Promotion of AMF and PGPR on the growth of F. elata and removal of PHE and PYR in soil
The effect of the inoculation of PGPR and/or AMF on the growth of different treatment soils was investigated after 60 days of experiments in greenhouse condition. Compared with the CK, F. elata inoculated with GV, PS, and GVPS produced larger fresh weight, dry weight and higher plant height under PHE and PYR stress conditions, however, the GV and PS did not have an effect on tiller number of F. elata. Moreover, the GVPS treatment produced the highest fresh weight (0.56 ± 0.03) g, dry weight (0.1177 ± 0.003) g, and plant height (36.7 ± 0.8) g (p<0.05) in the concentration of PHE and PYR at 100 mg·kg-1. The fresh weight, dry weight, and plant height increased by 1.43-fold, 93.90% and 51.03% compared with that of CK, respectively (Table 1).
Table 1
Growth indexes of F. elata in response to different treatments
Treatment
|
FW(g)
|
DW(g)
|
PH(cm)
|
TN
|
CK
|
0.23±0.01d
|
0.0607±0.004d
|
24.3±0.9d
|
2.7±0.6a
|
GV
|
0.29±0.01c
|
0.0675±0.005c
|
26.6±1.2c
|
2.3±0.6a
|
PS
|
0.43±0.02b
|
0.0836±0.002b
|
30.3±1.0b
|
2.7±0.6a
|
GVPS
|
0.56±0.03a
|
0.1177±0.003a
|
36.7±0.8a
|
3.0±0.0a
|
The data represent the mean ± standard deviation of three replicates. FW means fresh weight, DW means dry weight, DW means dry weight, PH means plant height, and TN means tiller number. Values in each column followed with different lowercase letters (a, b, c and d) indicated significant differences between different treatments.
The mycorrhizal status was best manifested in the roots of plants inoculated with GVPS; the percentage of root mycorrhizal proliferation of GVPS treatment was 69% (Fig 1). GVPS treatment significantly increased the PGPR proliferation amounts in tall fescue rhizosphere soil. The PGPR proliferation amounts reached a maximum of 9.5×107 CFU·g−1 at 100 mg·kg−1 of PHE and PYR. Meanwhile, the GVPS treatment significantly enhanced the hyphal density, entry point number, and mycorrhizal relative dependence (p < 0.05, Fig 1) by 75%, 73% and 383%, respectively. However, the treatment did not significantly (p < 0.05) increase the infection, spore density, vesicle number, or arbuscule infection of tall fescue (Fig 1). By the end of the experiment, the PHE concentrations decreased from the initial value of 100 mg·kg−1 to 2.85, 2.85, 2.84, and 2.46 mg·kg−1 dry soil in CK, GV, PS and GVPS, respectively, corresponding to degradation efficiencies of 97.10%, 97.10%, 97.10%, and 97.50%, respectively. The PYR concentrations decreased from the initial value of 100mg·kg−1 to 10.12, 8.72, 8.92 and 5.11 mg·kg−1 dry soil in treatments CK, GV, PS and GVPS, respectively, corresponding to removal efficiencies of 89.67%, 91.10%, 90.90% and 94.80%, respectively (Table 2). Residual concentrations of PHE and PYR in tall fescue shoots and roots are also shown in Table 2, and high concentrations of PHE and PYR were detected in tall fescue roots, root concentrations of PHE in tall fescue grown for 60 days in soils with GV, PS, and GVPS inoculation were 22.62%, 31.13%, 53.63% higher than those of CK, and root concentrations of PYR in tall fescue with GV, PS, and GVPS inoculation were 56.95%, 30.21%, and 67.11% higher than those of CK. Concurrently, PHE and PYR concentrations of shoots in contaminated soil inoculated with GV, PS, and GVPS were significantly (p < 0.05) higher than those of CK (Table 2).
Table 2 The content of PHE and PYR in soil as well as roots and shoots of F. elata under different treatments
Treatment
|
PHE in soil
|
PYR in soil
|
Plant concentrations of PHE (mg·kg-1)
|
Plant concentrations of PYR (mg·kg-1)
|
RC
(mg·kg-1)
|
DE
(%)
|
RC
(mg·kg-1)
|
DE
(%)
|
Shoot
|
Root
|
Shoot
|
Root
|
CK
|
2.85±0.02a
|
97.10
|
10.12±0.12a
|
89.67
|
2.25±0.10c
|
35.24±0.70d
|
0.93±0.08d
|
3.74±0.21d
|
GV
|
2.85±0.03a
|
97.10
|
8.72±0.08b
|
91.10
|
2.30±0.26c
|
43.21±0.40c
|
1.40±0.13c
|
5.87±0.10b
|
PS
|
2.84±0.02a
|
97.10
|
8.92±0.70b
|
90.90
|
2.34±0.10b
|
46.21±2.12b
|
1.48±0.18b
|
4.87±0.43c
|
GVPS
|
2.46±0.07b
|
97.50
|
5.11±0.22c
|
94.80
|
2.52±0.04a
|
54.14±3.54a
|
2.50±0.19a
|
6.25±0.09a
|
The data represent the mean ± standard deviation of three replicates. RC means residual concentration, DE means degradation efficiency, Values in each column followed with different lowercase letters (a, b, and c) indicated significant differences between different treatments. The same letter within a column indicates no significant difference assessed by Duncan’s multiple range test (P ≤ 0.05) following analysis of variance.
Evaluation of sequencing results of soil microbial library
After sequencing the original data, the low-quality data or non-biologically meaningful data (such as chimeras) are removed to ensure the statistical reliability and biological validity of subsequent analysis. The sequencing run of 16S rRNA amplicons yielded an average of 68,534.67 ± 10,870.14, 69,611 ± 7,337.083, 72,296.333 ± 9,922.511, and 71,144 ± 1,136.746 clean tags (per sample), with 4,916, 5,164, 5,570 and 6,327 total OTUs from the CK, GV, PS and GVPS samples, respectively (Table 3). The sequencing run of ITS amplicons yielded 96023 ± 2098.435, 92420.67 ± 8008.382, 100643.3 ± 2112.008, and 102455 ± 6585.639 clean tags, with 595, 649, 783, and 825 total OTUs from the CK, GV, PS and GVPS samples, respectively (Table 3).
Table 3 Summary of sequencing date, number of operational taxonomic units (OTUs), and alpha diversity in different treatment under the pollution of PHE and PYR.
|
Bacteria
|
Fungi
|
|
CK
|
GV
|
PS
|
GVPS
|
CK
|
GV
|
PS
|
GVPS
|
Total number of raw tags
|
207059
|
210277
|
218332
|
214889
|
292090
|
289128
|
306577
|
311715
|
Total number of clean tags
|
205604
|
208833
|
216889
|
213432
|
288069
|
277262
|
301930
|
307365
|
Mean number of raw tags (per sample)
|
69019.67±11152.14
|
70092.33±7485.706
|
72777.333±10175.39
|
71629.67±1165.009
|
97363.33±2204.543
|
96376±8256.634
|
102192.3±1807.5
|
103905±6356.831
|
Mean number of clean tags (per sample)
|
68534.67±10870.14
|
69611±7337.083
|
72296.333±9922.511
|
71144±1136.746
|
96023±2098.435
|
92420.67±8008.382
|
100643.3±2112.008
|
102455±6585.639
|
Total OTUs
|
4916
|
5164
|
5570
|
6327
|
595
|
649
|
783
|
825
|
Shannon diversity
|
8.195±0.342
|
8.176±0.445
|
8.426±0.224
|
8.640±0.150
|
3.762±0.153
|
3.795±0.391
|
4.203±0.319
|
4.113±0.288
|
Simpson diversity
|
0.991±0.003
|
0.985±0.008
|
0.992±0.002
|
0.992±0.001
|
0.863±0.019
|
0.849±0.027
|
0.894±0.013
|
0.846±0.055
|
Chao1 diversity
|
1976.371±278.593
|
2041.666±180.040
|
2242.989±473.870
|
2486.449±239.018
|
259.417±5.596
|
274.682±35.375
|
341.247±31.128
|
361.605±38.804
|
Ace diversity
|
1918.487±256.318
|
1987.574±177.560
|
2209.904±443.234
|
2451.972±271.607
|
283.638±1.677
|
288.165±40.010
|
361.482±31.444
|
368.293±28.812
|
Coverage
|
0.994±0.001
|
0.995±0.001
|
0.994±0.002
|
0.993±0.002
|
0.999±0.000
|
0.999±0.000
|
0.999±0.000
|
0.999±0.000
|
observed_species
|
1638.667±252.526
|
1721.333±137.027
|
1856.66±330.390
|
2109.000±130.771
|
198.333±11.676
|
216.333±17.214
|
261.000±17.349
|
275.000±4.000
|
The total number of OTUs detected at 97% that shared sequence similarity was very high in PHE and PYR contaminated soil, both in terms of bacteria and fungi, and the estimated α-diversities indicated abundant microbial diversity present in all samples. For bacteria, the number of different phylogenetic OTUs ranged from 1,639 to 2,109, with dual inoculation (GVPS) showing higher 16S rRNA gene diversity than single inoculation (GV, PS) and CK. For fungi, the number of different phylogenetic OTUs in all samples ranged from 198 to 275, with GVPS exhibiting higher diversity than CK, GV, and PS. The GVPS displayed the highest Shannon index and number of OTUs, whereas CK samples had the lowest (Table 3).
Venn diagrams were created in R, based on the shared OTU tables from 4 different soil groups (Fig 2a). The total number of unique bacterial OTUs was 3,415, of which 119 OTUs were shared between PS and GVPS treatments, 187 were associated only with treatment of GV (GV, GVPS), and 1035 were shared by all samples (Fig 2a). Furthermore, in terms of fungi, 504 different OTUs were identified, both PS vs GVPS and GV vs GVPS groups, shared only 46 and 21 OTUs, respectively, and 92 were shared by all samples (Fig 2b).
Analysis of microbial community composition
All valid reads were classified from the phylum to the genus level using the default settings in QIIME. The bacterial and fungal communities from the 12 samples were analyzed at phylum, family, and genus levels. In total, all the bacteria and fungi identified were classified into 28 and 6 phyla, respectively. Proteobacteria, Saccharibacteria, and Parcubacteria were the dominant bacterial phyla, and there are three main phyla of fungi : Ascomycota, Chytridiomycota, and Basidiomycota. All the treatments shared similar bacterial and fungal communities. Most samples from the same group shared high similar bacterial communities at all classification levels.
At the phylum level, the CK, GV, PS and GVPS samples shared common phyla, Proteobacteria was the most prevalent bacteria phylum, while different proportions of valid reads from 33.80% to 41.73% were observed for all treatments. More Proteobacteria taxa (41.73%) were detected in GVPS than that in GV, PS and CK (Fig 3a). Fungal classification results showed that the dominant phylum was Ascomycota, accounting for 33.13–52.04% of all valid reads, with an average relative abundance of 43.56%. The next most dominant fungal phyla were Chytridiomycota (average abundance 12.13%) and Basidiomycota (average abundance 6.60%), and the abundance of Glomeromycota (0.27%) in GVPS was significantly higher than that in other treatments (Fig 3b).
The most prevalent bacterial families detected in all 12 groups included Xanthomonadaceae (7.40%-12.58%), Planctomycetaceae (average abundance 6.25%), and Sphingomonadaceae (average abundance 3.59%). The abundance of Xanthomonadaceae (12.58%), Phytophthoraceae (6.76%), and Sphingomycidae (4.43%) in GVPS was significantly higher than others (Fig 3c). At the family level, according to the classification of fungi, Debaryomycetaceae (average abundance 17.46%) is the richest fungus family in all samples, accounting for 9.94% - 27.67% of the total. Spizellomycetaceae is the second most abundant fungal family with an average abundance of 12.12%. The proportion of Nectriaceae (11.76%), Pseudoglobulaceae (4.44%), and Cladosporidae (1.08%) were significantly higher in GVPS samples compared to other samples (Fig 3d).
At the genus level, according to the results of bacterial taxonomy, Planctomyces is the richest genus in all samples, accounting for 3.0% - 3.39% of the total. Sphingomonas is the second most abundant bacteria genus with an average abundance of 2.36%. The other major bacterial genera were Mycobacterium (average abundance 2.31%), Arenimonas (average abundance 1.92%), Pseudomonas (average abundance 1.75%), and Pirellula (average abundance 1.53%). The abundance of Sphingomonas (3.17%), Pseudomonas (2.05%), and Piriformis (1.79%) in GVPS was significantly higher than that in other treatments (Fig 3e). Meanwhile, Meyerozyma is the richest fungi genus in all samples, accounting for 9.94% - 27.67% of the total. Spizellomyces is the second most abundant fungi genus with an average abundance of 12.12%. The other dominant fungal genera were Gibberella (average abundance 4.14%), Fusarium (average abundance 3.93%), Serendipita (average abundance 3.17%), Alternaria (average abundance 2.93%), Aspergillus (average abundance 2.09%), and Chalastospora (average abundance 0.88%). The abundance of Fusarium (8.65%), Alternaria (4.09%), and Cladosporium (1.07%) in GVPS treatment was significantly higher than other treatments (Fig 3f). Heatmap clustering analysis results revealed that Planctomyces, Mycobacterium bacterial genera had high abundance in CK, GV, and PS, while the abundance of Sphingomonas, Planctomyces, and Arenimonas genera were higher in GVPS (Fig 4a). For fungi, heatmap clustering analysis showed that Meyerozyma and Spizellomyces fungus genera had relatively high abundance among all the treatments, while Fusarium had a high abundance in GVPS (Fig 4b). These findings were consistent with previous results (Fig 3).
Effects of AMF and PGPR on soil microbial community richness and diversity in the root zone of F. elata
The rarefaction curve can evaluate whether the sequencing quantity is sufficient to cover all groups and indirectly reflect the species richness in the treatments. Rarefaction curves of four treatments (CK, PS, GV, GVPS) for bacteria and fungi are shown in (Fig A1). None of the rarefaction curves are parallel with the x-axis, the rarefaction curves of bacteria and fungi calculated at 97% levels showed that the order of OTUs numbers from high to low among samples both were GVPS > PS > GV > CK. The OTU densities of GVPS were higher than the other three treatments (Fig A1). The bacteria and fungi richness based on rarefaction curves were strongly supported by statistical diversity estimates, based on the abundance results of OTUs, the Alpha diversity of each treatments were calculated by QIIME software, including Chao 1 value, ACE value, Shannon index, and Simpson index (Table 3). The results showed that the values of Chao 1 and ACE of GVPS treatment were higher, which indicated that the richness of microbial community under GVPS treatment was higher. The Simpson diversity index of the four treatments had little difference, indicating that the uniformity of the four treatments and the dominant OTU of the community were similar. The Shannon diversity index was higher in GVPS treatment, indicated a richer microbial community in GVPS treatment, (Table 3). Based on the relative abundance of the genera from (Fig 5), the genera with an average abundance of >1 % in at least one group were defined as dominant.
In addition,principal component analysis (PCA) was used to identify the microbial community composition differences under different treatments (Fig 5). The data are presented as a 2-dimensional plot to better illustrate the relationship among treatments. At OTU level, PCA demonstrated that four treatments of 12 soil samples were clustered. In bacteria, except for CK-1 and GV-3, microorganism communities in most treatments gathered together, and different soil samples from CK and PS gathered together than others. In addition, the GV samples had a relatively higher PC1 value, followed by PS and GVPS treatment, whereas the CK samples had a higher PC2 value at OTU level (Fig 5a). In fungi, the GVPS groups had a relatively higher PC1 value, followed by PS and CK, while the samples from GV were closer than the other groups. Meanwhile, no significant gatherings were observed among four groups (Fig 5b).
UPGMA clustering obtained a phylogenetic tree by using unweighted group averaging method (Fig A2). Results indicated that same type of samples showed high similarity of bacterial communities (Fig A2-a), while similarity of fungal communities from the same treatment were relatively weaker (Fig A2-b).