Plant Rhizosphere Growth-Promoting Bacterium with
Root-Knot Nematode Inhibition and Its Effect on the
Tomato Rhizosphere Microbial Community Structure

Jianfeng Du; Qixiong Gao; Zhaoyang Liu; Chaohui Li; Xin Song; Ruiping Xu; Yanyan Zhou; Yue Liu; Huying Li; Rui Zheng; Xunli Liu

Research Article

J Bacteriol Mycol. 2020; 7(8): 1159.

Plant Rhizosphere Growth-Promoting Bacterium with Root-Knot Nematode Inhibition and Its Effect on the Tomato Rhizosphere Microbial Community Structure

Jianfeng Du^1,2, Qixiong Gao¹, Zhaoyang Liu¹, Chaohui Li¹, Xin Song¹, Ruiping Xu¹, Yanyan Zhou¹, Yue Liu¹, Huying Li¹, Rui Zheng¹, Xunli Liu¹*

¹College of Forestry, Shandong Agriculture University, China

²State Key Laboratory of Crop Biology, Shandong Provincial Key Laboratory for Biology of Vegetable Diseases and Insect Pests, College of Plant Protection, Shandong Agricultural University, China

*Corresponding author: Xunli Liu, College of Forestry, Shandong Agriculture University, No. 61, Daizong Street, Taian, Shandong 271018, China

Received: November 17, 2020; Accepted: December 15, 2020; Published: December 22, 2020

Abstract

The purpose of this study was to evaluate the ability of Bacillus aryabhattai P-3 to control Meloidogyne incognita and its influence on the tomato rhizosphere microbial community. When the P-3 strain was used to treat the J2s of Meloidogyne incognita for 24 hours, the corrected mortality of the J2s of Meloidogyne incognita was 81.23%± 1.23b%. When the P-3 strain was used to treat the J2s of Meloidogyne incognita for 48 hours, the corrected mortality rate of the J2s of Meloidogyne incognita was 83.56%±2.56 % for in vitro tests. The P-3 was identified as Bacillus aryabhattai by 16srDNA and physiological biochemical tests. In the pot experiment, the control effect of Bacillus aryabhattai on Meloidogyne incognita was 41%. Bacillus aryabhattai P-3 was proven to control Meloidogyne incognita. MiSeq sequencing and bioinformatics analysis verified that the P-3 can change the composition of the microbial community in the tomato rhizosphere and reduce the number of plant pathogens, increase the complexity of the bacterial microbial community, and make the bacterial community structure more stable. The P-3 as the ability to control Meloidogyne incognita. Meanwhile, the P-3 can be developed as a microbial agent. This research hopes to contribute to the development of microbial inoculants. We demonstrated Bacillus aryabhattai P-3 efficacy and value to control Meloidogyne incognita. We also clarified the effect of Bacillus aryabhattai P-3 on tomato rhizosphere microbial community.

Keywords: PGPR; Meloidogyne incognita; Microbial Community; Microbial Inoculant

Introduction

Root-knot nematode disease is a common plant disease that seriously endangers world agricultural production [1] and affects many plants such as tomatoes [2]. It is mainly caused by Meloidogyne incognita [3]. The disease commonly occurs in tomato plants based in greenhouses and open fields [4]. Particularly in greenhouses, it may occur all the year-round, making it a serious threat to tomato production [5]. Root-knot nematode disease can decrease crop yields by 10%-20% that can reach more than 75% in severe cases [6]. With the continuous development of facility horticulture in China, the production area of vegetables grown in greenhouses is increasing. In China, Shandong Province is an important vegetable planting area especially for tomatoes [7,8]. Currently, the methods of controlling Meloidogyne incognita in agriculture mostly involve chemical control [9]. However, chemical control can lead to Meloidogyne incognita developing a resistance, which can also damage the ecological balance [10]. Some chemical pesticides can cause environmental pollution [11,12]. With the increase in awareness of environmental protection and increasing concern for food safety [13], strengthening the exploitation of microbial resources is of great significance for future agricultural production [14,15].

After years of research, many microbial resources have been screened for controlling Meloidogyne incognita, including fungi, bacteria, and actinomycetes. For example, Paecilomyces lilacinus is currently widely used in the agricultural field [16]. Rhizosphere bacteria are important to help the control of Meloidogyne incognita [17,18]. Studies have shown that many rhizosphere bacteria can control Meloidogyne incognita, such as Bacillus subtilis, Bacillus licheniformis, Bacillus megaterium, Bacillus coagulans, and Pseudomonas fluorescens [19]. Plant-growth-promoting rhizobacteria are important biological resources [20]. They can increase crop yields and help plants resist pathogenic microorganisms [21]. [22] Evaluated the effects of 662 rhizobacteria on Meloidogyne incognita and found Bacillus to be causing the highest Meloidogyne incognita mortality [22]. Bacillus can not only directly stimulate plant growth by enhancing nutrient acquisition or stimulating the host plant's defense mechanism but also by inhibiting the growth of pathogenic microorganisms [23]. Antoun demonstrated that approximately 2-5% of rhizobacteria can promote plant growth [24]. Moreover, growth, and single or multiple rhizosphere bacteria can control root-knot nematodes. A study shows that rhizobacterial can be used to prevent parasitic nematodes of grapevine [25]. A study used Phanerochaete chrysosporium to inhibit J2s and eggs of Meloidogyne incognita [26]. Liu identified Bacillus halotolerans, B. kochii, B. oceanisediminis, B. pumilus, B. toyonensis, B. cereus, Pseudomonas aeruginosa, and B. pseudomycoides as rhizobacteria effective at controlling Meloidogyne incognita [27]. Rhizosphere bacteria can also induce resistance in plants to Meloidogyne incognita [28]. The combination of Bacillus amyloliquefaciens and Bacillus subtilis strains can reduce the number of Meloidogyne incognita in the soil [29]. Studies have shown that rhizobacteria not only have the ability to control Meloidogyne incognita [30,31] but also have the ability to improve soil fertility [32] and reduce the number of plant pathogens in the soil [33,34]. Bacillus aryabhattai is an important component of rhizobacteria [35]. It can not only synthesize biological hormones or active organic matter but also promote plant growth [36]. For example, Bacillus aryabhattai AB211 can dissolve inorganic phosphate, synthesize iron carriers, and produce hormones such as Indole Acetic Acid (IAA) [37]. This species also controls root-knot nematodes. For example, Bacillus sneb517 controls Heterodera glycines through seed coating ichinohe to promote plant growth Bacillus aryabhattai SRB02 can increase the yield of crops such as rice and soybean [38]. At the same time, Bacillus aryabhattai can control plant pathogens in the soil. For example, Bacillus aryabhattai inhibits Pyricularia oryzae and Fusarium moniliforme to increase rice yield [36]. It is well known that the composition and function of microbial communities in the rhizosphere in soil play a vital role in the healthy growth of plants [39]. In the underground ecosystem, the soil rhizosphere microbial community is a key component, which can directly or indirectly affect the growth of plants and change the soil’s functional performance [40]. In fact, some studies have shown that rhizosphere bacteria are able to prevent and control soil-borne diseases and increase available phosphorus in the soil [41], but there are few studies investigating the effect of Bacillus aryabhattai on underground microbial communities. This study used Miseq sequencing technology and bioinformatics methods to comprehensively analyze and compare the microbial community composition of tomato rhizosphere. It is expected to contribute to the development of the microbial inoculum.

Materials and Methods

Determination of the effect of P-3 strain poisoning the J2s of Meloidogyne incognita

The P-3 strain was inoculated in Lysogeny Broth (LB) medium, cultured at 30^°C, 200 r/min in the dark for 48 hours, centrifuged at 1073 × g for 10 minutes, filtered through a 0.22 μm bacterial filter, and 0.8 mL of the filtrate was placed in a 1.5 centrifuge tube. One hundred J2s of Meloidogyne incognita were added to each centrifuge tube, and their corrected mortality was calculated at 24 hours and 48 hours. And each treatment had 9 duplicates.

Identification and phylogenetic analysis of the P-3 strain

According to the common bacterial system identification manual, the bacterial morphology and physiological and biochemical indicators of P-3 strains were measured [42]. The 16S rDNA fragment was amplified [43], and the sequencing results were analyzed with BLAST from the NCBI's GenBank database. The neighbor-joining phylogenetics were then analyzed with MEGA of multiple sequence homology [44].

Pot test

The tomato Micro-Tom of the tested variety was sown in a nursery tray, and when the tomato seedlings grew to four true leaves, they were transplanted into a plastic pot with a diameter of 20-cm containing diseased soil. Two days after transplanting, each tomato was watered with P-3 strain 10×10⁹ CFUs, and the same amount of sterile water was used as a control. After inoculation, pots were randomly placed on the operating platform of a glass greenhouse. After 60 days of cultivation, the plants were taken out of the pots. Each treatment is repeated 3 times, each time 10 tomato seedlings are replicated. The incidence index was recorded and the effect of controlling southern root-knot nematodes was calculated according to the method of Liu [27]. The rhizosphere soil collected from each duplicated 10 pots of tomato seedlings was thoroughly mixed as a duplicate, so each treatment had 3 duplicates. Rhizosphere soil was collected around the tomato rhizosphere and stored at -80^°C for microbial community structure analysis.

DNA extraction and Illumina MiSeq high-throughput sequencing

The BIO-TEK OMEGA Soil DNA Kit method (Omega Bio-tek, Norcross, GA) was used to extract the total DNA from the soil. At the same time, the bacterial 16S rDNA V3–V4 region and the fungal rDNA-ITS gene were amplified. Polymerase Chain Reaction (PCR) amplification was performed according to a method previously described [45], and Illumina MiSeq was used for sequencing. All reads were clustered with a 97% similarity cut-off using UPARSE (ver. 7.1, http://drive5.com/uparse/), and chimeric sequences were identified and removed using UCHIME [46]. The taxonomy of each 16S rRNA and ITS rDNA gene sequence was analyzed using the RDP Classifier against the Silva (SSU123) 16S rRNA database [47] and the UNITE 7.0/ITS database [48] using a confidence threshold of 70%. Bacterial population functions were performed using the PICRUSt 2 database. The fungal ecosystem analysis was performed using the FUNGuild database [49].

Statistical analysis

In the strain function test and pot test, the data was tested using the Duncan multi-pass test, and the difference was significant. The "Vegan" software package was also used in PCoA to determine community composition differences and community succession based on Bray-Curtis sums. All statistical analyses were performed using R software v. 3.5.2. Using the psych package, the abundance matrix of the top 50 species in the bacterial microbial community and the top 49 species in the bacterial microbial community were calculated at the genus level. Using Gephi 0.9.2, the topological properties of the co-occurring network graph were calculated and drawn.

Results and Analysis

P-3 with controlling J2s of Meloidogyne incognita and phosphorus-dissolving property

In this study, long-term preservation of rhizosphere growth-promoting bacteria in the laboratory was used to screen for the prevention and control of Meloidogyne incognita. Subsequently, these bacterial strains were evaluated against Meloidogyne incognita. However, only the P-3 strain has a 24-hour corrected mortality of Meloidogyne incognita greater than 80%. When the Meloidogyne incognita J2s were treated with the P-3 fermentation supernatant for 24 hours, the mortality rate of the Meloidogyne incognita J2s was 81.23%± 1.23b%. The Meloidogyne incognita J2s had a mortality of 83.56%±2.56% after 48 hours (Table 2). The controlling of Meloidogyne incognita of P-3 strains is 41%. The results showed that the P-3 strain had functions that controlled Meloidogyne incognita. Thus, it can be concluded that P-3 had a strong ability to kill Meloidogyne incognita J2s.

Figure 1: Phylogenetic tree based on 16S rDNA sequence of the P-3.

    
    
    Figure 1: Phylogenetic tree based on 16S rDNA sequence of the P-3.

Figure 2: Composition and succession of microbial communities.
A) Family richness table of tomato rhizosphere bacterial;
B) Family richness table of tomato rhizosphere fungi;
C) PCoA analysis based on Bray Curtis distance of bacterial community;
D) PCoA analysis based on unweighted UniFrac distances of bacterial community.

    
    
    Figure 2: Composition and succession of microbial communities.

A) Family richness table of tomato rhizosphere bacterial;

B) Family richness table of tomato rhizosphere fungi;

C) PCoA analysis based on Bray Curtis distance of bacterial community; 

D) PCoA analysis based on unweighted UniFrac distances of bacterial community.

Figure 3: Analysis of rhizosphere bacterial community function and functional guild of fungi.
a) CoG function classification analysis;
b) FUNGuild functional classification statistical histogram.

    
    
    Figure 3: Analysis of rhizosphere bacterial community function and functional guild of fungi. 

a) CoG function classification analysis; 

b) FUNGuild functional classification statistical histogram.

Identification of bacterial strain P-3

The P-3 strain was round, white, and transparent and had a moist surface, regular edges, rod-shaped bacteria, no spore production, and a positive gram stain. Details of their physiological and biochemical properties are summarized in Table 1. The homology of 16S rRNA between the P-3 strain and the known strain Bacillus aryabhattai (EF114313) reached 99% (Figure 1). Combined with the observation results of its morphology and colony characteristics, and the determination of physiological and biochemical indicators, P-3 strain was identified as Bacillus aryabhattai.

Effect of P-3 on the composition and structure of tomato rhizosphere microbial community

The composition and cluster analysis of the microbial community of tomato rhizosphere microorganisms are shown in Figure 2. P-3 treatment can change the composition of bacterial communities in tomato rhizosphere. Among all identified families, the relative abundance of 27 families in all samples was >1%. As shown in Figure 1, the dominant families in the control (relative abundance in at least one sample was >3%) were Bacillaceae, norank_c_Subgroup_6, Nocardiodaceae, and JG30-KF-CM45. The dominant family in the P-3 processing were Bacillaceae, norank_c_Subgroup_6, Nocardiodaceae, JG30-KF-CM45, and Gemmatimonadaceae. In general, there were differences in the composition of the dominant gates of the two groups of samples. From PCoA analysis based on Bray–Curtis distance, it was also confirmed that the P-3 can change the composition of bacterial communities in the tomato rhizosphere. PCoA analysis based on unweighted UniFrac distances showed that compared with CK, the use of P-3 microbial inoculants did not cause significant succession for a tomato rhizosphere bacterial community. Bacillus aryabhattai can also alter the composition of tomato rhizosphere fungi. Of all the identified families, the relative abundance of 15 families in all samples was more than 1%. As shown in Figure 2, the dominant families (relative abundance > 3% in at least one sample) were Mortierellaceae, Chaetomiaceae, unclassified-c-omycetes, Aspergellaceae, Plectosephaerellaceae, Nectriaceae, Acodesmidaceae, unclassified-o-Sordarales, unclassified-fungi, and Gymnoasccae. The dominant families in P-3 processing were Mortierellaceae, Chaetomiaceae, unclassified_c_sordariomycetes, Aspergillaceae, Plectosaphaerellaceae, Nectriaceae, Ascodesmidaceae, and unclassified_o_sordariales. In general, the composition of the dominant families of the two groups of samples is different. PCoA analysis based on Bray-Curtis distance distances showed that compared with CK, the use of P-3 microbial inoculants did not significantly change the composition of tomato rhizosphere fungi. PCoA analysis based on unweighted UniFrac distances showed that compared with CK, the use of P-3 microbial inoculants caused tomato rhizosphere bacterial community succession. In summary, the P-3 can change the composition of bacterial and fungal microbial communities in the tomato rhizosphere and allow fungal communities in the tomato rhizosphere to undergo directional succession.

Figure 4: Tomato rhizosphere fungi and bacterial species correlation network.
(a) Tomato rhizosphere bacterial species correlation network diagram of CK;
(b) Tomato rhizosphere bacterial species correlation network diagram of P-3;
(c) Tomato rhizosphere fungi species correlation network diagram of CK;
(d) Tomato rhizosphere fungi species correlation network diagram of P-3.

    
    
    Figure 4: Tomato rhizosphere fungi and bacterial species correlation network. 

(a) Tomato rhizosphere bacterial species correlation network diagram of CK; 

(b) Tomato rhizosphere bacterial species correlation network diagram of P-3;  

(c) Tomato rhizosphere fungi species correlation network diagram of CK; 

(d) Tomato rhizosphere fungi species correlation network diagram of P-3.

Table 1: Physiological and biochemical properties of the P-3 strain.




  
    Property 
    Result 
    Property 
    Result 
  
  
    Morphology 
    Rod-shaped 
    Glucose    oxidative fermentation 
    Fermented 
  
  
    Swelling    spore 
    - 
    Aerobic 
    + 
  
  
    Gram    staining 
    + 
    Nitrate    reduction 
    + 
  
  
    Colony    color 
    white 
    2?NaCl 
    + 
  
  
    Colony    morphology 
    Round,    transparent 
    5?NaCl 
    + 
  
  
    Colony    edge 
    neat 
    Starch    hydrolysis 
    + 
  
  
    Colony    surface 
    Moist 
    Methyl    red test 
    - 
  
  
    Bulge 
    Raised

(+) = positive; (-) = negative



Table 1: Physiological and biochemical properties of the P-3 strain.

Table 2: Identifying the ability of the P-3 to kill the Meloidogyne incognita and dissolve phosphorus.




  
    Inhibition    effect on Meloidogyne incognita
    24h 
    48h 
  
  
    Corrected    mortality% 
    81.23±1.23b 
    83.56±2.56 a 
  
  
    Effect    of controlling of Meloidogyne incognita
    - 
    41%

24 h and 48 h represent J2 mortality of (Bacillus aryabhattai) P-3 in 24 h and 48 h in vitro exposure. Means in each column followed by the same letter do not differ significantly according to ANNOVA's multiple range test at P= 0.05.



Table 2: Identifying the ability of the P-3 to kill the Meloidogyne incognita and
dissolve phosphorus.

Effect of the P-3 on rhizosphere bacterial community function and functional guild of fungi

Co-occurrence analysis of the tomato rhizosphere bacteria microbiome by CK and P-3 demonstrated in the gate-level correlation network diagram revealed that tomato rhizosphere bacteria had significant interactions between different gates. In the bacterial microbial community of the tomato rhizosphere, the total number of edges in CK treatment is 456, of which the number of positively and negatively correlated edges accounts for 55.26% and 44.74%, respectively. Nonomuraea, Agromyces, and Bacillus are the key flora. The total number of edges in P-3 processing is 494, of which the number of positively and negatively correlated edges accounts for 57.89% and 42.11% of the total edges, respectively. Nocardioides and norank_c__Subgroup_6 are the key flora. In the tomato fungal microbial community, the total number of edges in CK treatment is 436, the number of positively and negatively correlated edges accounts for 65.37% and 34.63%, respectively. Cephaliophora, Mortierella, Conocybe are the key flora. The total number of edges in the P-3 treatment is 424. The number of positively and negatively correlated edges accounts for 57.78% and 42.22% respectively. Mortierella, unclassified_c__Sordariomycetes, and Myceliophthora are the key flora (Table 3). The results showed that the P-3 treatment increased the complexity of the bacterial microbial community and reduced the complexity of the fungal microbial community, and the P-3 treatment also changed the key flora of the tomato rhizosphere microbial community by increasing the number of positive and negative correlation edges, which indicates that P-3 treatment makes the bacterial microbial community more stable. However, in the tomato rhizobacterial fungal microbial community, P-3 strains reduce the number of positive correlation edges and increase the number of negative correlation edges. Combining the data from the FUNGuild database, this phenomenon may be related to the P-3 strain reducing the number of plant pathogens in the soil. The average degree and clustering coefficient in the topological properties of the co-occurrence network graph also verified that the P-3 treatment increased the complexity of the bacterial microbial community and reduced the complexity of the fungal microbial community (Figure 4).

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Citation: Du J, Gao Q, Liu Z, Li C, Song X, Xu R, et al. Plant Rhizosphere Growth-Promoting Bacterium with Root-Knot Nematode Inhibition and Its Effect on the Tomato Rhizosphere Microbial Community Structure. J Bacteriol Mycol. 2020; 7(8): 1159.

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