Rhizosphere microbes play important roles for sustaining ecosystems. For example, they accelerate phytoremediation processes and enhance plant ecosystem productivity [23]. Microbes inhabiting rhizospheres help plants grow and function more effectively through bolstering water retention, disease resistance, and nutrient acquisition [24]. Many studies have also shown that rhizosphere microbes promote soil remediation and restoration. Crops have been observed to reduce salt content and increase bacterial rhizosphere diversity in coastal saline soils, improving soil quality [25]. In addition, the inoculation of plant growth-promoting bacteria can change rhizosphere bacterial communities and accelerate restoration processes in eroded desert soils [26]. Rhizosphere bacteria foster arsenic bioaccumulation by plants and then improve phytoremediation of arsenic-contaminated soils [27]. However, little is known about microbes in PES. Previous studies have investigated functional bacteria taxa in PES and have identified 377 isolates that exhibited phosphate-solubilizing potential [28], although biodiversity and distribution of bacteria still remain unclear. Understanding bacterial diversity and distribution is the first step towards harnessing functional taxa to improve phytoremediation and recalibrate restoration efforts. This work highlights the urgency of studying microbial community structures in rhizospheres to support the restoration of PES.

The main objectives of this study were to investigate divergences in structures of soil bacterial communities between rhizosphere and bulk soils of plants in PES as well as understand the environmental factors that affect bacterial communities. In previous studies on phosphorus-rich mountains, efforts have centered around understanding phytoremediation. This work reports for the first time the structure of PES microbial communities influenced by dominant plants of PES.

## **2. Materials and Methods**

## *2.1. Study Area*

The sampling was conducted on phosphorus-rich mountains near Dianchi Lake in central Yunnan, China (Figure 1). In this study area, the average annual temperature is 14.7 ◦C, and the annual temperature difference is 10–15 ◦C. The average annual rainfall is 985.5 mm, and the rainy season lasts from May to October, accounting for 84–90% of the annual rainfall. In this study area, the variation range of the total phosphorus concentration in the soil and the nitrogen/phosphorus ratio are 1.15–80.2 g/kg and 0.006–0.98, respectively, [29] both of which are typical in a phosphorus-rich region.

**Figure 1.** Geological phosphorus-rich regions around Dianchi Lake basin and sampling sites.

Most vegetation in the research area comprises natural secondary forests, and the original subtropical semi-moist evergreen broad-leaved forest has been almost completely destroyed [30]. The dominant vegetation species identified for the study were *Pinus yunnanensis, Coriaria nepalensis, Eupatorium adenophora, Erianthus rufipilus, Rumex hastatus, Keteleeria evelyniana, Pinus armandii,* and *Eucalyptus urophylla.* This study selected three dominant plants for research, i.e., *E. rufipilus*, *C. nepalensis,* and *P. yunnanensis,* based on the investigation of previous research. *E. rufipilus* belongs to the family *Gramineae*, is a drought-tolerant herbaceous plant growing between elevation 1300–2400 m, has a plant density of 2610 plant/ha and a P removal potential of 22.78 kg/ha in PES. *C. nepalensis* belongs to the family *Coriariaceae*, is an actinorhizal N-fixing species growing between elevation 400–3200 m, has a plant density of 670 plant/ha and a P removal potential of 16.91 kg/ha in PES. *P. yunnanensis* belongs to the family *Pinaceae* growing between elevation 400–3500 m, has a plant density

of 497 plant/ha, a P removal potential of 27.69 kg/ha in PES, and features secondary communities that suffer from disturbance and invasion [17,22].

## *2.2. Soil Sampling*

Fieldwork was conducted in March 2016. This study was conducted during the dry season, when rhizosphere soil acquisition is feasible, while also limiting the occurrence of rain erosion on bacterial communities. A total of thirteen sites were selected for the study area. Sampling sites were selected according to target plant communities. The soil samples in thirteen sites (Table 1) included the following: (1) rhizosphere and bulk soil of *E. rufipilus* from three sites (Er-R and Er-B), (2) rhizosphere and bulk soil of *C. nepalensis* from three sites (Cn-R and Cn-B), (3) rhizosphere and bulk soil of *P. yunnanensis* from three sites (Py-R and Py-B), and (4) soils from grassland plots from four sites (CK) with removal of surface grass debris at a random 0–20 cm soil depth in the absence of vegetation coverage. We selected plots of 10,000 m2 (100 × 100 m) for each site. Five subplots (5 × 5 m, with at least one target plant in each plot) were chosen for soil sampling using an S-shaped sampling method [31] within sampling sites. Rhizosphere soils were collected from the fine roots of *E. rufipilus, C. nepalensis,* and *P. yunnanensis*. Bulk soil samples were taken at a depth of 0–20 cm in the same plots as rhizosphere soils, and then mixed thoroughly. Rhizosphere soils were collected by gently shaking off the bulk soil that adhered to the roots at a depth of 0–20 cm, and then mixed well. Each soil sample was sieved through a 2 mm mesh to remove plant roots and other plant materials. Sampling equipment including mesh, scalpels, and spoons was cleaned with 95% alcohol, followed by heating using an alcohol lamp for 30 s. Soil collections among samples were conducted after all sampling equipment was sterilized and cooled down. All soil samples were tagged and sealed in valve bags from fine roots at 0–20 cm depth. At the same time, the soil temperature (Tem) of each plot was measured using soil temperature instruments for five replicates. Next, all 22 soil samples were manually homogenized and divided into three parts. The first portion was preserved within sterile centrifuge tubes (2 mL) and put in liquid nitrogen for DNA extraction and molecular analysis; the second portion was kept in plastic bags for water content measurement; and the third portion was stored at 4 ◦C refrigerator for 24 h, and then dried at 25 ◦C for chemical analysis.

**Table 1.** Information of soil samples.

## *2.3. Soil Physicochemical Analysis*

Chemical properties for all the 22 soil samples from the study area were analyzed based on the following method: Soil water content (SWC) was determined using the oven-drying method [32]. The pH value (pH) was determined in a 1:2 (soil to water ratio) using a pH meter with a standard combination of electrodes [33]. Soil organic matter content (SOM) was determined through the potassium dichromate sulfuric acid oxidation method [34]. Total nitrogen (TN) was measured using Kjeldahl's method as modified by Bremner and Mulvaney [35]. Alkali solution nitrogen (AN) was determined using the alkali soluble diffusion method [36]. Total phosphorus (TP) content was measured using the ammonium molybdate spectrophotometric method [37]. Concentrations of

available phosphorus (AP) were measured using the ammonium molybdate spectrophotometric method, following hydrochloric and sulfuric acid leaching. The value of nitrogen/phosphorus (N/P) was calculated by the ratio of total nitrogen to total phosphorus. All 22 soil samples from the four parts were used in chemical tests. Lab analyses were repeated three times, and final data were averaged.

## *2.4. Illumina MiSeq for High-Throughput Sequencing of 16S rRNA*

Soil samples stored in liquid nitrogen were used for DNA extraction. An Agilent High Sensitivity DNA Kit (Agilent Technologies Inc., Lexington, MA, USA) was used with 0.5 g of soil, according to the manufacturer's instructions. Extraction protocol followed the manufacturer's instructions with recommended modifications to enhance the efficiency of cell lysis. To assess the quality and purity of DNA, crude DNA extracts (2 μL) of each sample were run on 2% agarose gel and analyzed using ultraviolet spectrophotometer (Eppendorf Corporation, Hamburg, Germany). Detection results of qualified DNA samples are shown in the Appendix A Table A1. Electrophoresis detection bands were single, indicating no degradation, and had no protein or RNA contamination.

Bacterial 16S rRNA genes were amplified using the following two primers: 520F (5-AYTGG GYDTAAAGNG-3) and 802R (5-TACNVGGGTATCTAATCC-3). PCR reactions were carried out in triplicate with 25 μL of reaction mixture, comprising 8.75 μL of sterilized ultrapure water, 5 μL of Q5 reaction buffer, 5 μL of Q5 GC high enhancer, 2 μL of 2.5 mM dNTPs, 2 μL of DNA template, 1 μL of each primer, and 0.25 μL Q5 polymerase. For the subsequent PCR cycling reaction, the following parameters were used: 98 ◦C and 2 min for initial denaturation, followed by 25 cycles of denaturation at 98 ◦C for 30 s, annealing at 50 ◦C for 30 s, and elongation at 72 ◦C for 30 s, followed by a final extension at 72 ◦C for 5 min. All the samples were amplified in triplicate and detected and quantified using a Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen Corporation, Waltham, MA, USA). This step ensured that all detected DNA samples had obvious and single bands before the next experiments. After quantification, paired-end sequencing of amplicons from each reaction mixture was performed using the Illumina MiSeq platform [38]. Sequencing services were provided by Personal Biotechnology Co., Ltd. Shanghai, China. The raw sequencing data of bacteria were deposited in NCBI Sequence Read Archive (SRA) under accession number PRJNA662457.

## *2.5. Data Analysis*

At least three groups of repeats and 22 soil samples in total from the geological phosphorus-rich mountains were collected. There were seven sets of mixed samples (Er-R, Er-B, Cn-R, Cn-B, Py-R, Py-B and CK) (as seen in Table 1) for the comparative analysis of bacterial communities. The resulting data from each set of repeated samples were averaged. For the FASTQ format of paired-end sequences, we ensured the mean quality of the base was ≥Q20 and sequence length ≥150 bp. FLASH was used to pair and connect the screened paired-end sequences in order to obtain high quality sequences [39]. UCLUST [40] was used to align sequences and call OTUs (operational taxonomic units) using 97% as the cut-off sequence similarity, showing the rarefaction curves, then removing OTUs in which the abundance value was lower than 0.001% of the total sequenced quantity [41]. Subsequent microbial classification and analyses were conducted based on classifying the information of each OTU. For the richness and diversity index of bacterial communities, the *Chao1* index (1) and *ACE* (2) index were used to describe the richness [42]:

$$
tau1 = S\_{\rm obs} + \frac{f\_1(f\_1 - 1)}{2(f\_2 + 1)}\tag{1}
$$

$$ACE = \sum\_{k=11}^{S\_{\text{obj}}} f\_k + \frac{\sum\_{k=1}^{10} f\_k}{1 - \frac{f\_1}{\sum\_{k=1}^{10} k f\_k}} + \frac{f\_1}{1 - \frac{f\_1}{\sum\_{k=1}^{10} k f\_k}} \max\left| \frac{\sum\_{k=1}^{10}}{1 - \frac{f\_1}{\sum\_{k=1}^{10} k f\_k}} \frac{\sum\_{k=1}^{10} k(k-1) f\_k}{\left(\sum\_{k=1}^{10} k f\_k\right) \left(\sum\_{k=1}^{10} k f\_k - 1\right)} - 1/0 \right| \tag{2}$$

where *Sobs* is the total number of species observed in a sample and *fk* is the number of species each represented by *k* individuals in a single soil sample.

The *Shannon* index (3) [43] and *Simpson* index (4) [44] were used to describe the evenness:

$$Shannon = -\sum\_{i=1}^{R} p\_i \ln p\_i \tag{3}$$

$$Simpsm = \frac{\sum\_{i=1}^{R} n\_i(n\_i - 1)}{N(N - 1)}\tag{4}$$

where *Pi* = *Ni*/*N*, *Ni* is the individual number of species (*i*), *N* is the total number of organisms of a particular species, and *Pi* is the proportion of *i* species.

Raw physicochemical data properties of soil samples were processed with Excel 2007, and the results were calculated for three (rhizosphere and bulk soil of three dominant plants) or four replicate (CK) samples and expressed by the mean ± standard deviation. Statistical significance was determined by one-way analysis of variance (ANOVA), followed by Dunnett's T3 post hoc test in SPSS ver. 19.0. To compare the structure of bacterial communities across all soil samples based on the relative abundance of bacterial phyla class, principal components analysis of soil properties using redundancy analysis (RDA) by R software package was conducted. Bacterial community composition data, for each classification level, were clustered according to their number of OTUs and taxonomic data using MEGAN [45], and a phylogenetic tree based on the sequenced result of each sample and NCBI database was constructed. Heatmap and Venn diagram were drawn by hierarchal clustering performed based on Ihaka and Gentleman [46]. GraPhlAn [47] was used to construct circular representations of the taxonomic phylogenetic tree, showing the dominant taxa of rhizosphere soils and soils from grassland plots.

## **3. Results**

## *3.1. Physicochemical Properties*

There were significant differences among the rhizosphere soils of *E. rufipilus* (Er-R), *C. nepalensis* (Cn-R), *P. yunnanensis* (Py-R), and grassland plots (CK) (Table 1) with respect to most physicochemical properties (Table 2). The amounts of SOM, AN, TP, and AP were significantly higher in Py-R as compared with Er-R, Cn-R, and CK. Gathered data demonstrate that rhizosphere soils of *P. yunnanensis* possess a rich nutrient content

**Table 2.** Physiochemical properties (mean ± SD) of rhizosphere and bulk soils from three dominant plants and grassland plots.

**Table 2.** *Cont.*

Notes: Value with different letters are significantly different under Dunnett's T3 post hoc test at *p* < 0.05. Er-R, rhizosphere soil of *Erianthus rufipilus*; Er-B, bulk soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Cn-B, bulk soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; Py-B, bulk soil of *Pinus yunnanensis*; CK, soil from grassland plots; Tem, temperature; SWC, soil water content; SOM, soil organic matter; TN, total nitrogen; AN, alkali solution nitrogen; TP, total phosphorus; AP, available phosphorus; N/P, total nitrogen/total phosphorus.

## *3.2. Sequencing Results*

Analyses revealed an average of 40,667 valid sequences per sample, and subsequent screening analyzed 38,072 high quality sequences (accounting for 89.3–98.05%), with a read length of 200–250 bp.

## *3.3. Di*ff*erences in Bacterial Diversity*

The rarefaction curves (Figure 2) show that Py-R had the lowest bacterial diversity, and CK were more diverse as compared with the rhizosphere soils of Er-R and Cn-R. For richness and diversity estimations based on OTUs picker data, four indices of each sample group were analyzed using QIIME (Table 3). As shown in Table 3, scores for indices were as follows: Chao1 (1595) and ACE (2036) for Py-R; Chao1 (2012) and ACE (2511) for CK; the Simpson index was 0.981 and the Shannon index 8.11 for Py-R; and the Simpson index was 0.992 and the Shannon index 8.93 for Er-R. The data show that CK had the highest richness and Er-R had the highest diversity, while Py-R had the lowest richness and diversity.

**Figure 2.** Rarefaction curves show the number of operational taxonomic units (OTUs) from sequencing data. Notes: Er-R, rhizosphere soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; CK, soil from grassland plots. (**a**) observed species from Er-R, (**b**) observed species from Cn-R, (**c**) observed species from Py-R, (**d**) observed species from CK.

**Table 3.** Comparison of richness and diversity indices among the rhizosphere soils and grassland plots.

Notes: The values in parentheses show the upper and lower limits; Er-R, rhizosphere soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; CK, soil from grassland plots.

## *3.4. Bacterial Communities and Diversity*

Relative bacterial OTU richness was present in four different soil samples across phylum, class, order, family, and genus (Figure 3). The dataset for phylogenetic analyses comprised 1 kingdom, 3 phyla, 7 classes, 7 orders, 16 families and 40 genera. The heatmap plot depicted the relative abundance of each dominant genera (variables clustering on the *Y*-axis) within soil samples (*X*-axis clustering) (Figure 4). As shown in Figure 4, four samples from CK grouped together; Cn-R2, Cn-R1, Er-R3, Er-R2 grouped together; and Py-R2 and Py-R3 grouped together. The 50 most abundant genera were depicted. The results show that the majority of sequences belonging to *Asteroleplasma*, *Enterococcus*, *Opitutus*, and *Alkaliphilus* were presented in soil from the CK group. *Dokdonella*, *Pseudomonas*, *Snaeromyxobacter,* and *Hyphomicrobium* were presented in soil from the Er-R and Cn-R groups. *Candidatus Xiphinematobacter*, *Mycobacterium*, *Bradyrhizobium,* and *Nostocoida* were presented in soil from the Py-R groups. We observed that the class *Proteobacteria* had the highest abundance (24.43%) in the rhizosphere soils of the three plants and soil samples from grassland plots, followed by *Acidobacteria* (21.09%)*, Verrucomicrobia* (19.48%)*, Planctomycetes* (9.20%), and *Anctinobacteria* (5.53%) (Figure 5).

A Venn diagram (Figure 6) illustrates that the bacterial communities of *E. rufipilus* (Er) shared 4095 OTUs between bulk (Er-B) and rhizosphere soils (Er-R) (Figure 6a); the bacterial communities of *C. nepalensis* (Cn) shared 3824 OTUs between bulk (Cn-B) and rhizosphere soils (Cn-R) (Figure 6b); the bacterial communities of *P. yunnanensis* (Py) shared 2817 OTUs between bulk (Py-B) and rhizosphere soils (Py-R) (Figure 6c); and the bacterial communities among the four groups (Er-R, Cn-R, Py-R, and CK) shared 2516 OTUs (Figure 6d). The OTUs derived from the soil associated with the three plant species showed that rhizosphere soils had more OTUs than bulk soils (Figure 6a–c).

**Figure 3.** The phylogenetic tree of partial 16S rRNA gene read information based on NCBI Taxonomy by MEGAN. Notes: Er-R, rhizosphere soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; CK, soil from grassland plots.

**Figure 4.** Hierarchically clustered heatmap of rhizosphere bacterial communities of dominant plants at the genus level. Soil samples are clustered laterally based on their bacterial similarity and bacterial taxa are clustered vertically. The red color represents the genus with higher abundance and green color represents the genus with lower abundance. Notes: Er-R, rhizosphere soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; CK, soil from grassland plots.

**Figure 5.** Hierarchical tree of dominant bacterial groups at classification level based on GraPhlAn software, it shows units of classification from phyla to genus (inner to outer rings). Size of nodes indicated the abundance.

**Figure 6.** Numbers of shared phylotypes (OTUs) observed between soil samples of different treatments. Notes: Er-R, rhizosphere soil of *Erianthus rufipilus*; Er-B, bulk soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Cn-B, bulk soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; Py-B, bulk soil of *Pinus yunnanensis*; CK, soil from grassland plots. (**a**) observed OTUs in Er-R and Er-B. (**b**) observed OTUs in Cn-R and Cn-B. (**c**) observed OTUs in Py-R and Py-B. (**d**) observed OTUs in Er-R, Cn-R, Py-R and CK.

## *3.5. Impact of Soil Properties on the Relative Abundances of Bacterial Taxa*

We found a significant association among bacterial community structure and physicochemical properties in the soils (Figure 7). Bacterial communities from Py-R, Py-B, and Cn-R tend to group together, whereas Er-R, Er-B, Cn-B, and CK are scattered. Soil water content (SWC), soil organic matter (SOM), and total nitrogen (TN) were the main limiting factors, and the first two axes in RDA analysis explained 47.24% of variance for the relationship between soil bacterial community composition and physicochemical factors.

**Figure 7.** Redundancy analysis (RDA) of bacterial communities as affected by the environmental and

chemical properties factors, based on the relative abundance and similarity of bacterial phyla. RDA1 explained 30.78% and RDA2 16.46% variability. Each point represents a sample, the closer the distance between two points, the higher the bacterial communities' similarity. The arrow shows the influence factor, the longer the arrow, the greater the effect. The angle between the factors for acute angle shows that the two factors are positively corrected; an angle that is an obtuse angle is a negative correlation. Notes: Er-R, rhizosphere soil of *Erianthus rufipilus*; Er-B, bulk soil of *Erianthus rufipilus*; Cn-R, rhizosphere soil of *Coriaria nepalensis*; Cn-B, bulk soil of *Coriaria nepalensis*; Py-R, rhizosphere soil of *Pinus yunnanensis*; Py-B, bulk soil of *Pinus yunnanensis*; CK, soil from grassland plots; Tem, temperature; SWC, soil water content; SOM, soil organic matter; TN, total nitrogen; AN, alkali solution nitrogen; TP, total phosphorus; AP, available phosphorus; N/P, total nitrogen/total phosphorus.

## **4. Discussion**

Results of this study demonstrate the relationships among soil physicochemical properties and the bacterial communities associated with three selected plants (*E. rufipilus*, *C. nepalensis*, and *P. yunnanensis*), as well as grassland plots in phosphorus-rich mountains in southwestern China. The associations among soil nutrients and bacterial community structure of rhizosphere and bulk soils has been demonstrated in several previous studies [48–52]. Plant species play an important role in shaping rhizosphere microbial communities through their root exudates [24,53–55]. In this study, we found that the content of SOM, TN, and AN was present in higher concentrations in rhizosphere soils as compared with bulk soils among three plants in PES. The contents of SOM, TN, AN, TP, and AP in rhizosphere soils were elevated 55.31%, 34.11%, 39.02%, −2.11%, and 3.50% relative to bulk soil, consistent with soils from other studies and regions [56,57]. The rhizosphere soils of *P. yunnanensis* have higher TP content (elevated 121.44% and 189.06% relative to *E. rufipilus* and *C. nepalensis*, respectively), AP content (elevated 115.70% and 294.24% relative to *E. rufipilus* and *C. nepalensis*, respectively), and lower nitrogen/phosphorus (N/P) (declined 50.91% and 52.63% relative to *E. rufipilus* and *C. nepalensis*, respectively) than the other two dominant plants. Differences in soil phosphorus content among land-use types in PES could possibly be due to geological reasons; for example, this study site is home to geological phosphorus-rich mountains, and phosphate deposited in Yunnan Province accounts for 80% of high-grade phosphate ore in China [17]. According to previous studies on PES, phosphorus is found in high concentrations in soils with low soil nitrogen content [21,58]. Therefore, the results of this study are congruent with previous studies.

The 16S rRNA gene sequencing survey provides exhaustive information about the relative abundance, diversity, and composition of bacterial communities. This study was the first implementation of Illumina MiSeq high-throughput sequencing technology on soil microbial communities in phosphorus-rich mountains. The relative abundance of bacteria among the soil samples showed that *P. yunnanensis* had the lowest bacterial OTUs and CK had the highest. In contrast, soil nutrient properties revealed that *P. yunnanensis* had the highest concentration of SOM, AN, TP, and AP, whereas CK had the lowest SOM. This suggests that plant species shapes soil nutrient properties and bacterial community characteristics in rhizospheres and bulk soils.

The most abundant phylum of bacterial communities in the rhizosphere soil among plants was *Proteobacteria*. This result corroborates the results of several previous bacterial community studies done on the rhizosphere soils of crops [15,59], mining soils [60,61], and PES bacterial community research [28]. Furthermore, the class *Alphaproteobacteria* occupied the majority of the phylum *Proteobacteria*. *Rhizobiales* are the most abundant order in *Proteobacteria* across all soil samples. The families *Bradyrhizobiaceae* and *Rhizobiaceae* in the order *Rhizobiales* from *C. nepalensis* have higher abundance than *E. rufipilus*, *P. yunnanensis,* and grassland plots; this is because *C. nepalensis* forms symbiotic relationships with nitrogen-fixing bacteria [62,63].

The phylum *Acidobacteria* is the second most abundant community among the rhizosphere of the plants and grassland plots in this study. *Acidobacteria* is the predominant phylum of bacteria in semi-arid and other mature soil environments [64]. *Acidobacteria* exists most abundantly in the rhizosphere soil of *E. rufipilus*; this is likely because *E. rufipilus* is highly drought resistant and suitable to grow in arid regions [65,66]. As a dominant species, *E. rufipilus* is widely distributed in phosphorus-rich regions and has a high phosphorus tolerance [63]. The next phyla in highest abundance were *Verrucomicrobia* and *Planctomycetes*. These two phyla were abundant in the rhizosphere soil of *P. yunnanensis* and grassland plots. *Planctomycetes* represented a small minority of aquatic bacteria found in seawater and freshwater environments [67,68]. However, the dry season occurs in central Yunnan, China from November to April [69], and *P. yunnanensis* exhibits drought tolerance [70], which may explain why *Planctomycetes* was present in soils linked to *P. yunnanensis* in study areas. According to the rhizosphere bacterial communities of *Y. yunnanensis* reported in other regions of Yunnan Province where phosphorus is deficient, the dominant bacterial taxa are *Acitinobacteria*, *Alphaproteobacteria,* and *Acidobacteira*, whereas *Verrucomicrobia* and *Planctomycetes* were found in low abundance [71]. In addition to the plants reported in this study, phosphorus also alters bacterial community composition in soybean rhizosphere soils, and phosphorus fertilization decreased the relative abundance of *Bacillales* and *Pseudomonadales* [72].

Plant root exudates also shape rhizosphere bacterial structures [73–75]. Previous studies about phosphorus-enriched soils have concluded that phytoremediation is an effective measure for nutrient (nitrogen and phosphorus) removal [17,76]. Fewer studies, however, has been focused on the biodiversity of soil microbial communities based on vegetation regeneration. This study showed that bacterial communities in PES are strongly influenced by the rhizospheres of different plant species and physicochemical soil parameters. The distribution of soil bacteria was affected by multiple environmental factors. Soil macro-environmental conditions, such as soil water content, has the most notable impacts on the distribution of bacteria, followed by soil organic matter and total nitrogen. Although phosphate content was high in PES, total phosphorus was found to have the lowest impact as compared with other nutrient factors on bacterial communities. The findings of this study verified the results of a previous study on low nitrogen levels in the region [19].

On a larger scale, in the phosphorus-rich and nitrogen-deficient environments of PES, most vegetation is secondary, and habitats are relatively fragile. *E. rufipilus, C. nepalensis*, and *P. yunnanensis* are widely grown in phosphorus-enriched soils of China because of their high tolerance to drought and arid conditions. The *P. yunnanensis* plant communities have higher plant diversity in PES, whereas bacterial communities tend to feature lower diversity under the forest soil of *P. yunnanensis*. Higher plant diversity and lower litter decomposition efficiency [77], as well as litter inhibitory effect on bacterial communities such as production of tannin [78] occurring under *P. yunnanensis* as compared with *E. rufipilus* and *C. nepalensis* likely explains this lower level of diversity. In addition, *P. yunnanensis* is a common native secondary coniferous species growing in low temperatures. Because of its rapid growth and higher plant community diversity beneath trees, it is a preferred species in Yunnan [37]. On the basis of the above findings, follow-up research in plant rhizosphere microbial compositions, and diversity could be fruitful. Nutrient properties and microbial communities can provide guidance for understanding biochemical processes and ecosystem functionalities in the soils of phosphorus-rich mountains.

## **5. Conclusions**

The richness and diversity of the bacterial communities reported in our study reveal prospective uncultured bacteria derived from rhizosphere soils of dominant plants in PES for the first time. Differences in the physicochemistry and structures of soil bacterial communities among the dominant plants form useful guidelines for examining how tree species and soil physicochemical parameters influence local soil environments in phosphorus-rich regions. The results from our study show that both bacterial communities and soil nutrients show Rhizospheric effects; rhizosphere bacteria are mainly composed of *Proteobacteria* and *Acidobacteria*, followed by *Verrucomicrobia* and *Planctomycetes*; bacteria abundance and diversity in PES are mainly influenced by soil water content, soil organic matter, and total nitrogen. Our results indicate that rhizosphere microbial communities could serve as

an important index for phytoremediation. This is of great significance for the restoration of disturbed ecosystems in PES.

**Author Contributions:** Conceptualization, C.D. and D.F.; Formal analysis, Y.H. and E.F.; Funding acquisition, C.D. and D.F.; Investigation, X.W. and K.Y.; Methodology, Y.H., C.D., and D.F.; Resources, C.D. and D.F.; Software, K.Y. and S.C.K.; Supervision, C.D., P.E.M., and J.X.; Writing—original draft, Y.H. and D.F. Writing—review and editing, I.P., P.E.M., and J.X. All authors have read and agree to the published version of the manuscript.

**Funding:** This research is supported by the National Science Foundation of China (NSFC) project codes 31670522 to Changqun Duan, NSFC project codes 31860133 to Denggao Fu, NSFC41807524 and<PHONE_NUMBER>2 to Kai Yan. Peter E. Mortimer thanks NSFC project codes<PHONE_NUMBER>5 and 41771063 for support. Samantha C. Kaunarathna thanks CAS President's International Fellowship Initiative (PIFI) for funding his postdoctoral research (no. 2018PC0006) and NSFC project code<PHONE_NUMBER>9.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **Appendix A**

**Table A1.** Basic information of UV spectrophotometry test on DNA extraction products among soil samples.

## **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Communication* **Long-Term Exposure to Azo Dyes from Textile Wastewater Causes the Abundance of** *Saccharibacteria* **Population**

**Ramasamy Krishnamoorthy 1,†, Aritra Roy Choudhury 2,†, Polpass Arul Jose 1, Kathirvel Suganya 1,3, Murugaiyan Senthilkumar 4, James Prabhakaran 5, Nellaiappan Olaganathan Gopal 4, Jeongyun Choi 2, Kiyoon Kim 2,‡, Rangasamy Anandham 1,4,\* and Tongmin Sa 2,\***

**Abstract:** Discharge of untreated wastewater is one of the major problems in various countries. The use of azo dyes in textile industries are one of the key xenobiotic compounds which effect both soil and water ecosystems and result in drastic effect on the microbial communities. Orathupalayam dam, which is constructed over Noyyal river in Tamil Nadu, India has become a sink of wastewater from the nearby textile industries. The present study had aimed to characterize the bacterial diversity and community profiles of soil collected from the vicinity of the dam (DS) and allied agricultural field (ALS) nearby the catchment area. The soil dehydrogenase and cellulase activities were significantly lower in DS compared to ALS. Additionally, the long-term exposure to azo dye compounds resulted in higher relative abundance of *Saccharibacteria* (36.4%) which are important for degradation of azo dyes. On the other hand, the relative abundance of *Proteobacteria* (25.4%) were higher in ALS. Interestingly, the abundance of *Saccharibacteria* (15.2%) were also prominent in ALS suggesting that the azo compounds might have deposited in the agricultural field through irrigation. Hence, this study revealed the potential bacterial phyla which can be key drivers for designing viable technologies for degradation of xenobiotic dyes.

**Keywords:** azo dye; textile; wastewater; diversity; xenobiotics; pollutant

## **1. Introduction**

Soil is a biologically balanced system and any variations in the soil micro-environment results in the changes in native microbial community profiles. Similarly, the accumulation of pollutants such as polycyclic aromatic hydrocarbons (PAHs) [1], petroleum compounds [2] and heavy metals [3] have drastic effect on the bacterial diversity. The driving factors which determine the abundance of the microbial community in a particular contaminated soil are the genetic variation which results in altered metabolic pathways or the selective enrichment of microbes which are able to transform the particular pollutant [4].

Rapid advent of industrialization has led to deleterious effect on the environment, mostly due to the improper discharge of industrial waste. The textile industries use a

**Citation:** Krishnamoorthy, R.; Roy Choudhury, A.; Arul Jose, P.; Suganya, K.; Senthilkumar, M.; Prabhakaran, J.; Gopal, N.O.; Choi, J.; Kim, K.; Anandham, R.; et al. Long-Term Exposure to Azo Dyes from Textile Wastewater Causes the Abundance of *Saccharibacteria* Population. *Appl. Sci.* **2021**, *11*, 379. https://doi.org/ 10.3390/app11010379

Received: 18 November 2020 Accepted: 29 December 2020 Published: 2 January 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

large amount of synthetic dyes which results in discharge of colored wastewater [5,6]. Azo dyes account for 70% of all the commercial dyes used in textile industries across the globe [7]. These dyes have been proven to be harmful for the aquatic life forms as they result in increasing the biological oxidation demand (BOD) [8]. Additionally, these azo compounds are also reported to be highly toxic and carcinogenic in nature [7]. It is estimated that around 50% of the synthetic dyes used in the textile industries does not bind to the fabric and result in getting discharged into the environment [9]. The compounds can leach into the groundwater and the use of those water sources for farming results in contamination of agricultural fields [10]. The bioremediation of contaminant by isolation and characterization of indigenous microbial community have been studied in various cases [11,12]. The classical enrichment technique does not give the broader idea about the various microbial activities occurring in the soil. Metagenomic analysis by using high-throughput sequencing helps to overcome the limitations of conventional methods of studying microbial community dynamics in soil. Researchers have concentrated on designing numerous technologies [13,14] for treatment of textile wastewater and also studied the changes in microbial community and diversity in those reactor systems which are used for remediating such wastewater [15]. However, there have been no studies on high-throughput detection of microbial community profiles of environmental samples such as water or soil which have been severely affected by long-term exposure to improper discharge of textile wastewater rich in azo dye compounds.

Orathupalayam dam is constructed on the Noyyal river in Tamil Nadu, India. The dam has become a reservoir of azo dye compounds due to the continuous discharge of effluents from the textile industries located in the nearby area of Tiruppur. In a previous study, bacterial and fungal species were isolated from the soil samples collected from the nearby catchment area and allied agricultural fields of this dam and characterized based on their ability to degrade azo dyes in a batch scale [16]. Whereas, in this study, we aimed to characterize the bacterial community profiles of soils collected from the nearby area of Orathupalayam dam and allied agricultural fields.

## **2. Materials and Methods**

## *2.1. Collection of Soil Sample*

Soil samples were collected from the vicinity of Orathupalayam dam and its allied agricultural lands. The dam is located (11◦06 31.56 N; 77◦32 26.33 E) in Tiruppur District, Tamil Nadu, India (Figure 1). A total of 6 composite soil samples were collected from the vicinity of the dam and 4 composite soil samples were collected from the agricultural lands situated within 2 km radius. Samples were collected by leaving at least 40 m distance between samples and 5–20 cm depth. Both the samples were made into a composite one which resulted in two soil samples: Dam Soil (DS) and Agricultural Soil (ALS).

## *2.2. Soil Enzyme Activities*

Dehydrogenase was measured by assaying 2,3,5-triphenyl tetrazolium chloride (TTC) as substrate and defined as production of triphenylformazan (TPF) g−1 soil h−1 at 37 ◦C [17]. Urease activity was measured based on the amount of ammonium released after incubation of soil samples with urea solution for 2 h at 37 ◦C and determined calorimetrically by indophenol reaction at 690 nm [18]. Cellulase activity was measured by determining the breakdown of carboxymethylcellulose (CMC) to glucose at 30 ◦C for 24 h [19]. Acid phosphomonoesterase activity was determined by measuring the concentration of *p*-nitrophenol (*p*-NP) released after incubation of soil with *p*-NP-linked substrates for 1 h at 37 ◦C [20].

## *2.3. Soil DNA Extraction*

Total soil DNA was extracted from 0.5 g of fresh soil sample by using HiPurA Soil DNA Purification Kit (Hi Media, Mumbai, India) following the manufacturer's protocol. Quality and quantity of the extracted DNA samples were checked using agarose

gel electrophoresis as well as Nanodrop ND-1000 spectrophotometer (ThermoScientific, Wilmington, NC, USA).

**Figure 1.** Overview of the soil sampling site and soil collection. (**A**) Google earth image of Orathupalayam dam constructed over Noyyal river in Tamil Nadu, India, (**B**) Orathupalayam dam inlet, (**C**) Orathupalayam dam outlet, (**D**) Soil sampling site, (**E**) Collected soil samples.

## *2.4. PCR Amplification and Phylogenetic Marker Library Preparation*

Library construction involved two PCR reactions (Kapa HiFi Hot start, Kapa Biosystems, MA, US): amplicon PCR and indexing PCR. In amplicon PCR, the 16S rRNA gene was amplified using PCR with primers 341F, 5 -CCTACGGGAGGCAGCAG-3 and 518R, 5 -ATTACCGCGGCTGCTGG-3 [21–23] targeting the V3-V4 region for construction of bacterial phylogenetic marker library. Subsequently, the Illumina sequencing adapters and dual indexing barcodes were added using indexing PCR. The library of final products was cleaned using HighPrep PCR (Magbio, Gaithersburg, MD, USA) magnetic beads and quality was evaluated on a Bioanalyzer, using a DNA1000 lab chip (Agilent, USA). The raw reads were deposited in SRA archives and can be accessed by BioProject number PRJNA522349.

## *2.5. Pyrosequencing and Pre-Processing of Sequence Reads*

Purified PCR products (library) were pooled in equimolar ratios and paired-end reads were generated on an Illumina GAIIx sequencer. Image analysis and base calling were done using Illumina Analysis pipeline (Version 2.2). High quality reads with more than 70% of bases with Phred Score greater than 20 were considered for subsequent analysis. Reads with adapter sequences, primer sequences, the barcode and the degenerate bases were removed using an automated Perl code generating processed reads. Duplicates and chimeras were removed using CD-HIT DUP [24].

## *2.6. Data Analysis*

The resulting dataset was pre-screened using uclust for a minimum of 70% identity to ribosomal sequences and then clustered at 97% identity against the Silva (SSU115) 16S rRNA database using in MG- RAST [25]. Taxonomic assignment from phylum level to strain level was assigned based on the hits. Abundance graphs were plotted based on the number of hits. Rarefaction curves were plotted using MG-RAST [25]. Diversity index was calculated using Mothur [26]. Differences in the relative abundances of microbial community between groups were evaluated with an unequal variances t-test (Welch's *t*-test) considering unequal variance in taxonomic groups.

## **3. Results and Discussion**

## *3.1. Soil Enzyme Activities*

Soil quality can be determined by measuring the enzyme activities [27]. Among the various soil enzymes, dehydrogenase is considered as one of the most abundantly used parameter to determine the soil quality and reflects the rate of nutrient transformations occurring in soil. [28]. Dehydrogenase activity is affected with respect to the presence of contaminant in soil [29]. The DS had shown significantly lower dehydrogenase activity compared to ALS (Table 1). The presence of high concentration of azo compounds in DS [16] might have resulted in decrease in microbial population and subsequently reducing the enzyme activity. Results of this study match with the results of Kaczy ´nska et al. [28], where the authors found reduced dehydrogenase activity due to soil contamination. On the other hand, the cellulase activity is higher in soils which are rich in plant biomass [30], and it corroborates to our study where the cellulase activity has been observed to be highly significant in ALS. It can be assumed that the DS contains low amount of organic plant biomasses due to azo dye impact on plant development than that of ALS. However, urease and acid phosphomonoesterase activities did not show any significant difference among the soil samples. Urease and acid phosphomonoesterase activities are used for indirect estimation of soil nitrogen and phosphorus transformation, respectively [20].

**Table 1.** Soil enzyme activities of DS and ALS.

a The enzyme activities are not significantly different from each other at 5% threshold (LSD). Values are mean ± SE (standard error) of three independent determinations.

## *3.2. Diversity Indices*

The microbial diversity is affected due to the presence of high amount of pollutants in the soil [31]. It has been observed that the azo dye contaminated soils have changes in microbial community structure based on the phospholipid fatty acid profiles [5]. Similarly, the total number of bacterial OTUs were observed to be 8302 and 12,162 for DS and ALS respectively (Table 2), after clustering at 3% cutoff level. Significant variation observed in OUT of DS and ALS, illustrated the negative impact of azo dye on soil microbial population and diversity. Similarly, the negative impact of individual azo dyes (Direct Red 81, Reactive Black 5 and Acid Yellow) on soil bacterial and fungal diversity was reported by Imran et al. [5]. In addition, the authors reported that azo dyes affect plant beneficial bacteria habitats in soil. The rarefaction curve confirmed the adequacy of sampling effort in the current microbial diversity analysis (Figure S1). The diversity indices measured in terms of Shanon and Inv-simpson indices, and the richness measured in terms of Chao1 index were higher in ALS compared to DS (Table 2). The diversity indices give the overview of richness and evenness of a community. Hence, the result of the diversity indices infers that the textile wastewater decreased the α-diversity of the microbial community and also decreased the richness and evenness of the microbial community in DS [32]. The major drawback of the study is that a single replicate was used for studying the bacterial diversity. However, it can be used as a preliminary study for understanding the effect of azo dyes on bacterial community profiles.

**Table 2.** Microbial diversity estimates of soil samples.

## *3.3. Bacterial Diversity and Community Profiles*

Soil contaminated with myriad of pollutants has become a serious problem across the world. Studies which concentrate on deciphering the microbial community profiles of contaminated soil helps us to design strategies to remediate such sites by targeting the key microbial players in degradation of the particular pollutant [33]. There have been numerous studies in designing reactors for treating textile wastewater which are rich in azo compounds for decreasing the levels of effluents in the environment [13,14].

In this study, a total of 50 and 54 phyla were detected for DS and ALS respectively (Figure 2). The phyla profiles were different for both DS and ALS. *Saccharibacteria* (36.4%) were observed to be the most abundant in DS (Figure 2a) whereas *Proteobacteria* (25.4%) were the abundant ones in ALS (Figure 2b). Negative impact of azo dyes on soil *Proteobacteria* were previously reported [5]. Reactive Black 5 Direct Red 81 used by Imran et al. [5] found to reduce the *Proteobacteria* population significantly in soil. The other phyla dominating DS are *Actinobacteria* (20.02%), *Proteobacteria* (15.49%), WS5 (4.63%), *Acidobacteria* (4.16%) and *Chloroflexi* (3.31%). Similarly, the other phyla dominating ALS are *Saccharibacteria* (15.24%), *Actinobacteria* (10.03%), *Acidobacteria* (9.94%), *Plantomycetes* (8.4%), *Gemmatimonadetes* (7.59%), *Chloroflexi* (6.34%) and *Bacteroidetes* (3.48%). Different genera of *Proteobacteria* were isolated from the textile effluents wastewater treatment plants [34], and these *Proteobacteria* might have been involved in degradation of azo dyes. *Saccharibacteria* have been observed to be highly active in sludge reduction and dye wastewater treatment plants [14,35]. Furthermore, *Saccharibacteria* are regarded as one of the active microbial group in anoxic carbon-based fluidized bed reactor treating coal pyrolysis wastewater which contains abundant phenolic compounds [36]. In another study, it has been reported that *Actinobacterial* extract [37] and its related enzymes [38] are important in degradation of azo dyes. Hence, the abundance of *Saccharibacteria* and *Actinobacteria* in this study can be attributed to the fact that these phyla are responsible for remediating/decolorizing azo dye compounds present in the textile wastewater. *Saccharibacteria* and *Actinobacteria* present in Azo dye contaminated soil, indicates their important in degradation of soil pollutants. Since the results obtained by pyrosequencing techniques, many of them might be unculturable. In future, selective culturing of *Saccharibacteria* and *Actinobacteria* from this azo dye contaminated soils could be the opportunity to obtain efficient strains for remediation of azo dye polluted soils.

**Figure 2.** Relative abundance of bacterial lineages of (**A**) DS and (**B**) ALS in phylum level.

On the other hand, the abundance of *Proteobacteria* in agricultural soil also corroborates to previous studies [32]. As the agricultural sector uses mostly inorganic NPK fertilizers, which has resulted in increase in the relative abundance of *Proteobacteria* in agricultural fields [39]. The abundance of *Saccharibacteria* in agricultural soil can be correlated to the evidence that the dam water used for irrigation of the agricultural soil has resulted in contamination of the field [13,34]. The abundance of *Actinobacteria* in ALS can be explained by the fact that these bacterial group consists of plethora of plant growth promoters which are predominantly found in agricultural soils [18]. The genus and species composition of these two soil groups had revealed the presence of a number of rare bacterial species (Figure 3). There have been approximately 75% and 78% of rare bacterial species in DS and ALS, respectively. Exploiting these bacterial species can be helpful in designing efficient technologies in remediating/decolorization of azo dyes.

**Figure 3.** Percentage of abundant and rare bacterial species in ALS and DS.

#### **4. Conclusions**

The long-term exposure of wastewater from textile industries has resulted in changes in soil enzyme activities and bacterial diversity. The azo-dye contamination caused the *Saccharibacteria* population to proliferate in higher abundance compared to other bacterial phyla in DS. Moreover, ALS had shown relatively high abundance of *Saccharibacteria* which might be due to the use of polluted water from the dam for irrigation purposes. Further studies concentrating on elucidating the fungal community dynamics will help to detect the major microbial drivers important for degradation of azo dyes. The isolation and enrichment of these specific microbes (*Saccharibacteria* and *Actinobacteria*) can help to design/propose novel technologies in remediation of textile wastewater for reducing the contaminant footprint in the environment.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2076-341 7/11/1/379/s1, Figure S1: Rarefaction curve of bacterial communities.

**Author Contributions:** R.A. and T.S.: conceptualization of the study; R.K. and A.R.C.: designed experiments, performed experiments and analysis of sequencing data; P.A.J., K.S., M.S., J.P. and N.O.G.: assisted in soil sampling and experiments; J.C. and K.K.: assisted in data analysis and discussion; R.K., A.R.C.: wrote the manuscript; R.A. and T.S.: critical reviewing and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Environmental Biotechnology task force, Department of Biotechnology (DBT), Ministry of Science and Technology, Government of India under grant no. BT/PR7518/BCE/8/994/2013 and by Basic Science Research Program, National Research Foundation (NRF), Ministry of Education, Science and Technology [2015R1A2A1A05001885], Republic of Korea.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data and analyses from the current study are available from the corresponding authors upon reasonable request. The raw reads were deposited in SRA archives and can be accessed by BioProject no. PRJNA522349.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

## *Article*

## **Identification of Bacterial and Fungal Communities in the Roots of Orchids and Surrounding Soil in Heavy Metal Contaminated Area of Mining Heaps**

## **Miroslav Böhmer 1,2,\*, Daniel Ozdín 3, Matúš Raˇcko 3, Michal Lichvár 4, Jaroslav Budiš 2,4,5 and Tomáš Szemes 1,2,4**

Received: 12 September 2020; Accepted: 19 October 2020; Published: 21 October 2020

**Abstract:** Orchids represent a unique group of plants that are well adapted to extreme conditions. In our study, we aimed to determine if different soil contamination and pH significantly change fungal and bacterial composition. We identified bacterial and fungal communities from the roots and the surrounding soil of the family *Orchidaceae* growing on different mining sites in Slovakia. These communities were detected from the samples of *Cephalanthera longifolia* and *Epipactis pontica* from Fe deposit Sirk, *E. atrorubens* from Ni-Co deposit Dobšiná and Pb-Zn deposit Jasenie and *Platanthera bifolia* by 16S rRNA gene and ITS next-generation sequencing method. A total of 171 species of fungi and 30 species of bacteria were detected from five samples of orchids. In summary, slight differences in pH of the initial soils do not significantly affect the presence of fungi and bacteria and thus the presence of the studied orchids in these localities. Similarly, the toxic elements in the studied localities, do not affect the occurrence of fungi, bacteria, and orchids. Moreover, *Cortinarius saturatus*, as a dominant fungus, and *Candidatus Udaeobacter* as a dominant bacterium were present in all soil samples and some root samples. Finally, many of these fungal and bacterial communities have the potential to be used in the bioremediation of the mining areas.

**Keywords:** *Orchidaceae*; soil; bacteria; fungi; microbiome; heavy metal; NGS

## **1. Introduction**

Orchids belonging to the family *Orchidaceae* are well known for their rarity and presence of mycorrhizal associations [1,2]. This specialization contributes to the diversity and rarity of orchid species [3,4]. They grow in specific habitats such as mining dumps. Mine heaps and mine wastes created by the mining industry are one of the extreme habitats made by anthropogenic activity. Interestingly, mine heaps create an environment with specific ecological conditions for plant adaptation. They are characterized by the lack of soil as well as nutrients and moisture, and the absence of a humus layer [5]. Unique species from the family *Orchidaceae*, such as narrow-leaved Helleborine (*Cephalanthera longifolia*; Figure 1D) and Pontic Helleborine (*Epipactis pontica*; Figure 1E) which grows on the Fe deposit in Sirk, dark-red Helleborine (*E. atrorubens*; Figure 1C) from the Ni-Co deposit Dobšiná and Pb-Zn deposit Jasenie (*E. atrorubens*; Figure 1A) and Lesser Butterfly orchid (*Platanthera bifolia*; Figure 1B) from the Pb-Zn deposit Jasenie which grows on the initial soils (rankers) and tolerates high concentration of

heavy metals, are well adapted to extreme conditions of the environment. These organisms germinate only after colonization with a suitable mycorrhizal fungus [6].

**Figure 1.** Unique species from the family *Orchidaceae*. *E. atrorubens* (**A**) and *P. bifolia* (**B**) from the Pb-Zn deposit Jasenie, *E. atrorubens* (**C**) from the Ni-Co deposit Dobšiná, *C. longifolia* (**D**) and *E. pontica* (**E**) from Fe deposit Sirk.

The fungi provide the basic physiological function for the orchids in the uptake of needed nutrients and water, otherwise inaccessible to plants [7], facilitate the emergence and survival of vegetation under stressful conditions [8], stabilize waste material through a network of veneers and improve its structure by producing substances that bind to soil particles and lead to the formation of soil aggregates [9].

The microorganisms are known to detoxify metals by several mechanisms including ion exchange, chelation, adsorption, crystallization, valence transformation, extra- and intracellular precipitation and active absorption [10]. The sorption and accumulation of metals depend on various factors such as pH, temperature, organic matter, ion species and the presence of other ions in solutions that may be in competition. They develop adaptation by temporarily altering their developmental patterns or modifying physiological characteristics depending on the toxicity of metals, which is affected by the concentration and form of salts in which the metal exists [11].

Bacteria play a key role in the element biotransformation, biogeochemical cycling, metal and mineral transformation, biological weathering and formation of the soil and sediment [12]. They have high importance in industrial processes, bioremediation, and heavy metal tolerance [13].

To identify fungi and bacterial communities the Illumina MiSeq platform was used. It is a scalable, ultra-high-throughput, cost-effective and a powerful tool to detect soil microbial communities at

greater depth and with more detailed sequence information [14,15]. It has been successfully applied to identify microbial communities almost everywhere [16,17], including heavy metal contaminated environments [18,19].

The aim of this paper is to identify the composition of bacterial and fungal communities present in the roots and the surrounding soil of the orchids growing on heavy metal contaminated areas of mining heaps. To detect these communities we used 16S rRNA gene and ITS next-generation sequencing approach. At the same time, our aim was to compare the data of fungal and bacterial communities with the pH value in the Pb-Zn mining heap Jasenie-Soviansko, Ni-Co mining heap Dobšiná-Dobrá nádej and Fe mining heap Sirk-Železník. The broader goal of the study was to determine the unique microbial content of plant root collected from contaminated soil as potential biomarker applicable in further studies or monitoring efforts.

## **2. Materials and Methods**

## *2.1. Site Description*

Plants, soils, and geological bedrock investigated in this study originated from three abandoned mining sites in Slovakia, Central Europe (Pb-Zn deposit Jasenie-Soviansko, Ni-Co deposit Dobšiná-Dobrá nádej and Fe deposit Sirk-Železník).

The Pb-Zn deposit Jasenie-Soviansko (N 48◦89 27, E 19◦44 15) is situated in the western Dumbier part of the N ˇ ízke Tatry Mts., 7 km north from the village Jasenie. The deposit consists of several old mining waste dumps, but orchids occurred only in the heap of the Emil adit, which is located at an altitude of 834 m a. s.l. *E. atrorubens* occurs mainly on a sharp slope of a mining heap with almost no moss or lower plants. Few orchids (*E. atrorubens and P. bifolia*) grew on the horizontal part of the waste dump under trees (especially spruce, willow and birch) or above heap material covered with moss, lower vegetation, and trees. *E. atrorubens* was extremely widespread in the mining heap and more than 1000 individuals grew on an area about 500 m2. Technogenic substrate is formed mainly of metamorphic rocks of the crystalline basement of the Tatric unit of the Western Carpathians (mostly orthogneisses and migmatites) with fragments of mineralized rocks and also partially ore veins. Parts of ore veins and hydrothermally altered rocks formed hydrothermal carbonates (siderite, dolomite, ankerite, calcite), quartz and baryte and the sulphides are represented mainly as tetrahedrite, galena, bournonite, pyrite, chalcopyrite and sphalerite [20–22]. At the sampling site of the orchid and the substrate, the size of the rock fragments was up to ~7 cm. *E. atrorubens* grew in a bright habitat, without the presence of other higher plants, mosses and lichens. The slope of the mining heap with orchids was oriented to the south (SSW).

The Ni-Co deposit Dobrá nádej in Dobšiná is located in the Spišsko-Gemerské Rudohorie Mts., in the central part of the Slovak Ore Mountains Mts. in the Inner Western Carpathians (N 48◦84 31, E 20◦39 08). The mining heap is situated at an altitude of 807 m a.s.l. Orchids occur on the vertical part of a heap without vegetation but also in the horizontal part of a waste dump between low spruces and sparse low vegetation represented mainly by grasses. Samples of the orchid *E. atrorubens* and technogenic substrate were taken from the mining heap, where metamorphic rocks (phyllites, acidic metavolcanites and metasediments) dominate the Gemer superunit. Hydrothermal minerals were represented by siderite, ankerite, dolomite, quartz, hematite, Fe-Ni-Co sulphides, pyrite, chalcopyrite and minerals of tetrahedrite group [20]. Up to 4 cm was the size of the rock fragments at the sampling point of the plant and substrate. The lighting and botanical conditions at the site and the slope orientation of the mining heap were the same as in the locality Jasenie.

The Fe deposit Sirk-Železník (N 48◦61 71, E 20◦10 54) represents a weathered zone of hydrothermal Fe deposit which is located in the Revúcka vrchovina Highlands, 10 km west of Jelšava, near the village Sirk at an altitude 416 m a.s.l. Phyllites, limestones, metaryolite tuffites and metalalydites [23] occurred mostly at this deposit site. Orchids collected for research were found in the forest of a technogenic substrate with a frequent abundance of fungi and incomplete decomposed plant residues. This initial substrate was located between pieces of limonite-quartz iron ore ~8–30 cm in size. No hydrothermal carbonates were present here. Orchids grew in a light deciduous to mixed forest, mostly on a horizontal part of a mining heap between moss-covered pieces of heap material. All individuals of *E. pontica* grew in one place, in an area of ~15 m2. *C. longifolia* grew in a disseminated forest a few meters to tens of meters from the occurrence of *E. pontica*.

Further information about localities is given in Raˇcko et al. (2020) [20].

## *2.2. Sampling and DNA Extraction*

The samples of the family *Orchidaceae* were taken from their place of growth. After the plant was collected, the surrounding soil was taken from this area (up to 30 cm in depth). The roots were washed with distilled water to remove remaining soil particles followed by sterilization, according to Cao et al. (2004) [24] with some modifications, with 70% ethanol for 5 min, sodium hypochlorite (2.5% available chlorine) for 5 min, and again with 70% ethanol for 1 min. After that, the roots were washed multiple times with distilled water to remove sterilization agents. Surface-sterilized roots were cut into 1–2 cm pieces and crushed on powder using mortar, pestle, and liquid nitrogen. Isolate II Plant DNA kit (Bioline, Toronto, ON, Canada) was used to extract DNA from these crushed roots. For DNA extraction from soil DNeasy PowerSoil kit (Qiagen, Hilden, Germany) was used.

## *2.3. Chemical Analysis*

The pH of the soil was determined in the distilled H2O and NH4NO3. Oxidisable organic carbon (%COx) was analyzed by oxidimetry under laboratory conditions. Collected soils contained various heavy metals and potentially toxic elements above limit values as described in detail at Raˇcko et al. (2020) [20].

## *2.4. Polymerase Chain Reaction and Library Preparation for Next-Generation Sequencing*

Bacterial 16S rRNA gene and fungal ITS region were amplified using primer pair sequences for the V3 and V4 region [25] and ITS region [26]. We used 16S Amplicon PCR Forward Primer (5 -TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC AG-3 ), 16S Amplicon PCR Reverse Primer (5 -GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA ATC C-3 ), ITS1 (5 -TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CTT GGT CAT TTA GAG GAA GTA A-3 ) and ITS4 (5 -GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GTC CTC CGC TTA TTG ATA TGC-3 ). All primers contained Illumina adapter regions. PCR mixture contained HotStartTaq® Plus Master Mix (Qiagen, Hilden, Germany) (10 μl), template DNA (20 ng), and amplicon primers (2 μL, 1 μM) in the total reaction volume of 20 μl. Reaction conditions consisted of an initial 95 ◦C, 3 min; 35 cycles of 95 ◦C for 60 s, 60 ◦C, 45 s, and 72 ◦C, 60 s, and final extension of 72 ◦C, 7 min. After Amplicon PCR, samples were purified with DNA Clean & Concentrator™-25 (Zymo Research, Irvine, CA, USA).

We used the 16S Metagenomic Sequencing Library Preparation protocol (Illumina Inc., San Diego, CA, USA) to create libraries. Index PCR was performed following the manufacturer's instructions using 2x KAPA HiFi HotStart ReadyMix (25 μL, Kapa Biosystems, Wilmington, MA, USA), Nextera XT Index Primers (5 μL per sample, Illumina Inc., San Diego, CA, USA), PCR grade water, and 5 μL of template DNA/cDNA solution in the total reaction volume of 50 μL. PCR Clean-Up 2 was performed as described in the protocol, followed by library validation using Qubit dsDNA high sensitivity assay (LifeTechnologies, Eugene, OR, USA) and Agilent® HS DNA Chip (Agilent® Technologies 2100 Bioanalyser, Santa Clara, CA, USA). Finally, DNA libraries were normalized to 4 nM concentration, denatured and processed to the sequencing run on MiSeq instrument (Illumina Inc., San Diego, CA, USA) using a MiSeq Reagent kit v3 (Illumina Inc., San Diego, CA, USA) with the paired-end setting of 2 × 300 bp reads.

## *2.5. Data Analysis*

Adapters and low-quality ends of sequenced reads were removed using Trimmomatic (version v0.36) [27], based on quality control statistics generated by FastQC (v0.11.5) [28]. After trimming, fragments without sufficient length of both reads (>35bp) were removed from the data set. All trimmed paired reads with sequence overlaps were merged using PEAR (v0.9.10) [29] and passed to QIIME 2 (v2019.10.0) for microbial analyses [30]. There, fastq files were dereplicated using built-in tool vsearch. Then, chimeras and "borderline chimeras" [31] were removed from the dataset using de novo chimera filtering with default parameters [30]. Operational taxonomic units (OTUs) with 99% similarity were created with de novo clustering of features.

Taxonomy of OTUs was assigned by QIIME's pre-fitted sklearn-based taxonomy classifier [32]. The pre-fitted classifier was trained by the Naive–Bayes classifier with default parameters on Silva 16S database (Silva release 132) [33] and ITS database (UNITE 8.2) [34]. Only taxons with <0.1% of all reads per sample were used for bacteria and <0.01% for fungi. Finally, Faith's phylogenetic diversity for all samples was calculated using faith-pd plugin [35]. All computational analyses were written and executed using the SnakeLines framework (v0.9.2) [36,37].

## **3. Results and Discussion**

*Orchidaceae* is a family of rare plants and their presence in metal-rich biotopes has ecological and conservation importance [38]. Orchids colonizing mining heaps rely on the fungal mycelium to obtain the necessary nutrients since their root system is not well developed. They belong to metal excluders, and mycorrhizal fungi seem to play an important role in filtering out the heavy metals [38–40]. Despite these extreme conditions, the environment is sufficiently tolerable to the population of orchids, soil filamentous fungi and bacteria.

In orchidaceous mycorrhiza, fungi have the ability to support the composition of plants in stressed ecological niches and to increase the plant's condition [41]. The properties of orchidaceous mycorrhiza in mycoheterotrophic plants that allow colonization under stress conditions are changes in root morphology, orchid metabolism, such as enzymatic activities, secretion of organic acids with low molecular weight and phenols, and associations with orchideous mycorrhizal fungus adapted to the environmental conditions in which orchids occur [42,43]. To identify fungal and bacterial communities in the roots of orchids and surrounding soil in heavy metal contaminated areas we used the marker gene sequencing approach which has been the most commonly used method to analyze these communities. It is simple, fast, cost-effective, and well-tested approach [44,45] in comparison to whole-genome sequencing [45,46].

A total of 171 species of fungi were detected from five samples of orchids, belonging to seven phyla, *Ascomycota*, *Basidiobolomycota*, *Basidiomycota*, *Chytridiomycota*, *Monoblepharomycota*, *Mortierellomycota*, and *Mucoromycota* (Table 1). The highest biodiversity of fungi was situated in the roots of *E. pontica* (Sirk), and the surrounding soil of *E. atrorubens* (Jasenie). Moreover, the most abundant phylum of fungi was *Basidiomycota* in both soil and the roots of orchids. Furthermore, the most abundant species of fungi in the roots of orchids was *Cortinarius saturatus*, *Mycena* sp., *Mycena citrinomarginata*, *Mycenella bryophila*, *Colletotrichum capsici*, *Trichophaea pseudogregaria*, *Phacidium* sp., *Russula solaris*, *Mortierella* sp., *Amphinema byssoides*, *Mycena sanguinolenta*, *Amphinema* sp., and *Piloderma byssinum* (Figure 2). Further, in the surrounding soil, it was *Cortinarius saturatus*, *Cortinarius scandens*, *Helvellosebacina concrescens*, *Mortierella* sp., *Cortinarius* sp., *Helvellosebacina* sp., *Cuphophyllus virgineus*, *Tetracladium* sp., *Colletotrichum capsici*, *Cortinarius vernus*, *Penicillium* sp., *Saitozyma podzolica*, and *Solicoccozyma terricola* (Figure 3). In addition, we observed that the biodiversity in sampled pairs were consistently higher in soil samples, both in the number of discovered species (median 2.7x higher) and the evenness (median 2.66x higher of Faith's phylogenetic diversity). Decreased diversity could be due to the specific environment in the roots of the orchids.

**Table 1.** DNA identification of the fungi isolated from the roots of the orchids and surrounding soils.

**Table 1.** *Cont*.

*Scleroderma* sp. −−−−−−−−− +

**Table 1.** *Cont*.

The pH value is a key factor affecting the plant, fungal and bacterial communities on the mining dumps. Soil fungi can grow over a broad range of pH [47], however, soil bacteria are more sensitive to low pH [48], so fungi can dominate this pH spectrum. Values of pH varied from acidic (4.98) to slightly alkaline (7.81).

A high number (57) of fungal species, found in the surrounding soil, tolerate acidic pH of 4.98. Regarding roots, it was 37. Similar to our study, fungi like *Cladophialophora* sp., *Cladosporium* sp., *Exophiala* sp., *Mortierella alpina*, *Mortierella* sp., *Mucor* sp., *Mucor hiemalis*, *Penicillium* sp., *Umbelopsis* sp. provided a great tolerance to a higher concentration of some heavy metals in high acidic to neutral pH of the soils [49]. In regard to to pH, we did not observe anything significant or different in comparison to other studies [50–52]. Organisms from extreme habitats have developed strategies for survival and growth in harsh conditions in the production of organic molecules [53]. They have the

ability of adaptation to high salinity, radiation, limited nutrients, extreme temperatures and pressure, and variable values of the acidity [54]. In these contaminated areas, metal-resistant fungi occur which have potential in the process of bioremediation [55].

**Figure 2.** Fungal communities detected in the roots of orchids. (1) *E. atrorubens* (Dobšiná); (2) *E. atrorubens* (Jasenie); (3) *P. bifolia* (Jasenie); (4) *E. pontica* (Sirk); (5) *C. longifolia* (Sirk).

The benefits of mycorrhizas to both plants and fungi is an uptake of nutrients. The fungi obtain carbon from the plants, and in return, enhance a plant's ability to take up minerals or water, subsequently leading to improvement of plant growth and reproduction [56]. Many species of fungi possess the ability to act as an effective biosorbent of the toxic metal. However, these elements may inhibit their growth and affect their reproduction [57].

Species, such as *Colletotrichum capsici*, *Cortinarius saturatus*, *Cortinarius* sp., *Mortierella* sp., *Penicillium* sp., and *Tomentella* sp. were present in soil in four or more samples. Regarding roots, it was *Mycena* sp., *Colletotrichum capsici*, *Cortinarius saturatus*.

The composition of fungi in orchid roots is usually much more uniform for orchid species growing in a forest community in the presence of more species of higher plants and trees than for orchids that form plant monocultures on the stony substrate of mining heaps. This difference is not so significant for the fungi present in the soil.

At the same time, the study of fungi in the roots of different species of orchids from different types of habitats and the surrounding technogenic substrate showed that the only species of fungus that occurred in an increased quantity of all the samples was *Cortinarius saturatus*. In all other fungi, their quantitative composition in the soils and roots of orchids did not correlate. In many cases, significantly present species in the roots were almost non-existent in the soil, and vice versa.

In the study of fungi from the mining sites [52] and recent study of microscopic fungi from five substrates of old environmental loads [50], species, such as *Cladosporium* sp., *Exophiala* sp., *Mortierella*

*alpina*, *Mortierella* sp., *Mucor hiemalis*, *Mucor* sp., *Penicillium spinulosum*, *Penicillium* sp., *Phialocephala* sp., and *Umbelopsis* sp. agreed with our results.

**Figure 3.** Fungal communities detected in the surrounding soil of orchids. (1) *E. atrorubens* (Dobšiná); (2) *E. atrorubens* (Jasenie); (3) *P. bifolia* (Jasenie); (4) *E. pontica* (Sirk); (5) *C. longifolia* (Sirk).

The function of the genus *Mycena*, which is one of the representatives to be present in four samples, is to influence the growth of roots [58]. Despite the great biodiversity of fungal genera present in the individual samples, a comparison of the root and soil samples suggests the specificity of both for the host plant. In another study by Cui et al. 2017 [59], *Mortierella* sp. effectively reduced the heavy metals and significantly shortened the remediation period and improved the poor habitat of mine tailings. Bioaccumulation and biosorption abilities of *Penicillium* spp. were also studied [60–62].

## *Bacterial Communities*

Bacteria have high importance in industrial processes, bioremediation, and heavy metal tolerance [13]. Bioremediation is the process of biological systems cleaning of the polluted environment by the bacteria and fungi, which are important for reclamation, immobilization and detoxification of heavy metals [63].

A total of 30 species of bacteria were detected from five samples of orchids, belonging to eight phyla, Acidobacteria, Actinobacteria, Bacteroidetes, Gemmatimonadetes, Planctomyces, Proteobacteria, Verrucomicrobia, and Tenericutes (Table 2). The highest biodiversity of bacteria was in the roots and also surrounding soil of E. atrorubens (Jasenie). Additionally, the evenness in sampled pairs was consistently higher in soil samples (median 1.2x higher of Faith's phylogenetic diversity). However, that was not the cause in the number of discovered species as it was in analysis of fungal communities.

**Table 2.** DNA identification of the bacteria isolated from the roots of the orchids and surrounding soils.

Our results show (Figures 4 and 5) that *Candidatus Udaeobacter* was the dominant bacterium at the Sirk deposit in the roots of two different orchids as well as in technogenic substrate and a high dominance of bacteria from the family *Pyrinomonadaceae* in a stony substrate on the mining heap in Dobšiná and the related very dominant abundance of the fungus *Trichophaea pseudogregaria* in the roots of *E. atrorubens*. The most abundant species in the roots of orchids was *Candidatus udaeobacter*, *Gemmata* sp., *Singulisphaera* sp., *Chthoniobacter* sp., *Pseudomonas* sp., *Luteolibacter* sp., *Nocardioides* sp., *Pirellula* sp. (Figure 4). In the surrounding soil, it was *Candidatus udaeobacter*, *Chthoniobacter* sp., *Pyrinomonadaceae*; *RB41*, *Gemmata* sp., and *Pirellula* sp. (Figure 5). Moreover, *Candidatus udaeobacter*, *Candidatus solibacter*, and *Chthoniobacter* sp. were present in four or more soil samples. Furthermore, 11 species tolerated pH of 4.98.

**Figure 4.** Bacterial communities detected in the roots of orchids. (1) *E. atrorubens* (Dobšiná); (2) *E. atrorubens* (Jasenie); (3) *P. bifolia* (Jasenie); (4) *E. pontica* (Sirk); (5) *C. longifolia* (Sirk).

Species, such as Candidatus solibacter, *Bradyrhizobium* sp., *Burkholderia* sp., *Gemmatimonas* sp., *Fimbriiglobus* sp., *Flavobacterium* sp., *Pseudomonas* sp., *Sphingomonas* sp., *Pedobacter* sp., and *Verrucomicrobia* sp. were also detected in heavy metal contaminated soils [64–68]. A bacterium with the highest relative abundance was Candidatus udaeobacter, which is an abundant soil bacterium that reduces its requirement for soil organic carbon by acquiring costly amino acids and vitamins from the environment [69]. Pirellula sp. found in both roots and soil gains energy from the aerobic oxidation of mono- or disaccharides derived from the cleavage of sulfated polymers produced by algae [70].

Bacteria from the genus *Pseudomonas* induce auxin production by plant growth-promoting bacteria [71]. They are also known as very metabolically active bacteria able to utilize many agrochemicals [72–74]. Together with *Luteolibacter* sp., *Vicinamibacter* sp., and *Sphingomonas* sp. they were identified by many other studies as an oil-degrading bacteria which is important for bioremediation [75–77]. *Acidibacter* sp. and *Candidatus solibacter* were suitable to be grown in oil-contaminated soils [78].

The genera representing the heterotrophic strain *Planctomycetes* have the ability to reduce sulfur and, in particular, play an important role in sugar metabolism [79]. The overlap of the genera present indicates a close connection of the plant with the microbiome, therefore the plant is able to adapt quickly to changing conditions. *Nitrosomonadaceae* is a strictly aerobic bacteria which has a chemolithoautotrophic metabolism using ammonia as an energy source producing nitrite [80]. *Nocardioides* spp. are often isolated as plant endophytes and are known to be capable of suppressing crop pathogens [81]. Together with the members of the genus *Flavobacterium*, they are widely distributed in various environments such as soil, water, and sediment [82].

According to *E. atrorubens* which was studied at two different localities, we showed that it is not important what species of mycorrhizal fungi and bacteria are associated with orchids, but their presence in the substrate. Therefore, the studied orchids can grow in technogenic or anthropogenic soils and substrates as well as other extreme habitats. The species composition of mycorrhizal fungi in the roots of *E. atrorubens* is very variable in each locality apart from the *Cortinarius saturatus* species, which is present in all examined roots of orchids. No other species had a significant quantitative representation in both localities of this orchid. Our research has shown that *E. atrorubens* can use either one dominant fungus (Dobšiná deposit, up to almost 65% representation of the species *Trichophaea pseudogregaria*) or even a larger number of species of quantitatively under-represented fungi (Jasenie deposit) for its enormous occurrence in these localities.

**Figure 5.** Bacterial communities detected in the surrounding soil of orchids. (1) *E. atrorubens* (Dobšiná); (2) *E. atrorubens* (Jasenie); (3) *P. bifolia* (Jasenie); (4) *E. pontica* (Sirk); (5) *C. longifolia* (Sirk).

## **4. Conclusions**

Due to its adaptation and survival strategy, the family *Orchidaceae* has become an interesting target for microbiome identification. In this work, we identified bacterial and fungal communities from the roots and surrounding soil of orchids from five heavy metal contaminated areas of the mining sites Fe deposit Sirk (*C. longifolia* and *E. pontica*), Pb-Zn deposit Jasenie (*E. atrorubens* and *P. bifolia*), and Ni-Co deposit Dobšiná (*E. atrorubens*). To sum up, slight deviations in pH of the initial soils do not significantly affect the presence of fungi and bacteria and thus the presence of the studied orchids in these localities. Similarly, the toxic elements (e.g., As, Pb, Cr, Ni, Co, Cu, Fe), in the studied localities, do not affect the occurrence of fungi and bacteria, and also orchids. Furthermore, the study of selected factors influencing the occurrence of orchids showed that the most important factors of the occurrence of orchids in technogenic soils are the presence of a sufficient number of fungi and bacteria, sufficient light and the absence of other plant species in the habitat. Moreover, microbial communities also provide a huge benefit for orchids to be able to grow in these polluted areas. Additionally, some of these microbial communities possess huge biotechnological potential in bioremediation of heavy metal

contaminated areas. However, to fully understand the microbiota and its interaction with orchids in heavy metal contaminated areas, further investigation is needed.

**Author Contributions:** Conceptualization, D.O.; methodology, D.O. and T.S.; software, J.B.; validation, M.B.; formal analysis, M.L. and M.B.; investigation, D.O. and M.B.; resources, D.O. and T.S.; data curation, J.B. and M.B.; writing—original draft preparation, M.R. and M.B.; writing—review and editing, D.O. and T.S.; visualization, M.B.; supervision, D.O. and T.S.; project administration, D.O.; funding acquisition, D.O. and T.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Slovak Research and Development Agency (APVV−0375−12 and APVV−16−0264).

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

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## **E**ff**ect of Arbuscular Mycorrhizal Fungi (AMF) and Plant Growth-Promoting Bacteria (PGPR) Inoculations on** *Elaeagnus aangustifolia* **L. in Saline Soil**

## **Jing Pan 1,2, Cuihua Huang 1, Fei Peng 1,3, Wenjuan Zhang 1,2, Jun Luo 4, Shaoxiu Ma 1 and Xian Xue 1,\***

Received: 30 December 2019; Accepted: 28 January 2020; Published: 1 February 2020

**Abstract:** Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are considered highly-efficient agents for conferring salt tolerance in host plants and improving soil fertility in rhizosphere. However, information about the inoculation of beneficial microbes on halophytes in arid and semi-arid regions remains inadequate. The objective of this study was to evaluate the influence of AMF (*Glomus mosseae*) inoculation, alone or in combination with PGPR (*Bacillus amyloliquefaciens*), on biomass accumulation, morphological characteristics, photosynthetic capacity, and rhizospheric soil enzyme activities of *Elaeagnus angustifolia* L., a typical halophyte in the northwest of China. The results indicate that, for one-year-old seedlings of *Elaeagnus angustifolia* L., AMF significantly promoted biomass accumulation in aboveground organs, increased the numbers of leaves and branches, and improved the leaf areas, stem diameters and plant height. AMF-mediated morphological characteristics of aboveground organs favored light interception and absorption and maximized the capacities for photosynthesis, transpiration, carbon dioxide assimilation and gas exchange of *Elaeagnus angustifolia* L. seedlings in saline soil. AMF also promoted root growth, modified root architecture, and enhanced soil enzyme activities. *Elaeagnus angustifolia* L. was more responsive to specific inoculation by AMF than by a combination of AMF and PGPR or by solely PGPR in saline soils. Therefore, we suggest that *G. mosseae* can be used in saline soil to enhance *Elaeagnus angustifolia* L. seedlings growth and improve soil nutrient uptake. This represents a biological technique to aid in restoration of saline-degraded areas.

**Keywords:** halophyte; arbuscular mycorrhizal fungi; plant growth promoting rhizobacteria; morphological characteristics; photosynthesis; soil enzymes

## **1. Introduction**

Soil salinity is a severe agronomical, ecological, and socioeconomic concern in most arid and semi-arid regions of the world [1,2]. Most of salt-affected land has become saline owing to natural accumulation of salts over long periods of time, while others are caused by anthropogenic mismanagement [1]. Salinity in soil provokes the loss of natural plant communities [2], destroys ecosystem diversity [3], reduces the production of crops and forages [4], accelerates the process of soil degradation [2], and reduces the potential utilization of halophytes as crops [5]. Salinity not only adversely affects agriculture and ecosystems, but also poses a threat to public health and security [6], which further exacerbates unsustainable livelihoods and inequalities in socio-economic development [7]. Moreover, saline soil is sensitive to global climate change, this further intensifies salinization [8,9]. It is estimated that salinization will threaten more than 50% of arable land worldwide by 2050 [10]. Hence, this silent hazard will continue to threaten agricultural sustainability, food security, ecosystem stability, human health and income generation.

The northwest arid area of China is one such region that is highly vulnerable to global climate change, and is widely affected by soil salinization [11]. The Minqin Oasis is considered an essential part of the Chinese Silk Road in the northwest arid area of China. As one of the world's driest and most fragile regions, the Minqin oasis has witnessed significant impacts of both natural and anthropogenic factors on soil salinization. Harsh natural conditions, such as very high temperatures, low rainfall, and strong evaporation, lead to soil natural salinization [11,12]. Many organism inhabitants are well well adapted to this naturally saline environment. Anthropogenic factors, such as outdated irrigation systems combined with excessive groundwater extraction, execrate soil secondary salinization. Secondary salinization inhibits plant growth, reduces crop yield, changes the habitat pattern of halophytes, and causes vegetation degeneration and ecosystem deterioration in the Minqin Oasis [13–15], which further results in wasted land. If this wasted land is not improved in a timely manner, Minqin oasis will become a new source of salt dust and a national ecological crisis zone in China. Therefore, strengthening saline soil research in the Minqin Oasis not only has a positive effect on the regional biodiversity conservation, but also guides the study of ecosystems in the northwest arid areas of China.

*Elaeagnus angustifolia* L., a very important halophytic perennial tree in the Minqin Oasis, has excellent tolerance to salinization, sand and barren land [16], and has high value in ecology, economics and medicine [17,18]. However, the persistent expansion and aggravation of soil salinization in the Minqin Oasis, driven by both natural and anthropogenic factors, is threatening the habitats of *Elaeagnus angustifolia* L. Salinity intrusion in this area not only adversely affects the growth, productivity and distribution of *Elaeagnus angustifolia* L. but also lowers the sheltering effects of the protective forest dominated by *Elaeagnus angustifolia* L. to farmland [16]. Previous studies have reported that indigenous halophytes can survive in saline habitats thanks to the co-evolution of halophytes and microbes [2,19,20]. The collaboration of halophytes and microbes not only enhances plant biomass and population diversity [21,22] but also improves soil microbial activities and other soil properties [19,23]. Therefore, there is potential to exploit beneficial soil microbes to promote the growth of *Elaeagnus angustifolia* L. and to further use these microbes to ameliorate saline soil in the Minqin Oasis.

Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are beneficial below-ground microbes that directly associate with plant roots [24,25]. Previous studies showed that the growth-promoting effects on host glycophytes under salt stress are attributable to AMF and PGPR, which could enhance salt tolerance by altering root morphology, modifying root-to-shoot communication, increasing nutrients uptake, maintaining ion homeostasis, decreasing oxidative damage, and elevating photosynthetic capacity [10,24,26,27]. As bio-inoculants, AMF and PGPR also play vital roles in soil biological activity, benefiting the remediation of saline soil, and consequently increasing the suitability of saline soil to plant growth [28,29]. However, little is known about the inoculation effects of different beneficial microorganisms on the biomass accumulation, morphological characteristics, photosynthetic capacities, and rhizospheric soil enzymes of halophytes, especially *Elaeagnus angustifolia* L. in saline soil.

Based on this existing knowledge, the objective of our study is to test the effects of AMF inoculation, both alone and in combination with PGPR, on *Elaeagnus angustifolia* L. in saline soil. We address the following research questions: (1) what are the impacts of AMF and PGPR inoculations on biomass accumulation, morphological characteristics, photosynthesis and soil enzymes of *Elaeagnus angustifolia*

L. in saline soils? (2) Is species diversity or a particular key species most important in controlling the growth characteristics and salt tolerance of *Elaeagnus angustifolia* L.?

## **2. Materials and Methods**

## *2.1. Study Site*

The study area is located at the Drylands Salinization Station affiliated to the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, China, which is located in the low reaches of the Shiyang River (N 39◦02 38", E 103◦36 36") (Figure 1).

**Figure 1.** The location of the Drylands Salinization Station.

Over a 30-year period, the mean annual precipitation is 119.46 mm. The maximum annual precipitation is 202 mm in 1994, and the minimum annual precipitation is 77.3 mm in 1989 (Figure 2a). In 2007, the total precipitation is 95 mm. The maximum temperature is 42.13 ◦C in July, and minimum temperature is −25.9 ◦C in January. The maximum and minimum photosynthetic active radiation is 730.2 μmol m−2s−1 and 41.57 μmol m−2s−1, respectively (Figure 2b).

## *2.2. Soil and Plant Treatment*

Soil and seeds utilized in this experiment were collected from the Drylands Salinization Station affiliated to the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, China, which is located in the low reaches of the Shiyang River (N 39◦02 38", E 103◦36 36") (Figure 1). The soil was collected from the top layer (0–20 cm) of an agricultural field, then passed through a 5 mm sieve. The soil was classified into Orthic Halosols in the Chinese taxonomic system and was identified as Ustifluvent in the taxonomic system of United States Department of Agriculture [30,31]. The soil used throughout this experiment before planting had the following properties: pH of 8.14±0.02, EC of 2015 ± 15 μS cm−1 (water-soil ratio of 5:1), organic carbon content of 9.36 ± 0.18 g kg−1, total N of 0.61 ± 0.01 g kg−1, available P of 16.41 ± 0.81 kg ha−1, and available K of 47.75 mg kg−1 [11]. Healthy fruits of *Elaeagnus angustifolia* L. were selected carefully, and peeled to obtain the seeds. These seeds were surface-sterilized with NaOCl (5%) for 10 min and then thoroughly rinsed with deionized water to completely remove all traces of NaOCl.

**Figure 2.** The characteristics of precipitation, temperature and photosynthesis active radiation (from meteorological data in the Drylands Salinization Station). (**a**) total precipitation amount and average temperature per year, (**b**) average temperature and photosynthesis active radiation per month.

## *2.3. Microbial Inoculum*

*Glomus mosseae*, the most efficient fungus to help plants to cope with the detrimental effects of salt stress [32]. The strain of *G. mosseae* was commercially provided by the Institute of Plant Nutrition and Resources, Beijing Academy of Agriculture and Forestry Sciences, which was isolated from the rhizospheric soil of *Populus euphratica* in Xinjiang Autonomous Region, China. *G. mosseae* was multiplied using *Sorghum bicolor* as host plant and a mixture of soil, river sand, perlite and quartz sand as substrate (with a mixing ratio of 2:3:3:3) for 4 months. The AMF inoculum contained growth substrate, spores (density of approximately 75 per 10 g dry substrate), mycelium and infected root fragments of *G. mosseae*. Each pot was inoculated with 100 g inoculum for mycorrhizal treatment. Non-mycorrhizal treatment received 100 g sterilized AM inoculum (160 ◦C, 4h). *Bacillus amyloliquefaciens* FZB42 was grown overnight on Luria–Bertani liquid medium with constant shaking at 200 rpm [33]. After incubating overnight, cells were obtained by centrifugation at 10,000 rpm for 6 min, washed once, and re-suspended in deionized water to 1.0 × 108 colony-forming units/mL for use as the PGPR inoculum [33,34].

## *2.4. Plant Growth Conditions and Experimental Design*

A pot experiment was performed outdoors under natural conditions in the Drylands Salinization Station during 11 May to 29 August 2017. Five seeds were sown in experimental pots filled with 1.3 kg saline soil. The pot bottom was covered by mesh (38 μm) to avoid root growth out of the pot. The experiment consisted of four treatments as follows: (1) Control: seeds were soaked in 40 ml sterile water for 30 min and the soil was mixed with sterile AMF inoculum. (2) AM treatment: seeds were soaked in 40 ml sterile water for 30 min and soil was mixed with AMF inoculum. (3) PGPR treatment: seeds were inoculated with PGPR inoculum for 30 min, soil was mixed with sterile AMF inoculum. (4) Co-microbial treatment: soil was treated following the AMF treatment; seeds were treated following the PGPR treatment. After 15 days of emergence, thinning was performed and one seedling was left in each pot. Seedlings had roughly equal heights. Then, seedlings in the PGPR treatment and co-microbial treatment were irrigated with 40 mL PGPR inoculum (108 CFU/ml). All plants were regularly irrigated with water from Shiyang River to maintain soil moisture near field capacity. Each treatment contained eight pots and the seedlings were harvested 110 days after sowing. Five pots were used to measure the parameters of plant biomass, organ morphology, and photosynthesis, and the remaining three pots were used to determine soil enzymes.

## *2.5. Parameter Measurements*

## 2.5.1. Plant Biomass, Organ Morphology, and AMF Colonization Rate

Five replicates of plant height and leaf number were measured and recorded before the end of the experiment. The basal stem diameter was determined by a Vernier caliper. Total leaf area was scanned by an Epson Expression 1480 digital scanner (Epson (China) Co., Beijing, China) and measured by the measurement tool in Adobe Photoshop CS4 software (Version 11.0.1). Plant fresh mass was measured at final harvest, plant dry mass was determined and calculated after oven drying at 60 ◦C to constant mass [35]. The degree of succulence was expressed as the ratio of fresh mass to dry mass [36,37]. Specific stem length was calculated as the ratio of plant height to stem dry mass [38]. AMF colonization rate was also measured at final harvest using fresh root segments which was cut into 1 cm length [39].

The fresh roots were carefully washed under running tap water, dried with paper towels and scanned using the digital scanner Epson Expression 1480 (Epson (China) Co., Beijing, China) to analyze root total length, surface area, projective area, and tip numbers using the WinRHIZO software (Regent Instruments Inc., Quebec, QC, Canada). Root volume was measured in a graduated cylinder by the drainage method. The specific root length was calculated as root length divided by the root dry mass [40].

### 2.5.2. Photosynthesis Measurement

Net photosynthetic rates (Pn), stomatal conductance (Gs), transpiration rate (Tr), and carboxylation efficiency (CE) were determined on the fully expanded leaves using a portable open-flow gas exchange system LI-6400XT (LI-COR, Lincoln, NE, U.S.A) during the period from 9:30 to 11:30 am under natural sunlight and CO2 (400 μmol mol−1) on a sunny day before harvest [41].

#### 2.5.3. Determination of Soil Enzymes

The aerial parts of seedlings were removed after harvesting from the remaining three pots. Visible root materials with adhering soil were removed manually. Remaining soil samples used for analyzing enzymes activities were collected and sieved (2 mm) before analysis. The activities of urease (UE) and sucrase (SC) were determined by indophenol blue colorimetry and 3,5-dinitrosalicylic acid method, respectively [42]. Soil alkaline phosphatase (AKP) was determined by disodium phenylphosphate method [43]. Soil catalase (CAT) was determined by colorimetric method conducted by ultraviolet spectrophometry [44]. All enzymes activities were detected using soil enzyme kits according to the manufacturer's instructions (Comin Biotechnology Co., Ltd, Suzhou, China).

### *2.6. Statistical Analysis*

The experimental data were log-transformed and then analyzed by the analysis of variance, and the comparison among treatment means was conducted using Tukey's test at the 5% level with the statistical software package SPSS 22.0 (SPSS for Windows, Version 22.0, Chicago, IL, USA). Non-transformed data appear in all figures, which were drawn by Sigma Plot version 10.0 (Systat Software Inc., Point Richmond, CA, USA).

## *2.7. Estimation of Salt Tolerance and Soil Enzyme Activities*

Salt tolerance of *Elaeagnus angustifolia* L. seedlings and rhizospheric soil enzyme activities were evaluated by the subordinate function value (SFV) [45] combined with weights. The SFV was calculated using the Equation (1):

$$\text{CLI}\{X\_{ij}\} = \frac{X\_{ij} - X\_{j\text{ min}}}{X\_{j\text{max}} - X\_{j\text{ min}}} \tag{1}$$

where *U*(*Xij*) is the SFV of the index (*j*) for the treatment (*i*), *Xij* is the actual measured value of the index (*j*) for the treatment (*i*), and *Xjmax* and *Xjmin* are the maximum and minimum values of the index (*j*) observed in the treatment (*i*).

The standard deviation coefficient method is used to determine the weight of different indexes. The coefficient of standard deviation (*Vj*) and weight (*Wj*) were evaluated via the following equations:

$$V\_j = \sqrt{\sum\_{j=1}^{n} \left(X\_{ij} - \overline{X}\_j\right)^2} / \overline{X}\_j \tag{2}$$

$$W\_{\bar{j}} = V\_{\bar{j}} / \sum\_{j=1}^{m} V\_{\bar{j}} \tag{3}$$

where *Xij* is the actual measured value of the index (*j*) for the treatment (*i*), *Xj* is the mean value of the index (*j*). Finally, the plant salt tolerance and rhizospheric soil fertility of different treatments are expressed by the comprehensive evaluation value (*D*). We then used Equation (4) to calculate the comprehensive evaluation value (*D*):

$$D = \sum\_{j=1}^{n} \left( \iota \mathcal{U} \{ \mathbf{x}\_{j} \} \times \mathcal{W}\_{j} \right) \tag{4}$$

where *U*(*Xj*) were the SFV of the index (*j*). *D* ranges from 0 to 1.

## **3. Results**

## *3.1. E*ff*ects on Biomass Accumulation and Arbuscular Mycorrhizal Fungi (AMF) Colonization Rate*

Leaf and stem dry masses in the AMF treatment and co-microbial treatment were markedly higher than those in the control (Figure 3a,b). Microbial inoculations significantly increased root dry mass when compared with the control (Figure 3c). AMF colonization rates ranged from 5% in non-inoculated plants to 89.2% in single AMF-inoculated plants, and there are also significant differences between the three microbial treatments (Figure 3d).

**Figure 3.** Effects of *Glomus mosseae* and *Bacillus amyloliquefaciens* on biomass and arbuscular mycorrhizal fungi (AMF) colonization rate of *Elaeagnus angustifolia* L. seedlings in saline soil. Values are the means ± standard deviation of five replicates. Value sharing the different letters indicate significant differences between treatments at the 5% level (Tukey's t-test).  E*ff*ects on Morphological Characteristics of Aboveground Organs*

Leaf numbers and total leaf areas in three microbial treatments statistically increased, while specific stem length in microbial treatments significantly decreased in saline soil when compared with the control (Figure 4a,b,f). Only a single AMF inoculation significantly improved plant height when compared with the control, by 64% (Figure 4c). The presence of AMF, whether singly or combined with PGPR, statistically increased basal stem diameters and branch numbers when compared with the corresponding controls (Figure 4d,e). Both leaf succulence and stem succulence significantly decreased in single AMF-treated plants when compared to the control, by 28.04% and 27.72%, respectively (Figure 4g,h).

**Figure 4.** Effects of *Glomus mosseae* and *Bacillus amyloliquefaciens* on aboveground organ morphological characteristics of *Elaeagnus angustifolia* L. seedlings in saline soils. Values are the means ± standard deviation of five replicates. Value sharing the different letters indicate significant differences between treatments at the 5% level (Tukey's *t*-test). C: Control, A: AMF (*Glomus mosseae*) treatment, P: PGPR (*Bacillus amyloliquefaciens*) treatment, AP: AMF + PGPR treatment. (**a**) Leaf numbers, (**b**) total leaf areas, (**c**) plant height, (**d**) basal stem diameter, (**e**) branch numbers, (**f**) specific stem length, (**g**) leaf succulence, (**h**) stem succulence.

## *3.3. E*ff*ects on Morphological Characteristics of Roots*

Root length significantly increased in the AMF treatment, by 43.89% when compared with the control, and was also markedly higher than that in the PGPR treatment (Figure 5a). Root surface area and root projected area in the PGPR treatments were considerably lower than those in the AMF treatment and co-microbial treatment (Figure 5b,c). The presence of AMF, singly or combined with PGPR, significantly increased the root average diameters and root tip numbers (Figure 5d,e). Compared to the control, all three microbial inoculations significantly increased root volumes (by 58.9–185.04%) (Figure 5f), but markedly decreased specific root lengths (by 54.74–64.38%) and root succulence (by 33.21–49.31%) (Figure 5g,h).

**Figure 5.** Effects of *Glomus mosseae* and *Bacillus amyloliquefaciens* on root morphological characteristics of *Elaeagnus angustifolia* L. seedlings in saline soils. Values are the means ± standard deviation of five replicates. Value sharing the different letters indicate significant differences between treatments at the 5% level (Tukey's *t*-test). C: Control, A: AMF (*Glomus mosseae*) treatment, P: PGPR (*Bacillus amyloliquefaciens*) treatment, AP: AMF + PGPR treatment. (**a**) root length, (**b**) root surface areas, (**c**) root projective areas, (**d**) root average diameters, (**e**) root tips numbers, (**f**) root volume, (**g**) specific root length, (**h**) root succulence.

## *3.4. E*ff*ects on Photosynthesis*

Pn and Gs in three microbial treatments significantly increased when compared with the corresponding controls under saline soil conditions, and significant differences were evident among the three microbial-inoculated treatments (Figure 6a,c). The presence of AMF, whether singly or combined with PGPR, statistically increased Tr (Figure 6b). CE only significantly increased in the AMF treatment when compared with control, by 40.84%. CE in the AMF treatment was also significantly higher than that in the PGPR treatment and co-microbial treatment, by 40.69% and 29.82%, respectively (Figure 6d).

**Figure 6.** Effects of *Glomus mosseae* and *Bacillus amyloliquefaciens* on photosynthetic parameters of *Elaeagnus angustifolia* L. seedlings in saline soils. Values are the means ± standard deviation of five replicates. Value sharing the different letters indicate significant differences between treatments at the 5% level (Tukey's *t*-test). C: Control, A: AMF (*Glomus mosseae*) treatment, P: PGPR (*Bacillus amyloliquefaciens*) treatment, AP: AMF + PGPR treatment. (**a**) net photosynthetic rate, (**b**) transpiration rate, (**c**) stomatal conductance, (**d**) carboxylation efficiency.

## *3.5. E*ff*ects on Soil Enzymes*

The CAT in the rhizosphere soils only significantly increased in the AMF treatment (Figure 7a). AMF inoculation, singly or combined with PGPR, significantly increased AKP in the rhizosphere soil, by an average of 12.86% when compared to the control (Figure 7b). A significant increase of UE was only found in the single AMF inoculation, by 36.01% (Figure 7c). Compared to the control, SC increased by 27.41% and 53.28% in the AMF treatment and co-microbial treatment, respectively (Figure 7d).

**Figure 7.** Effects of *Glomus mosseae* and *Bacillus amyloliquefaciens* on photosynthetic parameters of *Elaeagnus angustifolia* L. seedlings in saline soils. Values are the means ± standard deviation of three replicates. Value sharing the different letters indicate significant differences between treatments at the 5% level (Tukey's *t*-test). C: Control, A: AMF (*Glomus mosseae*) treatment, P: PGPR (*Bacillus amyloliquefaciens*) treatment, AP: AMF + PGPR treatment. (**a**) soil catalase, (**b**) soil alkaline phosphatase, (**c**) soil urease, (**d**) soil sucrase.

## *3.6. Salt Tolerance Assessment*

Based on the ranking of SFVs of 18 parameters, the AMF treatment had the highest SFV and control had the lowest. The salt tolerance ranking of different treatments was AMF treatment > AMF and PGPR treatment > PGPR treatment > control (Table 1).

**Table 1.** Salt tolerance assessment of *Elaeagnus angustifolia* L. under different treatments using the subordinate function value method.

 Soil Fertility Assessment*

We used the SFV method to evaluate the soil fertility in the rhizosphere of *Elaeagnus angustifolia* L. seedlings in saline soils. Based on the ranking of SFVs, the soil enzymes ranking was AMF treatment > co-microbial treatment > PGPR treatment > control (Table 2).

**Table 2.** Soil fertility assessment in the rhizosphere of *Elaeagnus angustifolia* L. seedlings under different treatments using the subordinate function value method.

#### **4. Discussion**

Soil salinity induces adverse effects on seedling establishment and biomass accumulation [1,46]. Although halophytes possess inherent salt-tolerant strategies, excessive soil salinity could damage seedling establishment and further inhibit growth in halophytes [47]. Soil microbes are of pivotal importance for plant growth, especially in adverse ecosystems such as those with saline soil conditions [48]. Previous studies reported that AMF and PGPR inoculations could reduce biomass losses induced by soil salinity, and that co-microbial inoculation performed better than single AMF or PGPR inoculations [49–52]. In contrast, the results in this study show that the single AMF inoculation promoted significantly greater biomass accumulation and AMF colonization rate than that in the non-inoculated control, and was even slightly greater than that in the co-microbial inoculation (albeit there was no statistical difference) (Figure 3). Thus, *Elaeagnus angustifolia* L. seedlings are more responsive to the specific AMF than to overall microbial richness or diversity in saline soils. Therefore, key specific microbial species, not the microbial richness or diversity, determined biomass accumulation in our study [53].

The *Bacillus amyloliquefaciens* FZB42 strain was used in this experiment as the PGPR inoculum. Previous studies showed that FZB42 could stimulate fresh and dry mass accumulation and induce systemic salt tolerance of *Arabidopsis thaliana* under 100 mM NaCl hydroponic culture conditions [33]. However, FZB42 was only effective in improving root biomass accumulation and salt tolerance of *Elaeagnus angustifolia* L. seedlings in the present study under saline soil conditions (Figure 3, Table 1). Hence, individual microbe species vary greatly in their effect on different plant species in different growth conditions. Moreover, both positive and negative effects of PGPR in plants have been reported in previous publications [54–56]. Hence, we suggest that PGPR efficiency of different plants may be influenced either by the growth environment or by the existence of "functional specificity" in the combination of plant and microbe species [48].

The growth and development of halophytes under saline conditions are inseparable from their own adaptive mechanisms, in which the adaptions of their morphological characteristics are the most intuitive [57]. The plant has to adjust its physiological functions and morphological characteristics in the leaf, stem and root to adapt to adverse environments as well as to ensure survival [37,58,59]. Root systems are the first "line of defense" to encounter saline soil, and root-system indicators are often used to quantify the acquisition capacity of water and nutrients in plants [60]. Soil salinity directly influenced root growth [57,59]. Previous studies have documented that AMF and PGPR colonization modulated the root-system architecture and reversed salinity effects on agricultural production both quantitatively and qualitatively in salt-sensitive plants such as soybean, citrus, and

maize [26,40,59,61,62]. The present investigation showed that AMF inoculation, singly or mixed with PGPR, significantly increased root biomass, length, surface area, average diameter, and tips number of *Elaeagnus angustifolia* L. seedlings when compared to control and PGPR inoculation (Figures 3 and 5). The root volumes in AMF inoculated seedlings were significantly higher than those in PGPR inoculated seedlings (Figure 5f), which indicates that *Elaeagnus angustifolia* L. seedlings are more responsive to AMF inoculation than to PGPR inoculation in saline soils.

Generally, a higher specific root length indicates higher root hydraulic conductivity and proliferation rate [57]. Root succulence is an adaptive mechanism to improve salt tolerance by diluting salt content in plants [63]. Our results confirmed that microbial inoculation significantly decreased specific root length and root succulence in *Elaeagnus angustifolia* L. seedlings when compared to the control (Figure 5g,h). It is possible that AMF hyphae replace the absorption function of roots, and that specific compounds exuded from PGPR and AMF provide more nutrients and exclude toxic ions from the rhizosphere, allowing the host to develop thicker roots and a larger absorption area [59,64,65]. Thus, *Elaeagnus angustifolia* L. seedlings with AMF and PGPR inoculation did not require greater specific root lengths, either as a surrogate for diameter to obtain more resources [66], or as an adaptive mechanism to compensate for loss of root biomass under osmotic stress induced by salinity [57,59]. Furthermore, *Elaeagnus angustifolia* L. seedlings with AMF and PGPR inoculations also had no requirement for a greater root succulence to reduce the damage caused by toxic ions [63].

The optimization of root morphology facilitated the transmission of soil water and nutrients to the stems, branches and leaves, which benefits the growth of aboveground organs [58]. Stems not only transport water and nutrients from the roots but also bear the full weight of aboveground tissues and provide growth spaces for branches and leaves [58]. Salinity stress suppresses stem and branch growth [67]. In this study, we found that stem biomass, plant height, stem diameter, and branch numbers in *Elaeagnus angustifolia* L. were increased markedly by the presence of AMF (Figures 3 and 4), consistent with previous reports on citrus, fenugreek and trifoliate orange [62,67,68]. However, the specific stem length in *Elaeagnus angustifolia* L. decreased significantly in three microbial treatments (Figure 4f). This result may be interpreted as AMF and PGPR reversing the salinity effects on stems and branches, such that *Elaeagnus angustifolia* L. with microbial inoculation did not require a greater specific stem length to ensure the effectiveness of associated functions. Hence, we suggest that increasing specific stem length may be one of the self-adaptive mechanisms used by *Elaeagnus angustifolia* L. without microbial inoculation to counter adverse salt stress conditions.

As well as the growth of stems and branches, we found that leaf biomass, leaf numbers, and leaf total areas in *Elaeagnus angustifolia* L. seedlings also increased with the presence of AMF (Figures 3 and 4). This result indicates that AMF and PGPR could reduce salt damage on leaves and promote the growth and surface expansion of leaves in *Elaeagnus angustifolia* L. seedlings under saline soil conditions, which is also consistent with studies of citrus [69], alfalfa [70], and beans [71] inoculated with AMF under salt stress conditions. Similar to the results of root succulence, microbial inoculation decreased the succulence of leaf and stem (albeit the differences were significant only in the single AMF inoculation) (Figures 4 and 5). Succulence is an anatomical adaption to permit the water accumulated in leaves, stems and roots to dissolve salt ions [57]. For *Elaeagnus angustifolia* L. with microbial inoculation, both the promotion of root biomass and the optimization of root morphology synthetically reduced the translation of salt ions to aerial organs, thereby mitigating the impact of toxic ions; consequently, the plants did not need to employ the succulence strategy to mediate salt stress. Meanwhile, the succulence level in root is higher than that in stem and leaf (Figures 4 and 5) and indicating that *Elaeagnus angustifolia* L. mainly relies on root succulence to increase salt tolerance [63].

Leaves, together with the stems and branches, are the carbon-fixing organs in halophytes [58,72]. Salinity stress stunts the growth of leaves, stems and branches [73], further impairing photosynthetic capacity [1,3,67,74]. Our findings provide further support for this view and showed that *Elaeagnus angustifolia* L. inoculated with AMF separately, or together with PGPR, had markedly higher Pn, Gs, Tr, and CE when compared to the control under salt stress (Figure 6), which is necessary to guarantee

the photosynthesis, transpiration, CO2 assimilation and gas exchange capacity [75]. These results are also consistent with other AMF-inoculated plant species, such as citrus [62], *Leymus chinensis* [76], and black locust [77]. The enhancement of photosynthesis may be caused by 1) growth promotion in the leaf and stem, which improves light interception and utility, and further benefits the photosynthetic capacity [28], 2) the optimization of the root structure, which is beneficial to the absorption of water and nutrients (such as nitrogen and magnesium), further promoting photosynthesis [24], and 3) combined enhancements in both gas exchange capacity and CO2 diffusion speed are instrumental in photosynthesis [78].

The result of SFVs including 21 plant parameters showed that the salt tolerance of *Elaeagnus angustifolia* L. seedlings with AMF inoculation was higher than that in co-microbial inoculation and PGPR inoculation (Table 1). This confirmed that AMF inoculation enhances salt tolerance of *Elaeagnus angustifolia* L. seedlings, and that *Elaeagnus angustifolia* L. seedlings are more responsive to AMF inoculation than co-microbial inoculation and PGPR inoculation in saline soils. Therefore, key specific microbial species, not the microbial richness and diversity, determined the salt tolerance of one-year old *Elaeagnus angustifolia* L. seedlings in saline soil in this study [53]. Previous results showed that the plant growth-promoting effects induced by different microbial inoculations varied markedly between different growth stages and also depended on the combination of host and microbes [79]. In this study, we just measured the relevant parameters in the seedling stages of *Elaeagnus angustifolia* L. A significant hurdle remains in addressing both the longevity of the microbial inoculum in the rhizosphere and the duration of plant growth-promoting effects induced by the interactions between halophytes and microbes. This aspect needs further study in the future.

Plant growth is inseparable from leaf photosynthesis and nutrient absorption by roots. Changes in soil nutrients are further closely related to soil enzyme activities. As key indicators of soil fertility levels, soil enzyme activities play a potentially important role in biochemical reactions of soil [28]. AKP indicates the level of phosphorus in soil; UE participates in soil N cycling; SC can increase soluble nutrients in soil; CAT can prevent the toxic effects of hydrogen peroxide on plants. However, the soil enzyme activities, such as CAT, AKP, SC, and UE, are inhibited by salinity [20] due to the inhibitory effect of salt on enzyme proteins through the disruption of the tertiary protein structure [28,80]. We found that the activities of four soil enzymes all significantly increased in AMF treatments, both AKP and SC markedly increased in co-microbial inoculation, and only AKP significantly increased in PGPR treatments (Figure 7), which indicates that the effects of microbial inoculation on soil enzyme activities are enzyme-specific. Soil enzymes in the rhizosphere are most affected by AMF inoculation in terms of the measured parameters.

SFVs results show the soil enzyme activities in the AMF inoculation are higher than those in the co-microbial inoculation and PGPR inoculation, and the SFVs of soil enzyme activities is lowest in the control (Table 2). Thus, microbial inoculation can effectively promote soil enzyme activities in the rhizosphere. One possible explanation could be that the hyphal effect of AMF, the exudation of specific compounds from PGPR, and the growth promotion of roots together contribute to stimulated microbial activity and modify nutritional status in the rhizosphere under salt stress conditions [20,53,65,81]. The enhanced activities of enzymes, such as AKP and UE, could benefit the transformation of soil nutrients (such as phosphorus and nitrogen) and further further promotes the overall availability of soil nutrients. Therefore, the efforts of soil enzymes are conducive to the benign development of the soil microenvironment in this study.

## **5. Conclusions**

Here, we observed that inoculation of *Elaeagnus angustifolia* L. with *G. mosseae* singly or synthetically with FZB42 mitigated the adverse effects of salt stress on biomass accumulation. The presence of AMF could promote root growth and modify root architecture, which may be conducive to the activities of soil enzymes and further boost nutrient acquisition. AMF inoculation also enhanced growth performance in leaves and stems, benefitting the interception and absorption of light and thus

maximizing photosynthesis, transpiration, CO2 assimilation and gas exchange capacity of *Elaeagnus angustifolia* L. in saline soil conditions. One-year-old *Elaeagnus angustifolia* L. seedlings are more responsive to the inoculation of special AMF identity per se than a combination of AMF and PGPR as well as single PGPR inoculation in saline soils. These results suggest that *Glomus mosseae* can be used in saline soil as a biotic elicits to stimulate *Elaeagnus angustifolia* L. growth and improve soil enzymes. Hence, selection of suitable microorganism inoculums is an important step before initiating any inoculation program, and could be beneficial in the recovery of saline-degraded areas.

**Author Contributions:** Conceptualization, J.P. and X.X.; Formal analysis, J.P. and W.Z.; Funding acquisition, C.H. and S.M.; Methodology, J.P., C.H., W.Z., and J.L.; Software, J.P. and W.Z.; Visualization, J.P., and W.Z.; Writing—original draft, J.P. and X.X.; Writing—review and editing, C.H., F.P., S.M., and X.X. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by National Key Research and Development Program of China (No. 2017YFE0119100).

**Acknowledgments:** We would like to acknowledge Pro. Ruoyu Wang for his donation of the *Bacillus amyloliquefaciens* FZB42 strain and assistance in this manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

## **Plant Species-Dependent E**ff**ects of Liming and Plant Residue Incorporation on Soil Bacterial Community and Activity in an Acidic Orchard Soil**

## **Xiaodi Liu 1,2, Zengwei Feng 1,2, Yang Zhou 1,2, Honghui Zhu 2,\* and Qing Yao 1,\***

Received: 22 July 2020; Accepted: 13 August 2020; Published: 15 August 2020

**Abstract:** Both liming and plant residue incorporation are widely used practices for the amelioration of acidic soils—however, the difference in their effects is still not fully understood, especially regarding the microbial community. In this study, we took the acidic soils from a subtropical orchard as target soils, and implemented liming and plant residue incorporation with a leguminous and a gramineous cover crop as test plants. After six months of growth, soil pH, total organic carbon (TOC), dissolved organic carbon (DOC) and nutrient contents were determined, soil enzymes involving C, N, P cycling were assayed, and microbial communities were also analyzed using Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE). Results showed that liming was more effective in elevating soil pH, while plant residue incorporation exerted a more comprehensive influence—not only on soil pH, but also on soil enzyme activity and microbial community. PCR-DGGE analysis revealed that liming changed the microbial community structure more greatly than plant residue incorporation, while plant residue incorporation altered the microbial community composition much more than liming. The growth responses of test plants to liming and plant residue incorporation depended on plant species, indicating the necessity to select appropriate practice for a particular crop. A further, detailed investigation into the microbial community composition, and the respective functions using metagenomic approach, is also suggested.

**Keywords:** acidic soil improvement; liming; microbial community; plant residue incorporation; soil enzyme activity; subtropical orchard soil

## **1. Introduction**

Acidic soils occupy around 40% of the total agricultural lands worldwide, representing one of the most important limiting factors of agriculture production [1]. In China, acidic soils mainly distribute in the subtropical regions, where hilly areas are predominant with orchards, tea gardens, forest lands as the main land-use types. Traditionally, the farmers use liming to ameliorate the soil acidity [2]. It is reported that liming increased the soil pH in a citrus orchard by 1.0~1.4 units, compared to the adjacent native forests [3]. In the tea gardens of 8-, 50-, 90-year old, liming with CaCO3 at the rate of 6.4 g·kg−1 increased the soil pH by 3.13, 3.68, 2.24 units, respectively [4]. On the other hand, these subtropical soils are typical of low organic matter content, due to fast mineralization under high temperature and humidity conditions. Consequently, plant residue incorporation is proposed and practiced as an

alternative to simultaneously increase the soil pH and the soil organic matter content. Xu et al. [5] reported the increase in soil pH by up to 3.3 units after 42 days of incubation with different types of plant residues. Hue [6] demonstrated that cowpea residue incorporation not only increased soil pH from 4.45 to 5.45, but also promoted the soluble carbon from 0.11 to 2.84 mM in the Ultisol.

It is clear that liming and plant residue incorporation do not share the common mechanisms in ameliorating acidic soils. The primary effects of liming are raising pH, base saturation and Ca content, and its secondary effects include reducing Al activity and P immobilization, modifying microbial activity, and etc. (see review by Fageria and Baligar [7]). Plant residue incorporation increases soil pH as well [5,6], although the amelioration process is time-consuming compared with liming. According to Sakala et al. [8], decomposition of plant residues and the subsequent release of base and mineralized N by soil microbes is the requisite of ameliorating acidic soils by plant residue incorporation. Moreover, a large number of studies demonstrate that plant residue incorporation can directly elevate the organic matter content [9,10] and indirectly promote the microbial activity via increased soil organic carbon [11,12] and enzyme activity [13]. It seems that, apart from neutralizing soil acidity, plant residue incorporation exert more extensive influences on soil properties (e.g., microbial activity) than liming. In this context, it is reasonable to speculate that the outcomes of ameliorating soil with liming or plant residue incorporation can be much different, especially in terms of microbial properties. However, information on this aspect is scarce thus far.

Soil microbe is the essential factor driving most soil biological processes [14], including the decomposition of soil organic matter [15], nutrient (C, N, P, S) cycling [16], soil respiration [17,18], and etc. In turn, soil microbes are strongly affected by environmental cues, with pH, soil organic carbon as the important factors [19–21]. This indicates that the increase of soil pH by liming or the increase of soil organic carbon by plant residue incorporation can further regulate the microbial community. Moreover, for plant residue incorporation, the additive effect of increased pH can make the regulation complicated, which differentiates the final effects of liming and plant residue incorporation on soil microbial community. Unfortunately, the difference between them has never been investigated up to date.

We hypothesized that (1) liming would be more effective in neutralizing soil acidity than plant residues, (2) plant residue incorporation would exert a greater influence on microbial community than liming, and (3) plant residues would affect the biological properties more extensively than liming. In this study, we compared the effects of liming and plant residue incorporation in alleviating the acidity of a subtropical orchard soil. Two plant species, one legume species *Stylosanthes guianensis* and one graminoid species *Paspalum natatum*, were taken as test plants for comparison, because they are routinely grown in orchards as cover crops in the subtropical areas of China [22]. The soil chemical properties and microbial properties were monitored to evaluate the respective effects of liming and plant residue incorporation.

## **2. Materials and Methods**

## *2.1. Soils and Test Plants*

Soil was collected from a subtropical orchard at Heshan Hilly Land Interdisciplinary Experimental Station (E112◦54 , N22◦41 ), Chinese Academy of Science in Guangdong province [22].  The soils were air-dried and sieved through a mesh of 2 mm pore size.

To evaluate the effects of ameliorating acidic soils by liming or plant residue incorporation, leguminous plant *S. guianensis* and gramineous plant *P. natatum* were taken as test plants. These two species are routinely grown in subtropical orchards as cover crops, and the cuttings (the aboveground