Experimental design.
Two-year-old fresh ginseng roots (Panax ginseng Meyer) were provided by dongdu ginseng technology development co., LTD in April 2017 and placed in sand at 23°C. After 6 days, the roots sprouted and were then washed with deionized water, and transplanted into PVC pots (120 × 180 mm, diameter × height) containing turfy soil (6 seedlings per pot). The ginseng seedlings were grown under greenhouse conditions: temperatures of 17–28°C, a relative humidity of 70%~80%, and a 14 h photoperiod. Before A. panax inoculation, half of the plants were pretreated for 2 weeks with potassium silicate (pH = 7.0) as the Si source. After Si pretreatment, the plants were inoculated with conidia of the appropriate A. panax pathogen. The conidia of A. panax infecting P. ginseng were identified by PCR of the internal transcribed spacer (ITS) region generating 553~554 bp fragments and the glyceraldehyde 3-phosphate dehydrogenase (gpd) for 565~566 bp fragments, respectively. Sequence showed 100% identical to that of A. panax (JF417572 of ITS, JF417653 of gpd). The A. panax strain was deposited in the Culture Collection Center of Yangtze University in Jingzhou, China. Spores were flushed from colonies and then resuspended in sterile distilled water at 1 × 105 spores/mL. The sterilized surfaces of detached spring ginseng leaves were inoculated with 20 µL conidial suspension and incubated under the same greenhouse conditions for 9 days, when black spot symptoms became visible on the leaves.
Plants were grown under four kinds of treatment: ginseng control plants (Control), plants only inoculated with A. panax (A), plants inoculated with A. panax + Si (AS), and plants only inoculated with Si (S), with 18 plants (3 pots) per treatment. To test the prophylactic role of Si, the Si concentration was set at 1.7 mM, i.e., the highest possible concentration of silica acid in solution [4].
Six seedlings of ginseng were randomly selected from each treatment group, and the soils were mixed to form a single representative sample. After inoculation with A. panax for 9 days, plants were removed from the soil and the excess soil was carefully shaken off. The rhizosphere soil (i.e., adhering to the roots) was collected as previously described by Bulgarelli et al. [41], with some modifications. Three replicate rhizosphere soil samples were obtained per treatment. Soil samples (n = 12) were air-dried for 2 weeks, passed through a 2 mm sieve, and stored at -80°C.
Plant dry weights and analysis of disease index and incidence.
For A. panax infected plants, ginseng black spot incidence was recorded from 9 days after A. panax inoculation. The 18 plants (3 pots) per treatment were collected to calculate the percentage of diseased plants and count disease index, using the following equations [42]:
Disease incidence = the number of diseased plants / the total number of plants × 100%
Disease index = Σ(A × B) × 100/Σ × 4
where A is the disease class (0, 1, 2, 3, 4) and B is the number of plants in the corresponding disease class.
For each plant, the shoots and roots were separated and weighed after air drying (dry weight, g) for 2 weeks at 30°C.
Sampling and chemical analysis.
Air-dried plants and soil samples were used in the nutrient analysis. About 50 mg oven-dried plant tissue was digested with a mixture of 8 mL HNO3 and 2 mL HClO4 at 200°C for 120 min in a semi-closed system. The digestates were cooled down to 25°C and made up to 50 mL with 4% (v/v) HNO3 solution. The soil pH (1:5, soil: water) was measured using a glass electrode (SK220, Switzerland). Soil nitrate nitrogen (NO3--N) was assayed using a continuous flow analytical system (SJAKAR SAN++, The Netherlands). Ammonium nitrogen (NH4+-N) in the soil was extracted with 0.01 M CaCl2, and the concentration was measured by an Auto Analyzer (Auto Analyzer 3, Germany). Potassium (K) in the soil was dissolved with ammonium acetate and calculated by flame photometry. Soluble phosphorus (P) was dissolved with sodium bicarbonate and its concentration measured using the molybdenum blue method [43].
High-throughput sequencing.
The total DNA was extracted from 0.5 g of each soil sample using a bacterial DNA Isolation Kit (Omega Bio-tek, Norcross, GA, USA) following the manufacturer’s instructions [44]. To assess the bacterial community composition, Illumina HiSeq platform (Illumina, San Diego, California, USA) was used in present study. The quantity and quality of extracted DNAs were measured using a Nanodrop 1000 (Thermo Fisher Scientific, Wilmington, DE, USA) and agarose gel electrophoresis, respectively. Primers for amplification and preamplification sequence: bacterial 16S rRNA gene V3-V4 region primers: 338F (5'-ACTCCTACGGGAGGCAGCA-3') and 806R (5'-GGACTACHVGGGTWTCTAAT-3'). DNA was amplified by PCR under conditions of 95°C 2 min, followed by 27 cycles of 95°C extends 30 s, 55°C for 30s and 72°C for 45 s; and a final extension at 72°C for10 min, then maintained at 10 °C until halted. The PCR reactions were performed triplicate in a 20 μL mixture contained 4 μL 5 Mix × FastPfu Buffffer, 2 μL of 2.5 mM dNTPs, 0.4 μL of each primer (5 μM), 0.4 μL of TransStart FastPfu DNA Polymerase (TransGen Biotech, Beijing, China), and 10 ng of template DNA [45] . PCR amplicons were purified with A gencourt AMPure Beads (Beckman Coulter, Indianapolis, IN) and quantified using the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). After the individual quantification step, amplicons were pooled in equal amounts, and pair-end 2×300 bp sequencing was performed using the Illumina HiSeq platform (Illumina, San Diego, California, USA) at Biomarker Technologies, Beijing, China.
The Quantitative Insights Into Microbial Ecology (QIIME, v1.8.0) pipeline was employed to process the sequencing data [46]. The low-quality sequences were filtered through the criteria [47, 48]. Paired-end reads were assembled using FLASH [49]. After chimera detection, the remaining high-quality sequences were clustered into operational taxonomic units (OTUs) at 97% sequence identity by UCLUST [50]. A representative sequence was selected from each OTU using default parameters. OTU taxonomic classification was conducted by BLAST searching the representative sequences set against the Greengenes Database [51]. Each OUT in each sample and the taxonomy was recorded in an OTU table, and OTUs containing less than 0.001% of total sequences across all samples were discarded. Sequences were deposited at the NCBI Short Read Archive and accession numbers are SRR9822023-SRR9822034.
Sequence data analyses were mainly performed using QIIME and R packages (v3.2.0). OTU-level alpha diversity indices, were calculated in QIIME. Beta diversity analysis was performed to investigate the structural variation of microbial communities across samples using UniFrac distance metrics [52, 53] and nonmetric multidimensional scaling (NMDS) [54]. Venn diagram was generated to visualize the shared and unique OTUs among groups using R package [55]. Taxa abundances at the phylum, class, order, family, genus and species levels were statistically compared among groups by Metastats [56]. PLS-DA (Partial least squares discriminant analysis) was also introduced as a supervised model to reveal the microbiota variation among groups, using the “plsda” function in R package “mixOmics” [57].
Data analysis.
One-way analysis of variance (ANOVA) was used to calculate the difference between treatments with variable soil pathogen abundance. The significance threshold was set at 0.05. The statistical analyses was performed using SAS 9.1 software (SAS Institute Inc., Cary, NC).