The tomato bacterial wilt pathogen R. solanacearum ZJ3721 (biovar 3) used in the experiments was kindly provided by Professor Jianhua Guo; the KP solution was adjusted to a pH of 7.0 with potassium hydroxide; Luvisol soil (FAO) was collected from the upper soil layer (5-30 cm) of an open field covered with grass at the Experimental Base of Nanjing Agricultural University (32.01´N, 118.85´E). The soil characteristics are listed in the Supplementary methods (Table S5). Two other soils Luvisol soil (FAO) from a grape plantation of Hebei province (36.96´N, 115.39´E) were collected from the upper soil layer (5-30 cm) of an open field covered with grass (HN) and planted grape for two years (HG). All soils were air-dried and sieved (20 mesh).
Effects of KP on the soil bacterial community
The experiment included one treatment (soil amended with KP) and a control (CK) (Fig. 7). Approximately 75 ml of sterilized water was added to 1.5 kg of dry soil from Nanjing to wet the soil. Next, 150 ml of an R. solanacearum cell suspension (cell density: 8×106 cfu ml-1) was added to the wet soil and mixed (final cell concentration: 8×105 cfu g-1 soil). R. solanacearum, as a soil-borne pathogen, can use root residuals to multiply; thus, tomato root tissues from healthy plants were added to the soils to simulate field conditions. Approximately 15 g of dry root tissues cut into approximately 1-mm lengths was added to 1.5 kg of soil at a rate of 1.0% (w/w) . Then, 750 g of soil containing root tissues was taken as the treatment and control. KP was applied at a concentration of 0.5% (w/w)  (KP treatment). The soil moisture of both the control and the KP treatments was adjusted to 45% of the soil capacity. Then, 750 g of soil was divided into 25 replicates consisting of 30 g of soil in a 50 ml centrifuge tube and then incubated at 30°C. The soils from the three replicates were randomly taken from all samples on days 7, 14 and 30 for soil DNA extraction.
The effects of KP on the numbers of culturable Actinobacteria were performed in two other soils (HN and HG). The same processes for the effects of KP on the microbial community of soil from Nanjing were performed. The three replicates from the two soils were randomly taken on days 7. One gram of the sampled soils was diluted and then spread on gauze No. 1 agar plates. The plates were incubated for 5 days at 28°C, and the numbers of culturable Actinobacteria were determined.
DNA isolation and Illumina HiSeq of the soil DNA
Total soil DNA was extracted using the PowerSoil® DNA Isolation Kit (MOBIO Laboratories, Carlsbad, CA, USA) according to the manufacturer’s instructions.
The V4 hypervariable regions of the 16S rRNA gene were ampliﬁed using primers 515F (5-GTGCCAGCMGCCGCGGTAA-3) and 907R (5-CCGTCAATTCCTTTGAGTTT-3). Subsequently, 0.4 µl of the primers and approximately 10 ng of template DNA were analysed via PCR with the following thermal cycling conditions: an initial denaturation at 98°C for 1 min, followed by 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s, and extension at 72°C for 60 s, with a final extension step at 72°C for 5 min after the cycling was complete. The PCR products were detected by electrophoresis in 1% (w/v) agarose gel and then purified with the GeneJET Gel Extraction Kit (Thermo Scientiﬁc). The purified PCR amplicons were sequenced using the Illumina HiSeq (250-bp paired-end reads) platform at the Novogene Bioinformatics Technology Co., Ltd. (Beijing, China).
The sequencing data were mainly processed on the USEARCH platform . Briefly, sequences with a quality score lower than 0.5 or a length shorter than 200 nt and singletons were discarded. Noisy sequences were filtered, chimerism was inspected and an OTU cutoff was assigned at the 97% identity level. Representative sequences for each OTU were selected and classified according to the RDP database for bacteria (cutoff = 80%). To correct for differences in the sequencing depth, the bacterial read counts were rarefied to the lowest number of sequences present in each sample set. The raw sequences were submitted to the NCBI Sequence Read Archive (SRA) under BioProject accession PRJNA577427.
The functional genes of the bacterial community were predicted by PICRUSt . The 16S sequences were used for closed-reference OTU selection with QIIME . The resulting OTU table was used to predict the functional genes based on the metagenome inference workflow.
Bacterial isolation and Sanger sequencing of 16S rRNA genes
The sampled soil at 7 days from the KP treatment was serially diluted and then spread on nutrient agar (NA) and gauze No. 1 agar plates. The plates were incubated for 3-5 days at 28°C. Because our target microbes are dominant taxa in the results of high-throughput sequencing, 33 dominant colonies (numbers of similar morphology > 5 in each plate) were selected. A loop of bacterial cells was added to 500 µl of water and incubated for 15 min at 95°C. Next, the cells were cooled on ice for 1 min and centrifuged at 10,000 × g for 1 min to remove the cell debris. The supernatant of the cell lysate was used as a DNA template for the amplification of the 16S rRNA genes. Information on the detailed primers F27 and R1492 and the PCR steps are listed in Table S6 and Table S7, respectively. Sanger sequencing was performed by the Qin Ke Company (Nanjing, China). The sequences of these bacteria were classified against the 16S ribosomal RNA database using NCBI BLAST. The 16S rRNA sequences of the isolates were clustered to the OTUs at 100% sequence similarity in USEARCH.
Draft genomes of two strains of bacteria identified as Paenibacillus favisporus Y7 and Streptomyces coelicoflavus F13
The genomes of the two isolates Paenibacillus favisporus Y7 and Streptomyces coelicoflavus F13, which were highly abundant in the microbial community of the KP-treated soil, were sequenced. The sequences were analysed according to the method described in a previous study . Briefly, the low-quality sequences were removed by adapter removal (version 2.1.7). After filtering, a total of 9,141,712 (98.65%) and 16,401,350 (97.68%) high-quality paired-end reads were obtained for strains Y7 and F13, respectively. All reads were quality corrected by SOAPec (version 2.0) based on the k-mer frequency, with the k-mer used for correction set to 17. The genome was assembled de novo using A5-miseq (version 20150522). The draft genome sequences of strains Y7 and F13 contained 17 and 59 contigs (a sequence length greater than 1 kb), respectively. The coding DNA sequences (CDs) in the draft genomes were predicted by GeneMarkS (version 4.32). The predicted CDs were searched against the NCBI NR protein database and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The whole-genome shotgun project has been deposited in GenBank under the accession number WIBG00000000 (strain Y7) and WFLH00000000 (strain F13).
Effect of KP on the growth of R. solanacearum,P. favisporus Y7 and S. coelicoflavus F13 in vitro
To measure the cell density (OD600) under KP conditions, 200 µl of R. solanacearum (approximately 108 cfu ml-1) and P. favisporus Y7 (approximately 108 cfu ml-1) was inoculated in 3 ml of LB (Luria Broth) liquid containing KP at a concentration of 0.5%. To measure the dry biomass of F13 under KP conditions, 200 µl of S. coelicoflavus F13 spores (approximately 108 cfu ml-1) was inoculated in 20 ml of LB liquid containing KP at a concentration of 0.5%. The LB liquid without KP was used as the control. Each treatment had four replicates. After 48 h of incubation at 30°C (R. solanacearum and P. favisporus Y7) and 28°C (S. coelicoflavus F13) and 170 rpm, the cell densities (OD600) of R. solanacearum and strain Y7 and the dry biomass of strain F13 were measured.
Inhibition of R. solanacearum growth by P. favisporus Y7 and S. coelicoflavus F13 in vitro
Approximately 2 µl of the strain Y7 cell suspension (cell density: 108 cfu ml-1) and 5-mm-diameter agar plugs of strain F13 grown in gauze No. 1 agar plates for 5 days were spotted onto the centre of NA medium agar plates and incubated at 30°C (strain Y7) and 28°C (strain F13) for three days. Then, 200 µl of R. solanacearum (cell density: 107 cfu ml-1) was sprayed onto the plates. After 48 h of incubation at 30°C, the inhibition diameters of the two strains were measured with a ruler. Each treatment had three replicates.
Mutual stimulation between strains S. coelicoflavusF13 and P. favisporusY7 in vitro
Strain P. favisporus Y7 and strain S. coelicoflavus F13 were cultured in 200 ml of one-tenth LB liquid at 30°C (strain Y7) for 2 days and 28°C (strain F13) for 5 days, respectively, at 170 rpm. Then, the culture suspensions were centrifuged at 10,000 × g for 5 min. The supernatants were sterilized with 0.22-mm sterile filter membranes. Next, 20 µl of cell suspensions of strains Y7 (approximately 1×108 cfu ml-1) was inoculated in 3 ml of one-tenth LB liquid containing the sterilized supernatants of strains F13 at concentrations of 10%, 30% and 50% (v/v). Approximately 20 µl of spore suspensions of F13 (approximately 1×108 cfu ml-1) was inoculated in 20 ml of one-tenth LB liquid containing the sterilized supernatants of strains Y7 at concentrations of 10%, 30% and 50% (v/v). The one-tenth LB liquid without strain supernatants was used as the control. Each treatment had four replicates. After 24 h of incubation at 30°C (strain Y7) and 28°C (strain F13) at 170 rpm, the cell density (OD600) of strain Y7 and the dry biomass of strain F13 were measured.
Inhibition of R. solanacearum by combined P. favisporus Y7 and S. coelicoflavus F13 in sterile soil
Approximately 50 ml of sterilized water was added to 1 kg of dry sterilized soil (2 × 99 min at 121 °C) to wet the soil. Approximately 50 ml of the R. solanacearum cell suspension (cell density at 2×106 cfu ml-1) and 10 g of sterilized root tissues (approximately 1 mm lengths) were added to the wet soils and mixed (final R. solanacearum concentration of 1×105 cfu g-1 dry soil). Then, all soils were divided evenly into 6 parts (per part: 166 g). Approximately 10 ml of the spore suspension of strain F13 at 1.66×106 cfu ml-1 (part 1), 10 ml of strain Y7 at 1.66×106 cfu ml-1 (part 2) and combinations of Y7 and F13 at different inoculation concentrations (Y7: F13 = 7:3 (part 3), 5:5 (part 4), 3:7 (part 5)) were added to the 166 g of soil to a final density of 1×105 cfu g-1 dry soil. Approximately 10 ml of sterile water was added to 166 g of soil as a control (part 6). Before being added to the soil, all strains were washed 5 times. Approximately 30 g of the soil from each part was placed in a 50-ml sterilized centrifuge tube with 5 replicates and incubated at 30°C for 20 days; then, the soil samples were used for DNA extraction.
Inhibition of R. solanacearum by the KP-modulated soil microbiome
A soil microbiome transfer experiment was performed to determine the function of the KP-modulated soil microbiome. The soil microbiome transfer experiment was performed based on a previous study  with slight modifications. The same processes for determining the effects of KP on the soil microbial community were performed but without the addition of R. solanacearum in the soil from Nanjing. On day 7, 5 g of KP-treated soil and control soil were added separately to 45 ml of sterile water in a flask on a shaker at 200 rpm for 30 min followed by sonification for 1 min at 47 kHz twice with shaking for another 30 min. Next, the soil suspension of each treatment was filtered with sterile filter paper (15 μm pore size) to remove soil particles. To remove water-soluble nutrients/chemicals, such as KP, the filtrate was centrifuged at 3,000 × g for 30 min, and the supernatant was discarded. The pelleted microorganisms were resuspended in 5 ml of sterile water.
Approximately 20 ml of sterilized water was added to 360 g of dry sterilized soil (2 × 99 min at 121 °C) to wet the soil; this soil was mixed with 9 ml of the R. solanacearum cell suspension (cell density at 8×107 cfu ml-1) and 3.6 g of dry sterilized tomato root tissues (approximately 1-mm lengths) and then divided evenly into 2 parts. Then, 3 ml of the cell suspension extracted from the KP treatment and control soils was applied separately to 180 g of sterilized soil containing root tissues. Each 180-g sample of the above soil was divided into 6 replicates of 30 g each in 50-ml sterilized centrifuge tubes, referred to as the MK microbial community from the KP-treated soil (MK) or the microbial community from the control soil (MC) treatments, and then incubated at 30°C. The soils from three replicates were randomly sampled on day 20  for DNA extraction.
Quantitative PCR to measure the copies of functional genes
The copy numbers of the fliC (R. solanacearum), 16S rRNA (total bacteria), con31_49 (S. coelicoflavus F13), con2_67 (P. favisporus Y7), the main antagonistic genes for Bacillus (srf (surfactin), itu (iturin) and fen (fengycin)) were quantified by quantitative PCR. After sequencing the genomes of S. coelicoflavus and strain P. favisporus, the unknown functional genes from contig31_6449 (strain S. coelicoflavus) and contig2_3067 (strain P. favisporus) were found without homologous genes in the NCBI. Thus, the gene fragments were used to design primers (con31_49 for S. coelicoflavus and con2_67 for P. favisporus) in Premier 5. The designed primers were tested by primer-blast (www.ncbi.nlm.nih.gov/tools/primer-blast/), and no microbes were obtained.
Quantitative PCR (qPCR) assays were performed using the SYBR Premix Ex TaqTM (Perfect Real-Time) Kit (Takara Biotechnology Co., Dalian, China) with the ABI StepOneTM Real-Time PCR System (Applied Biosystems, USA). Each reaction was performed in a 20 µl volume. The detailed primer information and PCR steps are listed in the supporting information (Table S6 and Table S7). Standard curves were developed by serially diluting the plasmids with known positive inserts to final concentrations of 102 to 107 gene copies µl−1. The QPCR efficiencies ranged from 90% to 105%, and the R2 values for all four assays were greater than 0.99.
The OTU tables were converted into a suitable input file for bacterial diversity analysis using Mothur . Principal coordinate analysis (PCoA) of the bacterial community structure was performed by calculating the Bray-Curtis dissimilarity in R. Differences between groups were tested for significance by a permutation-based analysis of variance by using the adonis function of the vegan package in R. The significant genera (top50) between the control and the KP treatment and the MC and MK treatments were identified with DESeq in R, and the significant genera were shown in a circular treemap using the ggraph package in R.
Significant differences in the bacterial community diversity indices, the number of culturable Actinobacteria, the number of functional gene copies, colony diameters, inhibition zone diameters, the cell densities (OD600) of R. solanacearum and strain P. favisporus Y7 and the biomass of strain S. coelicoflavus F13 from the inhibition level results were assessed using Student’s t test; the data conformed to a normal distribution according to the Shapiro-Wilk test in R. Significant differences in the relative abundance levels of the PICRUSt-predicted genes were assessed using Welch's t-test.
The data on the cell density (OD600) of strain P. favisporus Y7 and the biomass of strain S. coelicoflavus F13 from the mutual stimulation results were subjected to one-way ANOVA and then Tukey’s test for multiple comparisons.
The OTU abundances (top 300) were used to build a microbial network by the function sparcc with 100 permutations in Mothur software. Edges whose p.adjust value was < 0.001 were retained. The link number of nodes (OTU degree) and visualized networks were assessed using Gephi software . Phylogenetic trees of nodes were built by MEGA7. Moreover, the associations between the relative abundances of hubs (link numbers >50) from bacterial networks and the predicted genes related to production of antagonistic substances were determined by the cor.test function in R with the “pearson” method. The p-values were adjusted by the “FDR” method.
The gene annotation protein.faa files of strains Y7 and F13 were used to construct genome-scale metabolic models with “carve” functions, and the genome-scale metabolic models of strains Y7 and F13 were used to generate the microbial community models with the “merge_community” functions by CarveMe . The metabolic substances and reactions of the microbial community models were obtained by the sybilSBML package in R, and the associations between metabolic substances and reactions were visualized using Cytoscape software .