Wide-spectrum verification of Frankia F1 against pathogenic fungi of ginseng
The phylogenetic tree of the F1 strain is shown in Figure 1. It has 100% homology with the Frankia casuarinae strain CCl3, which has been published in GenBank. The sequence accession number is GU296535. The fungistasis spectrum test of Frankia F1 against pathogenic fungi of ginseng (Table 1) showed that Frankia F1 had significant inhibitory effects on Fusarium solani, Sclerotinia schinseng, Cylindrocarpon destructans, Alternaria panax, and Rhizoctonia solani with inhibition rates of 80.23%, 73.91%, 72.12%, 70.87%, and 68.31%, respectively. It also showed some inhibitory effect on Phytophthora cactorum and Botrytis cinerea. In conclusion, Frankia F1 has a broad-spectrum fungistatic effect against ginseng pathogenic fungi under the conditions of the in vitro plate test.
Table 1. Inhibition of activity of Frankia F1 against pathogenic fungi of ginseng. All the presented values are means of three replicates. Means were subjected to analysis of variance and were separated by the LSD test. Letters represent the significant differences among the mean values and the “±” is followed by the standard error values of the means.
Pathogenic fungus
|
Colony diameter(mm)
|
Fungal inhibition rate(%)
|
Fusarium solani
|
22.45±3.12 g
|
80.23 a
|
Cylindrocarpon destructans
|
23.13±4.06 f
|
72.12 c
|
Phytophthora cactorum
|
35.32±3.63 a
|
63.82 g
|
Alternaria panax
|
29.58±2.98 d
|
70.87 d
|
Rhizoctonia solani
|
30.37±2.37 c
|
68.31 e
|
Sclerotinia schinseng
|
25.28±5.10 e
|
73.91 b
|
Botrytis cinerea
|
31.18±3.27 b
|
66.37 f
|
Preparation of microbial inocula
Among the five carrier materials, corn straw biochar, rice biochar and wheat straw biochar showed the best properties. At 7 d, the water absorption rates of the three carrier materials were 86.3%, 64.1% and 58.6%, respectively (Table 2), and the antibacterial activities were 80.4%, 72.2% and 64.6%, respectively. When stored at room temperature (25℃±5℃), corn straw biochar had the highest effective number of living bacterial cells of all five types of carrier material. The pore layered structure of corn stalk biochar, rice straw biochar and wheat straw biochar formed a complex three-dimensional structure, indicating that the three kinds of biochar had a highly porous structure (Figure 2a, b, e). Such structure is expected to be beneficial to the adhesion and reproduction of bacteria, and the diffusion of primary and secondary metabolites supporting the normal metabolism of the introduced biocontrol strain. In contrast, cotton biochar (Figure 2c) had relatively sparse pore structures, and peanut shell biochar (Figure 2d) did not show pore structures suitable for the survival of microorganisms, suggesting bacteria could only attach to the surface of biochar, making for a poor carrier. Based on these results, biochar derived from corn, rice or wheat straw were selected as the most optimal carrier materials for producing microbial inoculum.
Table 2. Adsorption stability of different carrier materials. WA is water absorption, FIR is fungal inhibition rate.
Stalk biochar
|
WA(%)
|
FIR(%)
|
Effective number of live cells (104 cfu/g)
|
1d
|
7d
|
14d
|
21d
|
28d
|
Corn
|
86.3 a
|
80.4 a
|
36.6±0.3 a
|
85.1±1.2 a
|
105.2±1.5 a
|
113.8±1.3 a
|
101.3±1.1 a
|
Rice
|
64.1 b
|
72.2 b
|
35.5±0.8 b
|
54.9±0.6 c
|
76.1±0.9 c
|
88.7±1.0 b
|
85.8±0.8 b
|
Cotton
|
35.9 d
|
43.1 d
|
9.2±0.6 d
|
21.7±0.6 d
|
26.3±0.5 d
|
19.2±0.8 d
|
18.4±0.5 d
|
peanut shell
|
17.7 e
|
39.7 e
|
8.6±0.5 e
|
7.4±0.5 e
|
6.1±0.3 e
|
5.6±0.5 e
|
4.8±0.2 e
|
Wheat straw
|
58.6 c
|
64.6 c
|
22.4±0.6 c
|
63.5±0.8 b
|
87.7±1.2 b
|
82.2±0.4 c
|
79.5±0.3 c
|
Effects of microbial inocula on physicochemical properties and enzyme activities of ginseng soil
At 28 days, microbial inocula significantly altered the characteristics of the soil (Table 3). Compared with the control group, the treatments with wheat straw biochar, rice straw biochar and corn straw biochar increased the pH by 4.43%, 6.55% and 11.18%, and organic matter by 7.43%, 22.10% and 55.43%, respectively. At the same time, there were significant differences between four treatments. The contents of total nitrogen, available nitrogen, available phosphorus, and available potassium in the soil in the corn straw biochar treatment were significantly increased by 33.07%, 26.70%, 16.40%, and 9.10%, respectively, compared with the control group. Microbial inocula had significant effects on the activities of urease, sucrase and catalase in the soil (Table 3), but had no significant effect on the activity of phosphatase. Compared with the control group, the contents of urease, catalase and sucrase activities in the soil in the corn straw biochar treatment were increased significantly (by 52.73%, 16.80% and 43.80%, respectively).
Table 3. Effect of biological control agents on repairing the diseased soil. A treatment is wheat straw biochar preparation of microbial inocula; B treatment is preparation of microbial inocula by rice straw biochar; C treatment is corn stalk biochar preparation of microbial inocula; CK treatment is do not add any substance as blank control. OM is organic matter, TN is total nitrogen, AN is available nitrogen, AP is available phosphorus, AK is available potassium, URE is urease activity; CAT is catalase activity; INV is invertase activity; NPH is neutral phosphatase activity.
Treatment
|
A
|
B
|
C
|
CK
|
pH value
|
5.42 ± 0.05 c
|
5.53 ± 0.03 b
|
5.77 ± 0.08 a
|
5.19 ± 0.06 d
|
OM (g/kg)
|
17.21 ± 0.45 c
|
19.56 ± 0.47 b
|
24.90 ± 0.55 a
|
16.02 ± 0.60 d
|
TN (g/kg)
|
1.42±0.06 b
|
1.33±0.08 c
|
1.69±0.06 a
|
1.27±0.05 d
|
AN (mg/kg)
|
136.33 ± 9.05 c
|
132.95 ± 7.48 b
|
156.20 ± 8.36 a
|
123.28 ± 7.95 d
|
AP (mg/kg)
|
24.38 ± 0.46 b
|
22.18 ± 0.35 c
|
25.98 ± 0.41 a
|
22.32 ± 0.52 c
|
AK (mg/kg)
|
160.65 ± 4.83 c
|
163.87 ± 6.32 b
|
172.90 ± 5.69 a
|
158.48 ± 6.56 d
|
URE (mg/g/d)
|
25.78 ± 0.49 b
|
24.12 ± 0.54 bc
|
30.21 ± 0.56 a
|
19.78 ± 0.75 d
|
CAT (g/mL)
|
1.63 ± 0.04 b
|
1.57 ± 0.06 c
|
1.73 ± 0.03 a
|
1.48 ± 0.05 d
|
INV (mg/g/d)
|
18.12 ± 0.63 b
|
16.42 ± 0.66 c
|
22.03 ± 0.45 a
|
15.32 ± 0.37 d
|
NPH (mg/g/d)
|
0.42 ± 0.03 ab
|
0.41 ± 0.02 ab
|
0.45 ± 0.03 a
|
0.39 ± 0.04 b
|
Composition of soil bacterial community
The four soil treatments showed a total of 421,879 effective bacterial sequences and a total of 7,114 OTUs (Figure 3). Compared with the unamended control group, total OTUs for wheat straw biochar, rice straw biochar and corn straw biochar treatments increased by 10.24%, 8.76% and 19.86%, respectively (Table 4). Shannon and Simpson indices reflect the diversity of taxa, and these indices were significantly increased in comparison to those in the control group (P<0.05). In order to more clearly observe the differences between treatments, we used the Bray-Curtis test to quantify the sample distances (Figure 4). The results indicated that the differences among different treatments were significant. Compared with the control treatment (CK), the distances were large with the treatments wheat straw biochar and corn straw biochar and small with the rice straw biochar treatment.
Table 4. Effect of different treatments on the α diversity of bacterial community.
Sample
|
Number
|
Chao1
|
Coverage
|
OTUs
|
PD-whole-tree
|
Shannon
|
Simpson
|
A
|
148035±1138
|
1842.39±98.11
|
0.987
|
1787±73 a
|
94±6
|
8.89±0.43 b
|
0.98
|
B
|
134853±1281 a
|
1732.94±112.15c
|
0.987
|
1763±101c
|
81±4cd
|
7.68±0.37 c
|
0.96
|
C
|
15309±1023cd
|
1987.33±102.32 a
|
0.988
|
1943±89 a
|
103±5 a
|
9.43±0.35 a
|
0.98
|
CK
|
123682±1302 b
|
1712.43±92.37 bc
|
0.985
|
1621±79 c
|
77±5 c
|
7.32±0.48 d
|
0.95
|
Clustering analysis of bacterial community at the class level
In all the soil samples, we detected 39 phyla, 97 classes, 153 orders, 225 families, and 306 genera. The twelve soil samples from four different treatments were divided into two categories (Figure 5). The soil samples from the unamended control were clustered into one branch, whereas the soil samples from the wheat straw biochar, rice straw biochar and corn straw biochar treatments were clustered into another branch. The relative abundance of bacterial community composition was analyzed at the class level, and there were five dominant phyla (abundance of > 2%) whose relative abundance in the soil was significantly different among the treatments. Compared with the control, the relative abundance of Alphaproteobacteria, Gammaproteobacteria and Sphingobacteria was significantly higher, and the relative abundance of Actinobacteria and Thermoleophilia was significantly lower. In three of the treatments, the relative abundance of class Actinobacteria accounted for 18.29% in the wheat straw biochar treatment, almost 16.53% in the rice straw biochar treatment and 15.62% in the corn straw biochar treatment. After the corn straw biochar treatment, the abundance of Alphaproteobacteria, Gammaproteobacteria and Sphingobacteria increased by 7.87%, 9.81% and 1.24%, respectively. In summary, the effects of the treatments wheat straw biochar and rice straw biochar on the improvement of bacterial community were similar, and both of them mainly enhanced the relative abundance of Alphaproteobacteria and Gammaproteobacteria.
The soil samples from different treatments were clustered by taxa, or similarity of abundance among samples, and the clustered data were used to construct a hierarchical clustering heatmap (Figure 6). The soil bacterial communities treated by wheat straw biochar, rice straw biochar and corn straw biochar were grouped into two groups, one of which was the community with high relative abundance of Thermoleophilia, Sphingobacteria, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria.
Significant differences in taxa among the treatment groups
Linear discriminant analysis (LDA), which allows comparisons among the treatment groups, also performs subgroup comparisons within the group comparisons to find taxa with significant differences in abundance among the groups. When LDA>4.0, there were 26 taxa groups with significant differences among wheat straw biochar, rice straw biochar, corn straw biochar and CK at each classification level (Figure 7a), and CK had the most significant differences with 14 taxa. Among the other three treatments, five taxa were significantly different in the wheat straw biochar treatment, and the rice straw biochar treatment had 1. There were many significantly different taxa in the corn straw biochar treatment; at LDA>4.0 it had six and at LDA>5.0 it had one Saccharibacteria. These results indicated that Saccharibacteria contributed greatly to the significance of differences and was the most important taxa that caused the differences among the four treatments.
LEfSe analysis showed (Figure 7b) that there were 24 significantly different taxa among the four treatments, including three in the wheat straw biochar treatment, whereas rice straw biochar had zero, corn straw biochar had 3, and CK had 18. The number and abundance of different taxa were the highest in the CK treatment. Different taxa treated in the wheat straw biochar treatment were mainly Xanthomonadaceae, Xanthomonadales and Gammaproteobacteria, and in the corn straw biochar treatment were mainly Sphingomonadaceae, Sphingomonadales and Alphaproteobacteria. After treatments wheat straw biochar, rice straw biochar, corn straw biochar and CK, the bacterial taxa with the largest contribution were Proteobacteria, Actinobacteria, Chloroflexi, and Saccharibacteria, respectively.
Redundancy Analysis (RDA) of Bacterial Community Structure and Soil Environmental Factors
Soil pH, organic matter (OM), total nitrogen (TN), and dominant taxa in the bacterial community were analyzed by RDA (Figure 8). Organic matter and total nitrogen were the main factors influencing bacterial community composition in ginseng soil after different treatments. In the RDA analysis, the distance between the corn straw biochar treatment and CK was large, and the two treatments occupied separate quadrants, indicating that the soil bacterial community structure of the corn straw biochar and CK treatments was significantly different. Treatments wheat straw biochar and rice straw biochar occupied a common quadrant, indicating the similar bacterial community structure. The correlation analysis showed that Alphaproteobacteria was significantly positively correlated with organic matter and total nitrogen (P<0.05). Acidobacteria, Thermoleophilia, Actinobacteria, and Spartobacteria were negatively correlated with organic matter and total nitrogen (P < 0.05).