest China. This area is characterized by a continental, subarctic dry climate, with an average annual temperature of 0 °C and an average annual precipitation of 161 mm. The soil type in this region is brown calcareous soil, which has low organic matter content and a pronounced calcium accumulation. It is conducive to the growth of drought-resistant plants, particularly Ferula feruloides. The P. tuoliensis strain 508 was isolated from the tissue of a wild strain collected from this conservation area.

2.2. Experimental Design and Soil Sampling

In natural habitats, the mycelium of P. tuoliensis grows as a saprotroph or weakly parasitizes the roots of F. feruloides. The mycelium spreads densely in the soil; the combination of P. tuoliensis mycelium, F. feruloides roots, and the surrounding soil forms a white, sponge-like structure (Figure 1D). In comparison, the roots of F. feruloides without mycelial colonization typically appear as dry and gray black (Figure 1C), a distinct and easily recognizable feature.
Based on these evident visual differences, 400 healthy F. feruloides plants with consistent above-ground growth and no P. tuoliensis mycelial colonization were selected and marked for identification in September 2021. Of these, 200 plants were designated as the natural control group, while the remaining 200 plants were subjected to field inoculation (Figure 1B). Fifty bags of P. tuoliensis strain 508 (200 g each) were each divided into four equal portions (50 g per portion), with each portion inoculated onto the root system of a single plant. No additional interventions were made after inoculation to ensure comparability. Environmental conditions, such as soil type, water availability, and photoperiod, were maintained identically to mirror natural conditions. These were treated as the field inoculation group, while the remaining 200 plants without field inoculation were treated as the natural group.
Rhizosphere soils were collected in May 2022 and classified into four experimental groups based on two criteria: inoculation status (natural control and field inoculation); and mycelial colonization (successful colonization and no colonization).
Natural Non-Mycelial Colonization (NN) Group: Soil samples were collected from the natural control group plants that exhibited no P. tuoliensis mycelial colonization, characterized by dry, gray black roots without the distinctive white, sponge-like mycelial association (Figure 1C). These samples represented undisturbed native soil without human intervention.
Natural Mycelial Colonization (NM) Group: Soil samples were obtained from the natural control group plants with spontaneous P. tuoliensis colonization, identified by the presence of dense white mycelia forming a sponge-like structure around F. feruloides roots (Figure 1D). These samples reflected naturally occurring mycelial–root associations in the native habitat.
Artificial Non-Mycelial Colonization (AN) Group: Soil samples were collected from the field inoculation group plants where P. tuoliensis mycelial colonization failed, despite field inoculation. The root morphology in this group resembled the NN group, with no visible mycelial colonization (Figure 1E), indicating unsuccessful establishment of the introduced mycelium.
Artificial Mycelial Colonization (AM) Group: Soil samples were obtained from the field inoculation group plants with confirmed P. tuoliensis colonization, displaying the characteristic white mycelial network around roots (Figure 1F). These samples represented successful artificial establishment of mycelial–root associations under inoculation conditions.
The five-point sampling method was employed to collect the rhizosphere soil of F. feruloides. Initially, large soil clumps were removed from the roots of F. feruloides, followed by the removal of loosely attached soil. Following this, soil within a 2.5-mm radius of the roots was collected using a sterile brush. These collected soil samples were designated as rhizosphere soil. Five replicates were collected from each sampling point; the samples were stored at −80 °C for subsequent analysis.

2.3. Analysis of the Physical and Chemical Properties of Soil

All soil samples, collected as described above, were air-dried and sieved through a 2 mm mesh. Soil pH was measured at a water-to-soil ratio of 2.5:1 using a pH meter (FE28 Meter, Mettler Toledo, Switzerland). Total salt content (TSC, g/kg) was determined using the residue drying method. Soil organic matter (SOM, g/kg) was assessed by the potassium dichromate oxidation external heating method. Total nitrogen (TN, g/kg) was estimated using the Kjeldahl method. Total potassium (TK, g/kg) was analyzed using a flame photometer. Total phosphorus (TP, g/kg) was determined by perchloric acid and sulfuric acid digestion molybdenum–antimony anti-colorimetry. Other physicochemical parameters and enzyme activities were analyzed using commercial soil test kits (Solarbio Science & Technology Co., Ltd., Beijing, China) following the manufacturer’s instructions. Ammonium nitrogen (NH4+, mg/kg) and nitrate nitrogen (NO3−, mg/kg) were determined by indophenol blue colorimetry and phenol disulfonic acid colorimetry, respectively. Available potassium (AK, mg/kg) was quantified using the tetraphenylboron-sodium turbidimetry method. Available phosphorus (AP, mg/kg) was measured using molybdenum blue colorimetry. The activities of sucrase, urease, and phosphatase in the soil were measured. Soil sucrase (S-SC, U/g) activity was measured using 3,5-dinitrosalicylic acid colorimetry. Soil urease (S-UE, U/g) activity was measured by sodium indophenol blue colorimetry. Soil alkaline phosphatase (S-AKP, U/g) activity was measured using phenyl disodium phosphate colorimetry. All analyses were performed with triplicate measurements, including blank controls.

2.4. DNA Extraction and Amplification

The soil genomic DNA was extracted using the Soil Genomic DNA Extraction Kit (Tiangen, China) following the manufacturer’s protocol. The quality and quantity of extracted DNA were assessed using 1.8% agarose (w/v) gel electrophoresis and a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The ITS1F/ITS2 [32] primer pair was used to amplify the ITS1 region, while the 338F/806R [33] primer pair was used to amplify the V3 and V4 regions of the 16S rRNA gene through polymerase chain reaction (PCR, Applied Biosystems, Carlsbad, California, USA). The PCR products were purified, quantified, and normalized to prepare the DNA library. Finally, paired-end sequencing of the DNA library was performed on an Illumina Miseq PE300 (2 × 300 bp) platform (Illumina, CA, USA).
Raw sequence reads were processed using Trimmomatic v0.33 software [34]. Using Cutadapt 1.9.1 software, primer sequences were identified and removed to obtain clean reads [35]. Then, QIIME2 2020.6 software was used to denoise, merge paired-end sequences, and remove chimeric sequences to obtain non-chimeric reads [36]. Taxonomic classification of each amplicon sequence variant (ASV) was performed. The microbial community composition in each sample was statistically analyzed across various taxonomic levels (i.e., Domain, Kingdom, Phylum, Class, Order, Family, Genus, and Species) using the Silva database (v132). Bacterial and fungal sequences were aligned against the Silva 132 and Unite 8.0 databases, respectively, with a minimum confidence of 0.7 [37]. Microbial community analysis and associated visualizations were generated using the BMK Cloud Platform (https://www.biocloud.net/).

2.5. Isolation of MGPB and Analysis of Their Mushroom Growth-Promoting Performance

Culturable bacteria were isolated from F. feruloides rhizosphere soil samples. A 1 g portion of the soil sample was added to 99 mL of sterile water in a conical flask and shaken at 30 °C and 200 rpm. The resulting soil suspension was then serially diluted to different concentrations (10−3 to 10−7). Diluted soil suspensions (150 µL) were evenly spread onto nutrient agar (NA), Luria-Bertani (LB), potato dextrose agar (PDA), and King B agar (KB) plates and incubated at 30 °C. Following incubation, single colonies with distinct morphologies were selected and subcultured on LB agar plates to obtain pure strains. The growth-promoting potential of the bacterial strains was evaluated by assessing their ability to produce 1-aminocyclopropane−1-carboxylate (ACC) deaminase, indole-3-acetic acid (IAA), hydrogen cyanide (HCN), and siderophores, as well as their abilities to solubilize phosphorus and potassium, and fix nitrogen [15,17,18].
ACC deaminase production was confirmed by growth on media containing ACC as the sole nitrogen source and no growth of the same strains in nitrogen-free media. IAA production was detected using a Salkowski colorimetric assay. HCN production was estimated using an HCN medium (nutrient agar supplemented with 4.4 g/L of glycine). The abilities of bacteria to produce siderophores, and to solubilize phosphorus and potassium were determined using the universal Chrome Azurol S (CAS), National Botanical Research Institute’s Phosphate (NBRIP) and Alexandrov agar plates. After incubation at 28 °C for 5 to 7 days, plates were observed for the formation of clear zones around the bacterial colonies, respectively [18,38]. Nitrogen-fixing ability was measured using Ashby’s nitrogen-free medium [39].

2.6. Analysis of Growth-Promoting Effects of Isolated Bacteria on P. tuoliensis

Cell-free Fermentation Broth Assay: The bacteria with potential mushroom growth-promoting abilities were inoculated into 100 mL of LB broth and incubated at 30 °C and 150 rpm for 3 days. After incubation, bacterial cells were separated by centrifugation at 8000 rpm for 15 min; the broth was filtered twice through a 0.22 μm bacterial filter to obtain the cell-free fermentation broth. Modified media were prepared by mixing different volumes of the cell-free fermentation broth with sterilized PDA media (v/v: 1.0%, 2.5%, 5.0%, and 7.5%, respectively). The prepared media were then poured into Petri dishes (φ = 90 mm). Discs of P. tuoliensis mycelia (φ = 7.0 mm) were inoculated at the center of the modified media plates and incubated at 25 °C. The diameters of the P. tuoliensis mycelia were measured to calculate their growth rates once they covered the entire plate [40].
Linear Growth Tests: The bacteria with potential mushroom growth-promoting abilities were inoculated into 100 mL of LB broth and incubated at 30 °C and 150 rpm for 16 h to obtain the bacterial suspension. The culture medium used for the cultivation of P. tuoliensis consisted of cottonseed hull (81%), bran (15%), calcium carbonate (1%), calcium sulfate (1%), and lime (2%) by weight. The culture medium was loaded into culture tubes with dimensions of 20 mm × 200 mm (each tube contained 17 ± 1 g of culture medium, with a height of 135 ± 1 mm) and sterilized by autoclaving at 121 °C for 120 min. After cooling, a 5 mL mixture of sterile water and bacterial suspension was added to the tubes. The volumes of bacterial suspension (108 CFU/mL) in different tubes were 0.1 mL, 0.2 mL, 0.5 mL, 1.0 mL, 2.0 mL, 3.0 mL, 4.0 mL, and 5.0 mL, respectively. An equal volume of sterile water was added to the control tubes. Each treatment group had 5 replicates. The culture tubes were then inoculated with P. tuoliensis mycelial discs (φ = 16.0 mm), placed in contact with the medium, and incubated at 25 °C for 15 days to assess the effect of bacteria on mycelial growth, visible through the glass tubes. The linear growth of mycelia was measured daily using a digital caliper; the growth rate was calculated in mm/day [17].

2.7. Identification of the Isolated MGPB

The total DNA of MGPB was extracted using a bacterial genomic DNA extraction kit (Tiangen, China). The quality and quantity of the extracted DNA were checked using 1.8% agarose (w/v) gel electrophoresis and a NanoDrop 2000 spectrophotometer. The universal primer pair 27F and 1492R was used to amplify the 16S rDNA sequence [41]. The amplified gene fragments were sequenced by Sangon Biotech Co., Ltd. (Shanghai, China). The obtained sequences were analyzed by comparison with reference sequences from the GenBank database using BLASTN (https://blast.ncbi.nlm.nih.gov/Blast.cgi) (accessed on 8 October 2024). Multiple sequence alignments were conducted in MAFFT; phylogenies of the dataset were inferred using Molecular Evolutionary Genetics Analysis (MEGA) version 7 software. Following this, a phylogenetic tree was inferred by using the Maximum Likelihood method based on the Hasegawa–Kishino–Yano model. Evolutionary analyses were conducted in MEGA7 [42].

2.8. Statistical Analysis

Statistical Package for the Social Sciences (SPSS) version 20 was used to analyze the data statistically. GraphPad Prism 8.3 and Origin 2021 software were employed to create the bar plots. One-way analysis of variance (ANOVA) was used to assess the effects of P. tuoliensis colonization on the chemical properties of soil in F. feruloides rhizosphere and isolated strains on the mycelial growth of P. tuoliensis. To compare groups for the Chao1 and Shannon indices, Student’s t-test and two-way ANOVA were applied, with p < 0.05 indicating a significant difference, and p < 0.01 indicating a highly significant difference. The F-statistic represents the ratio of the variation between the group means to the variation within the groups. A higher F-statistic indicates a greater likelihood that there is a real difference between the groups. β-diversity was assessed using Canonical Analysis of Principal Coordinates (CAP) based on the Bray–Curtis distance matrix. The microbial community structure was analyzed using permutational multivariate analysis of variance (PERMANOVA, permutations = 999). The R2 obtained by PERMANOVA indicates the degree of interpretation of the sample differences by different groups, that is, the ratio of group variance to total variance. A larger R2 indicates that the grouping has a higher interpretation degree to the difference; p < 0.05 indicates the high reliability of the test. The non-parametric Kruskal–Wallis H test was employed to examine the effects of P. tuoliensis colonization on the diversity and composition of the bacterial and fungal communities in the F. feruloides rhizosphere. Correlation analysis between the ASVs and soil chemical properties of soil in the F. feruloides rhizosphere was performed using Pearson’s correlation. The sequences of all primers used in this study are listed in Table S2.

3. Results

3.1. Effect of P. tuoliensis Colonization on the Chemical Properties of Soil in F. feruloides Rhizosphere

The rhizosphere soil samples were collected from the four groups (NN, NM, AN, and AM) and their physical and chemical properties were analyzed (Figure 1). The soil pH and contents of NH4+, NO3−, TSC, SOM, TN, TK, AK, TP, and AP were determined; the activities of S-SC, S-UE, and S-AKP enzymes in the soil were measured. The results revealed no significant differences in the pH and TN content of soil samples across the four treatment groups (p > 0.05, Figure 2A,D). The SOM content showed significant differences between the NN and NM groups, as well as between the AN and AM groups, with higher levels observed in the P. tuoliensis mycelial colonization groups (NM and AM; p < 0.05, Figure 2C). Compared to the AN treatment, the AM treatment resulted in higher TSC, NH4+, and TP in the soil, particularly for TSC (p < 0.05, Figure 2B,E,H). In particular, the TK and AP contents were lower in the field inoculation groups (AN and AM), compared to the natural groups (NN and NM; p < 0.05, Figure 2F,I). Furthermore, the AK content in the NM group was significantly lower than in the NN group. In comparison, no difference in AK content was observed between the AN and AM groups (p > 0.05, Figure 2G). Furthermore, the activities of three key enzymes in the soil samples were measured. The results showed no significant differences in S-SC and S-UE enzyme activities across the four treatments. However, the activity of S-AKP enzyme was higher in the NM group compared to the other three groups (p < 0.05, Figure 2J–L).

3.2. Effects of P. tuoliensis Colonization on the Diversity and Composition of the Bacterial Community in F. feruloides Rhizosphere Soil

A total of 1,599,405 raw reads with high-quality 16S rRNA sequences of bacteria were produced. After length filtering and chimera removal, 1,063,351 non-chimeric bacterial reads were obtained and verified (Table S2). The rarefaction curves of the bacteria tended to approach the saturation plateau in all samples, suggesting that the sequencing data could comprehensively and truthfully reflect the bacterial composition and community (Figure S1).
The bacterial community structure in the rhizosphere soils was comprehensively assessed through α- and β-diversity analyses. The Chao1 and Shannon indices, which measure bacterial community richness and diversity, revealed significant differences among the experimental groups (Figure 3A,B). Specifically, the α-diversity indices in the AM group were significantly lower than those in the NN and NM groups (Student’s t-test, p < 0.05). The AN group did not show significant differences compared to the other groups (Student’s t-test, p > 0.05). Further analysis using two-way ANOVA demonstrated significant interaction effects between field inoculation and mycelial colonization on Shannon diversity (F = 4.875, p < 0.05), while the Chao1 index showed a marginal interaction (F = 4.432, p = 0.051; Table S5).
Furthermore, canonical analysis of principal coordinates (CAP), based on Bray–Curtis dissimilarity, revealed a clear separation among the experimental groups (Figure 3C). Permutational multivariate analysis of variance (PERMANOVA) indicated that both field inoculation and mycelial colonization significantly influenced the bacterial community composition of the soil samples (F = 3.046, R2 = 0.363, p < 0.01); however, the effects of these two factors differed. Specifically, the impact of mycelial colonization was evident in the comparisons between NN and NM (R2 = 0.042, p < 0.05), as well as between AN and AM (R2 = 0.049, p < 0.01). In comparison, the effects of field inoculation were evident in the comparison of NN vs. AN (R2 = 0.156, p < 0.01) and NM vs. AM (R2 = 0.052, p > 0.05). Synergistic effects were identified in the comparison of NN vs. AM (R2 = 0.086, p < 0.01) (Figure S2A; all comparisons via PERMANOVA).
Across all analyzed soil samples, the predominant bacterial phyla ranked within the top 10 relative abundance were identified and selected. These included: Pseudomonadota; Acidobacteriota; Actinomycetota; Gemmatimonadota; Bacteroidota; Myxococcota; Chloroflexota; Bacillota; Nitrospirota; and Methylomirabilota [43]. Pseudomonadota, Acidobacteriota, Actinomycetota, Gemmatimonadota, and Bacteroidota were the dominant phyla, each showing average relative abundances > 5% (Figure 3D). This study revealed that Bacteroidota and Bacillota were significantly enriched in the AM group (p < 0.05), while Acidobacteriota and Nitrospirota were depleted compared to the NN group (p > 0.05, Figure 3D). The top 10 most abundant bacterial genera were identified based on their relative abundance across all samples. These genera included: Sphingomonas; Bryobacter; Nitrospira; Gemmatimonas; Bacillus; Streptomyces; Luteimonas; Rubrobacter; Brevundimonas; and Altererythrobacter. Sphingomonas, Bryobacter, Nitrospira, Gemmatimonas and Bacillus were the dominant genera, with average relative abundances exceeding 1% (Figure 3E). P. tuoliensis colonization altered the relative abundance of the bacterial genera in the rhizosphere soil of F. feruloides. Specifically, Bacillus, Streptomyces, and Brevundimonas were obviously enriched in the AM group, while Bryobacter, Nitrospira, and Rubrobacter were depleted in the AM group compared to the NN or NM groups (p < 0.05, Figure 3E).
Moreover, biomarker bacteria showing statistical differences in their abundance across the different groups were identified using line discriminant analysis (LDA) effect size (LEfSe) analysis (Figure 4 and Figure S2). An LDA value greater than two indicated significant species differences, with higher LDA values reflecting greater divergence between species. In the NM group (LDA > 3.5), the biomarker bacteria predominantly belonged to the Chloroflexota phylum, including the Vicinamibacteria and Thermoanaerobaculia classes, as well as the Solirubrobacterales and Thermoanaerobaculales orders. On the other hand, the AM group (LDA > 3.5) was dominated by bacteria from the Bacillota and Actinomycetota phyla, Bacilli class, Rhizobiales, Sphingobacteriales, Micrococcales, and Bacillales orders, and families such as Sphingobacteriaceae, Rhizobiaceae, Xanthobacteraceae, and Bacillaceae. Genera, such as Olivibacter and Bacillus, along with species, like Olivibacter soli and unclassified Bacillus species, were also prominent.

3.3. Effects of P. tuoliensis Colonization on the Diversity and Composition of Fungal Community in F. feruloides Rhizosphere Soil

A total of 1,598,593 high-quality fungal ITS sequences were generated. After applying length-based filtering and removing chimeric sequences, 1,510,628 non-chimeric fungal reads were obtained and confirmed (Table S4). The rarefaction curves of ASVs for all samples approached the saturation plateau, indicating adequate sequencing depth (Figure S1B). Fungal α-diversity patterns were similar to those observed in bacterial communities, with significant reductions in both the Chao1 and Shannon indices in the AM group compared to the NN and NM groups (Student’s t-test, p < 0.05; Figure 5A,B). While no significant difference in Chao1 was observed between the AN group and other groups (Student’s t-test, p > 0.05; Figure 5A), the Shannon index in the AN group was significantly higher than in the AM group (Student’s t-test, p < 0.05; Figure 5B). Two-way ANOVA revealed independent suppressive effects of field inoculation (F = 5.867, p < 0.05) and mycelial colonization (F = 5.349, p < 0.05), with no significant interaction between these factors (F = 0.000, p > 0.05; Table S6).
Furthermore, the CAP analysis based on Bray–Curtis dissimilarities using OTU-level abundance data revealed significant structural differences in soil microbial communities among the four treatment groups, with distinct separation patterns (PERMANOVA, R2 = 0.526, p < 0.01; Figure 5C). Specifically, the effects of mycelial colonization were observed in the comparisons of NN vs. NM (R2 = 0.103, p < 0.01) and AN vs. AM (R2 = 0.260, p < 0.01). While the effects of field inoculation were evident in the comparison of NN vs. AN (R2 = 0.098, p < 0.01), and NM vs. AM (R2 = 0.321, p < 0.01), synergistic effects were identified in the comparison of NN vs. AM (R2 = 0.292, p < 0.01) (Figure S2B; all comparisons via PERMANOVA).
The fungal community composition was analyzed across all samples at both the phylum and genus levels. The predominant fungal phyla identified in all samples, with average relative abundances exceeding 1%, included: Ascomycota; Basidiomycota; Mortierellomycota; Chytridiomycota; and Glomeromycota. Among these, Ascomycota and Basidiomycota were the dominant phyla, each with average relative abundances greater than 40% (Figure 5D). P. tuoliensis colonization altered the diversity and composition of the fungal community in the F. feruloides rhizosphere. Specifically, the predominant fungal phyla Ascomycota, Mortierellomycota, and Glomeromycota were depleted, while Basidiomycota was enriched in the AM group compared to the NN group (p < 0.05, Figure 5D). The most abundant fungal genera identified in all samples (with average relative abundances >1%) included: Pleurotus; Tulostoma; Fusarium; Agaricus; Mortierella; and Preussia. Further analysis revealed that Fusarium and Mortierella were depleted, while only Pleurotus was enriched in the AM group compared to the NN group (p < 0.05, Figure 5E).

3.4. Correlations Between the Chemical Properties of F. feruloides Rhizosphere Soil and Microbial Community

Based on the preliminary analysis of changes in the structure and functions of the microbial community, Pearson correlation analysis and the Mantel test were performed to examine the relationship between these changes and the chemical properties of F. feruloides rhizosphere soil (Figure 6 and Figure S4). The TK was significantly correlated with the bacterial and fungal communities. (Mantel’s r ≥ 0.4, p < 0.01; Figure S4). The results indicated significant positive correlations between Rubrobacter, Actinobacterium, Nitrospira, and Bryobacter and the changes in the chemical properties of F. feruloides rhizosphere soil (p < 0.001). Similarly, the fungi Scutellinia and Tulostoma demonstrated significant positive correlations with these soil chemical changes (p < 0.01, Figure 6A). However, Pleurotus, Psathyrella, and Preussia showed significant negative correlations with the changes in the chemical properties of F. feruloides rhizosphere soil (p < 0.05, Figure 6B).

3.5. Effect of Bacillus on the Growth of P. tuoliensis Hyphae

A total of 117 well-grown bacterial isolates were isolated from the soil samples of NM and AM groups. Among them, 45 isolates representing different bacterial colony morphologies were selected based on the shape, size, and color of the colonies. These 45 isolates were subsequently subjected to analysis of their growth-promoting potential, including the production of ACC deaminase, HCN, IAA, and siderophores, as well as their abilities to solubilize phosphorus and potassium, and to fix nitrogen [15,17]. Five bacterial isolates, each with at least four positive attributes, were initially selected. (Table S6). These five isolates were further analyzed and screened using cell-free fermentation broth and linear growth tests of mushroom mycelia. Finally, two strains, L5 and S16, were identified as significantly promoting the growth of P. tuoliensis mycelia and were selected for further study. They were preserved in the China General Microbiological Culture Collection Center (accession number CGMCC 32190) and the Guangdong Microbial Culture Collection Center (accession number GDMCC 65722), respectively.
As shown in Figure 7A,B, varying volumes of L5 and S16 fermentation broths promoted the hyphal growth of P. tuoliensis. In the modified medium containing 2.5% to 7.5% fermentation broth, the mycelial growth rate of P. tuoliensis was significantly faster than that in the control group (p < 0,05, Figure 7B). At a fermentation broth concentration of 5.0%, the mycelial growth rates of L5 and S16 reached 8.37 mm/d and 7.87 mm/d, respectively, representing a 59.73% and 55.84% increase compared to the control group (Figure 7B). The linear growth rate of mycelia was also analyzed by inoculating the bacterial culture into culture tubes filled with moistened cottonseed hulls (Figure 7C,D). Strain L5 significantly increased the mycelial growth rate of P. tuoliensis when added in volumes ranging from 0.1 to 5.0 mL (p < 0.05, Figure 7C). The most pronounced effect was observed at the 0.1 to 0.5 mL dose, resulting in a 65.75% increase in the mycelial growth rate. On the other hand, S16 significantly promoted mycelial growth in a volume range of 3.0 to 5.0 mL (p < 0.05), with the most significant increase of 70.11% at a dose of 4.0 mL.
A phylogenetic tree was constructed to compare 16S rRNA sequences of strains L5 and S16 with the sequences of other closely related bacterial strains in the GenBank online database (Figure 7E). Based on the similarity index, Strain L5 was identified as Bacillus cereus group, while S16 was identified as Bacillus safensis.

4. Discussion

P. tuoliensis is an endemic edible fungus native to northwest China [5]; however, the effects of its hyphal colonization and field inoculation on soil microbial communities have not been systematically investigated. This study focused on the mycelial colonization phase of P. tuoliensis in the Qinghe Bailingu Conservation Area. Four distinct groups of soil samples were analyzed and categorized based on inoculation status and mycelial colonization (see Section 2). The samples were collected from brown calcareous soil, which is the native soil type in the habitat of P. tuoliensis, ensuring that the research was conducted under conditions most representative of the Bailinggu’s natural environment. Additionally, the growth status of F. feruloides, including its growth trend and size, was consistent across all samples. The P. tuoliensis strain 508 was isolated from wild samples collected from this region. All environmental management practices, including water availability and sunlight exposure, were rigorously controlled across the four treatment groups to replicate natural, wild conditions without artificial intervention. This approach preserved the inherent ecological dynamics of the system and ensured comparability between experimental groups. It should be noted that simultaneous soil sample collection may limit the understanding of dynamic environmental processes associated with mycelial colonization. However, existing studies in the literature support the validity of single-sampling combined with functional analyses in providing ecologically relevant insights within specific soil systems and research contexts [44,45].
High-throughput sequencing revealed that the field inoculation of P. tuoliensis significantly altered the rhizosphere microbiome of F. feruloides during mycelial colonization, affecting both bacterial and fungal populations. Notably, field inoculation resulted in a substantial increase in the relative abundance of Pleurotus (57.98% compared to 14.11%), accompanied by significant reductions in microbial community diversity. Moreover, the relative abundances of Pseudomonadota, Bacteroidota, and Bacillota significantly increased following field inoculation. Importantly, two mushroom growth-promoting bacteria (MGPB), B. cereus group (L5) and B. safensis (S16), were successfully isolated, providing new insights into beneficial microbe–fungus interactions during P. tuoliensis cultivation.
Previous studies have reported decreases in microbial biodiversity during mycelial colonization in the cultivation of Pleurotus spp. and A. bisporus. In A. bisporus, a notable decrease in bacterial diversity was observed during the compost’s full colonization [16,46], with Pseudomonadota emerging as the dominant phylum and an increase in the relative abundance of Bacillota [15,47]. Similar changes were found in P. eryngii industrial production, where bacterial diversity at the full-bag mycelial stage was lower than at the half-bag stage, followed by a shift towards biocontrol and growth-promotion functions [40]. Furthermore, the reduction in microbial diversity during P. ostreatus colonization implies not only a numerical change but also a functional shift within the microbial community [48,49,50]. These findings reveal consistent effects of edible fungi on soil and compost microbial communities at similar growth stages, suggesting that the growth stage is a critical factor influencing microbial community composition.
As diversity declines, Bacillus spp. and Paenibacillus polymyxa develop increasingly symbiotic associations with P. ostreatus, suppressing competitive molds and supporting fungal health [49]. These functions are comparable to the benefits conferred by Bacillus in A. bisporus cultivation, where this genus enhances lignocellulose degradation and inhibits pathogenic bacteria [15]. In the present study, the enrichment of Pseudomonadota, Bacteroidota, and Bacillota following the inoculation of P. tuoliensis reflects microbial shifts during P. tuoliensis mycelial colonization. This process aligns with the mushroom holobiont [16,51], which suggests that fungi assemble functional microbial communities through the stage-specific recruitment of beneficial microorganisms, prioritizing ecosystem services, such as nutrient mobilization and pathogen antagonism, over maintaining high species richness.
The growth of edible mushrooms represents a dynamic interplay between bacteria and fungi, in which interactions, such as bacteriolytic nutrient acquisition, chemotaxis-driven bacterial colonization, and the bacterial secretion of growth-promoting factors, including phytohormones, siderophores, and ACC deaminase, are critical for mycelial development [17,50,52]. In this study, 5 bacterial isolates, each with at least 4 positive attributes, were initially selected from 45 isolates representing various bacterial colony morphologies. Finally, two strains, L5 (B. cereus group) and S16 (B. safensis) were identified as exhibiting growth-promoting properties. While B. cereus has been previously linked to fungal growth promotion in A. bisporus [15] and P. eryngii [40], B. safensis is reported here for the first time as a mushroom growth-promoting bacterium. This finding broadens the known repertoire of MGPB and indicates a previously unexplored functional diversity within the Bacillota phylum.
While this study offers novel insights into the interactions between P. tuoliensis and soil microbes, its single time-point design and focus on a single conservation area (Qinghe County) limit the ability to draw dynamic or cross-ecosystem conclusions. Long-term monitoring and multi-omics approaches (e.g., metagenomics, metabolomics) are necessary to capture temporal shifts in microbial function and to identify keystone taxa or metabolites crucial for fruiting body formation. Moreover, the effectiveness of the isolated Bacillus strains (L5 and S16) should be further validated under field conditions, particularly regarding their competition with indigenous microbiota and their resilience to environmental stressors.
Successful mycelial colonization is essential for conserving and cultivating wild P. tuoliensis. Gaining a deeper understanding of the physicochemical properties and microbial communities in the rhizosphere of P. tuoliensis is crucial for enhancing conservation efforts and ensuring sustainable management practices. Furthermore, the interactions between Bacillus, P. tuoliensis, and other soil microorganisms must be explored in greater detail. This will help to build a theoretical framework for establishing a more stable and efficient soil ecosystem, supporting the sustainable development of the artificial cultivation industry of P. tuoliensis.

5. Conclusions

In summary, this study employed high-throughput sequencing technology to examine the effects of field inoculation and mycelial colonization on the composition and structure of soil microbial communities in the rhizosphere of F. feruloides, as well as the potential of isolated bacteria to promote P. tuoliensis growth. The results indicated that field inoculation remarkably affected the abundance, diversity, and composition of these microbial communities, particularly by enhancing the relative abundance of beneficial bacteria and fungi. These microorganisms play a pivotal role in fostering fungal colonization and growth. Two Bacillus strains (L5 and S16) were identified as key growth-promoting bacteria for P. tuoliensis. The insights from this study provide a significant theoretical foundation for a better understanding of bacterial–fungal interactions, which will, in turn, support further research on the in situ conservation of edible fungi. These findings contribute to developing medium- and long-term strategies to improve the industrial profitability and sustainability of artificial P. tuoliensis cultivation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15051136/s1. Figure S1: Rarefaction curves of the number of ASVs; Figure S2: PERMANOVA analysis box plot based on Bray–Curtis distance; Figure S3: Histogram of LDA discrimination; Figure S4: Correlations of the soil physicochemical variables with bacterial and fungal communities in F. feruloides rhizosphere soil; Table S1: Numbers of wild P. tuoliensis collected in each distribution area; Table S2: Primers for ITS1 region, 16S V3 and V4 region and 16s rRNA region; Table S3: High-throughput sequencing results of 16S rRNA sequences; Table S4: High-throughput sequencing results of ITS sequences; Table S5: Two-way ANOVA of variance for α-diversity of bacterial community; Table S6: Two-way ANOVA of variance for α-diversity of fungal community; Table S7: Test results of bacterial growth-promoting properties.

Author Contributions

Y.L.: Conceptualization, writing—original draft; H.L.: Formal analysis and Writing—review and editing; W.J.: Investigation; N.Y. and Q.Z.: Writing—review and editing; P.J.: Conceptualization and Supervision; Y.H. and W.S.: Data curation and Validation; C.S. and J.G.: Resources. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Xinjiang Academy of Agricultural Sciences Youth Science and Technology Backbone Innovation Ability Training Project (grant number xjnkq-2021017), the Postgraduate Education Research Innovation Program of Xinjiang Uygur Autonomous Region (XJ2024G111), the Tianshan Talents Cultivation Plan Project, and the Earmarked Fund for CARS (grant number CARS-20).

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Acknowledgments

We appreciate all the people who collaborated on this project.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Galappaththi, M.C.A.; Dauner, L.; Madawala, S.; Karunarathna, S.C. Nutritional and medicinal benefits of Oyster (Pleurotus) mushrooms: A review. Fungal Biotec 2021, 1, 65–87. [Google Scholar] [CrossRef]
  2. Raman, J.; Jang, K.-Y.; Oh, Y.-L.; Oh, M.; Im, J.-H.; Lakshmanan, H.; Sabaratnam, V. Cultivation and Nutritional Value of Prominent Pleurotus spp.: An Overview. Mycobiology 2020, 49, 1–14. [Google Scholar] [CrossRef] [PubMed]
  3. Corrêa, R.C.G.; Brugnari, T.; Bracht, A.; Peralta, R.M.; Ferreira, I.C.F.R. Biotechnological, nutritional and therapeutic uses of Pleurotus spp. (Oyster mushroom) related with its chemical composition: A review on the past decade findings. Trends Food Sci. Technol. 2016, 50, 103–117. [Google Scholar] [CrossRef]
  4. Zhao, M.; Zhang, J.; Chen, Q.; Wu, X.; Gao, W.; Deng, W.; Huang, C. The famous cultivated mushroom Bailinggu is a separate species of the Pleurotus eryngii species complex. Sci. Rep. 2016, 6, 33066. [Google Scholar] [CrossRef]
  5. Jia, P.; Nurziya, Y.; Luo, Y.; Jia, W.; Zhu, Q.; Tian, M.; Sun, L.; Zhang, B.; Qi, Z.; Zhao, Z.; et al. Evolution and Genetic Differentiation of Pleurotus tuoliensis in Xinjiang, China, Based on Population Genomics. J. Fungi 2024, 10, 472. [Google Scholar] [CrossRef]
  6. Zhang, J.X.; Huang, C.Y.; Ng, T.B.; Wang, H.X. Genetic polymorphism of ferula mushroom growing on Ferula sinkiangensis. Appl. Microbiol. Biotechnol. 2006, 71, 304–309. [Google Scholar] [CrossRef]
  7. Zhao, M.; Huang, C.; Chen, Q.; Wu, X.; Qu, J.; Zhang, J. Genetic variability and population structure of the mushroom Pleurotus eryngii var. tuoliensis. PLoS ONE 2013, 8, e83253. [Google Scholar] [CrossRef]
  8. Ren, Z.; Li, J.; Xu, N.; Zhang, J.; Song, X.; Wang, X.; Gao, Z.; Jing, H.; Li, S.; Zhang, C.; et al. Anti-hyperlipidemic and antioxidant effects of alkali-extractable mycelia polysaccharides by Pleurotus eryngii var. tuolensis. Carbohydr. Polym. 2017, 175, 282–292. [Google Scholar] [CrossRef]
  9. Xu, N.; Gao, Z.; Zhang, J.; Jing, H.; Li, S.; Ren, Z.; Wang, S.; Jia, L. Hepatoprotection of enzymatic-extractable mycelia zinc polysaccharides by Pleurotus eryngii var. tuoliensis. Carbohydr. Polym. 2017, 157, 196–206. [Google Scholar] [CrossRef]
  10. Yan, B.; Jing, L.; Wang, J. A polysaccharide (PNPA) from Pleurotus nebrodensis offers cardiac protection against ischemia–reperfusion injury in rats. Carbohydr. Polym. 2015, 133, 1–7. [Google Scholar] [CrossRef]
  11. Wang, C.; Cui, H.; Wang, Y.; Wang, Z.; Li, Z.; Chen, M.; Li, F. Bidirectional Immunomodulatory Activities of Polysaccharides Purified From Pleurotus nebrodensis. Inflammation 2014, 37, 83–93. [Google Scholar] [CrossRef] [PubMed]
  12. Yang, Y.; Fu, C.; Zhou, F.; Luo, X.; Li, J.; Zhao, J.; He, J.; Li, X.; Li, J. Chemical composition, antioxidant and antitumor activities of sub-fractions of wild and cultivated Pleurotus ferulae ethanol extracts. PeerJ 2018, 6, e6097. [Google Scholar] [CrossRef] [PubMed]
  13. Wang, S.; Zhao, S.; Huang, Z.; Yin, L.; Hu, J.; Li, J.; Liu, Y.; Rong, C. Development of a highly productive strain of Pleurotus tuoliensis for commercial cultivation by crossbreeding. Sci. Hortic. 2018, 234, 110–115. [Google Scholar] [CrossRef]
  14. Gao, W.; Qu, J.; Zhang, J.; Sonnenberg, A.; Chen, Q.; Zhang, Y.; Huang, C. A genetic linkage map of Pleurotus tuoliensis integrated with physical mapping of the de novo sequenced genome and the mating type loci. BMC Genom. 2018, 19, 18. [Google Scholar] [CrossRef]
  15. Braat, N.; Koster, M.C.; Wösten, H.A.B. Beneficial interactions between bacteria and edible mushrooms. Fungal Biol. Rev. 2022, 39, 60–72. [Google Scholar] [CrossRef]
  16. Carrasco, J.; Preston, G.M. Growing edible mushrooms: A conversation between bacteria and fungi. Environ. Microbiol. 2020, 22, 858–872. [Google Scholar] [CrossRef]
  17. Kumari, S.; Naraian, R. Enhanced growth and yield of oyster mushroom by growth-promoting bacteria Glutamicibacter arilaitensis MRC119. J. Basic Microb. 2021, 61, 45–54. [Google Scholar] [CrossRef]
  18. Zarenejad, F.; Yakhchali, B.; Rasooli, I. Evaluation of indigenous potent mushroom growth promoting bacteria (MGPB) on Agaricus bisporus production. World J. Microbiol. Biotechnol. 2012, 28, 99–104. [Google Scholar] [CrossRef]
  19. Zhang, C.; Zhang, G.; Wen, Y.; Li, T.; Gao, Y.; Meng, F.; Qiu, L.; Ai, Y. Pseudomonas sp. UW4 acdS gene promotes primordium initiation and fruiting body development of Agaricus bisporus. World J. Microbiol. Biotechnol. 2019, 35, 163. [Google Scholar] [CrossRef]
  20. Cho, Y.S.; Kim, J.S.; Crowley, D.E.; Cho, B.G. Growth promotion of the edible fungus Pleurotus ostreatus by fluorescent pseudomonads. FEMS Microbiol. Lett. 2003, 218, 271–276. [Google Scholar] [CrossRef]
  21. Park, Y.; Park, Y.; Jang, M. Growth Characteristics of Pseudomonas putida and Pleurotus ostreatus After Co-Cultivation. Mycobiology 2025, 53, 72–78. [Google Scholar] [CrossRef] [PubMed]
  22. Kim, M.K.; Math, R.K.; Cho, K.M.; Shin, K.J.; Kim, J.O.; Ryu, J.S.; Lee, Y.H.; Yun, H.D. Effect of Pseudomonas sp. P7014 on the growth of edible mushroom Pleurotus eryngii in bottle culture for commercial production. Bioresour. Technol. 2008, 99, 3306–3308. [Google Scholar] [CrossRef] [PubMed]
  23. Hao, H.; Yue, Y.; Wang, Q.; Xiao, T.; Zhao, Z.; Zhang, J.; Chen, H. Effects of the rice-mushroom rotation pattern on soil properties and microbial community succession in paddy fields. Front. Microbiol. 2024, 15, 1449922. [Google Scholar] [CrossRef] [PubMed]
  24. Pandin, C.; Védie, R.; Rousseau, T.; Le Coq, D.; Aymerich, S.; Briandet, R. Dynamics of compost microbiota during the cultivation of Agaricus bisporus in the presence of Bacillus velezensis QST713 as biocontrol agent against Trichoderma aggressivum. Biol. Control. 2018, 127, 39–54. [Google Scholar] [CrossRef]
  25. Xu, W.; Sun, T.; Du, J.; Jin, S.; Zhang, Y.; Bai, G.; Li, W.; Yin, D. Structure and ecological function of the soil microbiome associated with ‘Sanghuang’ mushrooms suffering from fungal diseases. BMC Microbiol. 2023, 23, 218. [Google Scholar] [CrossRef]
  26. Zheng, Q.; Hu, Y.; Zhang, S.; Noll, L.; Bockle, T.; Dietrich, M.; Herbold, C.W.; Eichorst, S.A.; Woebken, D.; Richter, A.; et al. Soil multifunctionality is affected by the soil environment and by microbial community composition and diversity. Soil Biol. Biochem. 2019, 136, 107521. [Google Scholar] [CrossRef]
  27. Cai, W.; Yao, H.; Feng, W.; Jin, Q.; Liu, Y.; Li, N.; Zheng, Z. Microbial Community Structure of Casing Soil During Mushroom Growth. Pedosphere 2009, 19, 446–452. [Google Scholar] [CrossRef]
  28. García-Montero, L.G.; Monleón, V.J.; Valverde-Asenjo, I.; Menta, C.; Kuyper, T.W. Niche construction by two ectomycorrhizal truffle species (Tuber aestivum and T. melanosporum). Soil Biol. Biochem. 2024, 189, 109276. [Google Scholar] [CrossRef]
  29. Li, Q.; Zhao, J.; Xiong, C.; Li, X.; Chen, Z.; Li, P.; Huang, W. Tuber indicum shapes the microbial communities of ectomycorhizosphere soil and ectomycorrhizae of an indigenous tree (Pinus armandii). PLoS ONE 2017, 12, e175720. [Google Scholar] [CrossRef]
  30. Jo, J.; Oh, J.; Park, C. Microbial community analysis using high-throughput sequencing technology: A beginner’s guide for microbiologists. J. Microbiol. 2020, 58, 176–192. [Google Scholar] [CrossRef]
  31. Dissanayake, A.J.; Purahong, W.; Wubet, T.; Hyde, K.D.; Zhang, W.; Xu, H.; Zhang, G.; Fu, C.; Liu, M.; Xing, Q.; et al. Direct comparison of culture-dependent and culture-independent molecular approaches reveal the diversity of fungal endophytic communities in stems of grapevine (Vitis vinifera). Fungal Divers. 2018, 90, 85–107. [Google Scholar] [CrossRef]
  32. Tedersoo, L.; Anslan, S.; Bahram, M.; Põlme, S.; Riit, T.; Liiv, I.; Kõljalg, U.; Kisand, V.; Nilsson, H.; Hildebrand, F.; et al. Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. Mycokeys 2015, 10, 1–43. [Google Scholar] [CrossRef]
  33. Zeng, Q.; An, S. Identifying the Biogeographic Patterns of Rare and Abundant Bacterial Communities Using Different Primer Sets on the Loess Plateau. Microorganisms 2021, 9, 139. [Google Scholar] [CrossRef]
  34. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef]
  35. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.J. 2011, 17, 10–12. [Google Scholar] [CrossRef]
  36. Zhou, X.; Zhang, J.; Khashi, U.R.M.; Gao, D.; Wei, Z.; Wu, F.; Dini-Andreote, F. Interspecific plant interaction via root exudates structures the disease suppressiveness of rhizosphere microbiomes. Mol. Plant 2023, 16, 849–864. [Google Scholar] [CrossRef]
  37. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2012, 41, D590–D596. [Google Scholar] [CrossRef]
  38. Dubey, A.; Kumar, K.; Srinivasan, T.; Kondreddy, A.; Kumar, K. An invasive weed-associated bacteria confers enhanced heat stress tolerance in wheat. Heliyon 2022, 8, e9893. [Google Scholar] [CrossRef]
  39. Wang, Y.; Sun, Z.; Zhao, Q.; Yang, X.; Li, Y.; Zhou, H.; Zhao, M.; Zheng, H. Whole-genome analysis revealed the growth-promoting and biological control mechanism of the endophytic bacterial strain Bacillus halotolerans Q2H2, with strong antagonistic activity in potato plants. Front. Microbiol. 2023, 14, 1287921. [Google Scholar] [CrossRef]
  40. Chen, L.; Yan, M.; Qian, X.; Yang, Z.; Xu, Y.; Wang, T.; Cao, J.; Sun, S. Bacterial Community Composition in the Growth Process of Pleurotus eryngii and Growth-Promoting Abilities of Isolated Bacteria. Front. Microbiol. 2022, 13, 787628. [Google Scholar] [CrossRef]
  41. Dos Santos, H.R.M.; Argolo, C.S.; Argôlo-Filho, R.C.; Loguercio, L.L. A 16S rDNA PCR-based theoretical to actual delta approach on culturable mock communities revealed severe losses of diversity information. BMC Microbiol. 2019, 19, 74. [Google Scholar] [CrossRef] [PubMed]
  42. Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar] [CrossRef] [PubMed]
  43. Oren, A.; Garrity, G.M. Valid publication of the names of forty-two phyla of prokaryotes. Int. J. Syst. Evol. Microbiol. 2021, 71, 005056. [Google Scholar] [CrossRef] [PubMed]
  44. Lu, T.; Xu, N.; Lei, C.; Zhang, Q.; Zhang, Z.; Sun, L.; He, F.; Zhou, N.; Peñuelas, J.; Zhu, Y.; et al. Bacterial biogeography in China and its association to land use and soil organic carbon. Soil Ecol. Lett. 2023, 5, 230172. [Google Scholar] [CrossRef]
  45. Tan, H.; Liu, T.; Yu, Y.; Tang, J.; Jiang, L.; Martin, F.M.; Peng, W. Morel Production Related to Soil Microbial Diversity and Evenness. Microbiol. Spectr. 2021, 9, e22921. [Google Scholar] [CrossRef]
  46. Vos, A.M.; Heijboer, A.; Boschker, H.T.S.; Bonnet, B.; Lugones, L.G.; Wösten, H.A.B. Microbial biomass in compost during colonization of Agaricus bisporus. Amb Express. 2017, 7, 12. [Google Scholar] [CrossRef]
  47. Mcgee, C.F.; Byrne, H.; Irvine, A.; Wilson, J. Diversity and dynamics of the DNA and cDNA-derived bacterial compost communities throughout the Agaricus bisporus mushroom cropping process. Ann Microbiol. 2017, 67, 751–761. [Google Scholar] [CrossRef]
  48. Snajdr, J.; Baldrian, P. Production of lignocellulose-degrading enzymes and changes in soil bacterial communities during the growth of Pleurotus ostreatus in soil with different carbon content. Folia Microbiol. 2006, 51, 579–590. [Google Scholar] [CrossRef]
  49. Banfi, R.; Pohner, Z.; Szabo, A.; Herczeg, G.; Kovacs, G.M.; Nagy, A.; Marialigeti, K.; Vajna, B. Succession and potential role of bacterial communities during Pleurotus ostreatus production. FEMS Microbiol. Ecol. 2021, 97, fiab125. [Google Scholar] [CrossRef]
  50. Shamugam, S.; Kertesz, M.A. Bacterial interactions with the mycelium of the cultivated edible mushrooms Agaricus bisporus and Pleurotus ostreatus. J. Appl. Microbiol. 2023, 134, lxac018. [Google Scholar] [CrossRef]
  51. Partida-Martinez, L.P. The fungal holobiont: Evidence from early diverging fungi. Environ. Microbiol. 2017, 19, 2919–2923. [Google Scholar] [CrossRef]
  52. Li, R.; Zhang, Q.; Chen, Y.; Gao, Y.; Yang, Y.; Liu, Q.; Kong, W.; Chai, H.; Sun, B.; Li, Y.; et al. The Mechanism of Ammonia-Assimilating Bacteria Promoting the Growth of Oyster Mushrooms (Pleurotus ostreatus). J. Fungi 2025, 11, 130. [Google Scholar] [CrossRef]
Agronomy 15 01136 g001
Figure 1. Soil samples of F. feruloides roots under both native environment and field inoculation with P. tuoliensis were collected: (A) P. tuoliensis conservation area in Xinjiang, northwest China (46°59′82″ N, 89°87′20″ E), the native habitat of P. tuoliensis; (B) colonization of wild P. tuoliensis in the roots of F. feruloides; and (C–F, arrows) colonization of P. tuoliensis in the roots of F. feruloides under NN, NM, AN, and AM treatments, respectively.
Figure 1. Soil samples of F. feruloides roots under both native environment and field inoculation with P. tuoliensis were collected: (A) P. tuoliensis conservation area in Xinjiang, northwest China (46°59′82″ N, 89°87′20″ E), the native habitat of P. tuoliensis; (B) colonization of wild P. tuoliensis in the roots of F. feruloides; and (C–F, arrows) colonization of P. tuoliensis in the roots of F. feruloides under NN, NM, AN, and AM treatments, respectively.
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Figure 2. The physical and chemical properties of soil samples under different treatments (NN, NM, AN, and AM): (A) Soil pH; (B) total soil carbon (TSC) content; (C) soil organic matter (SOM) content; (D) total nitrogen (TN) content; (E) ammonium nitrogen (NH4+) content; (F) total potassium (TK) content; (G) available potassium (AK) content; (H) total phosphorus (TP) content; (I) available phosphorus (AP) content; (J) soil sucrase (S-SC) activity; (K) soil urease (S-UE) activity; and (L) soil alkaline phosphatase (S-AKP) activity. Each treatment group had 5 replicates and each replicate had 3 technology replicates. The statistical significance of variance was denoted using different letters in the graphs. The relevant differences between the groups were assessed by performing one-way ANOVA at a significance level of p < 0.05.
Figure 2. The physical and chemical properties of soil samples under different treatments (NN, NM, AN, and AM): (A) Soil pH; (B) total soil carbon (TSC) content; (C) soil organic matter (SOM) content; (D) total nitrogen (TN) content; (E) ammonium nitrogen (NH4+) content; (F) total potassium (TK) content; (G) available potassium (AK) content; (H) total phosphorus (TP) content; (I) available phosphorus (AP) content; (J) soil sucrase (S-SC) activity; (K) soil urease (S-UE) activity; and (L) soil alkaline phosphatase (S-AKP) activity. Each treatment group had 5 replicates and each replicate had 3 technology replicates. The statistical significance of variance was denoted using different letters in the graphs. The relevant differences between the groups were assessed by performing one-way ANOVA at a significance level of p < 0.05.
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Figure 3. Changes in the bacterial community in the soil of F. feruloides (A,B): the Chao1 index (A); and Shannon index (B) were employed to assess bacterial α-diversity, using the Student’s t-test and two-way ANOVA to compare groups, with p < 0.05 indicating a significant difference, and p < 0.01 indicating a very significant difference; and (C) the β-diversity of bacteria was revealed through canonical analysis of principal coordinates (CAP) analysis. PERMANOVA (permutations = 999) was used to analyze microbial community structure. R2 indicates the degree of interpretation of sample differences by different groups, that is, the ratio of group variance to total variance. A larger R2 indicates that grouping has a higher interpretation degree to the difference, and p < 0.05 means high reliability of the test (D,E): the relative abundance of the main bacterial phyla (D); and genera (E) under each treatment. For more than two groups, means were compared between treatments using the Kruskal–Wallis H test at a significance level of p < 0.05. * and ** indicate significance levels at p < 0.05 and p < 0.01, respectively.
Figure 3. Changes in the bacterial community in the soil of F. feruloides (A,B): the Chao1 index (A); and Shannon index (B) were employed to assess bacterial α-diversity, using the Student’s t-test and two-way ANOVA to compare groups, with p < 0.05 indicating a significant difference, and p < 0.01 indicating a very significant difference; and (C) the β-diversity of bacteria was revealed through canonical analysis of principal coordinates (CAP) analysis. PERMANOVA (permutations = 999) was used to analyze microbial community structure. R2 indicates the degree of interpretation of sample differences by different groups, that is, the ratio of group variance to total variance. A larger R2 indicates that grouping has a higher interpretation degree to the difference, and p < 0.05 means high reliability of the test (D,E): the relative abundance of the main bacterial phyla (D); and genera (E) under each treatment. For more than two groups, means were compared between treatments using the Kruskal–Wallis H test at a significance level of p < 0.05. * and ** indicate significance levels at p < 0.05 and p < 0.01, respectively.
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Figure 4. Evolution diagram obtained after LEfSe analysis. The circle radiating from the inside to the outside represents the classification levels ranging from phylum to genus. Each node represents a species inferred from amplicon sequences, not from cultured bacteria. The diameter of each circle is proportional to the relative abundance of the corresponding species. Species with no significant differences are highlighted in white, while other species are colored according to the group with the highest abundance.
Figure 4. Evolution diagram obtained after LEfSe analysis. The circle radiating from the inside to the outside represents the classification levels ranging from phylum to genus. Each node represents a species inferred from amplicon sequences, not from cultured bacteria. The diameter of each circle is proportional to the relative abundance of the corresponding species. Species with no significant differences are highlighted in white, while other species are colored according to the group with the highest abundance.
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Figure 5. Changes in the fungal community in F. feruloides rhizosphere soil: (A,B) the Chao1 index (A); and Shannon index (B) were employed for fungi α-diversity. The Student’s t-test was used to compare groups. The p < 0.05 indicated a significant difference, and the p < 0.01 indicated a very substantial difference. (C) β-diversity of fungi revealed by CAP analysis. PERMANOVA (permutations = 999) was used to analyze microbial community structure dissimilarity. R2 obtained by PERMANOVA indicates the degree of interpretation of sample differences by different groups; that is, the ratio of group variance to total variance. A larger R2 indicates that grouping has a higher interpretation degree to the difference, and p < 0.05 means high reliability of the test. (D,E) Relative abundance of: main fungal phyla (D); and genera (E) under each treatment. For more than two groups, means were compared between treatments using the Kruskal–Wallis H test at a significance level of p < 0.05. * and ** indicate significance levels at p < 0.05 and p < 0.01, respectively.
Figure 5. Changes in the fungal community in F. feruloides rhizosphere soil: (A,B) the Chao1 index (A); and Shannon index (B) were employed for fungi α-diversity. The Student’s t-test was used to compare groups. The p < 0.05 indicated a significant difference, and the p < 0.01 indicated a very substantial difference. (C) β-diversity of fungi revealed by CAP analysis. PERMANOVA (permutations = 999) was used to analyze microbial community structure dissimilarity. R2 obtained by PERMANOVA indicates the degree of interpretation of sample differences by different groups; that is, the ratio of group variance to total variance. A larger R2 indicates that grouping has a higher interpretation degree to the difference, and p < 0.05 means high reliability of the test. (D,E) Relative abundance of: main fungal phyla (D); and genera (E) under each treatment. For more than two groups, means were compared between treatments using the Kruskal–Wallis H test at a significance level of p < 0.05. * and ** indicate significance levels at p < 0.05 and p < 0.01, respectively.
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Figure 6. Heatmap matrix obtained from Pearson correlation analysis, describing the associations between the chemical properties of F. feruloides rhizosphere soil and microbial community: (A) bacteria; (B) fungi. Red represents a positive correlation, while green represents a negative correlation. The darker the color, the stronger the correlation. *, **, and *** indicate significance levels at p < 0.05, p <  0.01 and p <  0.001, respectively. Total soil carbon (TSC), soil organic matter (SOM), total nitrogen (TN), ammonium nitrogen (NH4+), nitrate nitrogen (NO3−), total potassium (TK), available potassium (AK), total phosphorus (TP), available phosphorus (AP), and enzyme activities such as soil sucrase (S-SC), soil urease (S-UE), and soil alkaline phosphatase (S-AKP).
Figure 6. Heatmap matrix obtained from Pearson correlation analysis, describing the associations between the chemical properties of F. feruloides rhizosphere soil and microbial community: (A) bacteria; (B) fungi. Red represents a positive correlation, while green represents a negative correlation. The darker the color, the stronger the correlation. *, **, and *** indicate significance levels at p < 0.05, p <  0.01 and p <  0.001, respectively. Total soil carbon (TSC), soil organic matter (SOM), total nitrogen (TN), ammonium nitrogen (NH4+), nitrate nitrogen (NO3−), total potassium (TK), available potassium (AK), total phosphorus (TP), available phosphorus (AP), and enzyme activities such as soil sucrase (S-SC), soil urease (S-UE), and soil alkaline phosphatase (S-AKP).
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Figure 7. Effects of strain L5 and S16 on mycelial morphology (A); and growth rate (B) of P. tuoliensis cultured in PDA media at different concentrations of L5 and S16 fermentation broths. Effects of L5 and S16 on mycelial morphology (C); and the growth rate (D) of P. tuoliensis cultured in culture tubes with varying volumes of strain L5 and S16 suspensions. Arrows indicate optimal addition volumes for strains L5 and S16 to promote mycelial growth. The relevant differences between the groups were assessed by performing a one-way analysis of variance (ANOVA) at a significance level of p < 0.05. Each treatment group had five replicates, and each replicate had three technology replicates. The statistical significance of variance was denoted by using different letters in the graphs. (E) The molecular phylogenetic analysis by maximum likelihood method showing the phylogenetic relationships of L5 and S16 strains. The superscript T at the end of the strain stands for type strain. Bootstrap values are based on 1000-fold resampling and are displayed at the branching points.
Figure 7. Effects of strain L5 and S16 on mycelial morphology (A); and growth rate (B) of P. tuoliensis cultured in PDA media at different concentrations of L5 and S16 fermentation broths. Effects of L5 and S16 on mycelial morphology (C); and the growth rate (D) of P. tuoliensis cultured in culture tubes with varying volumes of strain L5 and S16 suspensions. Arrows indicate optimal addition volumes for strains L5 and S16 to promote mycelial growth. The relevant differences between the groups were assessed by performing a one-way analysis of variance (ANOVA) at a significance level of p < 0.05. Each treatment group had five replicates, and each replicate had three technology replicates. The statistical significance of variance was denoted by using different letters in the graphs. (E) The molecular phylogenetic analysis by maximum likelihood method showing the phylogenetic relationships of L5 and S16 strains. The superscript T at the end of the strain stands for type strain. Bootstrap values are based on 1000-fold resampling and are displayed at the branching points.
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MDPI and ACS Style

Luo, Y.; Liu, H.; Jia, W.; Yalimaimaiti, N.; Zhu, Q.; Jia, P.; Huang, Y.; Shi, W.; Sun, C.; Guan, J. Field Inoculation of Pleurotus tuoliensis in Natural Habitat Promotes Microbial Communities That Enhance Its Growth. Agronomy 2025, 15, 1136. https://doi.org/10.3390/agronomy15051136

AMA Style

Luo Y, Liu H, Jia W, Yalimaimaiti N, Zhu Q, Jia P, Huang Y, Shi W, Sun C, Guan J. Field Inoculation of Pleurotus tuoliensis in Natural Habitat Promotes Microbial Communities That Enhance Its Growth. Agronomy. 2025; 15(5):1136. https://doi.org/10.3390/agronomy15051136

Chicago/Turabian Style

Luo, Ying, Hanbing Liu, Wenjie Jia, Nuerziya Yalimaimaiti, Qi Zhu, Peisong Jia, Yilin Huang, Wenting Shi, Chunhua Sun, and Jianhua Guan. 2025. "Field Inoculation of Pleurotus tuoliensis in Natural Habitat Promotes Microbial Communities That Enhance Its Growth" Agronomy 15, no. 5: 1136. https://doi.org/10.3390/agronomy15051136

APA Style

Luo, Y., Liu, H., Jia, W., Yalimaimaiti, N., Zhu, Q., Jia, P., Huang, Y., Shi, W., Sun, C., & Guan, J. (2025). Field Inoculation of Pleurotus tuoliensis in Natural Habitat Promotes Microbial Communities That Enhance Its Growth. Agronomy, 15(5), 1136. https://doi.org/10.3390/agronomy15051136

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