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Composition and diversity of soil microbial communities change by introducing Phallus impudicus into a Gastrodia elata Bl.-based soil

BMC Microbiology volume 24, Article number: 204 (2024) Cite this article

Abstract

Background

The Gastrodia elata Bl. is an orchid, and its growth demands the presence of Armillaria species. The strong competitiveness of Armillaria species has always been a concern of major threat to other soil organisms, thus disrupting the equilibrium of soil biodiversity. Introducing other species to where G. elata was cultivated, could possibly alleviate the problems associated with the disequilibrium of soil microenvironment; however, their impacts on the soil microbial communities and the underlying mechanisms remain unclear. To reveal the changes of microbial groups associated with soil chemical properties responding to different cultivation species, the chemical property measurements coupled with the next-generation pyrosequencing analyses were applied with soil samples collected from fallow land, cultivation of G. elata and Phallus impudicus, respectively.

Results

The cultivation of G. elata induced significant increases (p < 0.05) in soil pH and NO3-N content compared with fallow land, whereas subsequent cultivation of P. impudicus reversed these G. elata-induced increases and was also found to significantly increase (p < 0.05) the content of soil NH4+-N and AP. The alpha diversities of soil microbial communities were significantly increased (p < 0.01) by cultivation of G. elata and P. impudicus as indicated with Chao1 estimator and Shannon index. The structure and composition of soil microbial communities differed responding to different cultivation species. In particular, the relative abundances of Bacillus, norank_o_Gaiellales, Mortierella and unclassified_k_Fungi were significantly increased (p < 0.05), while the abundances of potentially beneficial genera such as Acidibacter, Acidothermus, Cryptococcus, and Penicillium etc., were significantly decreased (p < 0.05) by cultivation of G. elata. It’s interesting to find that cultivation of P. impudicus increased the abundances of these genera that G. elata decreased before, which contributed to the difference of composition and structure. The results of CCA and heatmap indicated that the changes of soil microbial communities had strong correlations with soil nutrients. Specifically, among 28 genera presented, 50% and 42.9% demonstrated significant correlations with soil pH and NO3-N in response to cultivation of G. elata and P. impudicus.

Conclusions

Our findings suggested that the cultivation of P. impudicus might have potential benefits as result of affecting soil microorganisms coupled with changes in soil nutrient profile.

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Background

More than 80% extant land plant species establish associations with mycorrhizal fungi to exchange key nutrients [1]. Orchidaceae showing mycorrhizal association with fungi, are partially or fully dependent on them during their life-cycle. The rare herb, Gastrodia elata Bl., a member of the orchid family, is widespread in Asian countries and valued as both medicine and food [2]. Evidence showed that the G. elata has abandoned photosynthetic genes and lives in symbiotic association with Mycena spp. and Armillaria species, e.g. Armillaria gallica, or Armillaria mellea, from germination to maturity to obtain its required nutrition [3].

In China, G. elata has been used for over 2,000 years in the treatment of headache, vertigo, and hemiplegia [4, 5]. For a long time, wild populations were sufficient to meet the needs of individuals suffering from such diseases. However, overexploitation has resulted in a significant decline in wild populations [6, 7]. Considerable efforts in artificial cultivation of G. elata were made to meet the growing demand, and the domestication of the wild G. elata plant succeeded until the late 1960s [8].

Modern cultivation practices of G. elata are often conducted under monoculture, which usually fails due to replanting issues. Successful re-cultivation requires leaving the land uncultivated for more than 3 years. Replanting activities have caused major supply bottlenecks not only for G. elata but also many other medicinal herbs, such as Pinellia ternate [9] and American ginseng [10]. These issues are often associated with allelopathy, autotoxicity or changes in soil physicochemical properties and soil microflora [9,10,11]. It is commonly believed that the replanting activities of G. elata are related to its essential symbiotic Armillaria species [12]. Because the Armillaria members usually compete with other microbes associated with secondary metabolites [13, 14], which would cause the simplification or disequilibrium of the biodiversity in soil environment.

There are no doubts that soil microenvironment comprises of abundant and complex soil microorganisms [15]. Their diversity and composition play significant roles in maintaining soil functions through involvement in the turnover of soil nutrients [16, 17]. Soil micro-ecological imbalance is considered as one of the critical factors associated with replanting work [18]. Evidence indicated that 3 years of continuous cultivation of American ginseng decreased the soil bacterial diversity, while increasing the fungal diversity [10]. Meanwhile, others revealed that soil microbial diversity and structure can gain benefits from the rotation of wheat with Pinellia ternate [9]. Therefore, if crop rotation can recover the stability of the microbiome which is beneficial to agricultural production, rotation management could be an environmental-friendly, sustainable, and low-cost remediation technology with a high efficiency [19]. The key point is to identify and distinguish the effects of rotation management on soil micro-ecological equilibrium.

To better utilize the land resources and maintain the ecology of the forest environment, farmers use an edible fungus, namely Phallus impudicus to cultivate after G. elata. A previous study showed that P. impudicus is capable of decomposing substrates and have been evidenced to be able to allocate, uptake and store nutrients [20]. However, how the cultivation of P. impudicus will influence the soil microenvironment remains unknown. Studies focusing on the equilibrium of soil microorganisms and soil biochemical properties in cultivation of G. elata and P. impudicus are needed. Herein, this study provided an insight into the soil biochemical properties and soil microbial communities (including both bacterial and fungal communities) associated with cultivation of G. elata and P. impudicus. The soil microenvironment before and after cultivation of G. elata and P. impudicus would also be disclosed. In so doing, it is intended to understand the effect of different cultivation practices of saprotrophic fungi on the soil microenvironment, and to elucidate the efficacy of this strategy (Fig. S1).

Materials and methods

Description of the trial site and experimental design

The trial site is located at Dafang county (105°55′ E, 27°13′ N, 1500 m a.s.l.), Bijie, Guizhou province, one of the major cultivation areas of G. elata in China. The climate is subtropical humid monsoon with an average temperature of 12.5℃ and mean precipitation of 1, 100 mm. The trial began with G. elata cultivation in October 2016 and harvested in November 2017. This was followed by immediate cultivation of P. impudicus which was harvested in November 2018. The experiment consisted of three treatments including CK (soil initially collected before cultivation), GE (soil collected from the G. elata at its harvest time), and PI (soil collected from the P. impudicus at its harvest time). Three replicate samples from each treatment were collected at the harvest time. Detailed cultivating and sampling information as described below.

Cultivation of G. elata and soil sampling

The trial was performed in a single field site that was newly explored to ensure uniformity. Three plots adjacent to each other, which were regarded as three biological replications, were chosen to dig holes for cultivation of G. elata. The holes were dug with sizes of 80 cm × 30 cm × 30 cm (length × width × depth) for each. After that, soil samples on the bottom of the hole (referred to as CK treatment) were initially collected by using five points sampling method. To cultivate G. elata, the bottom of the hole was carpeted with pieces of chestnut wood (size: 15 cm × 8 cm) that were fully soaked with water and infected with A. gallica. Subsequently, both sides of each chestnut wood were placed with two pieces of juvenile tubers (G. elata seeds) of G. elata in uniform sizes. The juvenile tubers of G. elata were then covered with twigs and leaves infected with A. gallica to maintain humidity at the growing season. Finally, soil was filled back into the holes and covered with twigs or leaves [12]. Considering that the growth of G. elata depended on the symbiotic association with Armillaria, and Armillaria species obtain nutrients from wood and require no fertilizers from the environment, no fertilizers were used in this field trial. The trial site is located under forest, and the twigs or leaves were used to keep humidity for the growth of G. elata. In this way, artificial watering was only conducted when the temperature was over 30℃ for more than 1 week.

During harvesting, topsoil, leaves, and bulk soil were carefully removed, then soil adhering to the G. elata (referred to as GE treatment) was collected, sieved (2 mm) and thoroughly homogenized within one hole. There were three biological replications for GE treatments. Each soil sample was divided into three portions for measurements: one portion with approximately 1 g was immediately frozen in liquid nitrogen and kept at − 80℃ until DNA extraction; another portion was stored at 4℃ for the measurement of soil ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3-N), and the remaining soil was air-dried prior to determination of soil properties.

Cultivation of P. impudicus and soil sampling

The commercial strains used for P. impudicus cultivation were provided by Guizhou Wumeng Fungi Industry Co., Ltd. The strains originated from spores collected from the wild. After the purification of the cultures, the hyphae were maintained and subcultured on 2% (w/v) malt extract agar and kept at 23–25℃. The numbers of subculture were less than 5 generations, and the high-quality hyphae with strong and fast growth were selected as cultivation strains. Sixty to ninety days before field cultivation, the hyphae were inoculated to inoculum bags which contained sawdust (80%), wheat bran (7%), maizena (6%), soybean meal (4%), lime and gypsum (2%), sugar, magnesium sulfate, and potassium dihydrogen phosphate (1%) as the main nutrient materials. All these materials were mixed evenly, soaked with water to a final moisture of 60–70%, and subjected to autoclaving before inoculation. After inoculation, the inoculum bags were kept at 23℃ in a dark culturing chamber used for the cultivation of P. impudicus.

The P. impudicus was cultivated in the holes where the G. elata was harvested. To form a cultivation “bed” for P. impudicus, chestnut wood with small sizes (3 cm × 5 cm) were put in the middle of the gaps between the big chestnut wood cultivated for G. elata. Then, the inoculum bags filled with P. impudicus hypha were chopped into chunks with a diameter of 3∼5 cm. The placement distances of strain chunks were 5 cm, and the distance between rows was 10 cm. The following procedures were in accordance with cultivation of G. elata by filling the holes with soil, twigs or leaves. Watering only conducted when the temperature exceeded 30℃ for more than 1 weeks.

The harvest time was during October to November in the following year, when the “eggs” or fruit body of P. impudicus were come up out of the soil. To sample, the “eggs” or fruit body of P. impudicus were carefully removed from soil. Then, the soil surrounding the P. impudicus (referred to as PI treatment) was sampled and divided into 3 portions for measurements as described above.

Measurements of soil biochemical properties

Carbon dioxide (CO2)-free water was used to for pH measurement. After mixing 2 g air-dried soil in 10 mL deionized water and letting this mixture to settle for 30 min, we measured the pH of each sample using a PHS-25 pH meter (Mettler Toledo, Giessen, Germany). Soil total nitrogen (TN) content was measured using the Kjeldahl method. Ammonium-nitrogen (NH4+-N) and nitrate-nitrogen (NO3-N) were extracted with fresh soils using 2 M potassium chloride (1:10), and their concentrations were measured using a continuous-flow analyzer (San++, Skalar, Netherlands).

Available manganese, zinc, and copper were extracted using diethylene triamine pentaacetic acid-triethanolamine-calcium chloride (DTPA-TEA-CaCl2, pH 7.3), while exchangeable potassium, calcium, and magnesium were extracted using ammonium acetate (pH 7.0). Contents of available elements and exchangeable cations were measured using atomic absorption spectrophotometry (AA-6880, Shimadzu, Japan). Humus was extracted using a mixture of 0.1 M sodium pyrophosphate and 0.1 M sodium hydroxide, and humus content was determined using the potassium dichromate heating oxidation-volumetric method.

Soil DNA purification and Illumina MiSeq sequencing

Microbial DNA was extracted using the E.Z.N.A.® soil DNA Kit (Omega Bio-tech, Norcross, GA, U.S.). For the Illumina Miseq sequencing, the 16 S rRNA genes were amplified with primers 338 F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), and the ITS rRNA genes were amplified with primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′) with a 12 nt unique barcode at the 5′ end. The assays were performed in a 20 µL mixture containing 10 µL of SYBR® Premix Ex Taq (Tli RNaseH Plus, 2×, Takara Bio, Japan), 1 µL of forward primer and 1 µL of reverse primer at 10 mM, 7 µL Milli-Q water, and 1 µL of 10-fold diluted DNA. The initial denaturation was at 95 °C for 2 min, followed by 25 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 45 s, with a final extension at 72 °C for 10 min [21]. The PCR products were isolated and extracted from a 2% agarose gel, then purified (TruSeqTM DNA Sample Prep Kit). Further, the purified amplicons were pooled in equimolar and paired-end sequenced (2 × 300) on an Illumina MiSeq platform (Illumina, San Diego, USA) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

Processing of illumina MiSeq sequencing raw data

The QIIME software package (version 1.9.1) was used to analyze the Illumina MiSeq sequencing raw data [22]. The reads were quality trimmed by discarding quality scores less than 20 and sequence lengths less than 400 bp. In total, 193, 498, 292 high quality reads for 16 S rRNA genes and 183, 686, 532 high quality reads for ITS rRNA genes were obtained. After preprocessing all the reads, the numbers of sequences among different samples ranged from 30, 414 to 42, 466 in 16 S rRNA genes and 49, 543 to 62, 089 in ITS rRNA genes. We randomly selected sequences based on the minimum reads for all the samples before further analysis. The operational taxonomic units (OTUs) were defined at 97% similarity level using Usearch (version 11 http://drive5.com/uparse/) with the remaining and unique sequences. The taxonomic identity of the phylotypes was determined by the Ribosomal Database Project (RDP) Classifier (version 2.13 http://sourceforge.net/projects/rdpclassifier/) at a confidence threshold of 70%.

Analysis of bioinformatics data

β-diversity and Venn analysis

Based on the calculated Bray-Curtis distance, principal coordinate analysis (PCoA) and hierarchical clustering analysis (HCA) were performed to investigate the variation of microbial community structure among treatments. To assess the difference in the microbial community composition variations, permutational multivariate ANOVA (PERMANOVA) was conducted using the anosim function in the R software package vegan (version 2.6-4).

The Venn diagrams were constructed to visualize shared and unique OTUs among samples. The core OTUs existing in all soil samples were selected and visualized as microbial community pie charts on the platform Majorbio (www.majorbio.com).

Bipartite network analysis

Based on the pairwise spearman method and correlation coefficient with threshold value r ≥ 0.5, the bipartite network analysis on genus level of bacterial and fungal were calculated respectively at p < 0.05 significant level. Then the network was visualized by Cytoscape software (version 3.7.1) by using the treatments as source nodes and the genera as target nodes [23], with edges corresponding to positive associations of genera under different cultivation management.

Canonical correspondence analysis

A mantel test was conducted to test the significance of the effect of the soil physicochemical properties [pH, SOC (soil organic carbon), TN, NH4+-N, NO3-N, AP (available phosphorus), AK (available potassium), and C/N (ratio of soil carbon to nitrogen)] on the bacterial and fungal community composition with a Euclidean distance dissimilarity matrix. The parameters identified as significant (p ≤ 0.05) in the mantel test were used to perform a canonical correspondence analysis (CCA) to assess the major environmental factors that determined bacterial and fungal community composition at the OTU level. Both mantel test and CCA analysis were performed using the vegan package (version 2.6-4) in R software (version 4.1.2) for Windows [24].

Soil bacterial and fungal composition and heatmap

The significance in relative abundance at the genus level among different soil samples was tested using the one-way analysis of variance (one-way ANOVA) and Tukey-Kramer test at a 0.05 significant level. Dominant genera with significant changes were presented in figures. Subsequently, the association of dominant genera with significant changes integrated with soil chemical properties were analyzed by performing a heatmap. The heatmap was constructed with the Psych, Pheatmap, and Reshape2 packages in R software (version 4.1.2) for Windows [24].

Statistical analysis

We performed one-way ANOVA to assess the significance of differences in α diversity of soil bacterial and fungal communities, soil biochemistry, available elements, exchangeable cations, and humus variations among different soil samples. Differences associated with p < 0.05 based on Duncan’s multiple range test were defined as significant. All analyses were performed using IBM SPSS Statistics 26.0 (IBM, Chicago, IL, USA).

Results

Cultivations of G. elata and P. impudicus affected soil biochemical properties

All soil samples, including the control, were acidic (Table 1), the CK (soil collected from fallow field) demonstrating the lowest pH value. The cultivation resulted in the increase in soil pH value in GE (soil adhering to the G. elata) and PI (soil surrounding the P. impudicus) treatments. A similar trend was also found in soil available elements and exchangeable cations, such as available manganese and copper, soil exchangeable potassium and magnesium (Fig. S2). There was no significant (p = 0.209) difference in NH4+-N concentrations between CK and GE. The highest NH4+-N concentrations was observed in PI sample. However, GE had significantly high NO3-N concentration than CK and PI samples did (p < 0.05). Total N content did not differ significantly among CK, GE and PI (p = 0.171, Table 1). The PI treatment resulted in the highest available phosphorus (AP), and significantly higher than that in CK treatment (p < 0.05), while there was no significant difference between CK and GE in AP content (p = 0.084).

Table 1 Changes of soil biochemical properties in response to different cultivation management systems
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The different letters within a column represent significant differences among the treatments (p ≤ 0.05), determined by one-way ANOVA and Duncan’s multiple range test. The data are the means of 3 replicates ± standard error. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively.

Soil bacterial and fungal α- and β-diversities responding to cultivation of G. elata and P. impudicus

The Chao 1 and Shannon indexes of bacterial and fungal communities were higher in GE and PI, compared to that in CK (p < 0.01, Table 2). There was no significant difference in the richness of microbial community between GE and PI as indicated by Chao 1 index (p = 0.707 for bacteria, p = 0.056 for fungi). In contrast, the Shannon index of bacterial and fungal communities in GE was significantly higher than that in CK and PI (p < 0.05). These results implied that either cultivation of G. elata or P. impudicus would greatly influence the diversity of soil bacterial and fungal communities.

Table 2 Soil microbial community diversity indices in different soil samples
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The different letters within a column represent significant differences among the treatments (p ≤ 0.05), determined by one-way ANOVA and Duncan’s multiple range test. The data are the means of 3 replicates ± standard error. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively.

Overall, the Bray-Curtis PCoA analysis showed that the bacterial and fungal community structure in GE and PI were greatly separated from CK (Fig. 1a, b), which indicated that cultivation of G. elata and P. impudicus had significant impacts on soil microbial community structure (p < 0.05). The tree diagram showed that group of CK and PI joined together and shared long distance with GE, and HCA result indicated that the taxa of CK and PI were more similar with each other in bacterial community (the HCA distance for CK and PI was 0.13, while that value for CK, PI and GE was 0.17, Fig. 1c) and more abundant than that in GE. Whereas, the tree diagram and HCA results of fungal community indicated that group or taxa in PI and GE were more similar than those in CK (the HCA was 0.12, Fig. 1d). Specifically, some taxa like unclassified_f_Russulaccac were abundantly present while others like Sclerodema, unclassified_f_Thelephoraceae were lost or less abundant in CK when compared with GE and PI.

Fig. 1
figure 1

Principal coordinate analysis (PCoA) on OTU level and hierarchical clustering analysis (HCA) on genus level, both were calculated based on the Bray-Curtis distance. Panels a, and b, the PCoA analysis of bacterial and fungal communities; panels c, and d, the HCA analysis of bacterial and fungal communities. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively

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The shared bacterial OTU numbers within CK and PI were 325 (15.34%), within GE and PI were 329 (15.53%), while within CK and GE were 62 (2.93%) (Fig. 2a). The shared OTU numbers within CK, GE and PI were 746 (35.22%) in which the others comprised 70.90% followed by OTU 328 (5.9%), OTU 478 (5.05%), and OTU 1894 (3.85%) (Fig. 2b). Moreover, the shared fungal OTU numbers within CK and PI, GE and PI, CK and GE were 252 (8.73%), 302 (10.46%), and 81 (2.81%) respectively (Fig. 2c). The shared OTU numbers within CK, GE and PI were 262 (9.08%) in which OTU 1211, OTU 1426, and OTU 1293 took up 17.49%, 10.8%, and 6.17% which occupied the first three compositions besides the others (34.34%) (Fig. 2d). Moreover, there are more peculiar OTU numbers in GE and PI compared to that in CK (Fig. 2a, c), especially in the soil fungal community.

Fig. 2
figure 2

Venn diagram and pie charts of different soil samples. Panels a, and b, the Venn diagrams and pie charts of bacterial community on OTU level; panels c, and d, the Venn diagrams and pie charts of fungal community on OTU level. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively

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The networks of soil bacterial and fungal communities became more complex in response to cultivation ofG. elata and P. impudicus

The bipartite networks of bacterial and fungal communities, respectively, were constructed to visualize the associations between genera and the different planting strategies or cultivation management (Fig. 3). The closeness centralities of CK, GE, and PI in bacteria were 0.57, 0.83, and 0.71 (Fig. 3a), and those in fungi were 0.49, 0.71, and 0.61, respectively (Fig. 3b).

Fig. 3
figure 3

Co-occurrence analysis of bacterial (a) and fungal (b) communities under different cultivation management systems

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Of the presented genera, 44.4% were most strongly associated with only one system in bacteria (Fig. 3a), and 53.8% were most strongly associated with only one system in fungi (Fig. 3b), confirming the basic distinctness of these genera in all managements. Approximately 32.1% of the significant genera were most strongly driven by GE, whereas another 7.0% were associated with PI in bacterial network. In fungal network, 27.9% of the significant genera were most strongly driven by GE, while 16.3% were associated with PI. There were 19.0% and 25% of the significant genera that were associated with two cross-combinations (genera nodes associated with two treatments) in bacterial and fungal networks, while the three cross-combinations (genera nodes associated with three treatments) accounted for 22.5% and 21.2% in bacterial and fungal networks, respectively.

Effect of cultivation of G. elata and P. impudicus on soil bacterial and fungal compositions

For bacterial genera (Fig. 4a), the relative abundances of Bacillus and norank_o_Gaiellales were significantly increased (p < 0.05), while the relative abundances of Acidibacter, Acidothermus, norank_c__JG37-AG-4, norank_f__Acidobacteriaceae__Subgroup_1_, norank_f__DA111, norank_f__ODP1230B8.23, and norank_f__YNPFFP1 were significantly decreased in GE compared to CK (p < 0.05). Interestingly, PI helped to increase the relative abundances of genera which GE decreased before. Alternatively, the relative abundances of some genera, like Bryobacter, Burkholderia-Paraburkholderia, Candidatus_Solicaber, and Roseiarcus showed no significant difference between GE and CK. However, compared with GE and CK, the relative abundances of these genera in PI were significantly increased (p < 0.05).

Fig. 4
figure 4

Relative abundances of bacterial (a) and fungal (b) genera under different cultivation management systems. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively. Lowercases a, b, and c in figures indicate significant differences among different soils (CK, GE and PI), determined by one-way ANOVA and Duncan’s multiple range test (p < 0.05)

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As for fungal genera (Fig. 4b), the relative abundances of Clavulinopsis, Russula, Sebacina, unclassified_f_Russulaceae, and unclassified_p_Ascomycota were significantly decreased in GE and PI compared to CK (p < 0.05). However, the relative abundance of Mortierella and unclassified_k_Fungi were greatly increased in GE compared with CK. No significant differences were found in relative abundances of Chaetosphaeria, Chloridium, unclassified_c_Leotiomycetes, and unclassified_f_Russulaceae between GE and CK, however, their abundances were greatly increased in PI samples (p < 0.05).

Association of bacterial and fungal communities with soil biochemical factors

The canonical correlation analysis (CCA) was performed to reveal the driving factors for developing soil bacterial and fungal communities on the genus level (Fig. 5). The result showed that the changes in bacterial communities were significantly correlated with soil pH and NO3-N (p < 0.05, Fig. 5a), while the fungal communities were significantly affected by soil factors such as pH, NO3-N, NH4+-N, SOC, and AK (p < 0.05, Fig. 5b). The first axis in the CCA results explained 30.6% and 17.0% of the bacterial and fungal community variations, respectively, which suggested a remarkable restrictive rate of CCA1 to microbial community and soil properties. The results of CCA indicated that soil properties, especially soil pH value might impose significant impacts on soil bacterial and fungal communities in G. elata or P. impudicus cultivation.

Fig. 5
figure 5

Canonical correlation analysis (CCA) of environmental characteristics (arrows) and MiSeq data (symbols) for (a) soil bacterial communities and (b) soil fungal communities under different cultivation management systems. Abbreviation: CK, GE, and PI represent soil samples collected from fallow field (control), soil adhering to the G. elata, and soil surrounding the P. impudicus, respectively

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To further analyze the correlation between the soil physicochemical properties and the relative abundance of soil microorganisms, Pearson analysis correlation was conducted based on a heatmap (Fig. 6). In general, the C/N ratio is an important index for indicating the nutritional balance, but only 6 taxa had significant correlations with it. Overall, the pH and NO3-N had strong correlations with the bacteria and fungi detected. Among all these 28 genera, 50% and 42.9% demonstrated significant correlations with pH and NO3-N, respectively. Microelements such as exchangeable magnesium and calcium, available zinc, and manganese also played an important role in controlling the relative abundances of microorganisms. They generally showed strong correlations with 13–15 genera, which accounted for 46.4–53.6% of all the genera provided. In addition, the carbon related soil factors such as SOC, C content in humin and humus, showed a strong positive correlation with the genera like Rhizomicrobium, Burkholderia-Paraburkholderia, unclassified_f_Thelephoraceae, Trichoderma, Cryptococcus, Acidibacter, Chloridium, unclassified_c_Leotiomycetes, Candidatus_Solibacter, Roseiarcus, Bryobacter, Chaetosphaeria, and Penicillium. These findings suggest that chemical properties such as soil pH, NO3-N, or soil C storage which would be regulated by G. elata or P. impudicus cultivations, may play a crucial role in regulating the relative abundance of soil microorganisms.

Fig. 6
figure 6

Heatmap based on Pearson correlation analysis between the physicochemical properties and the genera (including both bacteria and fungi) under different cultivation management systems. Significant differences (p-FDR < 0.05) to planting strategies indicated by “*”

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Discussion

Monoculture management has substantially reduced soil biodiversity as well as agroecosystem functions not only in agricultural crops but also medicinal herbs. Proper agricultural management practices, such as crop rotation, may promote soil biodiversity [25]. Unlike plants that can influence soil microbial activity and diversity through root exudations, it is more likely that the saprotrophic fungi like Armillaria species and P. impudicus influence their microenvironment through secretions and suppress the growth of some fungi by competing with niche status in the soil.

The present study found that cultivation of either G. elata or P. impudicus would result in the absence of fungi unclassified_f_Russulaccac (Fig. 1d), which is different from previous studies reporting that farming induced higher relative abundances of saprotrophic fungi [26]. Being as saprotrophic fungi, it is possible that the nutrients required by A. gallica (the symbiont of G. elata) and P. impudicus were partially in common with unclassified_f_Russulaccac, and that the strong inhibiting tendency of Armillaria and Phallus members restrained the growth of saprotrophic fungi like unclassified_f_Russulaccac and others [27]. Additionally, P. impudicus impelled the soil bacterial taxa classification to be more similar with that in fallow land, while closely associating with fungal taxa in G. elata cultivation (Fig. 1b, d). These findings suggested that P. impudicus contributed and shaped the taxonomic distribution patterns of different types of microorganisms in this trial.

In addition, the relative abundance of some potentially beneficial organisms, such as Candidatus_Solibacter and Penicillium, significantly increased in soil surrounding the P. impudicus compared with that in fallow land and soil adhering to the G. elata (Fig. 4). The members of Candidatus_Solibacter were reported to be related to the degradation of potential soil allelochemicals [28]. Although some species of Penicillium can cause crop diseases, most of them have been discovered as beneficial fungi which can control plant diseases by inhibiting the growth of pathogenic organisms [29]. The relative abundance of other microbes such as Trichoderma, showed the same trend with Candidatus_Solibacter and Penicillium, implying the sensitivity of these potentially beneficial fungi to tillage practices, especially the cultivation of P. impudicus. This indicated that the P. impudicus may recruit potentially beneficial genera to adapt to the environment. Results of these findings could have important implications for our understanding of the role of appropriate targets in manipulating beneficial organisms to improve the environment in artificial cultivation of G. elata.

There is a consensus that cultivation of G. elata does not need fertilizers and that its nutrient requirements are fulfilled by its symbiont fungi, Armillaria, which are well-known as wood decomposers [30]. If this was the case, how could it happen that some soil biochemical properties changed with cultivation of G. elata and P. impudicus? The possible explanations for these observations in this study may be in partial attributed to some soil functional genera that were activated by simple compounds degraded by enzymes that were secreted by Armillaria members [31, 32] or the direct secretions of A. gallica.

For instance, the relative abundance of Bacillus significantly increased in the cultivation of G. elata, and sequentially decreased in the cultivation of P. impudicus (Fig. 4), which was in accordance with the changes of NO3-N and microelements (Table 1 & Fig. S2). The response of Bacillus in our study coincided with a previous study which indicated that the rhizomes of G. elata may specifically attract high nitrogen-dependant bacteria such as Bacillus and others [12]. It has been reported that elements such as potassium, zinc, magnesium, and calcium are easily accessible to soil microorganisms and are prone to change the activity and composition of the microbial community [33]. The genus Bacillus is capable of producing antibiotic substances and certain species have the capacity to fix nitrogen [34]. It is likely that the microelements released by A. gallica through secretions presumably induced the enrichment of Bacillus in cultivation of G. elata [35], then the soil nitrogen was solubilized into available form by the enriched Bacillus members. Evidence is also provided by the heatmap which revealed that elements such as NH3-N, available zinc, exchangeable magnesium, and calcium were in strong positive correlation with Bacillus (Fig. 6). If so, these results seem to suggest that the distribution of this genus and others like norank_o_Gaiellales, unclassified_k_Fungi, and Mortierella are in a particular trophic niche, and will rather be influenced and characterized by cultivation systems [36].

Additionally, numerous studies have demonstrated the ability of Armillaria species, as well as P. impudicus in accumulating available nutrients such as phosphorus from soil [37, 38], even though they are all saprotrophic wood-decaying Basidiomycotas. Therefore, the redistribution of available nutrients to soil by Armillaria and P. impudicus species may also possibly contribute to changes in the soil’s biochemical properties.

According to previous studies, soil biochemical properties, notably pH, are considered as major drivers of determining the soil bacterial diversity and composition [39]. Examining the effects of specific soil attributes, for instance the soil pH, on microbial taxa should help to reveal what drives their population changes [40]. The cultivation of P. impudicus decreased soil pH, which cultivation of G. elata increased before (Table 1). The observed increase of pH in soil associated with G. elata might be caused by the abundance of alkaline rhizomorph exudates released by A. gallica [35]. The CCA analysis suggested that soil pH integrated with soil nutrition had a strong correlation with microbial community changes in the cultivation of G. elata (Fig. 5). The truth is, the cultivation of G. elata and P. impudicus affected the abundances of several genera across several phyla, in which most of the genera were also associated with soil physicochemical properties, especially some soil taxa that were more sensitive to soil pH variations. For example, Acidothermus, an acidophilic genus, whose abundance initially decreased with the increase of pH in G. elata cultivation, then increased with the reduction of pH under cultivation of P. impudicus (Fig. 4a; Table 1), was also found to have strong correlation with soil pH (Fig. 6). This indicated that cultivation of P. impudicus helped to improve the environment for acidophilic genera in soil. In other words, the cultivation of P. impudicus can help maintain soil microbial composition by recovering soil nutrient equilibrium, which is also closely related to other soil microorganisms’ activities [41].

According to previous studies, Armillaria members normally assimilate soil carbon and significantly reduced carbon content in humus, especially levels of fulvic acid to obtain its growth materials [42]. However, P. impudicus was reported to have the ability to producing dense cross-linked networks of thick hyphae, and bonding soil particles into a coacervate [43]. Therefore, in our study, cultivation of P. impudicus was observed to increase the ratio of humic to fulvic acid, a measure of humification (Table S1). This implied that soils where P. impudicus was applied after G. elata had greater carbon storage capacity than soils where only G. elata was cultivated. It is commonly accepted that high C storage is vital for soil health and long-term ecosystem sustainability [44]. Considering that G. elata is normally cultivated in acidic soils [45, 46], and the A. gallica rhizomorphs typically grow well at a depth of 30 cm in soil with pH 4.3–4.6 [47], soil microenvironment re-optimized by cultivation of P. impudicus might become preferable for the growth of G. elata and its symbiont A. gallica.

In this study, several genera showed significantly higher relative abundance in soil associated with cultivation of P. impudicus (Fig. 4), which was consistent with the changes in soil humus composition and properties among different treatments (Fig. 6, Table S1). This indicated that, in addition to soil pH value, other soil parameters such as soil C sources, also contributed to the microbial community composition. The CCA result of fungal community strongly resembled and confirmed this observation (Fig. 5b). Similar observations were also made by previous authors who emphasized that SOC was essential in explaining the differences in the soil bacterial community structures in tropical agricultural soil [48]. Overall, the shift in patterns of soil microbial community composition and structure in soil associated with cultivation of G. elata and P. impudicus were related to soil physicochemical changes, which were mediated by the means of cultivation.

However, to conduct a comprehensive assessment on the effect of introducing P. impudicus into this G. elata-based soil system, it is necessary to conduct a more rational and long-term trial in future research. For example, addressing G. elata monoculture in parallel with P. impudicus cultivation, as well as cultivation systems sustained until the third year. Furthermore, the assessment needs to be extended to measure the secretions of A. gallica or P. impudicus at the harvesting period. This optimization and promotion of trial design will make it possible to assess the inferences of fungi secretions imposed on the biodiversity, which is closely related to the achievement of truly sustainable agriculture.

Conclusion

Changes in the soil biochemical properties and soil microbial communities before and after cultivation of G. elata and P. impudicus were assessed and discussed in this study. The introduction of P. impudicus in the G. elata based soil, had an implication in improving soil quality by reversing G. elata-induced changes in soil pH, nutrient levels, and humus composition. The composition and diversity of soil microbial communities were greatly altered in response to the cultivation of G. elata and P. impudicus, especially some genera that have potentially beneficial functions in soil nutrient cycling, such as Acidibacter, Acidothermus, Cryptococcus, and Penicillium. By analyzing the correlation of soil microbial communities and chemical properties, a strong correlation of potentially beneficial genera with the soil pH and nutrients contents was observed. These results imply that cultivation of P. impudicus, compared to cultivation of G. elata, was likely to have a beneficial effect on plant health in the following growing season due to the rebalanced soil biochemical properties and the corresponding response in the soil microbial communities.

Data availability

Raw data of 16 S rRNA and ITS rRNA amplicon sequences supporting the findings of the present study are available in the Sequence Read Archive of NCBI under Bio Project accession PRJNA905858 and PRJNA905861, respectively.

References

  1. Feijen FAA, Vos RA, Nuytinck J, Merckx VSFT. Evolutionary dynamics of mycorrhizal symbiosis in land plant diversification. Sci Rep. 2018;8:10698. https://doi.org/10.1038/s41598-018-28920-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Chen L, Wang YC, Qin LY, He HY, Yu XL, Yang MZ, et al. Dynamics of fungal communities during Gastrodia elata growth. BMC Microbiol. 2019;19:158. https://doi.org/10.1186/s12866-019-1501-z.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Yuan Y, Jin XH, Liu J, Zhao X, Zhou JH, Wang X, et al. The Gastrodia elata genome provides insights into plant adaptation to heterotrophy. Nat Commun. 2018;9(1):1615. https://doi.org/10.1038/s41467-018-03423-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bensky D, Gamble A. Chinese herbal medicine: materia medica. In: revised edition, Seattle; 1993. pp. 971–974.

  5. Jung T, Suh S, Lee H, Kim I, Kim H, Yoo H, et al. Protective effects of several components of Gastrodia elata on lipid peroxidation in gerbil brain homogenates. Phytother Res. 2007;21(10):960–4. https://doi.org/10.1002/ptr.2193.

    Article  PubMed  Google Scholar 

  6. Liu H, Luo Y, Liu H. Studies of mycorrhizal fungi of Chinese orchids and their role in orchid conservation in China-A Review. Bot Rev. 2010;76:241–62. https://doi.org/10.1007/s12229-010-9045-9.

    Article  Google Scholar 

  7. Howes M, Rui F, Houghton PJ. Effect of Chinese herbal medicine on alzheimer’s disease. Int Rev Neurobiol. 2017;35:29–56. https://doi.org/10.1016/bs.irn.2017.02.003.

    Article  Google Scholar 

  8. Xu JT, Guo SX. Retrospect on the research of the cultivation of Gastrodia elata bl, a rare traditional Chinese medicine. Chin Med J. 2000;113(8):686–92.

    CAS  PubMed  Google Scholar 

  9. He ZG, Mao RJ, Dong JE, Liang ZS, Zhang HH, Liu L. Remediation of deterioration in microbial structure in continuous pinellia ternata cropping soil by crop rotation. Can J Microbiol. 2018;65(4). https://doi.org/10.1139/cjm-2018-0409.

  10. Dong LL, Xu J, Zhang LJ, Yang J, Liao BS, Li XW, et al. High-throughput sequencing technology reveals that continuous cropping of American ginseng results in changes in the microbial community in arable soil. Chin Med. 2017;12(1):18. https://doi.org/10.1186/s13020-017-0139-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Lü L, Wu Q. Mitigation of replant disease by mycorrhization in horticultural plants: a review. Folia Hortic. 2018;30(2):269–82. https://doi.org/10.2478/fhort-2018-0023.

    Article  Google Scholar 

  12. Yuan QS, Xu J, Jiang WK, Ou XH, Wang YH, Guo LP, et al. Insight to shape of soil microbiome during the ternary cropping system of Gastradia Elata. BMC Microbiol. 2020;20(1). https://doi.org/10.1186/s12866-020-01790-y.

  13. Sipos G, Prasanna AN, Walter MC, O’Connor E, Bálint B, Krizsán K, et al. Genome expansion and lineage-specific genetic innovations in the forest pathogenic fungi Armillaria. Nat Ecol Evol. 2017;1:1931–41. https://doi.org/10.1038/s41559-017-0347-8.

    Article  PubMed  Google Scholar 

  14. Heinzelmann R, Dutech C, Tsykun Labbé F, Soularue JP, Prospero S. Latest advances and future perspectives in Armillaria research. Can J Plant Pathol. 2019;41:1–23. https://doi.org/10.1080/07060661.2018.1558284.

    Article  Google Scholar 

  15. Torsvik V, Øvreås L. Microbial diversity and function in soil: from genes to ecosystems. Curr Opin Microbiol. 2002;5(3):240–5. https://doi.org/10.1016/S1369-5274(02)00324-7.

    Article  CAS  PubMed  Google Scholar 

  16. Marschner P. Plant-microbe interactions in the Rhizosphere and Nutrient Cycling. In: Marschner P, Rengel Z, editors. Nutrient Cycling in Terrestrial ecosystems. Berlin, Heidelberg: Springer Berlin Heidelberg; 2007. pp. 159–82. https://doi.org/10.1007/978-3-540-68027-7_6.

    Chapter  Google Scholar 

  17. Fernandez AL, Sheaffer CC, Wyse DL, Staley C, Sadowsky MJ. Associations between soil bacterial community structure and nutrient cycling functions in long-term organic farm soils following cover crop and organic fertilizer amendment. Sci Total Environ. 2016;566–567:949–59. https://doi.org/10.1016/j.scitotenv.2016.05.073.

    Article  CAS  PubMed  Google Scholar 

  18. He H, Zhang SY, Shen WQ, Zhu W, Noor I, Liu JW, et al. Benzoic acid plays a part in rhizosphere microbial composition of peach seedlings grown in replanted soil. Rhizosphere. 2021;19:100364. https://doi.org/10.1016/j.rhisph.2021.100364.

    Article  Google Scholar 

  19. Li Y, Li LJ, Sui P, Liu XF, Zhang TT, Li XT. Crop rotation to diversify the soil microbiome in the semi-arid area of Inner Mongolia, China. Arch Agron Soil Sci. 2023;69:1161–76. https://doi.org/10.1080/03650340.2022.2070159.

    Article  CAS  Google Scholar 

  20. Wells JM, Boddy L. Wood decay, and phosphorus and fungal biomass allocation, in mycelial cord systems. New Phytol. 1990;116:285–95. https://doi.org/10.1111/j.1469-8137.1990.tb04716.x.

    Article  CAS  Google Scholar 

  21. Wang YH, Yu ZH, Li YS, Wang GH, Liu JJ, Liu JD, et al. Microbial association with the dynamics of particulate organic carbon in response to the amendment of elevated CO2-derived wheat residue into a Mollisol. Sci Total Environ. 2017;607–608:972–81. https://doi.org/10.1016/j.scitotenv.2017.07.087.

    Article  CAS  PubMed  Google Scholar 

  22. Caporaso JG, Bittinger K, Bushman FD, Desantis TZ, Andersen GL, Knight R. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinform. 2010;26:266–7. https://doi.org/10.1093/bioinformatics/btp636.

    Article  CAS  Google Scholar 

  23. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. https://doi.org/10.1101/gr.1239303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. R Development Core Team. R: a Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2010.

    Google Scholar 

  25. Zhang K, Maltais-Landry G, Liao HL. How soil biota regulate C cycling and soil C pools in diversified crop rotations. Soil Biol Biochem. 2021;156(1). https://doi.org/10.1016/j.soilbio.2021.108219.

  26. Cai YS, Zhang JB, Zhong LW, Lu SL, Huang LP, Yan Y, et al. Response of the fungal diversity to different tillage modes in the farming areas of karst peak-cluster depressions, southwest China. Acta Ecol Sin. 2021;41(12):4886–99. https://doi.org/10.5846/stxb202001150119.

    Article  CAS  Google Scholar 

  27. Collins C, Keane TM, Turner DJ, O’Keeffe G, Fitzpatrick DA, Doyle S. Genomic and proteomic dissection of the Ubiquitous Plant Pathogen, Armillaria mellea: toward a new infection Model System. J Proteome Res. 2013;12:2552–70. https://doi.org/10.1021/pr301131t.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Wang HW, Sun K, Guan YX, Qiu MH, Zhang L, Dai CC. Fungal endophyte Phomopsis liquid ambari biodegrades soil resveratrol: a potential allelochemical in peanut monocropping systems. J Sci Food Agric. 2019;99:5899–909. https://doi.org/10.1002/jsfa.9865.

    Article  CAS  PubMed  Google Scholar 

  29. Van Wees SC, Van der Ent S, Pieterse CM. Plant immune responses triggered by beneficial microbes. Curr Opin Plant Biol. 2008;11:443–8. https://doi.org/10.1016/j.pbi.2008.05.005.

    Article  CAS  PubMed  Google Scholar 

  30. Schmidt O. Wood and Tree Fungi: Biology, damage, Protection, and use. Berlin Heidelberg: Springer-; 2006. https://doi.org/10.1007/3-540-32139-X.

    Book  Google Scholar 

  31. Purahong W, Arnstadt T, Kahl T, Bauhus J, Kellner H, Hofrichter M, et al. Are correlations between deadwood fungal community structure, wood physicochemical properties and lignin-modifying enzymes stable across different geographical regions? Fungal Ecol. 2016;22:98–105. https://doi.org/10.1016/j.funeco.2016.01.002.

    Article  Google Scholar 

  32. Yafetto L. The structure of mycelial cords and rhizomorphs of fungi: a mini-review. Mycosphere. 2018;9(5):984–98. https://doi.org/10.5943/mycosphere/9/5/3.

    Article  Google Scholar 

  33. Bais HP, Weir TL, Perry LG, Gilroy S, Vivanco JM. The role of root exudates in rhizosphere interactions with plants and other organisms. Annu Rev Plant Biol. 2006;57:233–66. https://doi.org/10.1146/annurev.arplant.57.032905.105159.

    Article  CAS  PubMed  Google Scholar 

  34. Aloo BN, Makumba BA, Mbega ER. (2019) The potential of Bacilli rhizobacteria for sustainable crop production and environmental sustainability. Microb Res. 2019;219:26–39. https://doi.org/10.1016/j.micres.2018.10.011.

  35. Mallett KI, Colotelo N. Rhizomorph exudate of Armillaria mellea. Can J Microbiol. 1984;30(10):1247–52. https://doi.org/10.1139/m84-197.

    Article  CAS  Google Scholar 

  36. Sielaff CA, Upton RN, Hofmockel KS, Xu X, Polley HW, Wilsey BJ. Microbial community structure and functions differ between native and novel (exotic-dominated) grassland ecosystems in an 8-year experiment. Plant Soil. 2018;432(1–2):359–72. https://doi.org/10.1007/s11104-018-3796-1.

    Article  CAS  Google Scholar 

  37. Morrison DJ. Ion uptake by rhizomorphs of Armillaria mellea. Can J Bot. 1975;53:48–51. https://doi.org/10.1139/b75-006.

    Article  CAS  Google Scholar 

  38. Wells JM, Hughes C, Boddy L. The fate of soil-derived phosphorus in mycelial cord systems of Phanerochaete velutina and Phallus Impudicus. New Phytol. 1990;114:595–606. https://doi.org/10.1111/j.1469-8137.1990.tb00430.x.

    Article  CAS  Google Scholar 

  39. Liu JJ, Sui YY, Yu ZH, Shi Y, Chu HY, Jin J, et al. High throughput sequencing analysis of biogeographical distribution of bacterial communities in the black soils of northeast China. Soil Biol Biochem. 2014;70:113–22. https://doi.org/10.1016/j.soilbio.2013.12.014.

    Article  CAS  Google Scholar 

  40. Yin C, Jones KL, Peterson DE, Garrett KA, Hulbert SH, Paulitz TC. Members of soil bacterial communities sensitive to tillage and crop rotation. Soil Biol Biochem. 2010;42:2111–8. https://doi.org/10.1016/j.soilbio.2010.08.006.

    Article  CAS  Google Scholar 

  41. Cao P, Wang G, Wei XM, Chen SL, Han JP. How to improve CHMs quality: enlighten from CHMs ecological cultivation. Chin Herb Med. 2021;13(3):301–12. https://doi.org/10.1016/j.chmed.2021.04.014.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Redfern DB. Growth and behaviour of Armillaria mellea rhizomorphs in soil. Trans Br Mycol Soc. 1973;61(3):569–IN16. https://doi.org/10.1016/S0007-1536(73)80126-3.

    Article  Google Scholar 

  43. Obara B, Grau V, Fricker MD. A bioimage informatics approach to automatically extract complex fungal networks. Bioinform. 2012;28(18):2374–81. https://doi.org/10.1093/bioinformatics/bts364.

    Article  CAS  Google Scholar 

  44. Jha P, Lakaria BL, Meena BP, Biswas AK, Patra AK. Plans and policies for Soil Carbon Storage. In: Meena RS, Rao CS, Kumar A, editors. Plans and policies for Soil Organic Carbon Management in Agriculture. Singapore: Springer Nature Singapore; 2022. pp. 123–40. https://doi.org/10.1007/978-981-19-6179-3_5.

    Chapter  Google Scholar 

  45. Doty JE, Cheo PC. Light inhibition of thallus growth of Armillaria mellea. Phytopathol. 1974;64:763–4. https://doi.org/10.1094/Phyto-64-763.

    Article  Google Scholar 

  46. Devkota P, Hammerschmidt R. The infection process of Armillaria mellea and Armillaria solidipes. Physiol Mol Plant Pathol. 2020;112(4):101543. https://doi.org/10.1016/j.pmpp.2020.101543.

    Article  CAS  Google Scholar 

  47. Morrison DJ. Vertical distribution of Armillaria mellea rhizomorphs in soil. Trans Br Mycol Soc. 1976;66:393–9. https://doi.org/10.1016/S0007-1536(76)80207-0.

    Article  Google Scholar 

  48. Sul WJ, Asuming-Brempong S, Wang Q, Tourlousse DM, Penton CR, Deng Y, et al. Tropical agricultural land management influences on soil microbial communities through its effect on soil organic carbon. Soil Biol Biochem. 2013;63:33–8. https://doi.org/10.1016/j.soilbio.2013.05.007.

    Article  CAS  Google Scholar 

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Acknowledgements

We sincerely thank Guizhou Wumeng Fungi Industry Co., Ltd. to support us with the fields for cultivation of G. elata and P. impudicus. The authors would like to thank the editor and anonymous reviewers for their professional review work, constructive comments and valuable suggestions on our manuscript.

Funding

This research was supported by the National Key Research and Development Program (2023YFC3503803), the Guizhou Provincial Basic Research Program (Natural Science, Z.K. [2021] General 523), and the Research Platform Team Project of the Education Department of Guizhou Province (Qian Jiao Ji [2022]021).

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  1. Yanhong Wang and Jiao Xu contributed equally to this work.

Authors and Affiliations

  1. Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guiyang, China

    Yanhong Wang, Jiao Xu, Qingsong Yuan, Chenghong Xiao, Changgui Yang, Weike Jiang & Tao Zhou

  2. State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China

    Lanping Guo

  3. The Second Affiliated Hospital of Zunyi Medical University, Zunyi, China

    Gang Zheng

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Contributions

All authors contributed to the study conception and design. JX, CX, GZ, and CY performed the trial design, material preparation, and laboratory work. YW and QY performed the visualization, formal analysis, original draft preparation. TZ, LG and WJ performed supervision, project administration. All authors commented on previous versions of the manuscript. All authors have read and approved the final manuscript.

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Wang, Y., Xu, J., Yuan, Q. et al. Composition and diversity of soil microbial communities change by introducing Phallus impudicus into a Gastrodia elata Bl.-based soil. BMC Microbiol 24, 204 (2024). https://doi.org/10.1186/s12866-024-03330-4

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