DOI QR코드

DOI QR Code

Analysis of Bacterial Diversity and Communities Associated with Tricholoma matsutake Fruiting Bodies by Barcoded Pyrosequencing in Sichuan Province, Southwest China

  • Li, Qiang (College of Life Science, Sichuan University) ;
  • Li, Xiaolin (Soil and Fertilizer Institute, Sichuan Academy of Agricultural Sciences) ;
  • Chen, Cheng (Institute of plant protection, Sichuan Academy of Agricultural Sciences) ;
  • Li, Shuhong (Biotechnology & Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences) ;
  • Huang, Wenli (Institute of Biological & Nuclear Technology, Sichuan Academy of Agricultural Sciences) ;
  • Xiong, Chuan (College of Life Science, Sichuan University) ;
  • Jin, Xing (Institute of Biological & Nuclear Technology, Sichuan Academy of Agricultural Sciences) ;
  • Zheng, Linyong (College of Life Science, Sichuan University)
  • Received : 2015.05.06
  • Accepted : 2015.09.28
  • Published : 2016.01.28

Abstract

Endophytes play an important role in the growth and development of the host. However, the study of endophytes is mostly focused on plants, and reports on bacteria associated with fungi are relatively rare. We studied the bacteria associated with fruiting bodies of Tricholoma matsutake picked from seven main T. matsutake-producing areas in Sichuan, China, by barcoded pyrosequencing. About 8,272 reads were obtained per sample, representing 40 phyla, 103 classes, and 495 genera of bacteria and archaea, and 361-797 operational taxonomic units were observed at a 97% similarity level. The bacterial community was always both more abundant and more diverse than the archaeal community. UniFrac analysis showed there were some difference of bacterial communities among the samples sites. Three bacterial phyla, Proteobacteria, Bacteroidetes, and Firmicutes, were dominant in all samples. Correlation analysis showed there was a significant correlation between some soil properties and bacterial community associated with T. matsutake. This study demonstrated that the bacteria associated with T. matsutake fruiting bodies were diversified. Among these bacteria, we may find some strains that can promote the growth of T. matsutake.

Keywords

Introduction

Tricholoma matsutake (S. Ito et Imai) is an ectomycorrhizal basidiomycete associated with Pinaceae and Fagaceae trees in China, Korea, and elsewhere in the Northern Hemisphere [43,49]. Its fruiting body, the pine mushroom, is commercially important as a valuable food because of its medicinal effects and attractive flavor [14,23]. Polysaccharides and terpenoids extracted from its fruiting body have antitumor and antioxidant properties [19,38,48,51]. The growth of wild T. matsutake is extremely slow, and it is selective to the environmental conditions, growing in virgin forests without pollution and human intervention [31,42,47]. Artificial cultivation of T. matsutake has not been successful [21,46].

It is still unclear how ecological factors such as host plant, soil properties, and the associated microbial communities influence the development of the T. matsutake fruiting body [2,23,28]. The soil surrounding T. matsutake contains diverse microbial communities that may affect the growth of T. matsutake mycelia and the formation of mycorrhiza [25]. The soil microbial communities may also play a role in the material exchange between mushroom mycelia and plant host. Furthermore, the soil bacteria may live extracellularly inside fungal tissue [15]. Their role in fungal development is still unclear. Therefore, understanding the bacteria affiliated with T. matsutake and the microbial community structure underneath the mushroom has important implications for the artificial domestication and cultivation of T. matsutake. The microbial community in soil-mycelia aggregates and in the T. matsutake fairy ring zone has been studied [26,41]. Park et al. [32] also found a new species associated with the pine mushroom. This suggests that the surroundings of T. matsutake contains rich microbial resources for us to understand. The microbial communities associated with T. matsutake fruiting bodies have been analyzed using denaturing gradient gel electrophoresis (DGGE) [29]. However, studies on the bacterial diversity associated with T. matsutake fruiting bodies have rarely used barcoded pyrosequencing.

A majority (over 99%) of the microbes living in natural environments have not been cultured. Despite continuing development of culture techniques for the isolation and identification of microbes, it is still difficult to assess the true diversity in microbial communities using the currently available culture techniques owing to their limitations [1,34]. Metagenomics is the study of genetic material recovered directly from environmental samples. Because of its ability to reveal the previously hidden diversity of microscopic life, metagenomics offers a powerful lens for viewing the whole microbial world in a sample, including unculturable microbes [18,34,35].

In this paper, we studied the bacteria associated with fruiting bodies of T. matsutake picked from seven main T. matsutake-producing areas in Sichuan, China. This paper provides knowledge on the fundamental aspects of T. matsutake, such as T. matsutake-associated bacterial diversity, that may be of particular significance to the artificial domestication and cultivation of T. matsutake.

 

Materials and Methods

Mushroom Sampling Strategy and Soil Analyses

T. matsutake fruiting bodies were picked from Xiaojin, Yajiang, Muli, Yanyuan, Yanbian, Huidong, and Mianning county at its mature stage in Sichuan, China (Fig. 1, Supplemental Fig. S1), and kept in sterile sealed bags on ice. We collected three fruiting bodies in each producing area, based on altitude difference, and 500 g of soil beneath the fruiting bodies with a soil sampler. DNA was extracted from the three fruiting bodies and mixed as one sample to analyze the bacterial diversity by barcoded pyrosequencing. Soil samples from the same site were mixed separately to analyze their properties. Soil particle size distribution was determined using the pipette method [22]. pH was measured in soil water extracted by dissolving air-dried soil in distilled water at a ratio of 1:5. Organic matter content was estimated using the Tyurin method [33]. Total nitrogen was determined by the Kjeldahl method [7]. Molybdenum antimony ascorbic acid spectrophotography was used to estimate total phosphorus. Total potassium was analyzed by flame photometry. Effective nitrogen was measured by the alkali solution diffusion method. Available phosphorus was determined by the baking soda leaching - molybdenum antimony colorimetric method. Available potassium was determined by ammonium acetate extraction - flame photometry [30]. Soil Mg, Ca, Cu, Mn, and Zn were determined by inductively coupled plasma optical emission spectroscopy (Optima 2000 DV; PerkinElmer, USA), with yttrium as the internal standard [8].

Fig. 1.Location of the sampling sites of Tricholoma matsutake fruiting bodies and soil beneath the fruiting bodies.

DNA Extraction and MiSeq Sequencing of 16S rRNA Gene Amplicons

DNA extraction was conducted by using the E.Z.N.A. Fungal DNA Kit (Omega Bio-Tek, USA). The DNA concentration and quality were checked using a NanoDrop Spectrophotometer. Extracted DNA was diluted to 10 ng/μl and stored at -40℃. Universal primers 515F (5’-GTGCCAGCMGCCGCGGTAA-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’) [45] with 10nt barcodes were used to amplify the V4 hypervariable regions of 16S rRNA genes for pyrosequencing using the MiSeq sequencer [11,12]. The PCR mixture (25 μl) contained 1 μl PCR buffer, 1.5 mM MgCl2, each deoxynucleoside triphosphate at 0.4 mM, each primer at 1.0 mM, 0.5 U of TransStart Fast Pfu DNA Polymerase (TransGen, China), and 10 ng of soil genomic DNA. The PCR amplification program included initial denaturation at 94℃ for 3 min, followed by 30 cycles of 94℃ for 40 sec, 56℃ for 60 sec, and 72℃ for 60 sec, and a final extension at 72℃ for 10 min. Two PCRs per sample were combined together after PCR amplification. PCR products were subjected to electrophoresis using 1.0% agarose gel. The band with a correct size was excised and purified using the Gel Extraction Kit (Omega Bio-tek, USA) and quantified with Nanodrop. All samples were pooled together, with an equal molar amount from each sample. A TruSeq DNA kit was used to prepare the sequencing samples. The purified library was diluted, denatured, re-diluted, and then mixed with PhiX (about 30% of final DNA amount) as described in the Illumina library preparation protocols, and then the samples were applied to an Illumina MiSeq system for sequencing with the Reagent Kit ver. 2 2×250 bp according to the manufacturer’s manual.

Pyrosequence Data Analysis

The sequence data were processed using QIIME Pipeline ver. 1.7.0 (http://qiime.org/tutorials/tutorial.html) [10]. Multiple steps were required to trim the sequences, such as trimming the barcoded fusion primers, and filtering low-quality sequences (read length <150 bp or average quality value <25, ambiguous base calls⩾2) out. Sequences were clustered into operational taxonomic units (OTUs) at a 97% identity threshold, and the cut-off values used for taxonomic assignments were as follows (x = similarity): genus (97% > x ⩾ 94%), family (94% > x ⩾ 90%), order (90% > x ⩾ 85%), class (85% > x ⩾ 80%), and phylum (80 > x ⩾ 75%). If the similarity was lower than the specific cut-off value, the sequence was assigned as “unclassified” [27]. The aligned 16S rRNA gene sequences were used for chimera check using the Uchime algorithm [17]. All the samples were randomly resampled to 9,700 reads. We conducted alpha-diversity (phylogenetic distance whole tree, Chao1 estimator of richness, observed species, and Shannon’s diversity index) and beta-diversity (PCoA, UniFrac) analyses [9], for which the rarefaction curves were generated from the observed species. Taxonomy was assigned using the Ribosomal Database Project classifier [44].

 

Results

Diversity Indices

About 8,272 reads were obtained per sample, representing 40 phyla, 103 classes, and 495 genera of bacteria and archaea, and 361–797 OTUs were observed at a 97% similarity level (Table 1). The numbers of observed OTUs were significantly different between the sampling sites (Table 1). The rarefaction curves (Fig. 2) calculated with QIIME pipeline at 97% similarity also showed a different OTU richness pattern for all sites. Other OTU richness estimations, such as Chao1, indicated that samples picked from Mianning contained the lowest number of bacteria. According to the comprehensive OTU richness results (Table 1 and Fig. 2), the bacterial community of fruiting bodies from Yanyuan was the most diverse (Simpson index, 0.969; Shannon index, 6.38), whereas the lowest bacterial OTU diversity (Simpson index, 0.932; Shannon index, 4.90) was in the samples from Huidong.

Table 1.Chao1, estimator of richness. Good’s coverage is proportional to the nonsingleton phylotypes in all sequences.

Fig. 2.Rarefaction curves for bacterial operational taxonomic units (OTUs) in each sampling site (cut-off value at 97% similarity).

Characteristics of Soil Beneath Tricholoma matsutake Fruiting Bodies

Soil samples, down to a depth of 15 cm, were collected from inside the T. matsutake fairy ring at seven different sites. The physicochemical properties of the soils in the sampling sites differed slightly (Table 2). The pHs of the soil samples obtained from the fairy rings varied between 5.08 and 6.48. The soil collected from Yanyuan had the highest content of organic matter (189.6 g/kg), total nitrogen (4.39 g/kg), total phosphorus (0.42 g/kg), and available phosphorus (10.12 mg/kg), and it also contained the lowest total potassium (17.3 g/kg). Soil samples from Mianning had the most acidic environment (pH 5.08) and the lowest available phosphorus (1.21 mg/kg). In terms of soil texture, the clay composition was lower (1.73%) and the sand composition was higher (88.5%) in Mianning than in the other sites. The mineral element contents were slightly different at different sites (Table 2).

Table 2.OM, organic matter; TN, total nitrogen; TP, total phosphorus; TK, total potassium; AN, effective nitrogen; AP, available phosphorus; AK, available potassium; TMn, total manganese; TCu, total copper; TZn, total zinc; TCa, total calcium; TMg, total magnesium.

Taxonomic Analyses of Bacterial Communities

Each bacterial 16S rRNA gene sequence was taxonomically assigned from the phylum level to the species level using the Ribosomal Database Project classifier. The proportion of unclassified bacteria was no more than 0.1%. A total of 40 phyla were identified, and 17 of the 40 phyla were identified in all seven samples (Fig. 3A). The bacterial community was always both more abundant and more diverse than the archaeal community. Two archaeal phyla, Crenarchaeota and Euryarchaeota, accounted for less than 1% of all bacteria associated with T. matsutake fruiting bodies. The most abundant archaeal community was Euryarchaeota, about 0.3% of all bacteria detected. More than 37 bacterial phyla were detected in the samples. Three bacterial phyla, Proteobacteria, Bacteroidetes, and Firmicutes, were dominant in all samples. The relative abundance of Proteobacteria was more than 47% of all bacteria detected. Overall, Firmicutes and Bacteroidetes were less abundant. However, in samples picked from Yajiang, Firmicutes presented 41.0% of the OTUs, and in Yanyuan samples, Bacteroidetes presented 44.1% of the OTUs.

Fig. 3.Taxonomic composition analysis of bacterial communities (from phylum to family).

A total of 103 classes were identified, and 26 of the 103 classes were identified in all seven sites (Fig. 3B). The class Gammaproteobacteria was dominant in all samples (the average relative abundance was 52.2%). In particular, Bacilli (39.3%) and Betaproteobacteria (36.9%) were the dominant classes in Yajiang and Muli samples, respectively. In general, the classes Gammaproteobacteria, Betaproteobacteria, Bacilli, and Sphingobacteria occupied a dominant position in T. matsutake fruiting bodies from different sites.

A total of 183 orders were observed, and 38 of these were detected in all samples (Fig. 3C). The most abundant observed orders at all sites were Pseudomonadales (average relative abundance 35.8%), Burkholderiales (average relative abundance 15.8%), and Enterobacteriales (average relative abundance 11.3%). In particular, Burkholderiales (35.4%), Enterobacteriales (28.3%), and Bacillales (37.1%) were the dominant classes in the Muli, Yanbian, and Yajiang samples, respectively.

A total of 310 families were observed and 65 were identified in all seven sites (Fig. 3D). The relative abundance of some families, including Pseudomonadaceae (average of 35.3%), Enterobacteriaceae (11.3%), Oxalobacteraceae (8.3%), and Sphingobacteriaceae (7.3%), were dominant in all samples, but differed significantly between the sites. Pseudomonadaceae was the biggest family in most samples except samples from Yanyuan and Yanbian, in which Sphingobacteriaceae and Enterobacteriaceae occupied a dominant position, respectively.

The relative abundance of the genera Pseudomonas (in the family Pseudomonadaceae), unclassified genus (in the family Enterobacteriaceae), unclassified genus (in the family Pseudomonadaceae) and Janthinobacterium (in the family Oxalobacteraceae) was dominant in all samples (Table 3). Among them, Pseudomonas was the most abundant (average abundance 26.3%) and occupied the dominant position in samples from Xiaojin, Yanyuan, Huidong, and Mianning. Janthinobacterium was the most abundant genus in Muli sample (25.4%). Unclassified genus (in the family Enterobacteriaceae) was dominant in Yanbian sample (28.2%). In particular, unclassified genus (in the family Planococcaceae) occupied a dominant position in Yajiang sample (22.1%).

Table 3.List of bacterial genera (>1% in at least one experimental site) associated with the Tricholoma matsutake fruiting bodies of different sites.

Several species showed average abundances greater than 1% (Table 4). The communities from the seven different sites shared the same dominant species, Pseudomonas sp., Janthinobacterium sp., Janthinobacterium lividum, Pseudomonas viridiflava, Chryseobacterium sp., and other unclassified species (in the family Enterobacteriaceae, Comamonadaceae, Xanthomonadaceae, Pseudomonadaceae, and so on). The predominant species were two Pseudomonas sp., belonging to the family Pseudomonadaceae.

Table 4.List of bacterial species (average abundance >1%) associated with the Tricholoma matsutake fruiting bodies of different sites.

UniFrac Analysis

The differences in bacterial communities between the samples were estimated using UniFrac analysis (Fig. 4). The bacteria community structure in Yajiang and Yanyuan were significantly different from the other sites. The communities from the geographically close and similar environments like Huidong and Mianning were highly similar, implying that the environmental conditions can affect the T. matsutake-associated bacterial community structure.

Fig. 4.Principal coordinate analysis using weighted UniFrac.

Correlation Analysis Between Bacterial Community Associated with the Fruiting Bodies of Tricholoma matsutake and Soil Properties

There was a significant correlation between some soil properties and bacterial community associated with T. matsutake fruiting bodies (Table 5). Chao1 and the numbers of observed OTUs were correlated with clay (positively) content and sand (negatively) content. The Simpson index and Shannon index were positively correlated with total nitrogen and available phosphorus. Chao1 was also positively correlated with total nitrogen and total zinc, and negatively correlated with total magnesium. The relative abundance of the phylum Proteobacteria, the predominant phylum in this study, was positively correlated with the presence of total potassium. In contrast, the relative abundance of the phylum Bacteroidetes was negatively correlated with total potassium but positively correlated with organic matter. The abundance of Actinobacteria was negatively correlated with available phosphorus and total zinc. Total zinc was also negatively correlated with the abundance of the phylum Nitrospirae and Euryarchaeota. The abundance of Acidobacteria was positively correlated with total nitrogen and total copper. There were no clear correlations between soil pH and phyla abundance.

Table 5.OM, organic matter; TN, total nitrogen; TP, total phosphorus; TK, total potassium; AN, effective nitrogen; AP, available phosphorus; AK, available potassium; TMn, total manganese; TCu, total copper; TZn, total zinc; TCa, total calcium; TMg, total magnesium. *Significant at p < 0.05; **Significant at p < 0.01. Chao1, estimator of richness.

 

Discussion

Host-associated microbes play an important role in the growth and development of the host [16,39]. They can participate in the metabolic processes of the host, produce biological macromolecules with growth-promoting or antibacterial activities, and affect the yield and quality of the host [3,4,50]. However, the study of host-associated microbes is mostly focused on plants, and reports on bacteria associated with mushrooms are relatively rare [6,15,20,33]. Many large mushrooms have a complex life history and demanding environmental requirements. Studying the community structure of bacteria in mushrooms may be significant for their cultivation.

Most microbes in nature cannot be obtained in pure culture because of the difficulty of simulating the conditions required for their growth and reproduction. Earlier, we characterized the T. matsutake fruiting body-associated bacteria using DGGE [29]. For a more comprehensive picture of the bacterial diversity, we applied barcoded pyrosequencing for culture-independent bacterial community analysis. The results indicated that the bacteria associated with T. matsutake fruiting bodies were relatively abundant. In agreement with the earlier results [29], the bacterial communities were also varied in different samples, possibly due to the different ecological environments, as the communities from similar environments were similar. In the fairy ring zone of T. matsutake, Proteobacteria and Acidobacteria were the dominant phyla, and the relative abundance of the Proteobacteria was approximately twice that of the Acidobacteria [27]. The bacterial communities associated with the fruiting bodies were different, as Proteobacteria, Bacteroidetes, and Firmicutes were distributed in all samples, and Proteobacteria were over 50 times more abundant than Acidobacteria. This indicated that microbial taxons associated with the T. matsutake fruiting bodies were selectively enriched or reduced compared with microorganisms in the fairy ring zone. It remains to be seen if this change in the composition of microbial populations is related to the growth of T. matsutake. Pseudomonas spp. that were abundant in T. matsutake fruiting bodies have shown the ability to promote the growth of plants [13,40]. Therefore, they might be made into microbial fertilizer applied in the artificial cultivation of T. matsutake. Janthinobacterium sp. and Pedobacter sp. have shown antimicrobial activity against pathogenic organisms [5,36]. Whether these bacteria are active against pathogens inside fruiting bodies needs to be tested.

Previous studies showed that soil properties significantly affect the microbial community structure beneath T. matsutake fruiting bodies [27]. Similarly, in our study, there was a significant correlation between some soil properties and bacteria associated with T. matsutake. From the previous studies, we knew that the clay content in the fairy ring of T. matsutake positively affected the OTU diversity and evenness. In addition, the relative abundance of the phylum Actinobacteria was similarly positively correlated with clay and negatively correlated with sand content [27]. Interestingly, in this study, the clay content and sand content were also correlated with the numbers of observed OTUs and Chao1 in the same pattern, yet there was no significant correlation with the abundance of the phylum Actinobacteria. In addition, we found that some mineral elements in soil also correlated significantly with some bacterial taxa. For example, total zinc was negatively correlated with the abundance of Actinobacteria, Acidobacteria, and Euryarchaeota, and total copper positively affected the abundance of Acidobacteria, possibly related to the demand of these mineral elements by the bacteria. Moreover, there were no clear correlations between phyla abundance and soil pH in the fairy ring zone or fruiting bodies.

Altogether, the diverse T. matsutake-associated bacteria showed good prospects for the cultivation of T. matsutake, yet the questions to be answered are many. Further study of the growth-promoting bacteria should be tested, and their role in the material exchange between host plant and mycorrhizal fungi and in pest resistance should be assessed. In conclusion, this study provides important knowledge about the bacterial community inhabiting the fruiting bodies of T. matsutake and will lay a good foundation for the cultivation of T. matsutake.

References

  1. Alvin A, Miller KI, Neilan BA. 2014. Exploring the potential of endophytes from medicinal plants as sources of antimycobacterial compounds. Microbiol. Res. 169: 483-495. https://doi.org/10.1016/j.micres.2013.12.009
  2. Amann RI, Ludwig W, Schleifer KH. 1995. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 59: 143-169.
  3. Amend A, Keeley S, Garbelotto M. 2009. Forest age correlates with fine-scale spatial structure of Matsutake mycorrhizas. Mycol. Res. 113: 541-551. https://doi.org/10.1016/j.mycres.2009.01.005
  4. Aschehoug ET, Callaway RM, Newcombe G, Tharayil N, Chen SY. 2014. Fungal endophyte increases the allelopathic effects of an invasive forb. Oecologia175: 285-291. https://doi.org/10.1007/s00442-014-2891-0
  5. Asencio G, Lavin P, Alegria K, Dominguez M, Bello H, Gonzalez-Rocha G, Gonzalez-Aravena M. 2014. Antibacterial activity of the Antarctic bacterium Janthinobacterium sp. SMN 33.6 against multi-resistant gram-negative bacteria. Electron. J. Biotechnol. 17: 1-1. https://doi.org/10.1016/j.ejbt.2013.12.001
  6. Azliza IN, Hafizi R, Nurhazrati M, Salleh B. 2014. Production of major mycotoxins by Fusarium species isolated from wild grasses in peninsular Malaysia. Sains Malays. 43: 89-94.
  7. Bremner JM, Mulvaney CS. 1982. Nitrogen-total, pp. 595-624. In Page AL (ed.). Methods of Soil Analysised. American Society of Agronomy, Wisconsin.
  8. Brzostowski A, Bielawski L, Orlikowska A, Plichta S, Falandysz J. 2009. Instrumental analysis of metals profile in Poison Pax (Paxillus involutus) collected at two sites in Bory Tucholskie. Chem. Anal. (Warsaw) 54: 907-920.
  9. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7: 335-336. https://doi.org/10.1038/nmeth.f.303
  10. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ. 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 108: 4516-4522. https://doi.org/10.1073/pnas.1000080107
  11. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N. 2012. Ultra-high-throughput microbial community analysis on the IlluminaHiSeq and MiSeq platforms. ISME J. 6: 1621-1624. https://doi.org/10.1038/ismej.2012.8
  12. Chang P, Gerhardt KE, Huang XD, Yu XM, Glick BR, Gerwing PD, Greenberg BM. 2014. Plant growth-promoting bacteria facilitate the growth of barley and oats in saltimpacted soil: implications for phytoremediation of saline soils. Int. J. Phytoremediat. 16: 1133-1147. https://doi.org/10.1080/15226514.2013.821447
  13. Ding XA, Tang J, Cao M, Guo CX, Zhang X, Zhong J, et al. 2010. Structure elucidation and antioxidant activity of a novel polysaccharide isolated from Tricholoma matsutake. Int. J. Biol. Macromol. 2: 271-275. https://doi.org/10.1016/j.ijbiomac.2010.04.010
  14. Deepika KM, Sudhakara R, Ramesh CU. 2013. Diversity of cultivable bacteria associated with fruiting bodies of wild Himalayan Cantharellus spp. Ann. Microbiol. 63: 845-853. https://doi.org/10.1007/s13213-012-0535-3
  15. Dudnik A, Bigler L, Dudler R. 2014. Production of proteasome inhibitor syringolin A by the endophyte Rhizobium sp. strain AP16.Appl. Environ. Microbiol. 80: 3741-3748. https://doi.org/10.1128/AEM.00395-14
  16. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27: 2194-2200. https://doi.org/10.1093/bioinformatics/btr381
  17. Handelsman J. 2004. Metagenomics: application of genomics to uncultured microorganisms. Microbiol. Mol. Biol. Rev. 68: 669-685. https://doi.org/10.1128/MMBR.68.4.669-685.2004
  18. Hou YL, Ding X, Hou WR, Zhong J, Zhu HQ, Ma BX, et al. 2013. Anti-microorganism, anti-tumor, and immune activities of a novel polysaccharide isolated from Tricholoma matsutake. Pharmacogn. Mag.9: 244-249. https://doi.org/10.4103/0973-1296.113278
  19. Hazen TH, Zhao LC, Sahl JW, Robinson G, Harris AD, Rasko DA, Johnson JK. 2014. Characterization of Klebsiella sp. strain 10982, a colonizer of humans that contains novel antibiotic resistance alleles and exhibits genetic similarities to plant and clinical Klebsiella isolates. Antimicrob. Agents Chemother. 58: 1879-1888. https://doi.org/10.1128/AAC.01605-13
  20. Iwase, K. 1997. Cultivation of mycorrhizal mushrooms. Food Rev. Int. 13: 431-442. https://doi.org/10.1080/87559129709541130
  21. Kataoka R, Siddiqui ZA, Kikuchi J, Ando M, Sriwati R, Nozaki A, Futai K. 2012. Detecting nonculturable bacteria in the active mycorrhizal zone of the pine mushroom Tricholoma matsutake. J. Microbiol. 50: 199-206. https://doi.org/10.1007/s12275-012-1371-7
  22. Kawagishi H, Hamajima K, Takanami R, Nakamura T, Sato Y, Akiyama Y, et al. 2004. Growth promotion of mycelia of the Matsutake mushroom Tricholoma matsutake by Disoleucine. Biosci. Biotechnol. Biochem. 11: 2405-2407. https://doi.org/10.1271/bbb.68.2405
  23. Kilmer VJ, Alexander LT. 1949. Methods of making mechanical analysis of soils. Soil Sci. 68: 15-24. https://doi.org/10.1097/00010694-194907000-00003
  24. Kim JY, Byeon SE, Lee YG, Lee JY, Park J, Hong EK, Cho JY. 2008. Immunostimulatory activities of polysaccharides from liquid culture of pine-mushroom Tricholoma matsutake. J. Microbiol. Biotechnol. 18: 95-103.
  25. Kim M, Yoon H, You YH, Kim YE, Woo JR, Seo Y, et al. 2013. Metagenomic analysis of fungal communities inhabiting the fairy ring zone of Tricholoma matsutake. J. Microbiol. Biotechnol. 23: 1347-1356. https://doi.org/10.4014/jmb1306.06068
  26. Kim M, Yoon H, Kim YE, Kim YJ, Kong WS, Kim JG. 2014. Comparative analysis of bacterial diversity and communities inhabiting the fairy ring of Tricholoma matsutake by barcoded pyrosequencing.J. Appl. Microbiol. 3: 699-710. https://doi.org/10.1111/jam.12572
  27. Li Q, Li XL, Huang WL, Xiong C, Yang Y, Yang ZR, Zheng LY. 2014. Community structure and diversity of entophytic bacteria in Tricholoma matsutake in Sichuan Province, Southwest China. J. Appl. Ecol. 25: 3316-3322 (in Chinese).
  28. Lian C, Narimatsu M, Nara K, Hogetsu T. 2006. Tricholoma matsutake in a natural Pinus densiflora forest: correspondence between above- and below-ground genets, association with multiple host trees and alteration of existing ectomycorrhizal communities. New Phytol. 171: 825-836. https://doi.org/10.1111/j.1469-8137.2006.01801.x
  29. Lozupone C, Knight R. 2005. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71: 8228-8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005
  30. Mehlich A. 1982. Comprehensive Methods in Soil Testing. North Carolina Department of Agriculture.
  31. Murata H, Yamada A, Maruyama T, Endo N, Yamamoto K, Ohira T, Shimokawa T. 2013. Root endophyte interaction between ectomycorrhizal basidiomycete Tricholoma matsutake and arbuscular mycorrhizal tree Cedrela odorata, allowing in vitro synthesis of rhizospheric “shiro”. Mycorrhiza 23: 235-242. https://doi.org/10.1007/s00572-012-0466-7
  32. Park MS, Oh SY, Cho HJ, Fong JJ, Cheon WJ, Lim YW. 2014. Trichoderma songyi sp. nov., a new species associated with the pine mushroom (Tricholoma matsutake). Antonie Van Leeuwenhoek 106: 593-603. https://doi.org/10.1007/s10482-014-0230-4
  33. Ruma K, Sunil K, Prakash HS. 2014. Bioactive potential of endophytic Myrothecium sp. isolate M1-CA-102, associated with Calophyllum apetalum. Pharm. Biol. 52: 665-676. https://doi.org/10.3109/13880209.2013.863950
  34. Santos T, Cruz A, Caetano T, Covas C, Mendo S. 2015. Draft genome sequence of Pedobacter sp. strain NL19, a producer of potent antibacterial compounds. Genome Announc. DOI:10.1128/genomeA.00184-15.
  35. Shokralla S, Spall JL, Gibson JF, Hajibabaei M. 2012. Nextgeneration sequencing technologies for environmental DNA research. Mol. Ecol. 21: 1794-1805. https://doi.org/10.1111/j.1365-294X.2012.05538.x
  36. Streit WR, Schmitz RA. 2004. Metagenomics - the key to the uncultured microbes. Curr. Opin. Microbiol. 7: 492-498. https://doi.org/10.1016/j.mib.2004.08.002
  37. Tara N, Afzal M, Ansari TM, Tahseen R, Iqbal S, Khan QM. 2014. Combined use of alkane-degrading and plant growthpromoting bacteria enhanced phytoremediation of diesel contaminated soil. Int. J. Phytoremediat. 16: 1268-1277. https://doi.org/10.1080/15226514.2013.828013
  38. Tong HB, Liu XM, Tian D, Sun X. 2013. Purification, chemical characterization and radical scavenging activities of alkali-extracted polysaccharide fractions isolated from the fruit bodies of Tricholoma matsutake. World J. Microbiol. Biotechnol. 29: 775-780. https://doi.org/10.1007/s11274-012-1232-x
  39. Truyens S, Jambon I, Croes S, Janssen J, Weyens N, Mench M, et al. 2014. The effect of long-term CD and NI exposure on seed endophytes of Agrostis capillaris and their potential application in phytoremediation of metal-contaminated soils. Int. J. Phytoremediat. 16: 643-659. https://doi.org/10.1080/15226514.2013.837027
  40. Tyurin IV. 1931. A new modification of the volumetric method of determining soil organic matter by means of chromic acid. Pedology 26: 36-47.
  41. Vaario LM, Fritze H, Spetz P, Heinonsalo J, Hanajik P, Pennanen T. 2011. Tricholoma matsutake dominates diverse microbial communities in different forest soils. Appl. Environ. Microbiol. 77: 8523-8531. https://doi.org/10.1128/AEM.05839-11
  42. Vaario LM, Kiikkila O, Hamberg L. 2013. The influences of litter cover and understorey vegetation on fruitbody formation of Tricholoma matsutake in southern Finland. Appl. Soil Ecol. 66: 56-60. https://doi.org/10.1016/j.apsoil.2012.11.009
  43. Van Gevelt T. 2014. The role of state institutions in nontimber forest product commercialisation: a case study of Tricholoma matsutake in South Korea. Int. Forest. Rev. 16: 1-13. https://doi.org/10.1505/146554814811031233
  44. Wang Q, Garrity GM, Tiedje JM, Cole JR. 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73: 5261-5267. https://doi.org/10.1128/AEM.00062-07
  45. Wu LY, Wen CQ, Qin YJ, Yin HQ, Tu QC, Nostrand JDV, et al. 2015. Phasing amplicon sequencing on Illumina Miseq for robust environmental microbial community analysis. BMC Microbiol. 15: 125. https://doi.org/10.1186/s12866-015-0450-4
  46. Yamada A, Endo N, Murata H, Ohta A, Fukuda M. 2014. Tricholoma matsutake Y1 strain associated with Pinus densiflora shows a gradient of in vitro ectomycorrhizal specificity with Pinaceae and oak hosts. Mycoscience 55: 27-34. https://doi.org/10.1016/j.myc.2013.05.004
  47. Yamada A, Maeda K, Kobayashi H, Murata H. 2006. Ectomycorrhizal symbiosis in vitro between Tricholoma matsutake and Pinus densiflora seedlings that resembles naturally occurring ‘shiro’. Mycorrhiza 16: 111-116. https://doi.org/10.1007/s00572-005-0021-x
  48. Yang B, Wang XM, Ma HY, Jia Y, Li X, Dai CC. 2014. Effects of the fungal endophyte Phomopsis liquidambari on nitrogen uptake and metabolism in rice. Plant Growth Regul. 73: 165-179. https://doi.org/10.1007/s10725-013-9878-4
  49. Yang XF, Luedeling E, Chen GL, Hyde KD, Yang YJ, Zhou DQ, et al. 2012. Climate change effects fruiting of the prize matsutake mushroom in China. Fungal Divers. 56: 189-198. https://doi.org/10.1007/s13225-012-0163-z
  50. You LJ, Gao Q, Feng MY, Yang B, Ren JY, Gu LJ, et al. 2013. Structural characterisation of polysaccharides from Tricholoma matsutake and their antioxidant and antitumour activities. Food Chem. 138: 2242-2249. https://doi.org/10.1016/j.foodchem.2012.11.140
  51. You QH, Yin XL, Zhang SN, Jiang ZH. 2014. Extraction, purification, and antioxidant activities of polysaccharides from Tricholoma mongolicum Imai. Carbohydr. Polym. 99: 1-10. https://doi.org/10.1016/j.carbpol.2013.07.088

Cited by

  1. Prediction of the potential geographic distribution of the ectomycorrhizal mushroom Tricholoma matsutake under multiple climate change scenarios vol.7, pp.None, 2017, https://doi.org/10.1038/srep46221
  2. Effect of fairy ring bacteria on the growth of Tricholoma matsutake in vitro culture vol.28, pp.5, 2016, https://doi.org/10.1007/s00572-018-0828-x
  3. Chinese Black Truffle ( Tuber indicum ) Alters the Ectomycorrhizosphere and Endoectomycosphere Microbiome and Metabolic Profiles of the Host Tree Quercus aliena vol.9, pp.None, 2016, https://doi.org/10.3389/fmicb.2018.02202
  4. Effect of fruiting body bacteria on the growth of Tricholoma matsutake and its related molds vol.13, pp.2, 2016, https://doi.org/10.1371/journal.pone.0190948
  5. Ectomycorrhization of Tricholoma matsutake with Quercus aquifolioides affects the endophytic microbial community of host plant vol.58, pp.3, 2018, https://doi.org/10.1002/jobm.201700506
  6. Root-associated bacteria influencing mycelial growth of Tricholoma matsutake (pine mushroom) vol.56, pp.6, 2018, https://doi.org/10.1007/s12275-018-7491-y
  7. Mycorrhization of Quercus acutissima with Chinese black truffle significantly altered the host physiology and root-associated microbiomes vol.7, pp.None, 2016, https://doi.org/10.7717/peerj.6421
  8. Bacterial Profiling and Dynamic Succession Analysis of Phlebopus portentosus Casing Soil Using MiSeq Sequencing vol.10, pp.None, 2016, https://doi.org/10.3389/fmicb.2019.01927
  9. Bacteria Associated With Shiraia Fruiting Bodies Influence Fungal Production of Hypocrellin A vol.10, pp.None, 2016, https://doi.org/10.3389/fmicb.2019.02023
  10. LC-MS-Based Metabolomic Approach Revealed the Significantly Different Metabolic Profiles of Five Commercial Truffle Species vol.10, pp.None, 2019, https://doi.org/10.3389/fmicb.2019.02227
  11. Chinese white truffles shape the ectomycorrhizal microbial communities of Corylus avellana vol.69, pp.5, 2019, https://doi.org/10.1007/s13213-019-1445-4
  12. Bacterial composition of biofilms formed on dairy-processing equipment vol.49, pp.5, 2016, https://doi.org/10.1080/10826068.2019.1587623
  13. Tuber borchii Shapes the Ectomycorrhizosphere Microbial Communities of Corylus avellana vol.47, pp.2, 2016, https://doi.org/10.1080/12298093.2019.1615297
  14. Isolation of bacteria at different points of Pleurotus ostreatus cultivation and their influence in mycelial growth vol.234, pp.None, 2016, https://doi.org/10.1016/j.micres.2019.126393
  15. Fruitbody chemistry underlies the structure of endofungal bacterial communities across fungal guilds and phylogenetic groups vol.14, pp.8, 2020, https://doi.org/10.1038/s41396-020-0674-7
  16. Colonization by Tuber melanosporum and Tuber indicum affects the growth of Pinus armandii and phoD alkaline phosphatase encoding bacterial community in the rhizosphere vol.239, pp.None, 2016, https://doi.org/10.1016/j.micres.2020.126520
  17. Bacterial community dynamics across developmental stages of fungal fruiting bodies vol.96, pp.10, 2016, https://doi.org/10.1093/femsec/fiaa175
  18. A Critical Review on Communication Mechanism within Plant-Endophytic Fungi Interactions to Cope with Biotic and Abiotic Stresses vol.7, pp.9, 2021, https://doi.org/10.3390/jof7090719
  19. Effects of ectomycorrhizal fungus bolete identity on the community assemblages of endofungal bacteria vol.13, pp.6, 2016, https://doi.org/10.1111/1758-2229.13007