Effects of Dark Septate Endophytes Strain A024 on Damping-off Biocontrol, Plant Growth and the Rhizosphere Soil Enviroment of Pinus sylvestris var. mongolica Annual Seedlings

Dark septate endophytes (DSEs) exert a vital role in promoting plant growth, improving mineral absorption, biological disease control, and enhancing plant stress resistance. The effects of dark septate endophyte strain, Phialocephala bamuru A024 on damping-off biocontrol, plant development, nutrients within the rhizosphere soil, as well as bacterial communities in the annual seedlings of P. sylvestris var. Mongolica were studied. According to our findings, following P. bamuru A024 inoculation, the damping-off disease morbidity decreased significantly compared with control, some physiological indices such as β-1,3-glucanase, chitinase enzyme activity as well as a soluble protein and proline content in P. sylvestris var. mongolica were elevated under R. solani stress. After inoculation with P. bamuru A024, the biomass in seedlings, nutrients in soil, root structure index, together with activities of soil enzymes were remarkably up-regulated relative to control (p < 0.05). As suggested by the results of high-throughput sequencing, the microbial structure in the rhizosphere soil of the P. sylvestris var. mongolica showed significant differences (p < 0.05) after P. bamuru A024 inoculation compared to control treatment and the rhizosphere soil bacterial community structure after DSE A024 inoculation was positively correlated to the main soil nutrition indices.


Introduction
Plant endophytes widely exist in plants [1]. Dark septate endophytes (DSE) represent a major group on endophytes within plants characterized by a dark mycelium color and distinct septum. They colonize the epidermis, cortex, and even the intercellular space of vascular tissue of healthy plant roots to form symbionts without causing plant diseases [2,3]. The host range of dark septate endophytic fungi covers nearly 600 species of plants from 114 families and 320 genera. DSE colonization has been found in mycorrhizal plants as well as roots of traditional non-mycorrhizal plants such as Cyperaceae, Cruciferae, and Chenopodiaceae [4]. In conifers, the main DSE fungi are the group of the Phialocephala fortinii s.l.-acephala applanata species complex (PAC) belonging to the ascomycetes. PACs can be found in the Northern Hemisphere from polar to tropical areas and play a leading role in the root system of conifers [5,6]. Several studies have reported that DSE fungi exhibit a positive effect on plant growth [7][8][9][10]. They enhance the mineralization process of insoluble phosphorus in soil [11,12], promote the uptake and utilization of nutrients like nitrogen (N) or phosphorus (P) by the plants [13] and increase the stress

Design of Experiments and Inoculation of Seedlings
In each treatment (also for control), 20 pots (about 10 seedlings/pot) were selected so altogether 200 seedlings were prepared in each treatment. The four treatments included: (1) inoculation with sterile cottonseed shell medium (CK); (2) P. bamuru A024 (DSE) inoculation alone; (3) R. solani SH01 (CK + SH) inoculation alone; and (4) inoculation with P. bamuru A024 and R. solani SH01 (DSE + SH). One month after sowing, the seedlings of P. sylvestris var. mongolica were incubated using the pathogen (50 mL per pot), spread flat around to the seedlings. Each treatment was randomly assigned in the greenhouse environment, as mentioned previously.

Damping-Off Control Together with Physiological Index Determination
Damping-off rate in seedlings was investigated after 45 days of inoculation with R. solani SH01, and the relative control effect was also calculated. The survival rate of seedlings was counted three months after sowing. About 100 seedlings were investigated per treatment.
Forty five days after inoculation with R. solani SH01, 40 P. sylvestris var. mongolica seedlings were collected for the physiological index measurements. The roots of seedlings were rinsed using sterile water, then sterile filter paper was used to absorb excess water. The seedlings were further cut into 1 cm pieces, ground in liquid nitrogen and transferred to a 5 mL centrifuge tube. An acid ninhydrin colorimetry approach was applied to measure proline. The thiobarbituric acid chromogenic method was applied to measure malonaldehyde (MDA) content. Anthrone colorimetry was applied in measuring soluble sugar content. The Coomassie brilliant blue G-250 staining method was applied to measure soluble protein content. The nitroblue tetrazolium colorimetry approach was applied to measure superoxide dismutase (SOD) activity. The guaiacol method was applied to measure peroxidase (POD) activity. A hydrogen peroxide ultraviolet absorption method was applied to measure catalase (CAT) activity. The 3,5-dinitrosalicylic acid (DNS) method was applied to measure chitinase activity. The reducing sugar colorimetry method was applied to measure β-1,3-glucanase activity. The deamination of phenylalanine method was applied to measure phenylalanine ammonia lyase (PAL) activity. All the above indices were determined with detection kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).

Sample Collection and Seedling Analysis
At 3 months after sowing, all seedlings were collected, and soil was carefully removed by washing so as to not damage the root system. Altogether 100 seedlings were randomized for every treatment, among which the initial 30 seedlings were adopted for measuring biomass indexes. In every seedling, the biomass indexes included plant height, dry weight, fresh weight upon collection, and ground level diameter. After measuring fresh weight, seedlings were dried in an oven for 5 h under 85 • C to measure their dry weight [36].
When sampling, after washing the root system to remove the soil trying to not damage the roots system of seedlings, 10 seedlings were randomly selected and an Epson v700 root scanner (Seiko Epson Corporation, Nagano, Japan) was used to scan and grade the root system of the seedlings. The indexes of mean diameter, root tip number, bifurcation number, root volume, root length and surface area were thus analyzed.

Soil Character Analysis
Soil was sampled from the place where the 100 seedlings were harvested for each treatment. Rhizosphere soil samples were obtained within the root zone at a depth of 5 mm by using a brush and then filtered by a 1-mm mesh sieve. Thereafter, those soil samples adopted for measuring enzymatic activities and determining physicochemical characters were dried in the air at 25 • C, packaged in the sterile sample bags, and finally preserved at 5 • C for later analyses.
The Kjeldahl approach was applied in measuring total nitrogen (TN) and the alkaline hydrolysis diffusion assay was conducted to determine the available nitrogen (AN). After sulfuric acid digestion, total phosphorus (TP) was determined by the anti-colorimetry of MO-SB method and total potassium (TK) was determined by flame photometry. The sulfuric acid-hydrochloric acid (double acid) extraction and anti-colorimetry of MO-SB method was applied to measure available phosphorus (AP). NH 4 OAc leaching and flame photometry was used to determine available potassium (AK). In addition, the potassium dichromate oxidation-external heating approach was employed for measuring organic matter (OM). The soil pH (1:2.5) was determined by using a pH meter [37]. The sodium phenol colorimetry approach was employed to measure urease activity. The glucose colorimetry approach was employed to measure saccharase activity. The disodium phenylphosphate colorimetry approach was employed to measure acid phosphatase activity. The hydrogen peroxide ultraviolet absorption method was applied to measure catalase activity. These four soil enzyme activities were determined using detection kits (Nanjing Jiancheng Bioengineering Institute).

Analysis of Bacterial Diversities
Rhizosphere soils were sampled according to the abovementioned method, then a 5.0 g sample was prepared for each biological replicate, which was put into a 50 mL sterilized centrifuge tube before it was sent to our laboratory in a cooler containing ice bags. In addition, soil that was utilized in high-throughput sequencing was preserved in a centrifuge tube at -80 • C for further assessment.
Then, total genome DNA was extracted from the 0.5 g soil sample using the EZNA Soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA) in accordance with manufacturer's protocol. The sample was then subjected to high-throughput sequencing for soil microbiota. Thereafter, 100 µL elution solution was obtained from the literature to elute the obtained DNA. The DNA quality (A 260 /A 280 ) and content were determined using a NanoDrop2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA). All treatments were repeated three times. Meanwhile, the 16S rRNA region was subjected to high-throughput sequencing for determining the bacterial community in the soil. The V3 + V4 region in the 16S rRNA gene of bacteria was amplified using the universal 338F (5 -ACTCCTACGGAGGCAGCAG-3 ) and 806R (5 -GGACTA CHVGGGTWTCTAAT-3 ) primers.

Data Analyses
WPS 2016 (Kingsoft Corporation, Beijing, China) was adopted to process data. Differences in index of root structure, biomass of plant, soil pH, soil enzymes and chemical characteristics were analyzed through one-way ANOVA (Tukey test) by adopting IBM SPSS 22.0 (IBM Corporation, New York, NY, USA). Moreover, correlation analysis was conducted by Pearson's approach. A difference of p < 0.05 indicated statistical significance.
The Mothur software (The University of Michigan, Michigan, MI, USA) was used for analyzing α-diversity indexes as well as rarefaction. At the same time, the sequencing depth was represented by the coverage index. Moreover, both Ace and Chao1 indices were adopted for describing abundances of microbiota, whereas Shannon and Simpson indices were applied in representing species richness as well as microbial community diversity. Unifrac distance was calculated to compare the bacterial β-diversity. Differences in the phylum and genus relative abundance between four treatments were analyzed through one-way ANOVA (Tukey test) by adopting IBM SPSS 22.0. Environmental factor correlation was analyzed using RDA methods. The Origin 2019b (Origin Lab Corporation, Northampton, MA, USA) software was employed for figure generation.

Damping-Off Control and Physiological Index Determination
The incidence rate of damping-off was 28.15%, and the survival rate was 80.15% with DSE + SH treatment. Conversely, the incidence rate of damping-off with CK + SH treatment was 72.15%, and the survival rate was 33.35%. The relative control effect of P. bamuru A024 treatment against the damping-off disease was 60.98%. Thus, the inoculation of strain P. bamuru A024 can effectively control the damping-off lesions resulting from exposure to R. solani. P. bamuru A024 and R. solani inoculation affected the main physiological indices in the seedlings for P. sylvestris var. mongolica (Table 1). Differences between control (CK) and P. bamuru A024 treatments (DSE) were statistically significant (p < 0.05). The chitinase, CAT and POD activity as well as soluble protein content of the seedlings from the P. bamuru A024 treatment were increased by 63.21%, 59.45%, 149.63% and 49.49%, separately, relative to control treatment. Following R. solani inoculation, differences between control (CK + SH) and P. bamuru A024 treatments (DSE + SH) were statistically significant (p < 0.05). β-1,3-Glucanase and chitinase activity, together with the contents of proline and soluble protein in seedlings from DSE + SH treatment increased by 18.41%, 92.54%, 101.27% and 30.48%, respectively, in comparison to the CK + SH treatment. However, differences in SOD, CAT, POD and PAL activity, as well as MDA and soluble sugar contents between CK + SH and DSE + SH groups were not significant.

Height of Seedlings
Dark septate endophytes strain, P. bamuru A024 inoculation, accelerated seedling growth ( Figure 1), as observed based on significant differences in height between different treatments and control (p < 0.05). However, the difference between DSE treatment and DSE + SH treatment showed no significance (p ≥ 0.05). The seedling heights under DSE and DSE + SH treatments were increased by 17.31% and 13.94%, separately, compared with control treatment.

Seedling Diameter
Differences in seedling diameter among DSE, DSE + SH, and CK treatment groups were not significant (p ≥ 0.05). However, differences among DSE, DSE + SH, and CK + SH treatment groups were significant (p < 0.05). Seedling diameters under DSE and DSE + SH treatments were increased by 21.49% and 15.71%, separately, compared with CK + SH treatment.

Seedling Biomass
Fresh Weight There were significant differences between DSE, DSE + SH groups, and CK, CK + SH groups (p < 0.05) for the seedlings' fresh underground weight. The fresh underground weight of seedlings from DSE and DSE + SH treatments was increased by 62.91% and 39.51% compared to the CK treatment, respectively. For the above-ground fresh weight, differences among DSE, DSE + SH, CK, CK + SH groups were significant. The fresh above-ground weight of seedlings from DSE treatment increased by 12.09% compared to CK treatment.

Dry Weight
There were significant differences in both the under-and above-ground dry weights of seedlings between all the treatments. The under-and above-ground dry weight of DSE treatment increased by 40.74% and 10.44% compared to the CK treatment, respectively.

DSE Strain Inoculation Effect on Seedling Root Structures
Several parameters, such as surface area and root length, play vital roles in determining root distribution. In contrast, tip number, fork number, root volume and average root diameter exert vital parts in determining the absorption efficiency of roots. It can be found from the data listed in Table 2 and illustrated in Figure 2 that inoculation with P. bamuru A024 dramatically enhanced the root system parameters including root surface area, fork number, root length and volume in comparison with control (p < 0.05).   The differences in the above indexes showed no significance between DSE and DSE + SH treatments, except for the tip number index. This result indicates that R. solani made no obvious difference to P. sylvestris var. mongolica root structure after P. bamuru A024 inoculation. However, there were significant differences after the CK and CK + SH treatment for all root structure indices except average diameter, indicating that a single inoculation with R. solani has a significant impact on the root structure. In addition, the root index values in CK + SH treatment were lower than that of CK group. In comparison with CK group, DSE and DSE + SH groups showed increased root length by 19.13% and 15.53%, root surface area by 17.41%, and 22.29%, root volume by 17.98% and 24.25%,  The differences in the above indexes showed no significance between DSE and DSE + SH treatments, except for the tip number index. This result indicates that R. solani made no obvious difference to P. sylvestris var. mongolica root structure after P. bamuru A024 inoculation. However, there were significant differences after the CK and CK + SH treatment for all root structure indices except average diameter, indicating that a single inoculation with R. solani has a significant impact on the root structure. In addition, the root index values in CK + SH treatment were lower than that of CK group. In comparison with CK group, DSE and DSE + SH groups showed increased root length by 19.13% and 15.53%, root surface area by 17.41%, and 22.29%, root volume by 17.98% and 24.25%, root forks number by 16.34% and 33.03%, respectively.

DSE Inoculation Impacts on the Rhizosphere Soil Physicochemical Characteristics in the Seedlings
It is observed from Table 3 that differences among four treatments were significant (p < 0.05). DSE treatment significantly increased the soil nutrient content compared to CK treatment. The soil nutrient index includes OM, TN, AN, TP, AP, TK, AK, that increased by 10.96%, 12.16%, 57.57%, 32.53%, 103.84%, 33.11% and 23.52%, respectively. R. solani inoculation (DSE + SH treatment) decreased the effect of DSE treatment of raising the nutrient index. However, compared to the CK + SH treatment, the soil nutrient index that includes TP, AP, and AK increased by 15.07%, 34.61%, and 32.35%, respectively. The effect of DSE inoculation on AN, AP, and AK improvement was more significant than TN, TP, and TK. It is possibly because that DSE can degrade the macromolecular nutrients in soils to the effective state to be used for plants, which thus accelerates the energy flow and nutrient recycling in soil.

DSE Inoculation Impacts on Enzyme Activities in the Rhizosphere Soil
The soil-borne enzymes that make up the organic components with the highest activity of biochemical processes of soil mostly come from secretions by animals, plants, or soil microorganisms. They exert a vital role in circulating soil OM and conserving energy.
According to Table 3, P. bamuru A024 inoculation significantly elevated several enzyme activities in seedling rhizosphere soil. In comparison to CK treatment, activities of CAT, urease, and acid phosphatase under DSE treatment increased by 12.97%, 20.93% and 19.67%, respectively. Additionally, catalase, urease, and protease of soil from DSE + SH treatment increased by 16.64%, 20.22%, and 38.57%, respectively. As suggested by the above findings, P. bamuru A024 exerted a vital role in soil energy flow and nutrient circulation, which also significantly promoted the nutrient circulation and activities of soil enzymes.
Pearson's analysis assessed the correlations of biomass index with soil physicochemical characters ( Table 4). TN indices showed a significant positive correlation with the total dry weight and the fresh underground weight. TP showed a significant positive correlation with above-ground dry weight, fresh underground weight, total dry weight, and underground dry weight. AP displayed a significant positive correlation with total dry weight, whereas the AK displayed a significant positive correlation with underground dry weight and total dry weight.  Altogether 444,738 bacterial sequences were acquired based on twelve blended soil samples from the four treatment groups by using the Illumina MiSeq PE300 platform. On the whole, following isolation and removal, this study acquired 1944 bacterial OTUs from clustering, with the similarity threshold of 97%. Those representative bacterial OTUs for DSE, DSE + SH, CK, as well as CK + SH treatments were 64, 38, 23, and 31, separately. In addition, DSE, DSE + SH, CK, and CK + SH treatments held 1174 common OTUs; whereas CK and DSE treatments held 1752 common OTUs, and DSE and DSE + SH treatments held 1638 OTUs (Figure 3).

Soil Microbial Distribution
According to categorical analysis on the typical OTUs sequences at a similarity threshold of 97%, altogether 32 phylum, 32 classes, 72 orders, 137 families, 252 genera, and 448 species of soil bacteria were detected. As showed in Table 5, the main bacterial phyla within the rhizosphere soil of the seedlings of P. sylvestris var. mongolica include Proteobacteria, Saccharibacteria, Actinobacteria, Gemmatimonadetes, Bacteroidetes, Chloroflexi, Acidobacteria, Firmicutes, Parcubacteria, Verrucomicrobia, Planctomycetes, and Cyanobacteria. Among them, the relative abundance of the Proteobacteria phylum was highest in all four treatments, CK, CK + SH, DSE, and DSE + SH, which were 44.01%, 39.55%, 42.63%, and 45.92%, respectively. There was no significant difference between the four treatments and the relative abundance of Proteobacteria, Acidobacteria, Parcubacteria, Verrucomicrobia, Planctomycetes, and Cyanobacteria phylum. The relative abundance of the Actinobacteria, Gemmatimonadetes were higher in CK and CK + SH treatments, whereas Bacteroidetes, Chloroflexi and Firmicutes were higher in DSE and DSE + SH treatments.The bacterial phylum with significant differences in relative abundance, that is, Gemmatimonadetes and and Actinobacteria were found higher in CK (10.78%) and CK + SH (14.32%) treatments. In contrast, Saccharibacteria (15.11%), Bacteroidetes (8.30%), and Chloroflexi (5.28%) were higher in DSE treatment, and Firmicutes were higher in DSE + SH treatment with 6.91%. The difference between the major bacterial phylum in different treatments indicated that DSE inoculation had little effect on the Proteobacteria phylum with the highest relative abundance but has a significant impact on the relative abundance of some other major bacterial phylum.

Sequencing Results for Soil Samples and Validation of Sampling Depth
Altogether 444,738 bacterial sequences were acquired based on twelve blended soil samples from the four treatment groups by using the Illumina MiSeq PE300 platform. On the whole, following isolation and removal, this study acquired 1944 bacterial OTUs from clustering, with the similarity threshold of 97%. Those representative bacterial OTUs for DSE, DSE + SH, CK, as well as CK + SH treatments were 64, 38, 23, and 31, separately. In addition, DSE, DSE + SH, CK, and CK + SH treatments held 1174 common OTUs; whereas CK and DSE treatments held 1752 common OTUs, and DSE and DSE + SH treatments held 1638 OTUs (Figure 3).

Soil Microbial Distribution
According to categorical analysis on the typical OTUs sequences at a similarity threshold of 97%, altogether 32 phylum, 32 classes, 72 orders, 137 families, 252 genera, and 448 species of soil bacteria were detected. As showed in Table 5, the main bacterial phyla within the rhizosphere soil of the seedlings of P. sylvestris var. mongolica include Proteobacteria, Saccharibacteria, Actinobacteria, Gemmatimonadetes, Bacteroidetes, Chloroflexi, Acidobacteria, Firmicutes, Parcubacteria, Verrucomicrobia, Planctomycetes, and Cyanobacteria. Among them, the relative abundance of the Proteobacteria phylum was highest in all four treatments, CK, CK + SH, DSE, and DSE + SH, which were 44.01%, 39.55%, 42.63%, and 45.92%, respectively. There was no significant difference between the four treatments and the relative abundance of Proteobacteria, Acidobacteria, Parcubacteria, Verrucomicrobia, Planctomycetes, and Cyanobacteria phylum. The relative abundance of the Actinobacteria, Gemmatimonadetes were higher in CK and CK + SH treatments, whereas Bacteroidetes, Chloroflexi and Firmicutes were higher in DSE and DSE + SH treatments.The bacterial phylum with significant differences in relative abundance, that is, Gemmatimonadetes and and Actinobacteria were found higher in CK (10.78%) and CK + SH (14.32%) treatments. In contrast, Saccharibacteria (15.11%), Bacteroidetes (8.30%), and Chloroflexi (5.28%) were higher in DSE treatment, and Firmicutes were higher in DSE + SH treatment with 6.91%. The difference between the  Pearson's analysis assessed the correlations of bacterial phylum with the physicochemical characters in soil (Table 6). Four bacterial phyla, including Actinobacteria, Gemmatimonadetes, Bacteroidetes, and Firmicutes, were significantly correlated with soil physicochemical properties. Actinobacteria showed a significant negative correlation with TN, TP, AP, AK and OM and a significant positive correlation with TK. Bacteroidetes displayed a significant positive correlation with OM and Plants 2020, 9, 913 11 of 19 AK, while Firmicutes showed a significant positive correlation with AP, TN and TP, but significant negative correlation with TK. Bacteroidetes and Firmicutes had the highest relative abundance in DSE treatment compared to other treatments. Conversely, Actinobacteria and Gemmatimonadetes had a higher relative abundance in CK treatment than other treatments.  This indicated that after dark septate endophytes inoculation, the bacterial phylum that showed an increase in its relative abundance has a positive effect on improving the rhizosphere nutrients of Pinus sylvestris var. mongolica.
This study identified altogether 252 bacterial genera under four treatments. One-way ANOVA analysis was used for testing the significant difference between bacterial genera and diverse treatments, followed by the post-hoc test to find the sample groups with differences in the multiple groups ( Figure 4). The analysis of the top 20 genera with significant differences showed that DSE treatment could change relative abundances for rhizosphere bacterial genera. Typically, relative abundances of norank_p_Saccharibacteria, Massilia, Rhizobium, Bacillus, Tumebacillus, Dongia, Norank_f_Blrii41 and Bradyrhizobium were higher in DSE treatments (DSE and DSE + SH), in contrast, the relative abundance of Streptomyces, Gemmatimonas, Ramlibacter, Sphingomonas, Bryobacter, norank_o_Acidimicrobiales was higher in CK treatments (CK and CK + SH).

α-Diversity Analysis
ANOVA was carried out on 16S rDNA diversity indexes for soil samples under CK, CK + SH, DSE, and DSE + SH treatments (Table 7). According to Table 3, although those coverage indices under K, CK + SH, DSE, and DSE + SH treatments approached 1, no significant difference was found. Based on the above results, our sequencing results might be used to precisely represent the real soil samples conditions. As for Chao1 and Ace indices, they followed the orders of DSE > CK and DSE + SH > CK + SH under different treatments, and apparent differences were detected under CK treatment compared with the other three treatments (p < 0.05). This indicates increased total bacterial community number as well as richness under the DSE treatment relative to the others, including CK treatment. Differences in Simpson index among CK, CK + SH, DSE, and DSE + SH groups were not significant. As for the Shannon index, it followed the order of DSE > CK, CK + SH, and DSE + SH, and differences of DSE were significant compared with other three treatments. These results showed that DSE significantly affected rhizosphere soil bacterial richness of P. sylvestris var. mongolica, but less on diversity.

α-Diversity Analysis
ANOVA was carried out on 16S rDNA diversity indexes for soil samples under CK, CK + SH, DSE, and DSE + SH treatments (Table 7). According to Table 3, although those coverage indices under K, CK + SH, DSE, and DSE + SH treatments approached 1, no significant difference was found. Based on the above results, our sequencing results might be used to precisely represent the real soil samples conditions. As for Chao1 and Ace indices, they followed the orders of DSE > CK and DSE + SH > CK + SH under different treatments, and apparent differences were detected under CK treatment compared with the other three treatments (p < 0.05). This indicates increased total bacterial community number as well as richness under the DSE treatment relative to the others, including CK treatment. Differences in Simpson index among CK, CK + SH, DSE, and DSE + SH groups were not significant. As for the Shannon index, it followed the order of DSE > CK, CK + SH, and DSE + SH, and differences of DSE were significant compared with other three treatments. These results showed

β-Diversity Analysis
Differences in bacterial communities of different soil samples were measured through the Bray-Curtis matrix. According to Figure 5, CK and CK + SH, DSE, and DSE + SH groups were divided into three parts, which showed distribution among diverse quadrants. The great distribution distance represented the great differences in composition in the three parts that included CK and CK + SH, DSE, DSE + SH samples. As figured out from this result, there were more differences in soil bacterial communities among CK and CK + SH, DSE, and DSE + SH treatments than those under each treatment (R = 1), with significant differences (p = 0.003).

β-Diversity Analysis
Differences in bacterial communities of different soil samples were measured through the Bray-Curtis matrix. According to Figure 5, CK and CK + SH, DSE, and DSE + SH groups were divided into three parts, which showed distribution among diverse quadrants. The great distribution distance represented the great differences in composition in the three parts that included CK and CK + SH, DSE, DSE + SH samples. As figured out from this result, there were more differences in soil bacterial communities among CK and CK + SH, DSE, and DSE + SH treatments than those under each treatment (R = 1), with significant differences (p = 0.003).  3.6.5. Environmental Factor Correlation Analysis DSE inoculation changes the bacterial community structures and environmental characteristics. Soil geochemical characteristics may primarily mediate the effect of DSE inoculation on bacterial communities. Therefore, this study investigated whether bacterial community structure and ecological characteristics are related. Redundancy analysis (RDA) was carried out for 30 bacterial genera with significant differences and the environmental variables that include soil pH, TN, OM, TP, TK, AK, AP, and AN. It is shown in Figure 6 that RDA was carried out to assess those associations of bacterial community structure with a variety of environmental factors by displaying samples in scattered form, quadrant distribution, and the arrow direction and length. RDA analysis showed that 70% of the information regarding the community structure were interpreted using eight environmental factors, among which 46.76% of the variation was explained by RDA1 and 23.53% by RDA2. RDA revealed that the primary environmental characteristics formed the microbial community structure. The environmental factors that showed a high correlation with the composition of the bacterial community of DSE and DSE + SH treatments soil samples were AN, OM, AP, AK, TN, TP, and pH. The environmental factor that showed a high correlation with the composition of the bacterial community structure of CK and CK + SH treatments soil samples was TK.
In addition, the environmental factors AN, OM, AP, AK, TN, TP, pH were positively correlated with each other. scattered form, quadrant distribution, and the arrow direction and length. RDA analysis showed that 70% of the information regarding the community structure were interpreted using eight environmental factors, among which 46.76% of the variation was explained by RDA1 and 23.53% by RDA2. RDA revealed that the primary environmental characteristics formed the microbial community structure. The environmental factors that showed a high correlation with the composition of the bacterial community of DSE and DSE + SH treatments soil samples were AN, OM, AP, AK, TN, TP, and pH. The environmental factor that showed a high correlation with the composition of the bacterial community structure of CK and CK + SH treatments soil samples was TK. In addition, the environmental factors AN, OM, AP, AK, TN, TP, pH were positively correlated with each other.

Discussion
The plant rhizosphere is a complex micro-ecological system wherein the interaction between beneficial microorganisms and host plants can promote the growth and stress resistance of plants. Dark septate endophytes (DSEs) can colonize the cortex and epidermis spaces inside and outside cells, or even the vessel tissue of healthy plant roots, to form symbionts. DSEs play an important part in promoting plant development and enhancing nutrient absorption, along with stress resistance. Strain A024 isolated and screened from the roots of P. sylvestris var. Mongolica was found to effectively suppress R. solani in vitro (unpublished data). To further study the interaction mechanism between the strain A024 and P. sylvestris var. mongolica and its control effect on R. solani, we have mainly

Discussion
The plant rhizosphere is a complex micro-ecological system wherein the interaction between beneficial microorganisms and host plants can promote the growth and stress resistance of plants. Dark septate endophytes (DSEs) can colonize the cortex and epidermis spaces inside and outside cells, or even the vessel tissue of healthy plant roots, to form symbionts. DSEs play an important part in promoting plant development and enhancing nutrient absorption, along with stress resistance. Strain A024 isolated and screened from the roots of P. sylvestris var. Mongolica was found to effectively suppress R. solani in vitro (unpublished data). To further study the interaction mechanism between the strain A024 and P. sylvestris var. mongolica and its control effect on R. solani, we have mainly focused on: (1) The control effect of strain A024 on R. solani; (2) the effect on promoting P. sylvestris var. mongolica; (3) the impacts on microbial community structure in rhizosphere soil.
This study reported a damping-off rate of 28.15% and a survival rate of 80.15% for DSE + SH treatment. Whereas for CK + SH treatment, the incidence rate of damping-off was 72.15%, and the survival rate was 33.35%. However, the relative control effect of strain A024 treatment against damping-off was 60.98%. These results of the seedling inoculation test showed that P. bamuru A024 could effectively control the occurrence of damping-off caused by R. solani on P. sylvestris var. mongolica seedlings. These results are similar to those of other Phialocephala studies. Christoph [34] isolated 85 PAC strains from Norway spruce (Picea abies) roots, among which P. europaea dramatically decreased Phytophthora citricola growth in vitro. The main inhibitory agents were identified as sclerotinin A and B, sclerolide, and sclerin, however, no seedling inoculation test was done. The result of the sterile seedlings inoculation experiment done by Terhonen indicated that P. sphareoides could prevented Norway spruce seedling root infection by the pathogen, Heterobasidion parviporum under in-vitro conditions. These results indicated that DSE fungi could colonize the host root system and effectively inhibit the occurrence of soil-borne diseases. Beside this, DSE fungi can also enhance seedlings' disease resistance against soil borne pathogens. In our research, under the stress of R. solani, the β-1,3-glucanase and chitinase activity, together with the contents of proline and soluble protein in seedlings from DSE + SH treatment increased by 18.41%, 92.54%, 101.27% and 30.48% respectively in comparison to the CK + SH treatment (Table 1). Su [41] found that the DSE strain Harpophora oryzae enhanced disease resistance in rice and reduced root blast disease caused by Magnaporthe oryzae by up-regulation of expression of key genes of salicylic acid (SA) signaling pathway. Therefore, improving plant resistance is one of the main reasons to reduce the occurrence of soil-borne disease.
Dark septate endophytes (DSE) also has an effect on plant growth. The direct effects include promoted plant growth, an increase in biomass, as well as boosting the root structure and development of plants. In our research, dark septate endophytes strain A024 enhanced annual seedling growth, compared to CK treatment, underground and aboveground fresh weight, seedling height, aboveground and underground dry weight of seedlings from DSE treatment increased by 17.31%, 62.91%, 12.09%, 40.74%, 10.43%, respectively. Similarly, fresh underground weight, ground diameter, seedling height, underground and aboveground dry weights under DSE + SH treatment increased by 15.82%, 15.71%, 43.43%, 36.11%, 36.11%, and 20.83%, respectively, compared to CK + SH treatment ( Figure 1). These results indicated that DSE has an effect on plant growth even under the stress of R. solani. Andrade [42] inoculated tomato plants with Leptodontidium orchidicola liquid inoculum, that increased the biomass by 20%, and number of fruits by two-fold, in comparison with control. The same result was found in an experiment that involved inoculation of Harpophora radicicola with Vulpia ciliate [43]. DSE fungi can secrete a variety of extracellular hydrolases, such as amylase, pectinase, laccase, cellulase, lipase, protease, tyrosinase, polyphenol oxidase, and xylanase. Thus, the presence of a variety of hydrolases ensures the utilization of various nutrients [44]. Dark septate root endophytic fungi, Phialocephala fortinii, increased the growth of the seedlings for Scots pine in the presence of increased CO 2 content via enhancing the utilization efficiency of nitrogen [45]. Surface area and root length account for the vital factors to measure root distribution, meanwhile, root volume, average root diameter, fork number and tip number are also the vital factors to measure the absorption efficiency of root. Inoculation with DSEs can regulate the plant root architecture and facilitate the growth of root systems. In our research, DSE A024 significantly (p < 0.05) enhanced root volume and length, fork number and root surface area in P. sylvestris var. mongolica in comparison with control treatment. Although, differences in the root architecture indexes were not significant between DSE and DSE + SH treatments, but CK and CK + SH treatments showed a significant difference (Table 2 and Figure 2). These results showed that DSE inoculation could counteract the negative effect of the pathogen on the root structure. The change of root structure promoted the growth of annual seedlings.These results are similar to other studies, Li [46] inoculated Leptosphaeria sp., knufia sp., and Darksidea sp., with A. mongolicus, and the plant root biomass and length remarkably elevated compared to control. P. graminicola inoculation can also change the specific root length, root diameter, and root hair number of Vulpia ciliata ssp. Ambigua [47].
A number of soil nutrient elements show low or no solubility, thus limiting soil nutrient circulation [48,49]. The existence of P and N within soil limits absorption and utilization efficiency of plants. Conversion of these organic nutrients to the inorganic ones to be easily taken up by plants depends on the microbes-derived extracellular enzymes, such as bacteria or fungi. DSE can improve the efficiency of plant uptake and utilization of soil nutrients. In our research, the seedlings of P. sylvestris var. mongolica, rhizosphere soil nutrient indices including AN, TP, AP, TK, AK increased by 57.57%, 32.53%, 103.84%, 33.11%, and 23.52%, respectively under the DSE treatment compared to the CK treatment (Table 3). Soil enzymes play a vital part in conserving energy and circulating organic matter in soil. P. bamuru A024 inoculation significantly elevated enzyme activities in seedling rhizosphere soil. In comparison to CK treatment, activities of catalase, urease, and acid phosphatase under DSE treatment increased by 12.97%, 20.93% and 19.67%, respectively (Table 3). Therefore, DSE can improve the content of soil available K and P, thereby improving plant absorption efficiency while increasing