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Article

Organic or Inorganic Amendments Influence Microbial Community in Rhizosphere and Decreases the Incidence of Tomato Bacterial Wilt

by
Sai Wang
1,†,
Zhanbing Bai
2,†,
Zhuo Zhang
3,†,
Jingjing Bi
1,
Enzhao Wang
1,
Miaomiao Sun
1,
Bismark Asante-Badu
1,
Jiayin Zhang
1,
Marie Claire Njyenawe
1,
Alin Song
1,* and
Fenliang Fan
1,*
1
Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2
Hunan Vegetable Research Institute, Hunan Academy of Agricultural Science, Changsha 410000, China
3
Key Laboratory of Pest Management of Horticultural Crops of Hunan Province, Hunan Plant Protection Institute, Hunan Academy of Agricultural Science, Changsha 410000, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally.
Agronomy 2022, 12(12), 3029; https://doi.org/10.3390/agronomy12123029
Submission received: 14 October 2022 / Revised: 18 November 2022 / Accepted: 28 November 2022 / Published: 30 November 2022
(This article belongs to the Special Issue Advances in Molecular Technologies on Plant Disease Management)
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Abstract

:
There are many kinds of soil amendments that consist of different materials. The soil amendment is usually of benefit to plant health. However, the effects of the soil amendments on plant disease have rarely been compared and the involved mechanisms are largely unknown. In the present study, we investigated the influences of five contrasting soil amendments (i.e., potassium silicate (PS), calcium silicate (CS), biochar (BC), calcium silicate humic acid (SCHA), and bio-organic fertilizer (BOF)) on tomato bacterial wilt. In addition, we dissected the mechanism with high-throughput sequencing. The results showed that BC, SCHA, and BOF significantly reduced the incidence and delayed the disease, while BOF significantly reduced the incidence of bacterial wilt disease in the whole tomato growing period. In the early stage of the disease, BC, SCHA, and BOF significantly reduced the soil pH compared to CK. However, the contents of soil NH4+-N and NO3−-N were significantly increased. Some beneficial bacteria genera (Burkholderia, Mortierella, and Trichoderma) had a certain correlation with the incidence. Burkholderia and Mortierella were negatively associated with morbidity, but Trichoderma was positively associated with morbidity. Particularly, the Spearman correlation and the least partial squares path analysis indicated that Trichoderma was significantly positively correlated with the disease incidence, the soil physicochemical properties, and the numbers of soil pathogens (NSP) were significantly positively correlated with the number of root pathogens (NRP) and the physicochemical properties of plants were negatively correlated with the disease incidence. Moreover, BOF had better inhibitory effect on the occurrence of tomato bacterial wilt. Our results have implications for the better integrated management of tomato bacterial wilt.

1. Introduction

Agrochemical usage has served as one of the most important agronomic practices for increasing crop yield and sustainability; however, the overuse of agrochemicals is detrimental to soil health and causes environmental challenges [1]. Additionally, the high-intensity in intensive agricultural production and the planting of a single crop for many years has resulted in soil acidification and an imbalance of soil nutrient content. Unreasonable fertilization measures lead to the occurrence of soilborne disease. The issue is now seriously challenging to sustainable development, food safety, and environmental protection in China, which bring about huge economic losses in crop production. In particular, bacterial wilt, caused by Ralstonia solanacearum, is a bacterial soilborne disease that is commonly observed among Solanaceous crops [2], which causes a significant reduction in crop yield and quality. Therefore, the amelioration of bacterial wilt in soil is an urgent and vital task to reduce its morbidity in soils, sustain healthy crops, and increase crop yield. Several remediation techniques including physical and chemical prevention and control techniques have been developed and studied [3,4,5].
Several studies have shown that a variety of soil control measures have a significant impact on the prevention and control of bacterial wilt. For example, in a certain range of soil acidity (pH 5.0–6.5), the disease index of bacterial wilt in tomato was significantly positively correlated with pH, and the onset time was significantly negatively correlated with soil pH [6]. The research of Bi et al. (2022) showed that a high-concentration of nitrogen fertilizer would aggravate the occurrence of tomato bacterial wilt [7]. After inoculation with R. solanacearum, the content of SA and JA in the roots increased. The application of potassium fertilizer can promote the healthy growth of plants and effectively reduce the occurrence of crop diseases [8]. Hence, He Xin et al. (2017) found that increasing the potassium nutrient concentration could reduce the incidence of tomato bacterial wilt through hydroponic experiments [9]. Studies have also shown that within a certain concentration range, a high-concentration of calcium can increase the content of hydrogen peroxide in tomato plants, thus increasing the activities of peroxidase and polyphenol oxidase, and significantly reducing the incidence index of tomato bacterial wilt [10]. Additionally, silicon (Si) application has a significant inhibitory effect on tomato bacterial wilt. Si can change the tissue structure of the cell wall by enhancing the mechanical strength of the cell wall and hindering the infection of pathogenic bacteria. It can also promote the accumulation of phenolic substances and lignin and improves disease resistance in plants. Si can also regulate tomato bacterial wilt by altering the enzyme activity in the soil and increasing the number of bacteria and actinomycetes in the soil [11].
Biochar (BC) is a low-density, porous, and organic carbon (C)-rich material derived from the pyrolysis of waste biomass. Research studies have shown that the application of BC in soil can alleviate plant diseases caused by soilborne pathogens and significantly reduce the incidence of bacterial wilt. BC can inhibit the swimming ability of R. solanacearum and reduce the number of R. solanacearum colonized in the tomato rhizosphere, thereby reducing the incidence of bacterial wilt [12]. Gao et al. (2019) showed that the soil bacterial community structure transferred by BC was beneficial to improve the resistance of bacterial wilt in tomato plants [13]. Recent studies have shown that bio-organic fertilizers can adjust the soil microbial community structure by increasing the soil microbial diversity, improving the soil micro-ecological environment, which makes it develop in a healthy direction, thereby reducing the occurrence of crop diseases to a certain extent [14].
The interaction between soil microorganisms and soil and plants plays an important role in regulating the process of ecosystems [15,16]. Many researchers have reported that soil microbes are the most vital environmental indicators of soil quality [17,18,19]. They maintain the biological activities of soils, and benefit soil nutrient cycling and inhibit pathogen activity. Previous reports have revealed that some amendments control soilborne disease by stimulating the growth of beneficial microorganisms [20,21]. Thus, microbial community diversity in soils can be a vital indicator of the effect of specific remediation techniques on soil microorganisms and health. However, the underlying mechanism of soil regulation on the soil physicochemical properties, microbial community structure, and number of pathogens remains unclear.
Bacterial wilt in tomato is one of the most serious bacterial diseases that endanger agricultural production [22,23]. Bacterial wilt caused by Ralstonia solanacearum infection is a serious threat to the development of the world tomato production industry [24]. Tomato is one of the most cultivated fruit vegetables in the world, and hence this industry has become one of the most important industries to increase farmers income. Therefore, the effective prevention and control of bacterial wilt in tomato is still a major theoretical and technical issue related to the sustainable development of the world tomato industry [25]. This paper describes the effect of PS, CS, BC, SCHA, and BOF on the incidence of tomato bacterial wilt and the involved mechanism using real-time quantitative PCR and MiSeq high-throughput sequencing technology. The objectives of this study were to: (1) assess the influence of PS, CS, BC, SCHA, and BOF ameliorators on the soil physical and chemical properties; (2) examine the amelioration effect of five amendments on the incidence of tomato bacterial wilt; and (3) explore the potential interaction of five different ameliorators with soil microorganisms. This study provides technical support for selecting appropriate soil control measures for tomato bacterial wilt prevention and control.

2. Materials and Methods

2.1. Materials

The experimental site was at the experimental base of the Vegetable and Flowers Institute of Hunan Academy of Agricultural Sciences, Changsha City, Hunan Province (28°28’ N, 113°20’ E). The area has a subtropical monsoon climate, with an annual average temperature of 17.2 °C, an annual accumulated temperature of 5457 °C, and an average annual precipitation of 1361.6 mm. The soil type is Hortic soil, and the basic physical and chemical properties of the soil are as follows: pH 4.85; total nitrogen 1.40 g/kg; soil available phosphorus 420.56 mg/kg; soil available potassium 366.69 mg/kg; organic matter 22.75 g/kg.

2.2. Experimental Design

2.2.1. Tomato Seedlings and Transplanting

The tomato variety is moderately susceptible with the variety number 20B861. The surface of tomato seeds was disinfected with 3% sodium hypochlorite solution for 5 min, then washed with sterile water four times, placed in a Petri dish with moist filter paper, and placed in an incubator at 25 °C for 2 d. The germinated seeds were sown into the plug trays (or sterilized seedling substrates), and the seedlings were raised in an incubator. The light conditions of the incubator were 14 h·d−1, and the light intensity was 200 μmol·m−2·s−1. Day and night temperature was 28 °C/25 °C and the relative humidity was 80%. When the tomatoes reached three leaves, they were transplanted to the field trials.

2.2.2. Field Trial

A one-way factor randomized block design was used in this experimental design. This experiment was carried out at this site from April to July 2021. The loofah–tomato rotation mode has been previously used for planting, and the tomato planting season showed serious symptoms of bacterial wilt infection. The experiment was set up with six treatments, namely CK (without basal fertilizer), PS (potassium silicate 781.64 kg/ha), CS (calcium silicate 1563.28 kg/ha), BC (biochar 15,632.81 kg/ha), SCHA (calcium silicate humic acid, 1563.28 kg/ha), and BOF (bio-organic fertilizer, 7816.41 kg/ha). The main physicochemical properties of the soil amendments were showed in Table 1. Each treatment plot was 9.6 m2 (length × width = 6 m × 1.2 m), with fur replicates. Each experiment treatment was applied to the experimental plot half a month before transplantation by means of basal fertilizer. After the tomatoes were transplanted, it was watered regularly by using drip irrigation facilities to supplement water in the middle of the tomato plants. Top dressing was carried out regularly, and twice at the beginning of planting to flowering, with 5.0–7.5 kg Huangbo No. 1 special fertilizer application per mu per time ((N-P2O5-K2O = 22-12-16)+TE+BS, TE refers to the chelated trace elements, BS refers to plant stimulants such as potassium alginate, plant antibacterial protein, etc.). The interval between top dressing was about 10 days. During the flowering to harvest stages, 7.5–10.0 kg of Huangbo No. 2 special fertilizer (N-P2O5-K2O = 19-6-25+TE+BS) was applied per mu each time, with top dressing once every 10 days. The plant phenotype was observed weekly during the tomato growth process, and the incidence of bacterial wilt was recorded.

2.2.3. Tomato Plant and Soil Sample Collection

Before the onset of tomato bacterial wilt (46 d after transplanting), we collected the fourth functional leaf, root, and rhizosphere soil of tomato plants. The fourth functional leaf, root, and rhizosphere soil of the diseased tomato plants were collected at the early stage (62 d after transplanting) and at the later stage (82 d after transplanting), respectively. The leaves of the plant were stored at 4 °C and sent to the laboratory for drying to determine the physical and chemical properties of the plant. Excess soil around the roots of the plants were shaken off, placed in a Ziplock bag, stored on dry ice and transported to the test, washed with deionized water, and stored in a −20 °C refrigerator for later use. After mixing, the soil samples were transported to the laboratory with dry ice and divided into 2 parts. One part was placed in a −20 °C refrigerator for further analysis. Another portion of soil was air-dried and sieved for the determination of the soil physicochemical properties.

2.2.4. Determination of Physical and Chemical Properties of Soil and Plants

For the determination of the soil and plant physicochemical properties, refer to (Soil Agrochemical Analysis) [26]. Briefly, soil pH was measured by a glass electrode acidity meter (V (water):m (soil) = 5:1). Soil organic matter was measured by the K2Cr2O7 oxidation external heating method. Total N was determined by Kjeldahl distillation. Nitrate (NO3−) and ammonium (NH4+) were determined via colorimetry. Soil available phosphorus (AP) was extracted with 0.5 mol·L−1 sodium bicarbonate, and the molybdenum-antimony resistance colorimetric method was used for the determination. Soil available potassium (AK) was extracted with 1 mol·L−1 ammonium acetate and determined by flame photometer. Soil available silicon (ASi) was extracted with acetic acid buffer and determined by Si molybdenum blue colorimetry. Soil exchangeable calcium (AGa) was exchanged with 1 mol·L−1 ammonium acetate and determined by atomic absorption spectrometry. The total amount of N, P, and K in plants was digested with H2SO4-H2O2, and the determination method was the same as above. Molybdenum in plants is heated and leached with NaOH, and the ratio of the Si molybdenum blue to Si molybdenum blue color method. Calcium in plants was digested with nitric acid-perchloric acid and determined by atomic absorption spectrometry.

2.2.5. DNA Extraction and High-Throughput Sequencing

Soil and tomato root DNA were extracted using the FastDNA SPIN Kit for Soil Kit (MP Biomedicals, Santa Ana, CA, USA). The roots were ground into powder using a mortar and poured with liquid nitrogen before DNA extraction. Subsequently, the DNA quality was checked on 1% agarose gels, and its concentration and purity were checked on a NanoDrop 2000 microspectrophotometer (Thermo Fisher, Scientific, Waltham, MA, USA). The obtained DNA was stored at −20 °C for further molecular analysis.
Soil microbial community high-throughput sequencing was performed using bacterial 16S rRNA amplification primers (515F 5′-GTGCCAGCMGCCGCGGTAA-3′ and 806R 5′-GGACTACHVGGGTWTCTAAT-3′). Amplification was carried out in 50 μL solution containing 35.5 μL ddH2O, 5 μL 10 × buffer, 4 μL dNTP, 0.5 μL rTaq (TaKaRa), 2 μL forward primer, 2 μL reverse primer, and 2 μL DNA template. The PCR amplification procedure was as follows: pre-denaturation at 94 °C for 5min, followed by 30 cycles of denaturing at 94 °C for 45 s, annealing at 55 °C for 35 s, and extending at 72 °C for 45 s, with a final elongation at 72 °C for 10 min. The internal transcribed spacer (ITS) between the ribosomal protein genes were amplified using two rounds of PCR amplification. Primers for the first round PCR were ITS1F (5′CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2r (5′GCTGCGTTCTTCATCGATGC-3′). Amplification was carried out in 25 μL solution containing 18.25 μL ddH2O, 2.5 μL 10 × buffer, 2 μL dNTP, 0.25 μL rTaq (Takara), 0.5 μL forward primer, 0.5 μL reverse primer, and 1 μL DNA template. Thermal cycling conditions were as follows: pre-denaturation at 94 °C for 5 min, followed by 20 cycles of denaturing at 94 °C for 40 s, annealing at 55 °C for 30 s, and extending at 72 °C for 40 s, with a final elongation at 72 °C for 10 min. Primers for the second round amplification were ITS1 (5′CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2 (5′GCTGCGTTCTTCATCGATGC-3′), each with a unique 10-bp barcode. Second round PCR was carried out in a 50 μL mixture containing the 36.5 μL ddH2O, 5 μL 10 × buffer, 4 μL dNTP, 0.5 μL rTaq (Takara), 1 μL forward primer, 1 μL reverse primer, and 2 μL DNA template, which was from the first round of amplification. The thermal settings for the second round PCR were pre-denaturation at 94 °C for 5 min and 25 cycles of denaturing at 94 °C for 30 s, annealing at 55 °C for 40 s and extending at 72 °C for 40 s, with a final extension at 72 °C for 10 min. PCR fragments were checked via electrophoresis on 1% agarose gels. A Picogreen dsDNA Quantitation Kit was used to determine the concentration of PCR products. PCR products were purified using a DNA Purification Kit (Tiangen Technologies, Beijing, China).
The high-throughput sequencing data were processed according to the previous method to obtain high-quality sequences, and then the classification operation unit (OTU) clustering was performed with a 97% similarity level [27]. Chimeras in the sequences were filtered with UCHIME and the sequence analysis was performed by the USEARCH package [28]. The sequences were deposited at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under the accession number SRR 21951488.

2.2.6. Ralstonia Solanacearum Quantitative PCR

The specific amplification of R. solanacearum was carried out using RSR/RSF (5′-GACGCCACCCGCATCCCTC-3′/5′-GTGCCTGCCTCCAAAACGACT-3′), and the plasmid containing the full-length Escherichia coli 16S and R. solanacearum RSR/RSF gene was diluted 108-101, and the ABI 7500 fluorescence quantitative PCR instrument was used to make a standard curve according to the standard procedure. Amplification conditions were: 7.5 μL SYBR® Premix Ex Taq, 0.5 μL upstream and downstream primers, 0.3 μL ROX Reference Dye, 2 μL template DNA, and 4.2 μL ddH2O. The PCR amplification program was as follows: pre-denaturation at 95 °C for 3 min, 40 cycles of denaturing at 95 °C for 30 s, annealing at 62 °C for 30 s, and extension at 72 °C for 30 s. All samples were replicated three times and ddH2O was used instead of the DNA template to set as the negative control. According to the Ct value of each sample, the number of copies contained in each gram of soil was calculated and converted into the number of copies formed per gram of dry soil, and the logarithmic value was taken, which was expressed as log (copies/g dry soil).

2.3. Statistical Analysis

The experimental data were statistically analyzed using Microsoft Excel 2019, SPSS 28, and R (4.1.2). One-way analysis of variance (ANOVA) was performed using the LSD test for multiple comparison (p < 0.05). Spearman correlation analysis was performed using the “psych” package in R. The high-throughput sequencing data of soil microorganisms were analyzed by the “vegan” package in R for community structure analysis, and the partial least squares path analysis modeling (PLS-PM) was completed by the “plspm” analysis in R. The plotting software used included Microsoft Excel 2019 and the “pheatmap” and “ggplot2” packages in R.

3. Results

3.1. Effects of Different Soil Control Measures on the Incidence of Tomato Bacterial Wilt

The results revealed that at transplanting 62 d and 82 d, there was significantly high evidence of tomato bacterial wilt incidence in all treatments, however, with the application of CS, the incidence of bacterial wilt in the other treatments was lower compared to CK (Figure 1). In the early stage of the disease (62 d), the morbidity of the treatment with BC, SCHA, and BOF was significantly lower than CK. In the late stages of the disease (82 d), the incidence of bacterial wilt in the PS, BC, and SCHA treatments were all lower than CK, but not significant. However, only BOF treatment had a significant lower incidence of tomato bacterial wilt compared to CK. It was also observed that in the early stage of the disease, BC, SCHA, and BOF treatments could significantly reduce the incidence and delay the disease, but with the development of the disease, only BOF had a better inhibitory effect (Figure 1).

3.2. Quantity of R. solanacearum in Soil and Roots

Generally, the number of R. solanacearum in the soil was significantly lower than that in the root. Before the onset (46 d), there was no significant difference in the number of R. solanacearum in the different treatments. In the early stages of the disease (62 d), the number of R. solanacearum in the tomato root with CS was significantly lower than that in the CK (Figure 2B). Similarly, in the soil, the number of R. solanacearum in the SCHA and BC was significantly lower than that in the CK (Figure 2A). In the late stages of the disease (82 d), there was no significant difference in the number of R. solanacearum among the treatments. It was observed that in the early and middle stages of the onset of bacterial wilt, the soil treated with CS, BC, and SCHA had a certain inhibitory effect on tomato bacterial wilt.

3.3. Variance Analysis of Disease Incidence and Soil Physicochemical Properties among Different Treatments, Spearman Correlation Analysis of Physicochemical Properties, Morbidity, and Number of Pathogenic Bacteria

After 62 days of transplanting, the results of the variance analysis of each index in the different treatments showed that the disease incidence and pH of BC, SCHA, and BOF were significantly lower than those of CK (Table 2). The contents of NH4+-N and NO3−-N in the soil of each treatment were higher than those of the CK, and the NO3−-N content of the SCHA and BOF was significantly higher compared to the CK. There was no significant difference in the soil available phosphorus (AP) content. The soil available potassium (AK) content in the PS and SCHA was significantly higher than that in the CK. The soil available silicon (ASi) content in the CS was significantly higher than that in the CK. There was no significant difference in the soil available calcium (ECa) content between the treatments and CK.
The correlation analysis showed that the disease incidence was significantly positively correlated with soil pH at 62 days after transplanting, negatively correlated with NH4+-N and NO3−-N in soil, but significantly negatively correlated with NO3−-N (Figure 3). After 82 days of transplanting, the incidence of disease was also significantly negatively correlated with NH4+-N and NO3−-N in the soil. The soil water content was significantly positively correlated with the number of pathogenics in the soil

3.4. Soil and Root Microbial Community Structure

Results from the principal component analysis are presented in Figure 4A,B. It was observed that the microbial community structure of the soil and roots in the different sampling periods was significantly changed, and the root bacterial community, fungal community, and soil fungal community were well distinguished on the coordinate axis. In the microbial community, the variance contribution rates of the first principal component and the second principal component were 19.84% and 7.66%, respectively, and the cumulative variance contribution rate was 27.50% (Figure 4A). For the fungal community, the variance contribution rates of the first principal component and the second principal component were 67.15% and 5.7%, respectively, and the cumulative variance contribution rate was 72.85% (Figure 4B). The root microbial community at 46 d and 62 d after transplanting was clearly divided into two regions, and the soil fungal community structure was more distinct than the soil bacterial community, but at different periods. There were no significant differences between the soil and root microbial communities in all treatments.
The Shannon index of bacteria and fungi in the soil and roots between different treatments at different periods are shown in in Figure 5. The result reveals that the Shannon diversity index of microbial communities in soils in each period was higher compared to those in the root. However, the Shannon diversity index of bacterial communities in the soil and root was significantly different, with bacterial diversity in the soil and root being higher than that in fungi in each period. During days 46 and 62 of transplanting, the bacterial community diversity in the tomato roots with CS treatment was higher than those of other treatments, but not significant. There was no significant difference in the diversity of bacterial communities in the soil in each period. On days 62 and 82 of transplanting, it was observed that the fungal community of BOF had higher diversity than the other treatments.
Our result also reveals that at the bacterial phylum level (Figure 6A), the soil and root differed greatly in microbial composition and relative abundance. Among them, Proteobacteria had a higher abundance in each treatment. At 46 days after transplanting, the relative abundance of Acidobacteria in other treatments decreased compared to CK. The result demonstrates that at the fungal phylum level (Figure 6B), the relative abundance of fungi in the soil and root differed greatly. The relative abundance of Zygomycota was higher in the soil treatments with low disease incidence at 62 days after transplanting, whereas the relative abundance of Ascomycota was lower.
As shown in the relative abundance at the bacterial genus level (Figure 6C), on day 46 of transplanting, the acid bacteria genus Gp1 in CK had a higher abundance than the other treatments. In the early and middle stages of the disease, the Burkholderia of each treatment was negatively correlated with the incidence (Figure 6C). Unlike, on day 46, the relative abundance of Ralstonia in the soil and root at 62 d was significantly increased, however, compared to the CK, the relative abundance of Ralstonia in the other treatments was significantly reduced.
However, at the fungal genus level (Figure 6D), some unclassified Ascomycota gradually decreased in relative abundance with disease severity, whereas Mortierella in soil gradually increased in relative abundance with disease severity.

3.5. Correlation Analysis

After 82 days of transplanting (Figure 7), the Spearman correlation analysis of the physicochemical indices and disease incidence within the different treatments and the level of soil fungi showed that Trichoderma were significantly positively correlated with the disease incidence. Soil pH significantly correlated with the disease incidence as some unclassified Agaricales showed a significant positive correlation.
Additionally, the PLS-PM analysis of the total effect between the variables showed that the soil physicochemical properties and the number of soil pathogens (NSP) were significantly positively correlated with the number of root pathogens (NRP), and the correlation coefficient of NSP was the largest (0.635) (Figure 8). The physicochemical properties of plants were negatively correlated with the disease incidence, but there was no significant difference between the variables and the incidence (Figure 8).

4. Discussion

4.1. Effect of Amendments on Incidence of Tomato Bacterial Wilt, the Number of R. solanacearum and Chemical Factors in Soil and Plant Parts

Different amendments have different effects on the occurrence of tomato bacterial wilt (Figure 1 and Figure 2). In the early stage of the disease, BC, SCHA, and BOF could significantly reduce the incidence and delay the disease, while BOF could significantly reduce the incidence of bacterial wilt disease in the whole tomato growing period (Figure 1). In previous studies, the addition of Si to soil inoculated with blight in the current study significantly reduced the incidence of blight, but Si did not reduce the number of wilt bacteria in rhizosphere soils [29]. Calcium regulates the activity of superoxide dismutase, catalase, polyphenol oxidase, and other enzymes in plants, and can also regulate the content of salicylic acid and jasmonic acid in plants, thereby mediating plant autoimmune defense responses to resist the invasion of pathogenic bacteria [30,31,32]. Our finding revealed that Si can improve the resistance of plants to blight caused by bacteria wilt and enhance the immune response of plants. BC application in soil was beneficial for the healthy development of plants because it has the potential to reduce soil acidity, improve soil water, and fertilizer retention capacity [33] as well as increase the biomass and microbial diversity of indigenous bacteria [34]. The significantly low disease incidence in SCHA and BC in the pre-morbid period (62 days) and no effect at the late stage could be a result of higher nutrients in the soil or the different soil properties. The mechanism of the amendment-mediated plant resistance against plant diseases may stem from several mechanisms such as chemical agents, stimulating the nutrient uptake of plants, improving the soil properties, influencing the soil microbial communities, and inducing plant resistance [35,36,37].
Soil pH significantly positively correlating with the disease incidence, lower soil pH may cause a reduction in the incidence of bacterial wilt to a certain extent (Figure 3). Zhang et al. [38] found that the pH of healthy soil was significantly lower than that of diseased soil. Some studies have shown that the optimal pH for the onset of tomato bacterial wilt is 6.4 [39], which is similar to the results in this study (Table 2). Nitrogen is the main component of protein, plays an important role in plant growth and fruit development, and is the nutrient element most closely related to yield. Studies have found that the lack of soil N will significantly increase the probability of plant diseases [40]. Nitrogen affects the resistance of plants to diseases, for instance, N deficiency can increase the susceptibility of tomato to Fusarium oxysporum [41]. In this study, the NH4+-N and NO3−-N in the soil were significantly negatively correlated with the incidence of bacterial wilt, and an appropriate increase in soil inorganic N content could indicate a reduction in the incidence of bacterial wilt.
Numerous studies have shown that the application of BOF can significantly reduce the incidence of tomato soilborne diseases and promote healthy plant growth [42,43,44]. In our study, the number of R. solanacearum in the soil or root with BOF addition was lower than that in CK (Figure 2). These results may be caused by bio-fertilizer application that improved the physical and chemical properties of the soil by providing a variety of plant nutrients such as an increase in the organic matter content, N, P, K availability, and trace elements in the soil (Table 2, Figure 3). Additionally, the bio-fertilizers improved the soil’s ability to retain water and fertilizer and reduce disease symptoms caused by bacterial wilt. This may be in line with previous studies where the application of bio-organic fertilizers can regulate the soil microbial community and affect the occurrence of soilborne diseases [45,46].

4.2. Effect of Amendments on Microbial Diversity in Rhizosphere Soil and Root

The soil microbial community structure plays an important role during plant growth as plants can benefit from different microbial communities [47]. The soil/root bacterial community and fungal community could be well separated on the coordinate axis (Figure 4). Plants were infected with bacterial wilt, and the rhizosphere soil microbial community was altered [48]. The microbial community structure of different sampling periods and treatments had obvious differences in this study (Figure 5). Studies have shown that the richer the soil microbial community structure and the higher the diversity, the stronger the comprehensive ability against pathogenic bacteria [49,50], implying that the high diversity of rhizosphere soil bacteria can inhibit the occurrence of soilborne diseases [51]. Shen et al. [25] found that the Shannon diversity index of bacterial community in healthy tomato rhizosphere soil was higher, which also confirmed the positive correlation between bacterial diversity and ecosystem productivity. However, in this study, the microbial diversity of the BOF with low incidence was not significantly different from other treatments (Figure 5), which may be related to the higher N, P, K, and other nutrients in the soil (Table 2). Higher nutrients in the soil allow microorganisms to obtain more nutrients, making them more numerous and more complex in community structure [52].
Studies have shown that Proteobacteria is the most abundant and dominant in the bacterial community of tomato rhizosphere soil [25,53], which was also reflected in this study (Figure 6A). In the fungal community analysis of this study, Ascomycota and Zygomycota were the most dominant (Figure 6B), which conforms to the results of Xiang et al. [54]. Ren et al. [55] found that the relative abundance of Ascomycota in the root perimeter soil of infection with Withering increased, whereas the relative abundance of Zygomycota was significantly reduced. Interestingly, after 62 days of transplanting, the relative abundance of Ascomycota in soil with a high incidence increased, and the relative abundance of Zygomycota decreased. The relative abundance of Mortierella and Zygomycota were consistently correlated (Figure 6A,B).
The occurrence of crop diseases is closely related to indigenous beneficial genus. Mortierella has the effect of promoting plant growth [56] and can also inhibit the occurrence of tomato bacterial wilt disease [57]. Trichoderma can remodel the rhizosphere, and is highly aggressive to plant pathogens and can promote plant growth [58]. A study found that the relative abundance of the indigenous beneficial bacteria Mortierella and Trichoderma in the rhizosphere within soil significantly reduced the occurrence of bacterial wilt [59]. In this study, the relative abundance of Mortierella with the addition of BOF was higher and positively correlated with the disease incidence, but the relative abundance of Mortierella gradually increased with the development of the disease (Figure 7). This suggests that bio-organic fertilizers can adjust the soil microbial community and increase the relative abundance of beneficial microorganisms to antagonize pathogenic bacteria, thereby reducing the incidence of disease. However, the relative abundance of Trichoderma being significantly positively correlated with the disease incidence could demonstrate that the number of Trichoderma increased along with the proliferation of pathogenic bacteria to resist the invasion of pathogenic bacteria. In addition, studies have shown that the relative abundance of Burkholderia with a growth-promoting effect is reduced in soil with bacterial wilt disease [60]. In roots infected with Cirtus Huanglongbing, the number of Burkholderia was higher than that of healthy trees [61]. However, in this study, the Burkholderia was negatively correlated with the disease incidence in each treatment in the early and middle stages of the disease, which may result from different crops or different species of Burkholderia in the soil, of which some are good for crops, while others are harmful.

4.3. Effect of Amendments on the Interaction between Soil Microbes and Tomato Bacterial Wilt

Soil amendments can improve the soil physicochemical properties and have a positive impact on microorganisms, so that the soil micro-ecological environment develops in a healthy direction, thereby inhibiting the development of diseases and improving the soil productivity [11,21]. Xiong et al. found that bio-organic fertilizers could induce the soil inhibition of wilt by remodeling soil microbial communities [62], and Deng et al. [63] showed that long-term application of bio-organic fertilizers produced inhibitory rhizosphere soil bacterial communities, where inhibitory action was caused by changes in the rhizosphere soil bacterial community composition and not only by the abundance of introduced biocontrol strains. However, in this study, the soil microbial community regulated by the bio-organic fertilizer did not change significantly, which may be due to the single application of the bio-organic fertilizer (applied as basal fertilizer) at the experimental site, which could not induce good induction. This effect may only appear after several seasons of continuous application.
There are complex interactions between soils, plants, and microorganisms, which together influence the disease incidence. The invasion of pathogenic bacteria can affect the composition and function of soil microbial community, change the soil micro-ecological environment, and then affect the health and growth of plants. In this study, PLS-PM was used to analyze the relationship between various factors and their impact on the incidence (Figure 8). There was a negative correlation between the soil, plant, and microbial indicators and the incidence. This suggests a significant positive correlation between the soil physicochemical properties and the number of pathogenic bacteria in soil and incidence, indicating that some indicators of soil, plants, and microorganisms may have a certain inhibitory effect on the incidence of plant diseases and the number of pathogenic bacteria. Through the reasonable regulation of soil physicochemical properties and microbial community by soil conditioners, the soil is in the best state of disease suppression, which will help to inhibit the disease occurrence and spread of bacterial wilt.

5. Conclusions

This study revealed that the incidence of tomato bacterial wilt was significantly reduced in the soil regulated by a bio-organic fertilizer. However, the effect of other organic amendments on the microbial community and the number of pathogenic bacteria in the tomato rhizosphere soil was not significant. We also found that the soil physicochemical properties and some beneficial genus were highly correlated with the disease incidence. Soil pH was significantly positively correlated with the incidence, but soil NH4+-N and NO3−-N were significantly negatively correlated with the incidence. Mortierella and Burkholderia were negatively associated with the incidence, but Trichoderma was positively associated. In addition, the soil physicochemical properties and soil pathogen quantity had a significant impact on the root pathogen quantity, and soil and plant physicochemical properties had a greater impact on the disease incidence.

Author Contributions

S.W.: Data curation, Writing-Original draft preparation. Z.B.: Investigation. Z.Z.: Investigation. J.B.: Data curation. E.W. and M.S.: Methodology. B.A.-B.: Review. J.Z.: Software. M.C.N.: Reviewing. A.S.: Review and editing. F.F.: Management of the experiments, Supervision, Reviewing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key Research and Development Program of China (2021YFD1901004, 2021YFF1000404, 2019YFD1002000); The Agricultural Science and Technology Innovation Program (ASTIP No. CAAS-ZDRW202202); the Fundamental Research Funds for Central Non-profit Scientific Institution (Nos. 1610132019011, 1610132020012); and the Zaozhuang Talents Gathering Project.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author, upon reasonable request.

Acknowledgments

The work of guidance on Bacterial wilt in tomato was supported mainly by Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China. We are grateful to Shidong Li technical assistance.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Incidence of tomato bacterial wilt with different treatments on 62 d and 82 d after transplanting. Different letters represent significant differences among different treatments at the same transplanting. Bars indicate standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Figure 1. Incidence of tomato bacterial wilt with different treatments on 62 d and 82 d after transplanting. Different letters represent significant differences among different treatments at the same transplanting. Bars indicate standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
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Figure 2. The number of R. solanacearum in the soil (A) and roots (B) of different treatments at 46 d, 62 d, and 82 d. Different letters represent significant differences among different treatments at the same transplanting. Bars indicate the standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Figure 2. The number of R. solanacearum in the soil (A) and roots (B) of different treatments at 46 d, 62 d, and 82 d. Different letters represent significant differences among different treatments at the same transplanting. Bars indicate the standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
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Figure 3. Spearman correlation analysis of the physicochemical properties [SMC (soil moisture content), AN (ammonia nitrogen), NN (nitrate nitrogen), AP (available phosphorus), AK (available potassium), ASi (available silicon), ECa (effective calcium), TN (total nitrogen), TP (total phosphorus), TK (total potassium), TSi (total silicon), TCa (total calcium), NSP (number of soil pathogens), NRP (number of root pathogens)] morbidity and number of pathogenic bacteria of different treatments at 62 d (A) and 82 d (B) after transplanting. p * < 0.05, p ** < 0.01.
Figure 3. Spearman correlation analysis of the physicochemical properties [SMC (soil moisture content), AN (ammonia nitrogen), NN (nitrate nitrogen), AP (available phosphorus), AK (available potassium), ASi (available silicon), ECa (effective calcium), TN (total nitrogen), TP (total phosphorus), TK (total potassium), TSi (total silicon), TCa (total calcium), NSP (number of soil pathogens), NRP (number of root pathogens)] morbidity and number of pathogenic bacteria of different treatments at 62 d (A) and 82 d (B) after transplanting. p * < 0.05, p ** < 0.01.
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Figure 4. Principal component analysis (PCOA) of the soil and root bacterial community (A) and fungal community (B) structure between different treatments at different periods (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Figure 4. Principal component analysis (PCOA) of the soil and root bacterial community (A) and fungal community (B) structure between different treatments at different periods (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
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Figure 5. The Shannon index of the soil and root bacteria (A) and fungi (B) among different treatments at different periods. Different letters represent significant differences among different treatments at the same compartment. Bars indicate standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Figure 5. The Shannon index of the soil and root bacteria (A) and fungi (B) among different treatments at different periods. Different letters represent significant differences among different treatments at the same compartment. Bars indicate standard error (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
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Figure 6. Relative abundance at the bacterial phylum level (A), bacterial genus level (B), fungal phylum level (C), and fungal genus level (D) among the different treatments (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Figure 6. Relative abundance at the bacterial phylum level (A), bacterial genus level (B), fungal phylum level (C), and fungal genus level (D) among the different treatments (n = 4). Amendment treatments include CK (no fertilization); PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
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Figure 7. The Spearman correlation analysis of the physicochemical indices (AN, NN, AP, AK, ASi, ECa, TN, TP, TK, TSi, TCa, NSP, NRP) and disease incidence of different treatments at 62 d (A) and 82 d (B) of transplanting and the soil microbial genera level. p * < 0.05, p ** < 0.01.
Figure 7. The Spearman correlation analysis of the physicochemical indices (AN, NN, AP, AK, ASi, ECa, TN, TP, TK, TSi, TCa, NSP, NRP) and disease incidence of different treatments at 62 d (A) and 82 d (B) of transplanting and the soil microbial genera level. p * < 0.05, p ** < 0.01.
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Figure 8. The least partial squares path analysis between the soil microbial community, soil and plant physicochemical properties (SMC, AN, NN, AP, AK, ASi, ECa, TN, TP, TK, TSi, TCa), soil and root pathogen numbers (NSP, NRP), and disease incidence. Solid lines represent significant correlations and dashed lines represent insignificant ones. Red lines represent negative interactions between two nodes, while blue lines represent positive interactions. p * < 0.05, p ** < 0.01.
Figure 8. The least partial squares path analysis between the soil microbial community, soil and plant physicochemical properties (SMC, AN, NN, AP, AK, ASi, ECa, TN, TP, TK, TSi, TCa), soil and root pathogen numbers (NSP, NRP), and disease incidence. Solid lines represent significant correlations and dashed lines represent insignificant ones. Red lines represent negative interactions between two nodes, while blue lines represent positive interactions. p * < 0.05, p ** < 0.01.
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Table
Table 1. The main physicochemical properties of the soil amendments.
Table 1. The main physicochemical properties of the soil amendments.
SampleTN
g·kg−1		TP
g·kg−1		TK
g·kg−1		pHSOM
g·kg−1		ASi
g·kg−1
PS--631.67 ± 0.3312.07 ± 0.02 185.86 ± 1.41
CS2.89 ± 0.091.04 ± 0.032.94 ± 0.6910.72 ± 0.12108.24 ± 0.858.57 ± 0.41
BC9.33 ± 0.932.97 ± 0.0117.47 ± 0.129.96 ± 0.05138.78 ± 5.080.46 ± 0.01
SCHA3.27 ± 0.470.27 ± 0.0162.80 ± 0.659.52 ± 0.0697.84 ± 0.430.58 ± 0.02
BOF29.87 ± 3.3714.24 ± 0.037.57 ± 0.524.68 ± 0.15380.13 ± 8.390.20 ± 0.02
Note: Total nitrogen (TN), total phosphorus (TP), total potassium (TK), available silicon (ASi). PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer).
Table
Table 2. The variance analysis of disease incidence and the soil physical and chemical properties in different treatments at 62 days after transplanting.
Table 2. The variance analysis of disease incidence and the soil physical and chemical properties in different treatments at 62 days after transplanting.
TreatmentIncidence
(%)		pHNH4+-N
(mg/kg)		NO3−-N
(mg/kg)		AP
(mg/kg)		AK
(mg/kg)		ASi
(mg/kg)		ECa
(cmol/kg)
CK30.00 ± 5.31a4.77 ± 0.11a21.00 ± 7.81b64.09 ± 23.78b400.20 ± 14.50a477.36 ± 40.56c30.45 ± 3.07b3.95 ± 0.26ab
PS27.50 ± 2.63a4.45 ± 0.11abc45.10 ± 14.82ab110.76 ± 30.30ab577.80 ± 20.94a656.88 ± 43.98ab52.08 ± 10.06b3.03 ± 0.43b
CS36.00 ± 8.45a4.59 ± 0.06ab33.29 ± 11.88ab84.54 ± 34.53ab594.98 ± 61.56a502.10 ± 40.78c187.12 ± 85.11a4.04 ± 0.58ab
BC12.75 ± 1.65b4.22 ± 0.13c47.50 ± 14.61ab93.85 ± 28.54ab539.29 ± 64.82a538.56 ± 24.88bc39.53 ± 11.31b2.47 ± 0.32b
SCHA13.25 ± 4.66b4.31 ± 0.12bc72.55 ± 12.35a180.15 ± 44.36a454.41 ± 122.32a781.07 ± 74.84a32.38 ± 1.92b4.81 ± 1.05a
BOF9.00 ± 0.07b4.46 ± 0.12bc55.21 ± 18.31ab176.78 ± 34.56a404.37 ± 50.21a503.37 ± 26.68c26.97 ± 1.92b3.60 ± 0.27ab
Note: Different letters represent significant differences between mean. Control (CK), PS (potassium silicate); CS (calcium silicate); BC (biochar); SCHA (calcium silicate humic acid); BOF (bio-organic fertilizer); available phosphorus (AP), available potassium (AK), available silicon (ASi), available calcium (ECa).
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Wang, S.; Bai, Z.; Zhang, Z.; Bi, J.; Wang, E.; Sun, M.; Asante-Badu, B.; Zhang, J.; Njyenawe, M.C.; Song, A.; et al. Organic or Inorganic Amendments Influence Microbial Community in Rhizosphere and Decreases the Incidence of Tomato Bacterial Wilt. Agronomy 2022, 12, 3029. https://doi.org/10.3390/agronomy12123029

AMA Style

Wang S, Bai Z, Zhang Z, Bi J, Wang E, Sun M, Asante-Badu B, Zhang J, Njyenawe MC, Song A, et al. Organic or Inorganic Amendments Influence Microbial Community in Rhizosphere and Decreases the Incidence of Tomato Bacterial Wilt. Agronomy. 2022; 12(12):3029. https://doi.org/10.3390/agronomy12123029

Chicago/Turabian Style

Wang, Sai, Zhanbing Bai, Zhuo Zhang, Jingjing Bi, Enzhao Wang, Miaomiao Sun, Bismark Asante-Badu, Jiayin Zhang, Marie Claire Njyenawe, Alin Song, and et al. 2022. "Organic or Inorganic Amendments Influence Microbial Community in Rhizosphere and Decreases the Incidence of Tomato Bacterial Wilt" Agronomy 12, no. 12: 3029. https://doi.org/10.3390/agronomy12123029

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