LlN Wei-peng ,JlANG Ni-hao ,PENG Li,FAN Xue-ying ,GAO Yang ,WANG Guo-ping,CAI Kun-zheng

1 College of Natural Resources and Environment,South China Agricultural University,Guangzhou 510642,P.R.China

2 Tea Research Institute,Guangdong Academy of Agricultural Sciences,Guangzhou 510640,P.R.China

3 Key Laboratory of Tropical Agricultural Environment in South China,Ministry of Agriculture,Guangzhou 510642,P.R.China

4 College of Agriculture,South China Agricultural University,Guangzhou 510642,P.R.China

5 College of Horticulture,South China Agricultural University,Guangzhou 510642,P.R.China

Abstract Silicon (Si) can increase plant resistance against bacterial wilt caused by Ralstonia solanacearum and enhance plant immune response.However,whether Si alleviates soil-borne disease stress through altering soil microbial community component and diversity is not clear.In this study,effects of Si application under R. solanacearum inoculation with or without plant on soil bacterial and fungal communities were investigated through high-throughput pyrosequencing technique.The results showed that Si addition significantly reduced bacterial wilt incidence.However,Si did not reduce the amount of R. solanacearum in rhizosphere soil.Principal components analysis showed that soil microbial community composition was strongly influenced by Si addition.Total 63.7% bacterial operational taxonomic units (OTUs) and 43.8% fungal OTUs were regulated by Si addition regardless of the presence of tomato plants,indicating the independent effects of Si on soil microbial community.Si-added soil harbored a lower abundance of Fusarium,Pseudomonas,and Faecalibacterium.Our finding further demonstrated that exogenous Si could significantly influence soil microbial community component,and this may provide additional insight into the mechanism of Si-enhanced plant resistance against soil-borne pathogens.

Keywords: bacterial wilt,deep pyrosequencing, Ralstonia solanacearum, silicon,soil microbial community

1.lntroduction

Silicon (Si) is the second most abundant mineral element in the Earth’s crust (Epstein 1994).However,until now,Si is still not considered as an essential element for most of the plants,although numerous studies have documented the role of Si in improving plant growth and yield as a fertilizer without adverse effects (Liang 1998;Epstein and Bloom 2005;Fuet al.2012;Yanet al.2018).Moreover,Si can enhance plant resistance against a wide range of stress caused by soil pathogens (Datnoffet al.1997;Caiet al.2008;Debonaet al.2014;Mburuet al.2016) in Si-accumulating plants (e.g.,rice,wheat,sugarcane,perennial ryegrass,banana,cucumber,pumpkin,and strawberry) (Menzieset al.1991;Bélangeret al.2003;Lianget al.2005;Kantoet al.2007;Gaoet al.2011;Kablanet al.2011;Camargoet al.2013;Mohagheghet al.2015).Most Si-accumulating plants absorb soluble Si from the soil,transport aboveground,and finally deposit it in leaves,where Si functions as a mechanical barrier to impede pathogenic penetration (Fauteuxet al.2005;Maet al.2011;Shettyet al.2012).Studies also showed that Si significantly increased the accumulation of antimicrobial compound,such as lignin,flavonoid,chlorogenic acid and aconitate in the leaves upon pathogen infection (Faweet al.1998;Rodrigueset al.2004;Rémus-Borelet al.2009;Rahmanet al.2015).Several defense-related enzymes in pathogen-infected leaves were also induced by Si (Yuet al.2010;Resendeet al.2012;Songet al.2016).A number of recent microarrays,proteome,and transcriptome analyses have shown that Si primes plant defense response not only through the formation of a physical barrier,but also altering gene and protein expression,influencing endogenous hormone balances (Chainet al.2009;Flecket al.2011;Ghareebet al.2011;Van Bockhavenet al.2015;Chenet al.2015).

Compared with large number of studies of Si-mediated plant resistance against leaf pathogen,the effect of Si on soil-borne pathogens has attracted relatively less attention.Moreover,the mechanism of Si in enhancing plant resistance against foliar pathogens cannot completely explain its effects on soil-borne pathogens.Bacterial wilt caused byR.solanacearumis a serious soil-borne disease in tomato(Genin and Denny 2012).Increasing evidence shows that Si has significant effects in alleviating bacterial wilt incidence of tomato,although tomato is considered as a Si-non-accumulator (Dannon and Wydra 2004;Ghareebet al.2011;Kiirikaet al.2013;Chenet al.2015).In tomato plants,Si mainly accumulates in the roots rather than stems or leaves,and Si is involved in induced resistance againstR.solanacearumon cell wall level (Dannon and Wydra 2004;Diogo and Wydra 2007).Several key genes related to the jasmonic acid or ethylene pathway,includingJERF3,TSRF1andACCO,oxidative stress geneFD-I,POD,and the basal defense geneAGP-1g,are upregulated by Si(Ghareebet al.2011).Our previous study demonstrated that Si could modulate the expression of various proteins related to glycolytic pathway,TCA cycle and defense response in tomato roots underR.solanacearuminoculation (Chenet al.2015).

The interactions between plants and their rhizobacteria are always fascinating and challenging topics.There are up to 1011microbial cells and more than 30 000 species per gram rhizosphere soil (Egamberdievaet al.2008;Mendeset al.2011).However,most rhizobacteria associated with plants are commensals showing a weak interaction with the host plants,and no visible effect on the growth and physiology of the host plants (Beattie 2006).Only a small fraction of rhizobacteria elicited the host plant response involved in negative consequence caused by phytopathogens and positive impacts by beneficial microbes.Many beneficial microorganisms referred to as plant growth-promoting rhizobacteria (PGPR),which can stimulate plant growth and enhance plant resistance against a range of biotic stress(e.g.,phytopathogen,insect and nematode) (Pieterseet al.2014) and abiotic stresses (e.g.,drought,salinity,heavy metal toxcity and low temperature) (Heet al.2017;Turanet al.2017).For example,some PGPR promote root growth(Mantelin and Touraine 2004) and change root architecture by producing the indole acetic acid (IAA) (Kloepperet al.2007),leading to an increase of root surface area and root tips,which could increase nutrient uptake of plants (Yanget al.2009).Phosphate solubilizing bacteria and nitrogenfixing bacteria help to increase nutrient supply in the soil (Piiet al.2015).Furthermore,accumulating evidence showed that some rhizobacteria suppressed the pathogens through competing for nutrients (Kamilovaet al.2005),producing antibiotic compounds (Welleret al.2002;Chaet al.2016) or lytic enzymes (Lugtenberget al.2009).In addition to directly inhibiting the pathogens,other rhizobacteria includingPseudomonas,Bacillus,Trichoderma,and mycorrhiza species have been found to prime the defensive capacity of the host plants by eliciting induced systemic resistance(ISR) (Pieterseet al.2014;Morrisonet al.2017).Beneficial rhizobacteria have important role in improving plant fitness in various environments,although they were only a small part of the entire rhizobacteria in the soil (Lau and Lennon 2012).In a word,microflora plays an important role in the survival of the plant.Hence,any agricultural measures such as tillage,fertilizer or pesticide use will influence rhizosphere microflora,which may lead to positive and negative effects on the crop.

To date,most of the studies of Si and pathogens focused on the effects of Si on enhancing plant immunity.However,plants and pathogens coexist in a specific environment,whether the plants exhibited health or disease was not only determined by plant immunity,but also pathogenicity of the pathogens and environment factors (e.g.,pH,temperature and humidity).The potential effect of Si on the pathogen and pathogenesis-related environment such as soil microbial community attracted less attention.Our previous study (Wanget al.2013) found that Si addition significantly increased the amount of soil bacteria and actinomycetes,and reduced the soil fungi/bacteria ratio under theR.solanacearuminfected condition,but the specific microbial groups influenced by Si were not known.In this study,we use highthroughput pyrosequencing technology to further identify soil bacterial and fungal microbial community component and diversity influenced by Si underR.solanacearuminfection,and to reveal the relationship between soil microflora and bacterial wilt incidence.

2.Materials and methods

2.1.Plant materials and growth condition

A susceptible tomato genotype (cv.HYT) from the College of Horticulture of South China Agricultural University was used in the experiment.Tomato seeds were surface-sterilized with 10% H2O2for 10 min,washed with sterile distilled water for five times,and finally germinated on moist filter paper for 48 h in Petri dishes.The germinated seeds were sown in peat substrate (Klasmann Deilmann,Germany)under greenhouse conditions and then transplanted after three weeks to the individual pot (10 cm in diameter and 15 cm in height) with 1.5 kg of soil.The soil was collected directly from the tomato-rice rotation field in Zhucun Village,Zengcheng City,Guangdong Province,China.The content of soil organic matter and soil-available N,P,K,and Si were 9.9 g kg-1,107.3 mg kg-1,37.2 mg kg-1,250.4 mg kg-1,and 281.3 mg kg-1,respectively.Soil pH is 4.75.

2.2.Experimental design

The following four treatments were set up in this study:(1) no Si addition with plant (Si-P+),(2) 2.0 mmol L-1Si addition with plant (Si+P+),(3) no Si addition without plant (Si-P-);and (4) 2.0 mmol L-1Si addition without plant (Si+P-).There are 12 replications for Si-P+ and Si-P+ treatments and six replications for Si-P-and Si-P-treatments.All treatments were inoculated withR.solanacearum.In treatments with Si addition (Si+P+and Si+P-),the plants (soil) for each pot were irrigated daily with a 50-100 mL nutrient solution which contains 5 mmol L-1Ca(NO3)2,1.88 mmol L-1K2SO4,1.63 mmol L-1MgSO4,0.5 mmol L-1KH2PO4,0.04 mmol L-1H3BO3,0.001 mmol L-1ZnSO4,0.001 mmol L-1CuSO4,0.01 mmol L-1MnSO4,0.00025 mmol L-1Na2MoO4,0.05 mmol L-1NaCl and 0.1 mmol L-1Fe-EDTA (Kurabachew and Wydra 2014)and amended with 2 mmol L-1potassium silicate (K2SiO3,powder,Alfa Aesar).In the no Si-added treatments (Si-P+and Si-P-),the soil was also irrigated daily with the same 50-100 mL nutrient solution but amended with potassium chloride (KCl) to replenish potassium.The pH of nutrient solutions (amended with K2SiO3or amended with KCl) were adjusted to 7.0 before use.

2.3.Ralstonia solanacearum cultivation and inoculation

Tomato plants were inoculated with a moderate pathogenicRalstonia solanacearumstrain belonging to race 1 biovar 3.R.solanacearumwas cultured in LB medium at 30°C for 48 h.Ralstonia solanacearumwas harvested from agar plates by sterile water flushing and adjusted to OD600=0.06(approximately 108CFU mL-1) (Dannon and Wydra 2004).At the sixth leaf stage of the tomato plants,50 mL bacterial inoculum suspension was poured over the soil surface per pot.

2.4.Soil sample collection and DNA extraction

At the end of the experiment (20 days after pathogen inoculation),tomato plants were removed from the soil,the roots were vigorously shaken,and the remaining soil attached to the roots was considered as rhizosphere soil.Rhizosphere soil extraction was modified from Teixeiraet al.(2010) as follows: 5 g of the roots with rhizosphere soil was immersed in 50 mL ddH2O,shaken at 180 r min-1for 30 min,then the supernatant was centrifuged for 10 min at 9 000 r min-1,the resulting pellet was obtained and defined as the rhizosphere soil.The bulk soil was collected from the no-plant treatment.All the soil samples were stored at-80°C until further use.Soil DNA was extracted from 0.5 g of rhizosphere soil (with plant treatments) and bulk soil (no plant treatments) using a Fast DNA SPIN Kit(MP Biomedicals,Santa Ana,CA,USA) in each treatment.DNA concentration and purity were determined using a spectrophotometer (Nanodrop 1000,Thermo Scientific,USA).Then the DNA purity was diluted to 10 ng μL-1,stored at-80°C for further analysis.

2.5.Quantification of R. solanacearum in soil

Real-time PCR modified from Chenet al.(2010) was performed to quantify the amount ofR.solanacearumin the soil.The primers RSF (5′-GTGCCTGCCTCCAAAACGACT-3′) and RSR (5′-GACGCCACCCGCATCCCTC-3′) were used in the quantification (Chenet al.2010).A total of 2 μL of DNA(extracted in the previous section) was used as template in 10 μL total volume as prescribed by the manufacturer of the SYBR PremixEx TaqMix Kit (TaKaRa,Japan),and quantitative PCR (qPCR) was performed using ABI 7500(ABI,USA).The cycling parameters were as follows: (1)holding stage at 95°C for 30 s;(2) cycling stage at 95°C for 5 s,62°C for 34 s,cycled for 40 times;(3) melting curve stage at 95°C for 15 s,60°C for 1 min,95°C for 30 s,and 60°C for 15 s.Each sample was replicated three times.The copy numbers were log10transformed to normalize the values before statistical analysis.

2.6.Pathogen symptom evaluation

Disease severity of bacterial wilt for each treatment was evaluated by a disease score according to Wanget al.(2013).The score was described as 0=no symptoms,1=one leaf wilted,3=two or three leaves wilted,5=all except the top leaves wilted,7=all leaves wilted,and 9=stems collapsed or plants died.

2.7.PCR amplification and deep pyrosequencing

The 16S rDNA genes of the regions (16S V3+V4) were amplified using specific primers 341F (5′-CCTAYGGGRBG CASCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′)targeting soil bacteria (Berget al.2012),and the ITS genes were amplified using the specific barcoded primer ITS5(5′-GGAAGTAAAAGTCGTAACAAGG-3′) with ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′) targeting soil fungi(Zhaoet al.2014).All the PCR reactions were carried out with 30 μL system with 15 μL of Phusion High-Fidelity PCR Master Mix (New England Bio-labs,USA).There were 0.2 μmol L-1of forward and reverse primers and about 10 ng template DNA under the following thermal cycling conditions: 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,elongation at 72°C for 30 s and finally at 72°C for 5 min.All samples were amplified in triplicate,and no-template controls were included in all steps of the process.Triplicate PCR amplicons were pooled together and then mixed with the same volume of 1× loading buffer(containing SYB green) and electrophoresis was operated on 2% agarose gel for detection.Samples with a bright main strip between 450-500 bp (16S rDNA for bacteria)and 200-400 bp (ITS for fungi) were chosen for next step.PCR products with bright band purified with Qiagen Gel Extraction Kit (Qiagen,Germany) were then detected by electrophoresis in a 2% (w/v) agarose gel.The purified PCR amplicons were sequenced using the Illumina Hiseq2500 platform at Novogene Bioinformatics Technology Co.,Ltd.(Beijing,China) and 250 bp paired-end reads were generated according to the protocols described by Caporasoet al.(2012).

2.8.DNA sequence accession numbers

The DNA sequence data have been deposited in the NCBI Sequence Read Archive (SRA) database with the accession number SRP125563.

2.9.Bioinformatics and statistical analysis

The sample reads were assembled by using Mothur ver.1.32(Schlosset al.2009).Chimeric sequences were removed using the USEARCH software based on the UCHIME algorithm (Edgaret al.2011).Operational taxonomic units (OTUs) were picked using an OTU picking protocol with a 97% similarity threshold,and the representative OTUs were subsequently classified using the GreenGene database (Wanget al.2007).Alpha diversity estimators including observed species,Chao1,ACE,and Shannon index were calculated for bacterial and fungal community analysis (DeSantiset al.2006;Rasuket al.2016).Principal component analysis (PCA) was used to separate samples according to the UniFrac distance metrics among the samples.The first two components from the PCA explained the differences in the bacterial and fungal community among the four treatments (Lozuponeet al.2011).The homogeneity of variances and normality of distribution were tested with the Levene and Kolmogorov-Smirnov tests,respectively.In addition,the non-normally distributed dependent variables were log10transformed before analysis.Data were statistically analyzed by one-way ANOVA with means and a post-hoc method (Duncan’s method) at a 5% significance level for multiple comparisons.All the statistical analyses were performed with SPSS 20.0 (IBM,Chicago,USA).

3.Results

3.1.Disease severity and amount of R. solanacearum in soil

Bacterial wilt incidence in Si-treated plants was 38.8% lower than that in no-Si treated control.However,no significant change was detected in the relative abundance (RA) ofRalstoniagenus between Si and no Si treatments (Table 1),and the qPCR also demonstrated that Si did not significantly inhibitR.solanacearumin the soil (Table 1).

3.2.Sequence data and taxonomic richness

After the filtering based on basal quality control,a total of 462 127 bacterial sequence reads were obtained from 12 samples (four treatments and three replications).The number of high-quality sequences per sample varied from 33 844 to 47 635 (Appendix A).The sequences were grouped into 4 048 OTUs at the 97% similarity cutoff level.Also,a total of 625 365 fungal sequence reads were obtained.The number of high-quality sequences per sample varied from 31 389 to 64 598 (Appendix A),resulting in 1 665 OTUs at the 97% similarity cutoff level.Rarefaction analyses showed that all the rarefaction curves tend to be asymptotic both in bacteria and fungi,indicating that sequence-derived diversity and richness in this study were sufficient for the subsequent analyses (Fig.1)

Rhizosphere soil with plants (Si+P+ and Si-P+ treatments)had significantly lower bacterial diversity (observed species richness) than the bulk soil without plants (Si+P-and Si-Ptreatments) regardless of Si treatment (Fig.2-A) but not for fungal diversity (Fig.2-B).Si application did not influence species richness of soil bacteria and fungi regardless of the presence of tomato plants.Similar results were obtained in Shannon,ACE,and Chao1 indices (Appendix B).

3.3.Variation of OTUs of bacteria and fungi among treatments

To narrow the range of the different OTUs,we omitted the OTUs at the 0.01% relative abundance (RA) cutoff level.We found an increase of 555 bacterial OTUs and a decrease of 271 bacterial OTUs in Si-added treatments compared with those in no Si-added treatments.These OTUs accounted for 63.7% of the retained bacterial OTUs (the intersection of circles of Fig.3-A).Moreover,65 fungal OTUs increase and 80 fungal OTUs decrease in Si-added treatments were also detected,and these OTUs accounted for 43.8% of the retained fungal OTUs (the intersection of circles of Fig.3-B).

Furthermore,Si significantly regulated 35 OTUs for bacterial and fungi,of which 13 OTUs increased (Table 2)and 22 OTUs decreased (Table 3) compared with treatments without Si addition.Moreover,the number of decreased OTUs were approximately two-fold of the number of increased OTUs.Five OTUs belonging to δ-Proteobacteria had high relative abundance in the Si-added treatments,and these OTUs accounted for 38.4% of the 13 increased OTUs (Table 2).

All the bacterial OTUs of less abundance in the Si-added treatment belong to Firmicutes and Proteobacteria (Table 3).The main decreased orders were Rhizobiales (4 OTUs),Burkholderiales (3 OTUs) and Clostridiales (3 OTUs).For soil fungi,special OTUs showed 95% similarity toFusarium oxysporumf.sp.Fragaria,which had low abundance in the Si-added treatment (Table 3).

3.4.Community composition and structure of bacteria and fungi

PCA revealed a clear separation of the bacterial community compositions among the four treatments (Fig.4-A).Thefirst principal component (PC1) contributes 40.1% of the total variation.We defined this component as a plant factor,because it separated the four treatments into two groups,that is,with plant (Si-P+ and Si+P+) and without plant (Si-P-and Si+P-).Principal component 2 accounts for 14.4% of the total variation among the differences in the bacterial communities.It separates the treatments into two groups,that is,Si group (Si+P+ and Si+P-) and no Si group(Si-P+ and Si-P-).The results demonstrated that both plant and Si application significantly influenced soil bacterial community,and plant identity was a more important factor to explain variation in their system (Fig.4-A).

Table 1 Tomato wilt disease incidence and pathogen abundance1)

Fig.1 Rarefaction analysis at 97% similarity levels for soil samples from different treatments.A,bacteria.B,fungi.Si-P+,no Si addition with plant;Si+P+,2.0 mmol L-1 Si addition with plant;Si-P-,no Si addition without plant;Si+P-,2.0 mmol L-1 Si addition without plant.OTUs,operational taxonomic units.Vertical bars represent SE (n=3).

Fig.2 Observed species richness for soil microflora from different treatments.A,bacteria.B,fungi.Si-P+,no Si addition with plant;Si+P+,2.0 mmol L-1 Si addition with plant;Si-P-,no Si addition without plant;Si+P-,2.0 mmol L-1 Si addition without plant.Different letters indicate statistically significant differences at the 0.05 probability level according to Duncan test.Vertical bars represent SE (n=3).

Fig.3 Venn diagram for soil samples collected from different treatments showing shared and unique operational taxonomic units(OTUs) identified in both Si+P+ vs.Si-P+ and Si+P-vs.Si-P-at the 0.01% relative abundances cutoff level.A,bacteria.B,fungi.Si-P+,no Si addition with plant;Si+P+,2.0 mmol L-1 Si addition with plant;Si-P-,no Si addition without plant;Si+P-,2.0 mmol L-1 Si addition without plant.↑,relative abundance increased;↓,relative abundance decreased.Average relative abundance was calculated from three replications for each treatment.

Similarly,PCA in soil fungal community showed that four treatments could be separated into two groups by PC1 which accounts for 24.1% of the total variance (Fig.4-B),one group included Si-P+ and Si+P+,and the other group included Si-P-and Si+P-.The second principal component (PC2)accounts for 19.1% of the total variation,but the samples from Si-added soil and no Si-added soil have a smaller degree of separation between categories on PC2.

The bacterial and fungal community structures in the rhizosphere soil from different treatments were compared at the phylum level (Fig.5).For all treatments,Nitrospirae,Proteobacteria,Acidobacteria,Crenarchaeota,Firmicutes,Chloroflexi,and Actinobacteria were the dominant bacterial phyla,accounting for more than 80% of the bacterial sequences;and Ascomycota,Basidiomycota,and Zygomycota were the dominant fungi phyla,comprising more than 60% of the fungi sequences.One-way ANOVA analysis results showed that Si did not influence the RAs of soil bacterial and fungal community at the phylum level.

At the genus level of the bacterial community,lower RAsofPseudomonasandFaecalibacteriumwere observed in the Si-added soil regardless of the presence of the plants(Fig.6-A),while a lower RA ofFusariumin Si-added soil compared with no Si-added soil in the fungal community(Fig.6-B).

Table 2 More abundan operational taxonomic units (OTUs) in Si-added treatments than in no Si-added treatments1)

Table 3 The operational taxonomic units (OTUs) more abundant in no Si-added treatment than in Si-added treatments1)

Fig.5 Relative abundance of main bacteria and fungi community at phyla level in soil from different treatments.A,bacteria.B,fungi.Si-P+,no Si addition with plant;Si+P+,2.0 mmol L-1 Si addition with plant;Si-P-,no Si addition without plant;Si+P-,2.0 mmol L-1 Si addition without plant.

4.Discussion

Many previous studies showed that Si could improve plant resistance against soil-borne pathogens by enhancing plant immune such as inducing defense-related enzymes in root (Mohagheghet al.2010;Fortunatoet al.2012),accumulation of phytoalexins in the stem (Diogo and Wydra 2007) or root (Fortunatoet al.2014),also altering gene and protein expression in stem (Ghareebet al.2011) and root (Chenet al.2015).However,all the above evidence focused on the interaction between plant and Si,whether Si addition directly inhibits the pathogens in soil is not clear.Our study revealed Si did not inhibitR.solanacearumin the soil,although it significantly reduced pathogen incidence(Table 1).Similarly,reports showed that the amount ofR.solanacearumin the roots and stems did not significantly decrease after Si application (Diogo and Wydra 2007;Kurabachew and Wydra 2014).In contrast,studiesin vitroexperiments showed that Si inhibited pathogen growth(Maekawaet al.2003;Bekkeret al.2006;Kantoet al.2007;Bekkeret al.2009;Liet al.2009).These above studies used potassium silicate and sodium silicate as Si source without adjusting pH,the pH of the medium can be as high as 10 (Liuet al.2010).High pH can inhibit the pathogenicity and survival of pathogens (Manteauet al.2003;Alkanet al.2013;Liet al.2017).Furthermore,Shenet al.(2010)confirmed that the inhibiting role of potassium silicate on pathogens was not effective when the pH in the medium was adjusted from 10 to 7.0 which was equivalent to no Si-added treatment.Combined with previous studies,our results showed Si did not directly suppressR.solanacearumin the soil.

Fig.6 Relative abundance of top 10 bacterial and fungal genera in soil from different treatments.A,bacteria.B,fungi.Si-P+,no Si addition with the plant;Si+P+,2.0 mmol L-1 Si addition with the plant;Si-P-,no Si addition without the plant;Si+P-,2.0 mmol L-1 Si addition without the plant.Different letters indicate statistically significant differences at the 0.05 probability level according to Duncan test.Vertical bars represent standard errors (n=3).

The diversity and stability of bacterial communities in the rhizosphere significantly influenced soil and plant quality and immunity (Raaijmakers and Mazzola 2016).The structure and function of soil microbial communities are influenced by numerous selection factors (Liet al.2014).The introduction of plants,pathogens,organic fertilizers,and even heavy metals has already been demonstrated to alter the species abundances and composition of the microbial community.Microbial communities are regarded as a key mechanism that can suppress soil-borne pathogens (Mendeset al.2011;Liet al.2014;Chaet al.2016).Our results clearly demonstrated that there was significant difference in soil bacterial and fungal community structure between Si-added and no Si-added treatments (Fig.4),indicating the Si is an important factor in influencing soil microbial community.In contrast,a recent study showed SiO2nanoparticles did not significantly change the relative abundance of most dominant genera in soil communities and soil fungal community structure of agricultural pastureland (McGeeet al.2017).These inconsistent results may be due to the different chemical form of silicon and different soils used in the two experiments.Our results also showed that 13 OTUs belonging to α-Proteobacteria and β-Proteobacteria were suppressed by Si (Table 3).This finding was similar to the results by Liet al.(2014),who reported that α-Proteobacteria and β-Proteobacteria are less abundant in healthy soils compared with those in the wilt-diseased bacterial soil.Our results indicated that the low relative abundance of α-Proteobacteria and β-Proteobacteria in the Si-added treatment might explain the reduction of wilt incidence in the plants.

Furthermore,our results showed that 13 OTUs belonging to α-Proteobacteria and β-Proteobacteria were suppressed by Si application (Table 3).This finding was similar to the results by Liet al.(2014),who reported that α-Proteobacteria and β-Proteobacteria are less abundant in healthy soils compared with those in the wilt-diseased bacterial soil.Our results indicated that the low relative abundance of α-Proteobacteria and β-Proteobacteriain the Si-added treatment might explain the reduction of wilt incidence in plants.

Our study also found Si addition resulted in a lower abundance ofFusariumgenus in soil (Fig.6-B),whileFusariumspp.has an extremely broad host range and is among the most serious soil-borne pathogens in crop production systems worldwide (Chaet al.2016).Also,an OTU with 97% similarity toFusarium oxysporumf.sp.Fragaria strain,the most devastating pathogens in the world,was significantly reduced by Si addition (Table 3).

Many pathogenicF.oxysporumspp.can infect the roots through penetration hyphae (Rodríguez-Gálvez and Mendgen 1995;Bao and Lazarovits 2001;Olivainet al.2006;Michielse and Rep 2010) and bring more wounds in the root,whileR.solanacearumonly infects the rootviawounds caused by various agents such as nematode,insect,and microbe (McGarveyet al.1999).Therefore,Si inhibitedF.oxysporummay lead to a reduction of root’s wounds which increases the difficulty ofR.solanacearuminfection.

Despite previous studies suggest thatPseudomonasspp.is involved in the biological control of soil-borne pathogens(Fridlenderet al.1993;Garbevaet al.2004;Couillerotet al.2009),but a lower abundance ofPseudomonaswas observed under Si addition in this study (Fig.6-A).Also,Si-added treatment resulted in a lower abundance of a OTU with 99% similarity toPseudomonas stutzeriA1501 strain(Table 3).Pseudomonas stutzeriwas isolated from rice paddy soils in China (Yanet al.2008),and especially withnifandrnfgenes which were essential for nitrogen fixation and yield improvement (Desnoueset al.2003).Thus,suppression of nitrogen-fixing strain by Si may lead to the reduction in nitrogen supply in rhizosphere soil,and further decrease of pathogen infection risk in plants,while slightly decrease of N support is beneficial to reduce pathogen susceptibility (Lacroixet al.2014;Ninget al.2017).

More interesting,we found that Si-added treatments showed a lower abundance ofFaecalibacterium(Fig.6-A),and an OTU with 99% similarity to theFaecalibacterium prausnitziistrain ATCC 27768 (Table 3).Faecalibacterium prausnitziiis regarded as one of the most abundant bacteria in the human intestinal microbiota of healthy adults,representing more than 5% of the total bacterial population (Miquelet al.2013).Some studies characterizedF.prausnitziias an anti-inflammatory bacteria and important factor in balancing immunity in the intestine (Sokolet al.2008,Miquelet al.2013,Heinkenet al.2014).As far as we know,our study is the first to report that Si can suppressF.prausnitziiin the soil.However,whether the lower abundance ofF.prausnitziiis associated with the reduction of bacterial wilt is unknown.

These results raise the question of how Si regulate soil microbial community,especially soil-borne pathogens.Our previous study provides some evidences,showing Si can induce the secretion of organic acid in the root,including citric acid,fumaric acid,and malic acid (Fan 2016),which have a significant influence on soil microbes(Haicharet al.2008;Wuet al.2015).Moreover,we found total 63.7% bacterial OTUs and 43.8% fungal OTUs were regulated by Si addition regardless of the presence of tomato plants (Fig.3),suggesting that Si had a direct effect on soil microorganism,which was independent on the plant.However,the mechanism of Si on soil microbe is unknown.Here,we present two possible explanations.First,plant available Si occurs mainly as monosilicic acid (Si(OH)4) in soil solution (Epstein 1994) which may buffer the environmental pH in the rhizosphere as an amphoteric hydroxide,and lead to directly affect the microorganism associate with plant root.Second,our recent study showed that Si had direct bioactivity onR.solanacearum,transcriptome and qPCR analyses demonstrated that some key virulence-related genes ofR.solanacearumsuch asphcA,xpsRandepsDwere significantly down-regulated by Siin vitro(Lin 2017),which provides the evidence that Si has the bioactivity to microbe.

5.Conclusion

Our study clearly demonstrated that exogenous Si did not directly inhibitR.solanacearumin soil,but changed soil bacterial community composition and structure at the genus level by reducing the relative abundance of soilborne pathogensFusariumspp.,which may provide a new perspective to decipher the mechanism of Si-enhanced plant resistance against soil-borne pathogen.

Acknowledgements

This study was financially supported by grants from the National Natural Science Foundation of China (31370456),the Doctoral Foundation of the Ministry of Education of China (20124404110007),the Natural Science Foundation of Guangdong Province of China (S2012010010331 and 2017A030313177),and the Project of International,as well as Hong Kong,Macao &Taiwan Science and Technology Cooperation Innovation Platform in Universities in Guangdong Province,China (2014KGJHZ004).

Appendicesassociated with this paper can be available on http://www.ChinaAgriSci.com/V2/En/appendix.htm