Metagenomic Analysis of Bacterial and Fungal Communities Inhabiting Shiro Dominant Soils of Two Production Regions of Tricholoma Matsutake S. Ito & S. Imai in Korea

: Tricholoma matsutake is an ectomycorrhizal fungus that has obligate symbiotic relationships with Pinus densiﬂora . Its fruiting body has a distinctive ﬂavor and is traded at a high price. Thus, it has been a signiﬁcant source of income for rural communities in Korea. We hypothesized that biotic factors considerably inﬂuence the formation of the T. matsutake mushroom, and the soils producing T. matsutake share similar microbial characteristics. Therefore, the present study aimed to detect the speciﬁc fungal and bacterial groups in T. matsutake production soils (shiro+) and nonproduction soils (shiro − ) of the Bonghwa and Yanyang regions via next-generation sequencing. In a total of 15 phyla, 36 classes, 234 genera of bacteria, six phyla, 29 classes, and 164 genera of fungi were detected from four samples at both sites. The species diversity of shiro+ soils was lower than the shiro − samples in both the fungal and bacterial groups. In addition, we did not ﬁnd high similarities in the microbial communities between the shiro+ soils of the two regions. However, in the resulting differences between the fungal communities categorized by their trophic assembly, we found a distinguishable compositional pattern in the fungal communities from the shiro+ soils and the shiro − soils of the two sites. Thus, the similarity among the microbial communities in the forest soils may be due to the fact that the microbial communities in the T. matsutake dominant soils are closely associated with biotic factors and abiotic factors such as soil properties.


Introduction
Tricholoma matsutake (S. Ito & S. Imai) that forms a symbiotic association with the root tips of Pinus densiflora (Siebold & Zucc.) provides attractive commercial benefits to rural communities in Korea [1,2]. The annual yields of this mushroom are highly limited and unpredictable. Since it has not yet been successfully artificially cultivated, the entire production of T. matsutake still depends upon natural harvesting from forests. In recent decades, many researchers have strived to succeed in the artificial production of T. matsutake [2][3][4][5][6]. However, the artificial cultivation of this fungus has not been established. As an obligated symbiont, the biology of this mycorrhizal fungus must be considered from the perspective of the ecological interaction with the surrounding biotic factors, especially microbial groups.
Soil ecosystems have a wide variety of microbial communities. Microorganisms in the soil can have positive or negative effects on the growth of ectomycorrhizal fungus [7]. Many studies have been conducted on the microbial communities in the soils adjacent to T. matsutake [6,[8][9][10][11]. The influence of the diverse microbial communities in soil on the life cycle of T. matsutake, such as the development of mycelia and the formation of fruiting bodies in various ways, has been investigated [4,12,13]. In particular, some soil bacteria, which are called mycorrhizal helper bacteria (MHB), have beneficial effects on the September 2019, soil sampling was conducted immediately after T. matsutake fruiting bodies were harvested. By using a soil sampler, soils containing shiro (shiro+) were collected at 10 cm depth from the soil surface at the three spots of the zone beneath the T. matsutake, and soils without shiro (shiro−) were collected at approximately 3-4 m intervals from the spots with the shiro+ soils. Each soil sample was placed into a polyvinyl bag and mixed well. Shiro can be distinguished by its features of whitish-gray-colored soil, in which fungal hyphae are aggregated [11]. Soil samples taken from each sampling site were transported on ice and stored at −4 °C before DNA extraction.

DNA Extraction, Library Construction, and Illumina Miseq Sequencing
For each sample, microbial DNA was extracted from 0.5-1 g per soil using a DNeasy Power Soil Kit (Qiagen, Hilder, Germany) according to the manufacturer's instructions. The extracted DNA was quantified using Quant-IT PicoGreen (Invitrogen). The sequencing libraries were prepared according to the Illumina 16S Metagenomic sequencing library protocols for the V3-V4 region for bacteria, and 5.8S and ITS2 regions for fungi. For bacteria, the input 2 uL (10 ng uL −1 ) was PCR amplified with 1× reaction buffer, 1 nM dNTP mix, 500 nM concentrations of the universal F/R PCR primers, and 2.5 U of Herculase II fusion DNA polymerase (Agilent Technologies, Santa Clara, CA, USA). The cycle condition for the 1st PCR was 3 min at 95 • C for heat activation, and 25 cycles of 30 s at 95 • C, 30 s at 55 • C, and 30 s at 72 • C, followed by a 5 min final extension at 72 • C, The 1st PCR product was purified with AMPure beads (Agencourt Bioscience, Beverly, MA, USA). Following purification, the 2 uL of 1st PCR product was PCR amplified for final library construction containing the index using the NexteraXT Indexed Primer. The cycle condition for the 2nd PCR was the same as the 1st PCR condition except for 10 cycles. The PCR product was purified with AMPure beads. The resulting PCR products were pooled, and the fragment sizes were checked using agarose gel electrophoresis and the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The final purified product was then quantified using qPCR according to the qPCR Quantification Protocol Guide (KAPA Library Quantification Kits for Illumina Sequencing platforms) and qualified using the TapeStation D1000 ScreenTape (Agilent Technologies, Waldbronn, Germany). The paired-end (2 × 300 bp) sequencing was performed by the Macrogen using the MiSeq™ platform (Illumina, San Diego, CA, USA).

Processing and Analyzing of Sequencing Data
The bacterial and fungal sequence reads were assembled using FLASH 1.2.11 (Fast Length Adjustment of Short reads, http://ccb.jhu.edu/software/FLASH/ (accessed on 17 December 2019)). After assembly, pre-processing and clustering were carried out using the CD-HIT-OTU program (http://weizhongli-lab.org/cd-hit-otu/ (accessed on 17 December 2019)) that performed the OTU (Operational Taxonomic Units) finding. CD-HIT-OTU comprises the following steps: (1) Low-quality reads are filtered out and extra-long tails are trimmed. (2) Filtered reads are clustered at 100% identity using CD-HIT-DUP. (3) Chimeric reads are identified. (4) Secondary clusters are recruited into primary clusters. (5) Noise sequences in clusters of size x or below are removed. Size x is statistically calculated. (6) Remaining representative reads from non-chimeric clusters are clustered into OTUs at a user-specified OTU cutoff (e.g., 97% identity at species level) [22]. Representative sequences for each OUT were selected and assigned to taxonomic data at RDP for bacteria [23] and UNITE for fungi [24] databases using the Quantitative Insights Into Microbial Ecology (QIIME) which is an open-source bioinformatics pipeline for performing microbiome analysis from raw DNA sequencing data [25]. Alpha diversity indices, such as the Shannon index, Chao 1, Simpson index, and Good's coverage were also calculated using QIIME [25]. Sorensen's classic similarity analysis that is based on the probability between two randomly chosen individuals, one from each of the two samples, was performed using EstimateS 9.1.0 [26].

Statistical Data Analysis for Bacterial Communities in Sampling Sites
A total of 473,975 reads and 1315 OTUs were detected in four sampling spots ( Table 2). The number of total reads ranged from 112,489 to 129,607. In all, 221 to 379 OTUs per sampling spot were obtained at a 99% similarity level. The result of the Chao1 estimation showed that the species richness of the shiro− soil samples of the Bonghwa and Yangyang sites was lower than that of the shiro+ soils. The diversity of species of bacterial communities for each sampling spot indicated that the shiro− soils included more bacterial communities than shiro+ soils at both sampling sites. The shiro− soil at the Bonghwa site represented the most diverse bacterial community (Shannon index = 6.777), while the shiro+ soil of Bonghwa had the lowest bacterial diversity (4.628). The Good's coverage of all sampling spots ranged from 0.997 to 0.999, indicating that the sequencing depth appropriately represented the bacterial diversity. The rarefaction curves, which reveal the species richness of each sample, also showed that the shiro− soil samples of both of the sampling sites have a greater bacterial community than the shiro+ soil samples (Figure 2a).

Relative Abundance of Bacterial Communities
Taxonomic composition analysis of bacteria for four sampling spots was conducted at the phylum level ( Figure 3a). In total, 15 phyla were identified: 12 phyla in the shiro+ soil of Bonghwa, 10 phyla in the shiro− soil of Bonghwa, 12 phyla in the shiro+ soil of Yangyang, and 13 phyla in the shiro− soil of Yangyang. At the Bonghwa site, Bacteroidetes and Proteobacteria in the shiro+ soil were relatively abundant (46.01% and 45.08%), compared with the shiro− soil (14.56% and 38.16%). Acidobacteria was the dominant phylum in the shiro− soil (37.92%) compared with the shiro+ soil (3.44%). At the Yangyang site, the highest abundance of phyla in the shiro+ soil was shown by Actinobacteria, and Chloroflexi compared with those of the shiro− soil, whereas Acidobacteria, Proteobacteria, and Verrucomicrobia were the dominant phyla in the shiro− soil.
The relative abundance at the class level for Acidobacteria, Actinobacteria, Bacteroidetes, and Proteobacteria, the most frequently observed phyla in the four soil samples, showed distinct differences between the soil samples and the sampling sites. Of the total 36 classes, four classes of Acidobacteria phylum, four classes of Actinobacteria phylum, four classes of Bacteroidetes phylum, and five classes of Proteobacteria phylum were mainly observed. Acidobacteria, Acidobaceriia, and Vicinamibacteria were commonly detected in all soil samples (Figure 3b). Within the phylum Actinobacteria, the most abundant class in all samples was Actinobacteria (Figure 3c). Chitinophagia and Sphingobacteriia commonly showed Bacteroidetes in all soil samples (Figure 3d). Five bacterial classes of Proteobacteria phylum, i.e., Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Oligoflexia, were commonly detected in all samples ( Figure 3e). The Alphaproteobacteria class was highly detected in the shiro− soils of both sites, while the Betaproteobacteria class was more abundant in the shiro+ soils than the

Statistical Data Analysis for Fungal Communities in Sampling Sites
A total of 496,994 reads and 781 OTUs were detected at four sampling spots (Table 3). For the number of OTUs, the shiro− soil sample of Bonghwa was the highest (364 OTUs), followed by the shiro− soil of Yangyang (244 OTUs), the shiro+ soil of Yangyang (107 OTUs), and the shiro+ soil of Bonghwa (66 OTUs). All indices of Chao1, Shannon diversity, and inverse Simpson were lower in the shiro− soil than the shiro+ soil samples in both sampling sites. In particular, the fungal diversity of the shiro− soil sample of Bonghwa (Chao1 estimation = 364; Shannon index = 5.846; Inverse Simpson index = 0.948) was the highest among the soil samples. All samples showed Good's coverage that indicated sufficient sequencing depth for characterizing fungal diversity. The rarefaction curves also showed that the shiro− soil samples of both of the sampling sites have a higher number of OTUs than the shiro+ soil samples of both sites (Figure 2b).

Relative Abundance of Bacterial Communities
Taxonomic composition analysis of bacteria for four sampling spots was conducted at the phylum level ( Figure 3a). In total, 15 phyla were identified: 12 phyla in the shiro+ soil of Bonghwa, 10 phyla in the shiro− soil of Bonghwa, 12 phyla in the shiro+ soil of Yangyang, and 13 phyla in the shiro− soil of Yangyang. At the Bonghwa site, Bacteroidetes and Proteobacteria in the shiro+ soil were relatively abundant (46.01% and 45.08%), compared with the shiro− soil (14.56% and 38.16%). Acidobacteria was the dominant phylum in the shiro− soil (37.92%) compared with the shiro+ soil (3.44%). At the Yangyang site, the highest abundance of phyla in the shiro+ soil was shown by Actinobacteria, and Chloroflexi compared with those of the shiro− soil, whereas Acidobacteria, Proteobacteria, and Verrucomicrobia were the dominant phyla in the shiro− soil.  In the total 234 genera of bacteria, 42 genera were observed in more than 1% of relative abundance in the shiro+ soils and shiro− soils of the two sampling sites (Table 4). Of these genera, Mucilaginibacter (26.19%) from Bacteriodetes phylum, Acidobacterium (11.46%) from Acidobacteria phylum, Actinoallomurus (18.17%) from Actinobacteria phylum, and Mycobacterium (14.50%) from Actinobacteria phylum were the most dominant genera in the shiro+ soil of Bonghwa, the shiro− soil of Bonghwa, the shiro+ soil of Yangyang, and the shiro− soil at the Yangyang site, respectively. Seven genera, Flavobacterium (4.44%), Pedobacter (2.92%), Sphingobacterium (8.56%), Novosphingobium (1.60%), Janthino- The relative abundance at the class level for Acidobacteria, Actinobacteria, Bacteroidetes, and Proteobacteria, the most frequently observed phyla in the four soil samples, showed distinct differences between the soil samples and the sampling sites. Of the total  36 classes, four classes of Acidobacteria phylum, four classes of Actinobacteria phylum, four classes of Bacteroidetes phylum, and five classes of Proteobacteria phylum were mainly observed. Acidobacteria, Acidobaceriia, and Vicinamibacteria were commonly detected in all soil samples (Figure 3b). Within the phylum Actinobacteria, the most abundant class in all samples was Actinobacteria (Figure 3c). Chitinophagia and Sphingobacteriia commonly showed Bacteroidetes in all soil samples (Figure 3d). Five bacterial classes of Proteobacteria phylum, i.e., Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Oligoflexia, were commonly detected in all samples (Figure 3e). The Alphaproteobacteria class was highly detected in the shiro− soils of both sites, while the Betaproteobacteria class was more abundant in the shiro+ soils than the shiro− soils at both sites.

Relative Abundance of Fungal Communities
Fungal taxonomic composition analysis for four sample soils was conducted at the phylum level (Figure 4a). A total of six phyla were detected in all samples. Ascomycota, Basidiomycota, Mortierellomycota, and Mucoromycota were commonly observed in all soil samples. Basidiomycota and Mucoromycota phyla were more dominant in the shiro+ soils than the shiro− soils of both sites. In contrast, Ascomycota and Mortierellomycota had a higher abundance in the shiro− soils compared with the shiro+ soils of both sites. Ascomycota were observed. The four classes that were commonly detected in all soil samples were Dothideomycetes, Eurotinomycetes, Leotiomycetes, and Sordariomycetes (Figure 4b). A total of nine classes from phylum Basidiomycota were observed in all samples, and three classes were only commonly detected: Agaricomycetes, Geminibasidiomycetes, and Tremellomycetes (Figure 4c). The class that occurred the most frequently was Agaricomycetes in all the samples, and this class had high relative abundance in the shiro+ soils compared with the shiro− soils of both sites. At the level of phylum Mucoromycota, only Umbelopsidomycetes was observed in all soil samples (Figure 4d). In addition, the classes of unidentified Chytridiomycota of phylum Chytridiomycota, and Mortierellomycetes of phylum Mortierellomycota were detected in very low proportions (Figure 4e). In the total 168 genera of fungi, 24 genera were observed at a higher than 1% relative abundance (Table 5). Especially one genus, Tricholoma was highly detected in the shiro+ soils (Bonghwa, 63.73%; Yangyang, 68.86%) compared with the shiro− soils (Bonghwa, 0.08%; Yangyang 29.46%) at the two sampling sites. In the Tricholoma genus of the shiro− The relative abundance of the class level for Ascomycota and Basidiomycota, the most frequently detected phyla in all samples, showed distinct differences between the production/nonproduction soils of T. matsutake. Of the total 29 classes, 10 classes from Ascomycota were observed. The four classes that were commonly detected in all soil samples were Dothideomycetes, Eurotinomycetes, Leotiomycetes, and Sordariomycetes (Figure 4b). A total of nine classes from phylum Basidiomycota were observed in all samples, and three classes were only commonly detected: Agaricomycetes, Geminibasidiomycetes, and Tremellomycetes (Figure 4c). The class that occurred the most frequently was Agaricomycetes in all the samples, and this class had high relative abundance in the shiro+ soils compared with the shiro− soils of both sites. At the level of phylum Mucoromycota, only Umbelopsidomycetes was observed in all soil samples (Figure 4d). In addition, the classes of unidentified Chytridiomycota of phylum Chytridiomycota, and Mortierellomycetes of phylum Mortierellomycota were detected in very low proportions (Figure 4e).

Similarity of Bacterial and Fungal Communities within/across Sampling Sites
The similarity in the bacterial and fungal communities within/across the sampling sites is shown in Table 6. The highest similarity index of the bacterial community was observed between the shiro+ soil in Bonghwa and the shiro− soil in Yangyang (0.769), and the lowest value was observed between the shiro− soil in Bonghwa and the shiro+ soil in Yangyang (0.565), or the shiro− soils in Bonghwa and Yangyang (0.565). In the similarity indices of the fungal community, the highest value was observed between the shiro− soils in Bonghwa and Yangyang (0.666), or between the shiro+ soil and the shiro− soil in Yangyang (0.666). The lowest value was observed between the shiro+ soil in Bonghwa and the shiro+ soil in Yangyang (0.578). In fungal communities separated from ECM and other fungi assemblages except for unknown fungi, the similarity of ECM communities was shown to be the highest value in the shiro− soils of the two sites (0.857), whereas low similarity indices were observed between the shiro+ soil and the shiro− soil at the Bonghwa site, the shiro+ soils of two sites, or the shiro+ soil at the Bonghwa site and the shiro− soil at the Yangyang site (Table S2). For other fungal assemblages, the highest similarity was observed between the shiro− soils of the two sites (0.889), and between the shiro− soil at the Bonghwa site and the shiro+ soil at the Yangyang site (0.889). Table 5. List of fungal genera inhabiting the Tricholoma matsutake production (shiro+) and nonproduction (shiro−) soils of Bonghwa and Yangyang sampling sites. The fungal genera present more than 1% of at least one sample among the four soil samples.

Discussion
Tricholoma matsutake forms in the shiro, as unique and massive aggregates of mycorrhizal hyphae, host plant roots, and soil particles [4,27]. As fruiting bodies form in natural conditions, an understanding of the environment near the fairy ring is crucial to understanding the ecology of T. matsutake [28]. Many studies have shown that the biological and physiochemical characteristics are different between the fairy ring and the adjacent soil, and between the positions within fairy rings likely due to the effects of T. matsutake hyphae [8,13,[29][30][31]. As a biotic environment in fairy rings, various co-existing microbial communities may influence T. matsutake occurrence in different ways [8,11,13].

Distinct Bacterial Community Structure
In the work reported here, we compared the difference in the microbial diversity and community between the presence and absence of the shiro (fairy rings) soils, and between two main production regions (Bonghwa and Yangyang) of T. matsutake in Korea. We found that both bacterial and fungal diversity was lower in the shiro+ soil than in the shiro− soil at both sites (Tables 2 and 3). For microbial diversity inhabiting the fairy ring, bacterial and fungal diversity was significantly lower in the T. matsutake-dominant soil compared with the T. matsutake minor soil [11]. The bacterial communities in the active mycorrhizal zone of T. matsutake were much simpler than those at locations far away from the shiro [29]. Moreover, the results of metagenomics analysis showed that the fairy ring zone of T. matsutake had the lowest OTUs, bacterial diversity, and evenness in all sampling zones [10]. In the taxonomic analysis of the bacterial community, our results are in part consistent with a previous study by Oh et al. [11], who documented that Acidobacteria and Proteobacteria were significantly higher in the Tm-minor soil. These phyla are abundant in soil environments, but low richness in the Tm-dominant soil could have a negative effect on T. matsutake, such as the competition for resources or secretion of antibiotics to exclude bacteria [32][33][34]. We found that Acidobacteria was more abundant in the shiro− soil than in the shiro+ soil of both sites. However, there is a large proportion of the phylum of Proteobacteria in the shiro+ soil at the Bonghwa site compared with the shiro− soil, whereas, at the Yangyang site, the phylum showed a higher abundance in the shiro− soil than in the shiro+ soil. Moreover, the Actinobacteria community showed the highest abundance in the shiro+ soil compared with the shiro− soil at the Yangyang site, whereas there was no difference between the shiro+ and shiro− soils at the Bonghwa site. Kim et al. [13] showed that Actinobacteria have a high abundance beneath the fairy ring, while some studies suggested that this community was negatively correlated with the activity of T. matsutake [6,8].

Distinct Fungal Community Structure
In this study, the total amounts of fungal OTUs richness of the shiro− soils were, respectively, approximately six (Bonghwa site) and two times (Yangyang site) higher than those of shiro+ soils (Table 3). Our results corroborate previous studies that investigated the decrease in fungal populations in the fairy ring zone of T. matsutake. The total numbers of OTUs and fungal taxa inside and outside the fairy ring zone were higher than those of the fairy ring zone, and the Tm-dominant soil had low fungal richness [9][10][11]. There are some observations that the sites of occurrence of T. matsutake have low fungal diversity, suggesting that the mycelia of T. matsutake form fruiting bodies under little competition with other microorganisms, and/or T. matsutake can secrete antifungal compounds to exclude other fungal species, promoting its own fitness by reducing competitors [10][11][12]35]. In our results of the fungal composition at the phylum level, Basidiomycota showed the greatest proportions in all samples, and it also showed higher relative abundances in the shiro+ soils than in the shiro− soils of both sites, whereas Ascomycota showed high abundance in the shiro− soils compared with the shiro+ soils at both sites. There are two previous studies that are consistent with our results about the dominant class in the fairy ring zone. In one study, Lian et al. [12], who compared fungal communities inside, beneath, and outside the fairy ring zone of T. matsutake, also frequently observed Agricomycetes from phylum Basidiomycota beneath the fairy ring zone. In another study, Buée et al. [36] found that Agaricomycetes was the dominant fungal class in forest soil. However, Oh et al. [11] found that Basidiomycota in OTU richness was significantly higher in the Tm-minor soils than in the Tm-dominant soils. They suggested that the reduction in fungal richness in the Tm-dominant soils may be caused by the dominance of T. matsutake. The results of the differentiation of the phylum Ascomycota community in all samples were consistent with the previous reports by Kim et al. [10] showing that the classes of Dothideomycetes, Leotiomycetes, and Sordariomycetes from phyla Ascomycota showed higher proportions inside and outside the fairy ring than those in the fairy ring zone. In addition to phylum Ascomycota, the phylum with the highest abundance was Mucoromycota in all samples. In the phylum Mucoromycota, Umbelopsis was the most abundantly detected from the shiro+ soil at the Bonghwa site as well as the shiro− soil at the Yangyang site. In the previous study, Umbelopsis was frequently detected from the fruiting body and the fairy ring of T. matsutake [28,37], and Oh et al. [11] suggested that Umbelopsis may have positive interactions with T. matsutake. However, there were some differences between the results of the previous study and those obtained in our study because it was also highly detected in the shiro− soil at the Yangyang site. From our results, it can be assumed that Umbelopsis is not necessarily positively correlated with the occurrence of T. matsutake in the shiro− present in soils.
In our results of the fungal communities, we separated two main assemblages, the ECM and symbiotic fungal assemblages, and another fungal assemblage. The ECM fungi of generas Tylospora, Astraeus, Sistotrema, Russula, Sebacina, and Tomentella thatwere also detected in a coastal pine forest in the eastern region of Korea, were abundantly detected in the shiro− soil at the Bonghwa site [38][39][40][41]. In other fungi assemblages, there are a few fungal genera in the form of saprotrophic fungi groups such as Cladophialophora, penicillium, unidentified Hyaloscyphaceae, and Mortierella [42]. The fungal communities, except for Tricholoma and other ECMs, have lower proportions in the shiro+ soils than those in the shiro− soils at the two sites (B_shiro+. 34.00%; B_shiro−, 74.20%; Y_shiro+, 25.42%; Y_shiro−, 61.74%). According to the report by Kujawska et al. [42], the fungal communities in the soil of forests could be divided into ECM, saprotrophic, pathotrophic, and other fungi assemblages from different trophic groups. They suggested that the fungal communities in forest soils were closely related to different trophic groups, and were similar in abundance and diversity. Consequently, we found a distinguishable compositional pattern in ECM, and other fungi from the shiro+ soils and the shiro− soils at the two sites.

Differences between Microbial Communities
We observed that the similarities of bacterial and fungal communities were relatively low within/across the sampling sites (Table 6). Before we started this study, it was initially expected that the microbial communities between the shiro+ soils of the two sampling sites would be similar to each other. It is well known that T. matsutake had inhibitory effects on soil bacteria and fungi, and it could eliminate the competition for their colonization, the growth of hyphae, and the formation of fruiting bodies. Unexpectedly, our results indicated that the similarity in the bacterial communities between the shiro+ soil of Bonghwa and the shiro− soil of Yangyang showed the highest similarity, whereas the lowest similarity was observed between the shiro− soil of Bonghwa and the shiro+ soil, or the shiro− soil of Yangyang. In addition, the fungal community also differed within/across the samples and sites. The fungal communities between the shiro+ soils at the Bonghwa and Yangyang sites have the lowest community similarity among the samples. However, this could be divided into two main fungal assemblages. For one assemblage of ECM except for unknown fungi, the similarity of ECM communities showed the highest value in the shiro− soils at the two sites (0.857). In a previous study by Kujawska et al. [42], the re-assembly of the soil fungal community at the trophic level could be a strong stochastic component to overcome a general reduction in the similarity of the community composition between different regions.
Overall, the simplest explanations for our results showing low similarity between microbial communities within/across the site are as follows. First, in this study, soil samples containing shiro+ and shiro− were only collected once from each site, which was insufficient to compare microbial communities between each site. This was different from sampling many points without favorable permission from farmers. In Korea, a stranger entering a mountain has generally been taboo among villagers of rural communities due to the fear it will result in a bad harvest for T. matsutake that year. Second, the annual mean temperature and annual precipitation of the Yangyang site were slightly higher than those of the Bonghwa site. The changes in climate related to temperature and precipita-tion influence the changes of microbial communities because the climate changes lead to consequences for the changes of plant communities [43,44]. Ectomycorrhizal fungal species, which are host-dependent symbiotic fungi, are also closely related to changes in climate [44,45]. T. matsutake and truffle, which are ectomycorrhizal mushrooms with high ecological and economic values, are the most sensitive to changes in environmental conditions. Yang et al. [46] reported that high temperature and high precipitation in August were correlated with the high productivity of fruiting bodies. Cejka et al. [44] demonstrated that precipitation is the most important factor for truffle production with drought events reducing truffle yields. We assumed that if climate changes caused changes in vegetation and microbial communities, and changes in vegetation and microbial communities are directly or indirectly affected by the formation of fruiting bodies of T. matsutake, the microbial community may also differ even if there are the same shiro+ soils in different regions. Third, an important environmental factor-soil properties-influence the microbial community. It is well known that the soil environment adjacent to T. matsutake had a lower organic content, and a higher CEC content [10,47], but there is still a large amount of controversy about whether T. matsutake prefers soils containing a low organic matter content or an organic soil content changed by T. matsutake [10]. Although the relationship between the formation of fruiting bodies of T. matsutake and soil properties is still unknown, the impact on microbial communities, diversity, and relative abundance is positively correlated with soil properties [48][49][50]. Moreover, the report by Kujawska et al. [42] showed that fungal communities differed from trophic groups, soil pH significantly influenced ectomycorrhizal fungal communities, and the volume of coarse woody debris and soil nitrate concentration influenced the saprotrophic fungi community [42]. However, the climate factors and soil properties of the two sites were not measured in this study. Fourth, this study investigated overall bacterial and fungal communities in the production (shiro+) and nonproduction (shiro−) soils of T. matsutake using the Illumina sequencing method. This technology has the advantage of acquiring high-throughput data more quickly for the assessment of microbial communities although there was a limitation in that it produced short read lengths of sequence [10,11,13]. To achieve the accurate assessment of microbial communities, it may be necessary to combine the massive throughput of the next-generation sequencer with the long read lengths by electrophoresis-based methods in Sanger sequencing [10,51]. Nevertheless, it is clear that our results may provide important information to contribute toward an expanding foundation for knowledge on the microbial community in habitats of T. matsutake. Based on the results of this study, further studies of both the microbial communities and abiotic factors in various sites and regions are needed. Furthermore, we expect that it will be the cornerstone for identifying differences in microbial community structure among T. matsutake production soils within/across sites.

Conclusions
We compared bacterial and fungal communities in T. matsutake production (shiro+) and nonproduction (shiro−) soils in two different regions using the Illumina Miseq sequencing platform. The shiro+ soils showed less OTUs and lower bacterial and fungal diversity than the shiro− soils. The similarity within the microbial communities of shiro+ samples was not significant. However, the similarity of fungal communities was affected by their trophic assembly. This suggested that abiotic and biotic factors are important factors that can determine not only the richness of the microbial community but also the quality of the microbial community structure. Further studies are needed to incorporate more diverse samples collected from multiple sites in different seasons. In addition, abiotic factors, such as soil characters, temperature, and humidity should also be synthetically considered. Therefore, the similarity between microbial communities may be due to the fact that the microbial communities in the T. matsutake-dominant soils are closely associated with abiotic factors and biotic factors. Our study may contribute to future studies where the number of study sites is sufficient for understanding the traits of microbial community structures in T. matsutake production soils.