Unraveling the characteristics of the microbial community and potential pathogens in the rhizosphere soil of Rehmannia glutinosa with root rot disease

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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Unraveling the characteristics of the microbial community and potential pathogens in the rhizosphere soil of Rehmannia glutinosa with root rot disease ⁎

Ruifei Wanga,1, Yan Wanga,1, Qingxiang Yanga, , Chunxiao Kanga, Mingjun Lia,b a b

College of Life Sciences, Henan Normal University, Xinxiang 453007, China Engineering Technology Research Center of Nursing and Utilization of Genuine Chinese Crude Drugs in Henan Province, Xinxiang 453007, China

A R T I C LE I N FO Keywords: Root rot R. glutinosa Rhizosphere microbial community Plant pathogens

Abstract: The roots of R. glutinosa are a high-demand traditional Chinese medicine with many pharmacological functions and great economic value. However, root rot disease leads to a dramatic reduction in the yield and quality of R. glutinosa. Here, we combined high-throughput sequencing technologies and cultural approaches to investigate characteristics of the microbial community in the rhizosphere soil of R. glutinosa with root rot disease and identified potential pathogens. The results indicated the following: 1) Root rot of R. glutinosa had an intimate relationship with the imbalance of the microbial community. Some genera, such as Pseudomonas, Un-sSordariales and Un-s-Ascomycota, were more abundant in rhizosphere soil from diseased R. glutinosa than that from healthy R. glutinosa, while other genera, such as Sphingomonas, Streptomyces and Myrothecium, displayed the opposite trend. 2) The six isolates (Pseudomonas hibiscicola, Rhizopus stolonifer, Fusarium solani, Actinomucor elegans, Enterobacter aerogenes and Aspergillus tubingensis) from rotten roots were confirmed to be pathogens for root decay of R. glutinosa in pot experiments with different pathogenicities of 33.33%–100%, suggesting the potential synergy of several pathogens in causing root rot in R. glutinosa. Quantitative PCR and pathogenicity tests indicated that Pseudomonas hibiscicola of the genus Pseudomonas was probably the main microbe responsible for root rot in R. glutinosa.

1. Introduction Root health is essential for plant development and controls of plant water and nutrient uptake (Peña et al., 2013). Root rot diseases negatively influence root function, cause root decay and finally plant death, leading to a dramatic reduction in plant yield and quality. It is widely accepted that plant diseases are often caused by one species of microbial pathogens or even by a specific strain. Correspondingly, the current recognition of the plant-pathogen interaction is largely based on the isolation of a single microbial pathogen grown in pure culture (Lamichhane and Venturi, 2015). However, the interactions between plants and pathogens cannot be simplified to just trench warfare between the two parties (Berendsen et al., 2012). Rather, the successful colonization of plant roots and subsequent growth of pathogens could be influenced by many factors, especially the rhi-

zosphere soil microbial community (Chapelle et al., 2016; Lareen et al., 2016). The different pathogens in rhizosphere soil probably display synergistic interactions, which induce more severe disease symptoms than the individual pathogens, although the mechanisms are currently unknown (Glen et al., 2007; Lamprecht et al., 2011; Petkowski et al., 2013). Furthermore, the pathogens must compete with other microbes for resources or for space in the rhizosphere and break through the protective microbial shield to infect plant roots (Weller et al., 2002). Therefore, investigating the changes in the rhizosphere microbial community compositions and abundances with root rot disease would greatly facilitate our understanding of the total population of microbial species involved in plant root rot diseases as well as the underlying mechanisms by which pathogens infect the root. Culture-independent methods, especially high-throughput sequencing technologies, have recently been widely applied to investigate the

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Corresponding author at: College of Life Sciences, Henan Normal University, Jianshe Road 46, Xinxiang 453007, China. E-mail address: [email protected] (Q. Yang). 1 Both authors contributed equally to this work. https://doi.org/10.1016/j.apsoil.2018.07.001 Received 13 February 2018; Received in revised form 2 July 2018; Accepted 5 July 2018 0929-1393/ © 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).

Please cite this article as: Wang, R., Applied Soil Ecology (2018), https://doi.org/10.1016/j.apsoil.2018.07.001

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medical plants in China.

relationship between the dynamic changes in the microbial community structure with plant disease (Lamichhane and Venturi, 2015; Dong et al., 2016; She et al., 2017; Karlsson et al., 2017). These methods can provide comprehensive recognition of potential plant pathogens, which will guide the direction for further isolating and confirming potential pathogens by traditional culture-dependent methods. Therefore, combining culture-independent and culture-dependent methods should be a good strategy to analyze the microbes intimately related to plant diseases, including root rot disease; however, few studies have investigated this. Rehmannia glutinosa has been used in traditional medicine due to pharmacological properties influencing hematologic conditions and tumor growth as cited by Yang et al. (2017). Indeed, more than 15,000 tons of R. glutinosa roots are consumed annually, and they have great medical and economic value. Under field conditions, R. glutinosa is normally planted in April and harvested in December every year. From July to October of the growth period, roots of R. glutinosa rapidly swell by absorbing nutrition and water. Unfortunately, root rot disease frequently occurs because of the hot and muggy weather conditions in this period, which results in a dramatic decrease in R. glutinosa yield and quality (Qi et al., 2009). Although members of the genus Fusarium are thought to be causal agents for R. glutinosa root rot (Lim et al., 2005), agricultural practices have indicated that fungicides against Fusarium often have a limited efficacy, suggesting that other rhizosphere microbes are probably also involved in root rot disease of R. glutinosa. In this study, we assumed that two reasons, the balance of healthy microbial community being broken and/or co-existence and synergistic interaction of different potential pathogens in the rhizosphere, are possibly responsible for root rot disease of R. glutinosa. By combining high-throughput sequencing with isolation of potential pathogens, we aimed to: 1) determine the characteristics of the microbial community in the rhizosphere of R. glutinosa, especially the dynamic relationship between potential pathogens and beneficial microbes, and 2) isolate potential pathogens from the rotten roots of R. glutinosa, detect their pathogenicity and discuss the possible mechanism by which these pathogens infect R. glutinosa roots. The results of this study will contribute to the biological control of root rot disease in R. glutinosa and other

2. Materials and methods 2.1. Site information and sample collection Because consecutive monoculture of R. glutinosa can result in high occurrence of root rot disease, we selected three fields (each approximately 60 m2) in which R. glutinosa had not been planted for at least 5 years before our experiments. This enabled the incidence of root rot disease under normal planting conditions to be reflected. R. glutinosa cultivar “85-5” was cultured in early April 2015 in Wenxian County, Jiaozuo (112°51′ E, 113°13′ N; a geo-authentic production zone for R. glutinosa), Henan Province, China. The main climate conditions of Wenxian County are as follows: annual mean temperature, 14.3 °C; annual average precipitation, 552.4 mm; annual sunshine duration, 2484 h; altitude, 102.3–116.1 m; soil type, loess soil. The rhizosphere soil samples were collected when R. glutinosa exhibited serious root rot in July 2015. Four to five sampling points in a portion of the test fields were randomly selected. At each sampling point, plants were carefully dug out and gently shaken off, after which the soil adhering to roots was separated. Following sampling, the soil was taken to the laboratory under sterile conditions. A total of 13 soil samples were divided into two groups: healthy soil (H1–H5, five parallel samples from healthy plants) and diseased soil (D1–D8, eight parallel samples from diseased plants). Before planting and after harvesting, the pH of the experimental soils was 6.94 ± 0.05 and 6.41 ± 0.30, the organic matter content was 8.56 ± 0.54 and 8.04 ± 0.95 g/kg, the total N was 1.00 ± 0.04 and 0.96 ± 0.01 g/kg, and the total P was 0.124 ± 0.010 and 0.115 ± 0.006 g/kg, respectively. All the above mentioned soil characteristics were measured as described by Wu et al. (2013). 2.2. DNA extraction and illumina sequencing The genomic DNA of the microbes in soil samples was extracted directly using a Soil DNA Kit (Omega Bio-tek, Doraville, USA) according to the manufacturer’s instructions. The concentration and purity of the

Table 1 The top bacterial genera with high contributions to the dissimilarity between the rhizosphere soils of healthy and diseased R. glutinosa. Bacteria

Health Average reads

Disease Average reads

Dissimilarity

Contribution %

Cumulation %

Pseudomonas Sphingomonas Ruminococcaceae_UCG-014 Lactobacillus Bacillus Unidentified_Acidobacteria Streptomyces Lachnospiraceae_NK4A136_group Burkholderia Arthrobacter Stenotrophomonas [Eubacterium]_coprostanoligenes_group Rhizobium Haliangium Ohtaekwangia Lysobacter Nocardioides Acidobacter Halomonas unidentified_Nitrospiraceae unidentified_GR-WP33-30 Opitutus Gaiella Polycyclovorans Gemmatimonas Psychrobacter_GR-WP33-30 Enterorhabdus

336.20 1068.20 271.80 168.80 309.40 423.00 226.20 94.60 68.20 242.80 127.40 86.60 245.00 266.20 36.60 107.20 141.40 99.20 58.80 158.60 188.80 85.40 194.20 118.40 103.80 61.20 77.60

943.13 871.38 295.13 342.25 335.63 440.38 88.88 221.50 92.88 151.00 39.38 119.88 205.13 258.00 107.50 102.13 74.75 113.50 26.25 123.75 160.13 53.63 136.13 87.00 95.25 17.38 102.00

3.13 1.90 1.55 1.21 0.79 0.74 0.71 0.63 0.63 0.53 0.52 0.49 0.45 0.37 0.37 0.35 0.34 0.32 0.31 0.30 0.29 0.29 0.28 0.28 0.28 0.28 0.27

8.90 5.41 4.41 3.44 2.24 2.10 2.03 1.80 1.78 1.51 1.48 1.40 1.27 1.06 1.06 1.00 0.98 0.90 0.89 0.87 0.82 0.82 0.80 0.79 0.79 0.79 0.78

8.90 14.32 18.73 22.17 24.41 26.51 28.54 30.33 32.11 33.62 35.10 36.50 37.77 38.83 39.89 40.89 41.87 42.78 43.66 44.53 45.35 46.16 46.96 47.75 48.55 49.33 50.11

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the segments were isolated and purified by plate streaking cultivation, and their morphologies were recorded by microscopy. Next, 16S rDNA of the bacteria and the internal transcribed region of the fungi were amplified and sequenced using the 27F (5′-AGAGTTTGATCCTGGCT CAG-3′)/1492R (5′-GGTTACCTTGTTACGACTT-3′) and ITS1 (5′-TCCG TTAGGTGAACCTGCGG-3′)/ITS4 (5′-TCCTCCGCTTATTGATATGC-3′) primers, respectively (Selige, 1990). All nucleotide sequences were submitted to GenBank (MF359553 to MF359556, MF356673 and MF356674) and subjected to BLAST analysis for homologous sequences of 16S rDNA or ITS in the NCBI database.

DNA extracts were measured with a spectrophotometer (Thermo Scientific, USA), after which the DNA extracts were diluted to a concentration of 1 ng/μL. The diluted extracts and barcoded primers were used for PCR amplification. Two pairs of primers, 515F (5′-GTGCCAG CMGCCGCGGTAA-3′)/806R (5′-GGACTACVSGGGTATCTAAT-3′) and ITS5 (5′-GGAAGTAAAAGTCGTAACAAGG-3′)/ITS2 (5′-GCTGCGTTCTT CATCGATGC-3′), were used to amplify the V4 region of the bacterial 16S rDNA and the fungal ITS1 region of the internal transcribed spacer, respectively. Equal amounts of purified amplicons from each sample were pooled to construct sequencing libraries using a TruSeq® DNA PCR-Free Sample Preparation Kit according to the manufacturer's recommendations. The qualities of libraries were evaluated using a Qubit® 2.0 Flurometer (Life Technologies, CA, USA) and real-time PCR. Based on the sequencing libraries, high-throughput sequencing was conducted to generate paired-end reads on the HiSeq2500 platform at Novogene Bioinformatics Technology Co., Ltd (Beijing, China). Pairedend reads were assigned to each sample according to the unique barcode and merged to raw reads using FLASH (Version 1.2.7, http://ccb. jhu.edu/software/FLASH/) (Tanja and Salzberg, 2011). Based on the quality control process of QIIME (Version 1.7.0, http://qiime.org/ scripts/split_libraries_fastq.html) (Caporaso et al., 2010), all raw reads were filtered and processed: 1) The raw reads with three or more sequential ambiguous bases (quality threshold ≤19) were truncated at the first ambiguous base position, after which any raw reads with consecutive high quality bases shorter than 75% of the total length were removed; 2) The UCHIME Algorithm was used to screen out and remove raw reads containing the chimeras (Edgar et al., 2011); 3) Raw reads shorter than 250 bps (for bacteria) or 200 bp (for fungi) were also removed. Finally, average lengths of effective reads from different samples were 253–256 bp for bacteria and 217–248 bp for fungi, respectively. The UPARSE algorithm and BAYESIAN algorithm (Ribosomal Database Project Classifier) on the QIIME platform were employed to cluster the high quality reads into operational taxonomic units (OTUs) with an identity of 97%, after which representative sequences of each OTU were used to taxonomically classify OTUs with a 0.80 confidence threshold. Rarefaction curves were produced using the R software (Version 2.15.3).

2.5. Pathogenicity of the potential pathogens To demonstrate pathogenicity of the isolated microbes, two healthy roots were placed into a pot, after which 10 mL of conidial or bacterial solution (2 × 107 conidia or thalli/mL) were inoculated into the sterile soil around the roots (Zhao et al., 2015). Each treatment was replicated three times. Roots treated with sterile water served as controls. The pots

2.3. Quantitative PCR analysis Quantitative PCR was conducted to quantify the total bacteria, total fungi, and the genera Pseudomonas, Sphingomonas and Fusarium in healthy and diseased soil. The primers used are listed in Supplementary Table 1. The reaction mixture consisted of 10 μL 2 × SYBR Green I Master Mix (Vazyme, Nanjing, China), 0.4 μL of each primer (10 μM), 2 μL template DNA (total soil DNA or 10-fold serial dilutions of plasmid DNA from 103 to 108 copies/μL for standard curves) and 7.2 μL sterile double-distilled water. Three independent quantitative PCR experiments were performed for each treatment. The specificity of the amplified product was verified by a melting curve analysis under the following conditions: 95 °C for 15 s and then 60 °C for 60 s, followed by 95 °C for 15 s. Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.apsoil.2018.07.001. 2.4. Isolation and identification of the potential pathogens Following the collection of soil samples, rotten roots of diseased R. glutinosa were placed in sterile plastic bags. The potential pathogens were then isolated using a general tissue separation method. Briefly, the tissue segments (1 cm3 each) adjacent to the disease lesions of R. glutinosa roots were surface-sterilized in 75% alcohol solution for 3 min. After rinsing three times with sterile distilled water, the washing water was spread onto solid Potato Dextrose Agar to confirm the removal of microbes on the root surface. These segments were then placed into the solid Potato Dextrose Agar for 5 days, after which the microbes around

Fig. 1. The relative abundance of the top 10 genera responsible for bacterial (A) or fungal (B) community dissimilarity in the healthy and diseased rhizosphere soils of R. glutinosa. For each genus, the median and range of the abundances are plotted (n = 5–8). 3

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were responsible for 33.62% of the community dissimilarity, of which Pseudomonas, Sphingomonas, Ruminococcaceae_UCG-014, Lactobacillus, Bacillus, Unidentified-Acidobacteria, Streptomyces, Lachnospiraceae_NK4A136_group, Burkholderia and Arthrobacter contributed approximately 8.9%, 5.41%, 4.41%, 3.44%, 2.24%, 2.10%, 2.03%, 1.80%, 1.78% and 1.51%, respectively (Table 1). Among these, Pseudomonas, Ruminococcaceae_UCG-014, Lactobacillus, Unidentified-Acidobacteria, Lachnospiraceae_NK4A136_group and Arthrobacter displayed higher medians in the diseased soil than in the healthy soil (Fig. 1A). In particular, the median of the genus Pseudomonas showed the most obvious increase in the diseased soil. In contrast, Sphingomonas, Bacillus, Streptomyces and Burkholderia had lower medians in the diseased soil than in the healthy soil, with Sphingomonas displaying the most obvious decrease in the diseased soil (Fig. 1A). Previous studies have indicated that many members of the genus Pseudomonas, including Pseudomonas putida and Pseudomonas aeruginosa (Kourosh and Mahdi, 2011; Islam et al., 2014), have frequently been used as plant growth-promoting rhizobacteria to control soil borne pathogens. However, some recent evidence suggests that, with changes in the microbial community, inhibitory Pseudomonas accumulates in the rhizosphere, resulting in poor nutrient uptake and root growth in no-tillage crops (Huang et al., 2016). Moreover, some Pseudomonas species such as P. syringae and P. solanacearum are known plant root pathogens (Wu et al., 2016; de Torres-Zabala et al., 2007; Vasse et al., 1995). Thus, the increase in the abundance of the genus Pseudomonas may signal that the microbial community balance in the rhizosphere of R. glutinosa was broken. The genus Sphingomonas has a ubiquitous distribution and diverse catabolic capabilities toward recalcitrant organic pollutants, which makes them important biocatalysts for soil bioremediation (Leys et al., 2004). Moreover, some members of the genus Sphingomonas can inhibit Fusarium head blight of winter wheat cv. Bogatka under greenhouse conditions (Wachowska et al., 2013). Thus, the decrease in the abundance probably weakens the effective protection of the genus Sphingomonas against pathogens. In addition, some low-abundance bacterial genera should also be monitored because of their abilities to produce special substances. For example, many members of the genus Streptomyces are capable of producing antibiotics to combat harmful microbes (El-Refai et al., 2011). Their decrease in rhizosphere soil would result in a decrease in combating some root rot pathogens and accelerate the process of R. glutinosa root rot. Taken together, it is possible that the opposite trend in the abundance of the beneficial and harmful rhizobacteria in diseased soil increases the risks of large-scale colonization and attack of R. glutinosa roots by the pathogens. In the fungal community, diseased soil samples displayed average dissimilarities from healthy soil samples of 60.72%. As shown in

were subsequently placed in the disinfection chamber, maintained at 30 °C and irrigated with sterile water. After 10 days, the roots were dug out and photographed. By day 20, the incidences of root rot were counted. The microbes from the rotten roots were then re-isolated and confirmed to ensure they were consistent with inoculates by microscopy and sequencing. 2.6. Statistical analyses A SIMPER (similarity Percentage) test was used to identify the contribution of each species to the average dissimilarities between the bacterial or fungal communities of healthy and diseased soil samples. Before starting the SIMPER analysis, samples were divided into a healthy group (H1-H5) and a diseased group (D1-D8). SIMPER analysis was then performed based on Bray-Curtis similarities using species abundance data in PRIMER V5 (Plymouth Routines in Multivariate Ecological Research V5) (Clarke, 1993; Clarke and Warwick, 2001). The significant differences in quantitative data between healthy and diseased soils were then analyzed using the unpaired Student’s T-test with the SPSS software version 17.0 (SPSS, 2008). 3. Results and discussion 3.1. Root rot incidence in R. glutinosa farming On Jul 20, 2015, the phenomena associated with typical root rot disease, including leaf wilt, stem discoloration and root decay, were observed in the R. glutinosa from our three 60 m2 test fields. Further statistical analyses indicated that the root rot incidence of R. glutinosa was 16.0 ± 3.3% under field conditions. 3.2. Characteristics of the microbial community in the rhizosphere soil of R. glutinosa with root rot disease Data based high-throughput sequencing can generally provide correlated information regarding the microbial community and a plant disease, which is very helpful for comprehensive recognition of the potential plant pathogens. Thus, we performed high-throughput sequencing, which produced 34,107–80,882 and 27,968–47,063 effective reads for bacteria and fungi among samples, respectively. The sequencing efforts were large enough for analysis of bacterial and fungal communities, as indicated in the rarefaction curves (Supplementary Fig. 1). The SIMPER analysis showed that in the bacterial community, diseased soil samples displayed 35.16% average dissimilarities from healthy soil samples. As shown in Table 1, the top 10 genera of bacteria

Table 2 The top fungal genera with high contributions to the dissimilarity between the rhizosphere soils of healthy and diseased R. glutinosa. Fungi

Health Average reads

Disease Average reads

Dissimilarity

Contribution %

Cumulation %

Un-s-Sordariales sp. Monographella Thielaviopsis Myrothecium Un-s-Ascomycota sp. Un-s-Nectriaceae sp. Un-s-Hypocreales sp. Phoma Un-s-Microascaceae sp. Un-s-Pleosporaceae sp. RS_5 Un-s-Sordariomycetes sp. Myrothecium Chaetomium Staphylotrichum Cryptococcus Mortierella Fusarium Un–s-Pleosporales sp.

2118.40 3193.40 2636.20 2651.80 2002.00 1560.20 785.80 1635.00 117.20 613.80 808.40 510.40 715.40 468.40 388.40 247.80 316.40 193.00

5905.00 1014.88 1171.13 1604.00 2847.25 2120.50 2408.25 448.63 886.63 757.50 950.75 145.25 546.50 393.00 176.13 341.50 338.25 164.75

10.16 5.70 5.65 5.22 4.83 4.02 3.70 3.04 1.61 1.18 1.10 0.83 0.77 0.74 0.54 0.49 0.47 0.43

16.73 9.39 9.31 8.59 7.96 6.61 6.10 5.01 2.66 1.94 1.82 1.37 1.26 1.22 0.89 0.80 0.77 0.72

16.73 26.11 35.42 44.01 51.97 58.58 64.68 69.69 72.35 74.29 76.11 77.48 78.74 79.96 80.85 81.65 82.42 83.14

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distant are more likely to have different susceptibilities to the same plant pathogen because the morphological and chemical traits of plants regulating the interactions with pathogens are often phylogenetically conserved (Gilbert and Webb, 2007). In contrast, the genera Un-s-Sordariales sp., Un-s-Hypocreales sp., Un-s-Ascomycota sp., Un-s-Nectriaceae sp. and Un-s-Pleosporaceae sp. displayed higher medians in diseased soil than in healthy soil. In particular, the genera Un-s-Sordariales sp. and Un-s-Ascomycota sp. showed an obvious increase in medians in diseased soil compared with healthy soil. In addition, the genus Fusarium which was long known to cause root rot in R. glutinosa, slightly increased in abundance in diseased soil compared with that in healthy soil and displayed a low contribution to the dissimilarity of the fungal community (Table 2). These results implied that some unidentified fungal genera might play important roles in root rot in R. glutinosa. The results of high-throughput sequencing were further confirmed

Table 2, the top 10 genera of fungi were responsible for 74.29% of the community dissimilarity, in which Un-s-Sordariales sp., Monographella, Thielaviopsis, Myrothecium, Un-s-Ascomycota sp., Un-s-Nectriaceae sp., Un-s-Hypocreales sp., Phoma, Un-s-Microascaceae sp. and Un-s-Pleosporaceae sp. contributed approximately 16.73%, 9.39%, 9.31%, 8.59%, 7.96%, 6.61%, 6.10%, 5.01%, 2.66% and 1.94% of the fungal community dissimilarity, respectively. Among these, the genera Myrothecium and Monographella had lower medians in the diseased soil than in the healthy soil (Fig. 1B). Previous studies indicated that members of the genus Myrothecium were the causal agents of root rot of some plants such as cereals, tobacco and alfalfa (Harris, 1986; Almario et al., 2014; Larsen et al., 2002; Leath and Kendall, 1981). In our study, this genus decreased in abundance in diseased soil when compared with healthy soil, suggesting that it is not a relevant pathogen of R. glutinosa root rot. This can be explained by the opinion that plants that are evolutionarily

Fig. 2. The absolute abundance of total bacteria (A), total fungi (B), the genus Pseudomonas (C), the genus Sphingomonas (D) and the genus Fusarium (E) in the healthy and diseased rhizosphere soils of R. glutinosa. For each genus, the median, average (□) and range of the content are plotted (n = 5–8). A significant statistical difference was indicated (p < 0.05). 5

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Fig. 3. The colony and microscopic morphology of the six isolates from root rot of R. glutinosa (microscopic morphology 1–4, 40×; 5–6, 100×).

an obvious increase in the diseased soil compared with that in the healthy soil (Fig. 1B). The possible reasons for this are as follows: 1) the culture conditions in this study were not suitable for isolating these microbes; 2) these microbes might have stimulated the colonization of other pathogens in the roots of R. glutinosa, but they lacked the ability to directly infect the roots of R. glutinosa by themselves. In further research, we will optimize the culture conditions and try to isolate the members of the two genera from diseased soil and rotten R. glutinosa roots, respectively. The results of the inoculation experiment showed that uninoculated control R. glutinosa roots remained healthy, and no diseased spots were found over the experimental period of 20 days (Fig. 4). However, the R. glutinosa roots inoculated with A. elegans, E. aerogenes, R. stolonifer, P. hibiscicola or F. solani exhibited obvious black disease spots or decay at day 10 and became more serious by day 20 (Fig. 4), while the R. glutinosa roots inoculated with A. tubingens is displayed obvious disease spots only after 20 days (Fig. 4). Moreover, all re-isolated strains from the focal zones of the inoculated roots were verified to be the same as the inoculated strains based on morphological observation and 16S/ITS sequencing. In previous studies, members of Fusarium have been shown to be serious pathogens that cause root rot disease in R. glutinosa (Lim et al., 2005; Wu et al., 2015). In the present study, we found that A. elegans, A. tubingensis and R. stolonifer of fungi as well as E. aerogenes and P. hibiscicola of bacteria are also involved in root rot of R. glutinosa. Among these strains, R. stolonifer is known to be the causal agent of Rhizopus rot disease among various fruits and vegetables, while A. tubingensis has also been reported to cause postharvest fruit rot of Prunus salicina Lindl. and leaf spot of J. curcas (Guo et al., 2017; HernándezLauzardo et al., 2008). However, there have been no reports that A. elegans, E. aerogenes and P. hibiscicola infect R. glutinosa or other plant roots. Nonetheless, the present experiments reveal that the six isolated microbes have an intimate relationship with the occurrence of R. glutinosa root rot. Further analysis showed that the incidence in the control group at 20 days was 0%, but that of the A. elegans, E. aerogenes, A. tubingensis, R. stolonifer, P. hibiscicola or F. solani treatments reached 33.33%, 66.67%, 83.33%, 100%, 100% and 100%, respectively (Table 4), implying that these microbes had obvious differences in pathogenicity, although all of them could lead to R. glutinosa root rot. In a recent review, Lamichhane

by quantitative PCR methods. On the one hand, although the statistical difference was not significant between the contents of total bacteria or fungi in the diseased and healthy soil, the medians of bacteria and fungi in the diseased soil exhibited an obviously increasing trend when compared with that in the healthy soil, suggesting a general shift in the microbial community in the rhizosphere soil of R. glutinosa with root rot disease (Fig. 2A and B). On the other hand, changes in the content of the representative genera Pseudomonas, Sphingomonas and Fusarium in the diseased and healthy soil were also confirmed. The copies of the genera Pseudomonas and Fusarium were generally higher in diseased soil than in healthy soil (p < 0.05), while the genus Sphingomonas generally exhibited the opposite trend (Fig. 2C–E). These results were consistent with those of the rhizosphere microbial community analysis, suggesting that the results of the high-throughput sequencing reflected the shift in community composition in the rhizosphere soil of R. glutinosa with root rot disease well. Taken together, the rhizosphere microbial community of R. glutinosa with root rot disease displayed an obvious imbalance when compared with that of healthy R. glutinosa. In particular, these results suggest that the increase in the abundance of the different potential pathogens probably facilitated the synergistic interaction of these pathogens to break through the protective microbial shield and overcome the innate plant defense mechanisms, which resulted in the occurrence of root rot disease of R. glutinosa. 3.3. Isolation, identification and pathogenicity analysis of pathogenic microbes A total of six morphologically distinct bacteria and fungi were isolated from rotten roots as pure cultures, and their colony and microscopic morphologies are shown in Fig. 3. The 16S rDNA/ITS sequences of the six strains were compared to those of known 16S rDNA/ITS sequences using BLAST searches of the GenBank database. The results indicated that the isolated strains 1, 2, 3, 4, 5 and 6 showed a high degree of interstrain similarity (99–100%) with Actinomucor elegans, Aspergillus tubingensis, Fusarium solani, Rhizopus stolonifer, Pseudomonas hibiscicola and Enterobacter aerogenes, respectively (Table 3). Notably, we did not isolate the members of the genera Un-s-Sordariales sp. and Un-s-Ascomycota sp., although the medians of the two genera displayed Table 3 Genetic characterization of isolated strains to gene level. The isolates

GenBank Accession no.

Closest relatives in NCBI (GenBank accession no.)

Max. identity (%)

Max. score

Total score

E-value

Query cover (100%)

1 2 3 4 5 6

MF359553 MF359554 MF 359555 MF 359556 MF356673 MF356674

Actinomucor elegans (AM745429) Aspergillus tubingensis (KY565472) Fusarium solani (KU528855) Rhizopus stolonifer (DQ641317) Pseudomonas hibiscicola (MG905301) Enterobacter aerogenes (KM974656)

100% 100% 100% 99% 99% 99%

1005 857 937 1576 2621 2597

1005 857 937 1576 2621 2597

0.0 0.0 0.0 0.0 0.0 0.0

100% 100% 100% 99% 98% 99%

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Fig. 4. Re-inoculation experiments in pot cultures revealing the effectiveness of the six potential pathogens causing root rot disease in R. glutinosa (10 or 20 days after inoculation). Magnified views of the arrowed area representing diseased spots are shown in the inserts.

and Venturi (2015) pointed out that plant disease occurs by two modes: a single infection by a certain pathogen or a mixed infection by different pathogens, with the latter leading to more severe disease symptoms than expected (Lamichhane and Venturi, 2015). Thus, the root rot disease of R. glutinosa observed in the field was probably a result of a mixed infection of several pathogens. According to Back et al., in the field, highly pathogenic microbes might induce an initial infection, disrupt the metabolism in plant roots and reduce host resistance (Back et al., 2002), leading to the proper micro-environment for subsequent colonization and growth of low-pathogenic microbes. In this study, the isolated P. hibiscicola not only had high pathogenicity (100%), but was also the representative member of

Table 4 The pathogenicity of the six isolates from the root of R. glutinosa with root rot disease. Inocula

Inoculated roots

Diseased roots

Incidence

Control Actinomucor elegans Enterobacter aerogenes Aspergillus tubingensis Rhizopus stolonifer Pseudomonas hibiscicola Fusarium solani

6 6 6 6 6 6 6

0 2 4 5 6 6 6

0 33.33% 66.67% 83.33% 100% 100% 100%

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the genus Pseudomonas occupying the highest abundance in the rhizosphere bacteria community of R. glutinosa with root rot. These findings implied that it might be a central pathogen inducing the initial infection of R. glutinosa roots. Of course, this finding needs to be confirmed in a further study. Notably, Aspergillus, Fusarium and Rhizopus among these isolated pathogens displayed very low abundances and made small contributions to the fungal community structure in the rhizosphere soil of diseased R. glutinosa (Table 2), which seems to be inconsistent with their rapid growth and high pathogenicity in R. glutinosa roots (Fig. 4 and Table 4). It is possible that the complex rhizosphere soil is not a suitable environment for the colonization and growth of these pathogens when compared with R. glutinosa root tissue. Rhizosphere soil is a “microbial hot-spot” that harbors various microbes that can compete with pathogens for resources or for space, thereby inhibiting pathogen growth and prevalence (Weller et al., 2002). Moreover, pathogens might degrade root exudates or induce the production of special root exudates that stimulate the chemotactic response of some beneficial microbes, directly combating pathogenic microbes in the rhizosphere soil (Berendsen et al., 2012; Liu et al., 2014). In contrast, root tissue contains abundant carbon and other nutrients, but limits the entrance of many microbes by the epidermal membrane and plant defense responses (Dehgahi et al., 2015; Lapin and den Ackerveken, 2013). Thus, once pathogenic microbes overcome these barriers and successfully colonize root tissue, they would face less pressure from competition and exhibit more rapid growth when compared with that in rhizosphere soil.

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4. Conclusion In conclusion, the present study indicated that 1) the imbalance of the rhizosphere microbial community, especially the increase of potential pathogens, was probably one reason for the rhizosphere microenvironment shift from “healthy” to “ill”, resulting in the occurrence of R. glutinosa root rot. 2) Six strains isolated from rotten roots displayed different pathogenicities, suggesting that a mixed infection by several pathogens was another reason for root rot in R. glutinosa. Among these strains, P. hibiscicola was probably the dominant microbe causing root rot in R. glutinosa. In further studies, we will focus on: 1) revealing the mechanism by which P. hibiscicola interacts with other pathogens to collaboratively induce root rot of R. glutinosa; 2) screening for potential microbes with antagonistic activities against pathogens, especially P. hibiscicola, and exploiting the microbial agents to perform biocontrol of root rot disease of R. glutinosa. Acknowledgements This work was supported by the National Natural Science Foundation of China (grant number 21477035 and U1504301); The Key Science and Technology Project of Henan Province (grant number 182102410042); The Outstanding Talented Persons Foundation of Henan Province (grant number 144200510007); National Chinese Medicine Industry Research Project (grant number 201407005-08); Innovation Scientists and Technicians Troop Construction Projects of Henan Province (grant number C20130037); Educational Commission of Henan Province of China (grant number 15A180016); and Doctor Initiative Foundation of Henan Normal University (grant number qd14166). We thank International Science Editing (http://www. internationalscienceediting.com) for editing this manuscript. References Almario, J., Muller, D., Défago, G., 2014. Rhizosphere ecology and phytoprotection in soils naturally suppressive to Thielaviopsis black root rot of tobacco. Environ. Microbiol. 16, 1949–1960. Back, M.A., Haydock, P.P.J., Jenkinson, P., 2002. Disease complexes involving plant parasitic nematodes and soilborne pathogen. Plant Pathol. 51, 683–697. Berendsen, R.L., Pieterse, C.M.J., Bakker, P.A.H.M., 2012. The rhizosphere microbiome

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