Insight into the assembly of root-associated microbiome in the medicinal plant Polygonum cuspidatum

Industrial Crops & Products 145 (2020) 112163

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Insight into the assembly of root-associated microbiome in the medicinal plant Polygonum cuspidatum

T

Yonghong Zhanga, Lanlan Zhenga, Yan Zhenga, Shen Xuea, Jingxuan Zhanga, Ping Huanga, Yongheng Zhaoa, Xincai Haoa, Zhikai Hea, Zhubing Hub, Chao Zhouc, Qinhua Chend, Jianping Liue, Guodong Wangf, Ming Sangg, Xiaodong Sung, Xuanbin Wangh, Xiao Xiaoa,*, Chen Lia,* a

Laboratory of Medicinal Plant, Institute of Basic Medical Sciences, School of Basic Medicine, Biomedical Research Institute, Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, Shiyan, 442000, China Center for Multi-Omics Research, Key Laboratory of Plant Stress Biology, State Key Laboratory of Cotton Biology, School of Life Science, Henan University, Kaifeng, 475001, China c Key Laboratory of Three Gorges Regional Plant Genetics & Germplasm Enhancement (CTGU) /Biotechnology Research Center, China Three Gorges University, Yichang, China d Affiliated Dongfeng Hospital, Hubei University of Medicine, Hubei, Shiyan, 442008, China e College of Bioscience and Bioengineering, Jiangxi Agricultural University, Nanchang, 330045, China f Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry, Ministry of Education, National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Life Sciences, Shaanxi Normal University, Xi’an, 710119, China g Central Laboratory of Xiangyang No.1 People’s Hospital, Institute of Parkinson's Disease, Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, Shiyan, 442000, China h Laboratory of Chinese Herbal Pharmacology, Oncology Center, Renmin Hospital, Biomedical Research Institute, Hubei University of Medicine, Shiyan, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Polygonum cuspidatum Medicinal plant Root-associated microbiome Cultivation year Bioactive compounds Rhizosphere

Polygonum cuspidatum (Polygonum cuspidatum Sieb. & Zucc.), a medicinal plant that is abundantly accumulating bioactive compounds in its roots, is the primary source of resveratrol in industry and has long been recognized as raw materials for traditional Chinese medicine. Plant root secondary metabolism is correlated to its surrounding microbial communities. However, the root-associated microbiomes of P. cuspidatum and the potential correlation between the bioactive compounds and microbiomes are poorly understood. To unveil the root-associated bacterial community, the microbiome compositions of P. cuspidatum roots across four cultivation years were analyzed by using 16S rRNA gene sequencing. Furthermore, the relationships among root-associated bacteria, soil properties, and four major bioactive compounds (polydatin, resveratrol, emodin, and physcion) were explored by a multivariate correlation study. The composition of the rhizosphere microbiome significantly differed from that of the endosphere microbiome. The composition of the rhizosphere microbiome significantly varied across different cultivation years and soil properties, contributing to the majority of variance. Regarding different cultivation years and soil properties, the compositions of the root endosphere microbiome remained relatively stable, indicating a strong selection effect in P. cuspidatum roots. Among root endosphere microbes, Stenotrophomonas was specifically enriched from rhizosphere with a 15 times increase of relative abundance, exhibiting no significant variation across different cultivation years. The relative abundance of rhizosphere Stenotrophomonas was positively correlated with the content of emodin. Taken together, this study demonstrated that the stability of the root endosphere microbiome with a dominance of Stenotrophomonas may maintain the growth of P. cuspidatum through the combined effect of emodin. The contents of bioactive compounds in roots exhibited distinct correlations with specific bacteria, suggesting that Bacteroides, Acinetobacter, Erysipelatoclostridium, and Achromobacter may enhance the accumulation of resveratrol. This study provides insights into the interaction networks among P. cuspidatum root-associated bacteria, cultivation years, soil properties, and bioactive compounds, giving us a new opportunity to manipulate the production of bioactive compounds, and thus improve the industrial and medicinal value of P. cuspidatum in future.

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Corresponding authors. E-mail addresses: [email protected] (X. Xiao), [email protected] (C. Li).

https://doi.org/10.1016/j.indcrop.2020.112163 Received 4 September 2019; Received in revised form 14 January 2020; Accepted 22 January 2020 0926-6690/ © 2020 Elsevier B.V. All rights reserved.

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1. Introduction

assembly of root-associated microbiome. Since previous studies mainly focused on model plants and crops (Breidenbach et al., 2016; Köberl et al., 2013), the assembly of rhizosphere microbiome and the root endosphere microbiome in the important medicinal plant P. cuspidatum remains unclear. It has been speculated that plant secondary metabolism is correlated to its surrounding microbial communities. For instance, bacteria of genus Pseudomonas and Bacillus identified from the rhizosphere and endosphere possess the ability to increase the production of plant secondary metabolites (Rilling et al., 2018). To be specific, Bacillus pumilus promotes the accumulation of flavonoid and glycyrrhizic acid in Glycyrrhiza uralensis Fisch (Xie et al., 2019), the inoculation of Azospirillum results in the modification of benzoxazine derivatives in maize (Walker et al., 2011), Rhizobacteria Streptomyces sp. PM9 contributes to the modulation of the secondary metabolism in eucalyptus (Salla et al., 2014), and the inoculation of Pseudomonas fluorescens enhances the biosynthesis of total phenolic product and essential oil of marigold (del Rosario Cappellari et al., 2013). The accumulation of metabolites is pivotal to the pharmacological value of the raw herbaceous materials (Lim, 2012). However, the understanding of the metabolism of the major bioactive components of P. cuspidatum and its root-associated microbiome is extremely limited. To address the relationship between P. cuspidatum and its root-associated microbiome, we studied the assembly of rhizosphere and root endosphere microbiome of P. cuspidatum and further explore the influence of soil properties and cultivation year on root-associated microbiome. We compared the root-associated microbiome compositions in field-grown P. cuspidatum across four different cultivation years by high-throughput sequencing. Furthermore, the correlation between the four bioactive compounds (resveratrol, polydatin, emodin, and physcion) and the root-associated bacteria were investigated in P. cuspidatum roots. The results demonstrated that cultivation year and soil physicochemical properties significantly influenced the composition of the rhizosphere microbiome in P. cuspidatum, while the composition of the root endosphere microbiome was relatively stable with a dominance of Stenotrophomonas, showing no significant variation along with cultivation year. Therefore, we speculated that the roots of P. cuspidatum have a strong selection on the endosphere microbiome, which expands our knowledge on the relationships between P. cuspidatum, endosphere microbiome and rhizosphere microbiome. Furthermore, the data uncovered distinct correlations and dynamic patterns between certain endosphere bacteria and the contents of resveratrol, polydatin, emodin, and physcion in roots, providing a feasible strategy to improve the medicinal value of P. cuspidatum by an ecological approach of manipulating root endosphere microbiome.

Polygonum cuspidatum (Polygonum cuspidatum Sieb. & Zucc.), known as Japanese knotweed or Huzhang in China, is an herbaceous perennial plant which is widely distributed and has been long recognized as crude medicine in East Asian countries, such as China, Japan, and Korea (Peng et al., 2013; Zhang et al., 2019). Currently, P. cuspidatum has been widely cultured as an economic crop in the Qinba mountain area, central China. The dried rhizomes and roots of P. cuspidatum have been used as traditional Chinese medicine in the application of promoting diuresis, dissipating stasis, relieving pain, suppressing cough, and resolving phlegm (Peng et al., 2013; Yuan et al., 2015). Recent pharmacological studies have suggested that P. cuspidatum possesses antitumor, anti-inflammatory, anti-viral and hepatoprotective properties (Yuan et al., 2015; Zahedi et al., 2013). Four major and diverse bioactive compounds have been identified with potential pharmacological values from root extracts of P. cuspidatum, namely resveratrol, polydatin, emodin, and physcion (Zahedi et al., 2013). Resveratrol is a natural antioxidant polyphenol that exerts health-enhancing properties to treat cancer and cardiovascular diseases (Hong et al., 2016; Singh et al., 2018). Polydatin, a natural precursor of resveratrol, alone or in combination with resveratrol synergistically induces cell cycle arrest and promote cell differentiation in the human colorectal Caco-2 cell (De Maria et al., 2013). The anthraquinone derivatives emodin and physcion have been demonstrated to have potential anti-neoplastic (Li et al., 2018) and anti-microbial effects (Hsu and Chung, 2012; Li et al., 2018; Pan et al., 2018; Xiang et al., 2019). The regulation of the productions of these four bioactive components remains widely unknown. Recent studies reported that resveratrol and emodin exhibit antagonistic effects against plant pathogens (Chen et al., 2016; Izhaki, 2002), suggesting that there are potential relationships between the accumulation of rootderived metabolites and its associated rhizosphere and endosphere bacteria in P. cuspidatum. With the increasing demand of resveratrol, P. cuspidatum is becoming an important industrial plant due to that the root extractions of the plant provide the largest resource of commercial resveratrol. (Mei et al., 2015). Rhizosphere is designed as a narrow zone that is surrounding the plant roots and inhabiting by various microbes (Canarini et al., 2019; Edwards et al., 2015; Lundberg et al., 2012). It has been thought that root exudates have impact on the compositions of root microbiome and have a selective role in the rhizosphere by attracting and maintaining a preferential soil microbial reservoir (Stringlis et al., 2018; Hu et al., 2018; Huang et al., 2019). For instance, in maize, it has been revealed that the root-derived metabolites benzoxazinoids drive plant-soil-feedbacks by shaping root-associated microbial communities, which in turn influence the growth and defence of the next plant generation in a heritable manner (Hu et al., 2018). Also, it has been demonstrated that the plant defensive secondary metabolites triterpenes possess the ability to selectively and directly modulate the assembly of root microbiome in Arabidopsis, providing biological significances of understanding rootmicrobial interaction and engineering root microbiome (Huang et al., 2019). Rhizosphere microbiome is vital for plant growth by providing direct or indirect protections to the plants, including facilitating the absorption of mineral nutrients, improving stress resistance, secreting plant hormones, and enhancing disease resistance (Berg et al., 2014a, b; Rolli et al., 2015; Shokati and Poudineh, 2017). Some recent studies showed that it could improve plant health and survival by the reconstitution of bacterial root microbiome with beneficial properties (Duran et al., 2018; Tsolakidou et al., 2019). After attaching on the root surface, certain rhizomicrobes can enter the root endosphere with no harmful effects (Edwards et al., 2015; Gaiero et al., 2013). It has been reported that soil properties and plant growth stages can influence the composition of root-associated microbiome (Breidenbach et al., 2016; Lundberg et al., 2012; Tkacz and Poole, 2015; Xiao et al., 2017a). Meanwhile, few studies focused on the effect of cultivation years on root-associated microbiome composition, which might relate to the

2. Materials and methods 2.1. Sample collection and DNA extraction The P. cuspidatum used in this study were the same cultivar. All samples were collected from different fields within a 25-square-kilometer area of the P. cuspidatum plantation at Hubei Province, China (25°20ʹ5.496ʺN, 114°57ʹ52.459ʺE) on November 10th, 2018, during the fruit stage of this plant, which is also the local harvest season of the rhizomes of P. cuspidatum. The cultivation years, namely 1 year, 2 year, 3 year, and 4 year, denotes the growth age of the corresponding plants which were cultured at the designated zones in March of 2018, 2017, 2016, and 2015, respectively. In detail, after removing the aerial parts, roots (top 10−20 cm depth into the soil) of three healthy P. cuspidatum were cut off by a sterilized knife and collected as one sample. Roots of each cultivation year were collected with three replicates. Meanwhile, the bulk soil (top 10−20 cm) apart from the roots was collected with three replicates. All samples were transported to the laboratory in the sterilized plastic zip-lock bags at room temperature within 6 h before temporally stored at 4 °C in the darkness. The collected roots were 2

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shaken vigorously to remove excess soil. After that, the soil that was still adhering to the roots was collected as rhizosphere soil, which was harvested from roots by vortexing them in sterile phosphate buffer (130 mM NaCl, 7 mM Na2HPO4, 3 mM NaH2PO4, pH 7.0, 0.02 % Silwet L77). After collecting the rhizosphere soil, roots were placed in new tubes with sterile phosphate buffer to vortex until they became clear. Afterwards, roots were placed in a new tube for a surface-cleaning procedure of sonication (five 30 s bursts with five 30 s gap at low intensity) according to the previous description with some modifications (Xiao et al., 2017a), and then the resulting root sample was quickfrozen in the liquid nitrogen and designated as the root endosphere. Altogether, 36 samples (3 replicates × 4 cultivation years; 12 root samples + 12 rhizosphere soil samples + 12 bulk soil samples) were taken and stored at −80 °C until DNA extraction. Metagenomic DNA was extracted from the soil samples (0.5 g for each) and the plant tissues (roots, 0.5 g each) by using the FastDNA SPIN Kit for Soil (MP Biomedicals, Solon, CA, USA) and the DNA secure Plant Kit (Tiangen Biotech, Beijing, China), respectively, in accordance with the manufacturers’ instructions. The DNA concentration and purity were estimated using a NanoDrop 2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA) before running the agarose (1 % w/v) gel electrophoresis (Lundberg et al., 2012).

of 97 % sequence identity by “pick_de_novo_otus.py” (Lundberg et al., 2012). The representative sequence was picked from each OTU and then annotated for its taxonomic affiliation by using the RDP classifier (Wang et al., 2007). In-house Perl scripts were used to analyze alphaand beta- diversity of the final set of obtained OTUs. Principal coordinate analyses (PCoA) based on weighted UniFrac distances (WUF) were implemented using the package “ape 3.4” in the R platform (v3.11) (Paradis et al., 2004). The permutational multivariate analyses of variance (PERMANOVA) were performed using the R package “vegan 2.3-0” (Dixon, 2003). This package was also used for the canonical analysis of principal coordinates (CAP) with 999 permutations. The canonical correspondence analyses (CCA) were performed using the R package “ade4 1.7-4” (Dray et al., 2007). Environmental variables were fitted using the ‘envfit’ function of package “vegan 2.3-0”. The significance of the variables was assessed with 999 random permutations. Wilcoxon rank-sum tests and linear regression were conducted with the R package “stats v3.2.4”. Those OTUs with significant variation along four cultivation years were identified with the R package “maSigPro” (Conesa et al., 2006). Statistical analyses of the co-occurrence network were carried out in the R environment, and network visualization was carried out using the interactive platform Cytoscape (Smoot et al., 2011).

2.2. PCR amplification and high-throughput sequencing

3. Results

Amplification of the V4-V5 region in the bacterial 16S rRNA gene was carried out with the primers F515 (5ʹ-GTGCCAGCMGCCGCGGTAA3ʹ) and R926 (5ʹ−CCGYCAATTYMTTTRAGTTT-3ʹ) (Peiffer et al., 2013). The total volume of the PCR reaction was 30 μL, which included 15 μL of Phusion® High-Fidelity PCR Master Mix (New England Biolabs, Ipswich, MA, USA), 0.2 μM of forward and reverse primers and approximately 10 ng of template DNA. The PCR procedure went as follows: 98 °C for 1 min, then 30 cycles of 98 °C for 10 s, 50 °C for 30 s, and 72 °C for 30 s, followed by a final extension at 72 °C for 5 min. The ensuing PCR products and a 1 × loading buffer (containing SYB green) were run on 2 % (w/v) agarose gel to ensure robust amplification, after which the products were purified with a GeneJET Gel Extraction Kit (Thermo Fisher Scientific, Waltham, MA, USA). Sequencing libraries were generated using the Illumina TruSeq DNA PCR-Free Library Preparation Kit (Illumina, San Diego, CA, USA) by following the manufacturer’s recommendations. Library quality was assessed on a Qubit@ 2.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and an Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). Finally, the library was sequenced on an Illumina HiSeq 2500 platform (Novogene, Beijing, China).

3.1. Bacterial community composition and alpha diversity A total of 2,904,453 high-quality sequences were obtained from the 36 samples, with an average of 80,679 reads per sample. By using a cutoff of > 97 % sequence identity, high-quality reads were clustered into 3063 bacterial OTUs of bulk soil, 2741 OTUs of rhizosphere, and 615 OTUs of root endosphere, respectively Table S2). At the phylum level, Proteobacteria, Acidobacteria, Actinobacteria, Chlorolexi and Gemmatimonadetes were the most abundant phyla of bulk soil and rhizosphere microbiome, while Proteobacteria was the most predominant one in the root endophyte (Fig. 1a). The alpha diversity significantly varied along with the sampling compartments (bulk soil, rhizosphere, and root endosphere) by the Wilcoxon rank-sum test (Fig. 1b and c; Table S3). The mean ShannonWeiner index and observed species decreased sequentially in the following order: bulk soil, rhizosphere, and root endosphere. Although no significant change was observed with cultivation years in the root endosphere samples, the alpha diversity of 1-year bulk soil and rhizosphere microbiome was significantly lower than those of 2-, 3- and 4year counterparts (Figure S1). These data indicated that the cultivation year has great impact on the alpha-diversity of the rhizosphere microbiome other than the endosphere microbiome.

2.3. Soil properties and natural product extraction The soil properties of bulk soil were analyzed by using routine methods (Xiao et al., 2017b), including soil pH, and the contents of organic carbon (C), total nitrogen (N), total phosphorus (P) and total potassium (K) content (Table S1). The comparative analysis of soil properties among samples was conducted by the methods of analysis of variance (ANOVA) and the Tukey test at the SPSS software 18.0 (SPSS Inc, Chicago, IL). Polydatin, resveratrol, emodin, and physcion of roots were extracted and detected according to previous studies (Chen et al., 2013; Zhang et al., 2019).

3.2. Microbiome community variation among sampling compartments The PCoA analyses were conducted to evaluate the relatedness in the composition of bacterial communities by using WUF and BrayCurtis distance (Fig. 2a and b). The results showed that microbiome communities were clearly distinct along different sampling compartments. However, no obvious cluster was formed based on cultivation years (Figure S2). Consistently, PERMANOVA analysis supported that the composition of the microbiome community significantly varied among different sampling compartments based on WUF and Bray-Curtis distance (WUF: 11.70 %, P = 0.009; Bray-Curtis: 13.26 %, P = 0.008; Table S4). Cultivation year contributed 6.71 % (P = 0.063) and 7.02 % (P = 0.040) of the variation in regard to WUF and Bray-Curtis distance, respectively (Table S4). The results of CAP analysis (Fig. 2c and d) were consistent with those of PERMANOVA analysis, indicating that the significant variation of microbiome community was influenced by both the compartment and the cultivation year (Bray-Curtis: 14.35 %, P = 0.043; WUF: 15.36 %, P = 0.048). When controlling the cultivation

2.4. Data analysis Raw reads were filtered by QIIME (Quantitative Insights Into Microbial Ecology) quality filters (Bokulich et al., 2013). The remaining reads from the original DNA fragments were merged using the FLASH tool (Magoč and Salzberg, 2011). Paired-end reads were assigned to each sample according to unique barcodes with QIIME (Caporaso et al., 2010). Operational taxonomic units (OTUs) were defined at a threshold 3

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the rhizosphere, the compositions of root endosphere microbiomes were relatively stable. Soil pH, cultivation year, and C content only contributed 38.99 % (P = 0.001; Fig. 3d) of variance in the root endosphere community compositions, among which soil pH contributed the greatest part of variation (r2 = 54.29 %, P = 0.016, Table S5). Furthermore, the WUF and Bray-Curtis distance between the microbiome of root endosphere were significantly smaller than that of the rhizosphere and bulk soil by the Wilcoxon rank-sum test (Figure S3 and Table S6). These data suggested that the assembly of the rhizosphere microbiome was influenced by two major contributors, the cultivation year and the soil properties. In contrast, the assembly of the root endosphere microbiome presented a relatively stable pattern. Next, we compared the distribution of the top 17 OTUs of bacteria in the rhizosphere (Fig. 4a and Table S7) and root endosphere (Fig. 4b and Table S8). The top 17 OTUs in the rhizosphere were 45.66 % of the rhizosphere microbiome and were 71.14 % in the endosphere. The top 17 OTUs in the endosphere, accounting for 94.50 % of microbiome in the root endosphere, were a small proportion of microbiome in rhizosphere (8.65 %). These results suggest a potential enrichment of specific microbes in endosphere from rhizosphere. In all these OTUs, only three OTUs, OTU_5087, OTU4872 and OTU_2, exhibited no significant variation between the endosphere and rhizosphere microbiome (P > 0.05, Table S8). Among the remaining OTUs, OTU_1 (Stenotrophomonas) is the dominant OTU in the root endosphere (accounting for 61.73 %), which occurred in the rhizosphere with a relative abundance of 3.47 %. In root endosphere, OTU_1265 (6.72 %), OTU_1846 (2.82 %), OTU_3254 (0.76 %) and OTU_5367 (0.75 %) all fell into Stenotrophomonas, accounting for 0.51 % in rhizosphere. On the genus level, the relative abundance of root endosphere Stenotrophomonas exhibited no significant difference between different cultivation years by one-way ANOVA with Tukey HSD (P < 0.05) using SPSS v18.0 (Fig. 4c). Whereas, the relative abundance of rhizosphere Stenotrophomonas was significantly more abundant in the third cultivation year than the first year (Fig. 4c). Notably, it was suggested that the dominant endosphere bacteria, Stenotrophomonas, were specifically recruited from the rhizosphere microbiome with a 15 times increase of relative abundance (mean of Stenotrophomonas in endosphere: 69.72 %; mean of Stenotrophomonas in rhizosphere: 4.57 %). Since the recruiting of a unique root endosphere microbiome is correlated to its secondary metabolism (Köberl et al., 2013), it would be appealing to understand whether and how the enrichment of Stenotrophomonas correlated to the accumulations of the bioactive compounds in roots of P. cuspidatum. To further explore the mechanism of bacterial recruitment in the root endosphere, we determined the contents of polydatin, resveratrol, emodin and physcion in root by HPLC method, showing that the contents of the latter three compounds in root are varied among 4 cultivation years (Table S9). The linear regression model showed that the content of emodin positively correlated with the relative abundance of rhizosphere Stenotrophomonas (Fig. 4d; Figure S4), suggesting emodin may contribute to the recruitment of Stenotrophomonas in the endosphere.

Fig. 1. The microbial community colonized in bulk soil, rhizosphere and the root endosphere. (a), the relative abundance on phylum level. The boxplot of Shannon–Weiner index (b) and observed species (c) of the microbiome colonized in bulk soil, rhizosphere, and root endosphere. “S”, “R” and “E” represent bulk soil, rhizosphere and root endosphere respectively.

year, the compartment contributed 7.97 % of the variation (P = 0.065) based on Bray-Curtis distance by the partial CAP analysis (WUF: 6.37 %, P = 0.084). When controlling compartment, the cultivation year contributed 7.39 % of the variation based on Bray-Curtis distance (P = 0.085; WUF: 7.98 %, P = 0.069). These results indicated that the beta diversity of the microbiome significantly varied along with sampling compartments and cultivation years. 3.3. The stability and recruitment of root endosphere microbiome Considering the significant variation among bulk soil, rhizosphere and endosphere microbiome, the canonical correspondence analyses (CCA) were conducted separately to investigate the potential relationships between the beta-diversity of microbiome and environmental factors (cultivation year, soil pH, the content of C, N, K and P) based on Bray-Curtis distance (Fig. 3 and Table S5). The CCA analyses showed that the microbiome composition of bulk soil was significantly influenced by soil pH, and the content of C, N and K, which explained 80.03 % of variance (P = 0.001; Fig. 3a), demonstrating that pH and K content were the two predominant influential soil physicochemical properties (Table S5). The composition of the rhizosphere microbiome was significantly influenced by the cultivation year, soil pH, C, N, and K content (P = 0.001; Fig. 3b). Variation partitioning allows us to determine the relative contributions of cultivation year and edaphic factors (soil pH, the content of C, N and K) to rhizosphere microbiome composition (Fig. 3c). These two components together explained 61 % of the variation in the rhizosphere microbiome composition. 44 % of this variation arose from the edaphic factors (soil pH, C, N and K). The collective effect accounted for 14 % of the variation, while pure cultivation year amounted to almost 3 %. Compared with the bulk soil and

3.4. Associations between root-associated microbes and environmental variables By employing MaSigPro, OTUs with significant variances among different cultivation years in rhizomicrobiome were detected and were classified into 4 clusters (Figure S5 and Table S10). In the first cluster (6 OTUs), the abundance of Enterobacteriaceae and Pseudomonadaceae were significantly enriched in the first year. In the second cluster (22 OTUs), Enterobacteriaceae, Pyrinomonadaceae, Desulfarculaceae, Chitinophagaceae, and Gemmatimonadaceae were significantly abundant in the third and fourth years. In the third cluster (13 OTUs), Xanthobacteraceae, Hyphomicrobiaceae, and Beijerinckiaceae were significantly abundant among the subsequent years when compared with the first year. In the fourth cluster (6 OTUs), Xanthobacteraceae, Rhizobiaceae, and Acidiferrobacteraceae were significantly enriched in 4

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Fig. 2. The principal coordinates analysis (PCoA) and canonical analysis of principal coordinates (CAP) of all samples using weighted Unifrac distance (WUF) and Bray-Curtis distance. (a), PCoA using WUF; (b), PCoA using Bray-Curtis distance; (c), CAP using WUF; (d), CAP using Bray-Curtis distance. “S”, “R” and “E” represent bulk soil, rhizosphere and root endosphere respectively.

that the rhizosphere microbiome responds dynamically to the changing soil physicochemical properties.

the second and third years. These results further demonstrated that the assembly of rhizosphere microbiome varied across different cultivation years. To further uncover the correlation of rhizosphere microbiome and soil physicochemical properties, the top 30 genera (account for 86.84 %, 88.01 % and 98.20 % of total bulk soil, rhizosphere, and endosphere microbiome, respectively) were then selected to calculate the Spearman’s rank correlation coefficient with soil physicochemical properties (Figure S6). In the rhizosphere, Acinetobacter was positively correlated with soil C content. Bacillus, Flavobacterium, Geobacter, Pantoea, Phyllobacterium, Sphingomonas, and Stenotrophomonas were positively correlated with soil K content. Acinetobacter, Bacillus, Flavobacterium, Pantoea, and Sphingomonas were positively correlated with soil N content (Figure S6). Bacillus and Streptomyces were positively correlated with soil P content, while Pseudomonas was negatively correlated with soil P content (Figure S6). Acidibacter, Arthrobacter, Bradyrhizobium, Bryobacter, Gemmatimonas, Haliangium, Pseudolabrys, and Streptomyces were negatively correlated with soil pH, while Klebsiella and Pseudomonas were positively correlated with soil pH. In the root endosphere, Bryobacter was negatively correlated with soil C content, whereas Phyllobacterium and Streptomyces were positively correlated with soil pH (Figure S6). Collectively, these data suggested

3.5. Relationships between root-associated microbiome and the contents of bioactive components To gain insights of the relationship between the bioactive components and rhizosphere microbiome, we performed network analysis based on the spearman’s correlation (P < 0.05) between the relative abundance of each genus (relative abundance > 0.5 %) and the content of polydatin, resveratrol, emodin and physcion (Figure S7a). The content of emodin positively correlated with the relative abundance of Stenotrophomonas, Hyphomicrobium, Sphingomonas, Pedomicrobium, Dokdonella, Nordella, Mesorhizobium, Phyllobacterium and others (Figure S7b). The relative abundance of Rhodomicrobium, Aquicella and Pedomicrobium were both negatively correlated with the content of resveratrol and polydatin (Figure S7b), suggesting the potential function of bioactive components in the recruitment of microbiome in endosphere. In the root endosphere, the relative abundance of Achromobacter is significantly increased along with the increasing amount of polydatin, while an unidentified Roseiflexaceae exhibits an opposite correlation 5

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Fig. 3. The correspondence analysis and redundancy analysis (CCA) of samples in bulk soil (a), rhizosphere (b), and root endosphere (d) using Bray-Curtis distance. (c) Variation partitioning analysis, illustrating the effects of cultivation year and edaphic factors (soil pH and the content of C, N and K) on the community structure of rhizosphere microbiome. Each ellipse represents the portion of variation accounted by each factor. Shared variance is represented by the intersecting portions of the ellipses.

Fig. 4. Asymmetrical distribution of OTUs in the rhizosphere and the root endosphere microbiome. (a) Cumulative histogram of the top 17 rhizosphere OTUs and their distributions in the rhizosphere and the root endosphere, respectively. (b) Cumulative histogram of the top 17 root endopshere OTUs and their distributions in the rhizosphere and the root endosphere, respectively. Red bars represents the relative abundance of OTUs in endosphere. Blue bars represents the relative abundance of OTUs in rhizosphere. The differences of relative abundance of OTUs between endosphere and rhizosphere were compared by using Wilcoxon rank-sum test (**: P < 0.01; *: P < 0.05; ●: P < 0.1). (c) The relative abundance of Stenotrophomonas in bulk soil, rhizosphere and root endosphere across different cultivation years. The differences of relative abundance of Stenotrophomonas between different cultivation years were compared by using one-way ANOVA. Different letters represent significant difference (P < 0.05). (d) The relative abundance of Stenotrophomonas in rhizosphere significantly correlated with the content of emodin by the linear regression analyses.

(Fig. 5a). The relative abundance of Acinetobacter, Bacteroides, Erysipelatoclostridium and Achromobacter increased along with the content of resveratrol, while the opposite of unidentified Roseiflexaceae (Fig. 5b). The relative abundance of Acinetobacter, Ralstonia, Micrococcus, Erysipelatoclostridium, Staphylococcus, Phyllobacterium, and unidentified Prevotellaceae significantly decreased along the content of emodin by linear regression (Fig. 5c and d). The relative abundance of Micrococcus, unidentified Prevotellaceae and Deinococcus significantly decreased along with the content of physcion (Fig. 5e).

4. Discussion 4.1. Different response of rhizosphere and root endosphere microbiome to environmental factors

2018; Lauber et al., 2009; Rousk et al., 2010; Zhao et al., 2018). Soil pH may directly favour specific species with proper pH range or indirectly influence related variables such as the concentration of calcium and other properties (Christian et al., 2009; Bahram et al., 2018). For instance, global research of topsoil microbiomes demonstrated that taxonomic diversity, composition, richness and biomass strongly responded to soil pH (Bahram et al., 2018). Furthermore, the major phyla of soil microbiome differently responded to soil pH, such as Acidobacteria favouring acidic conditions, and Proteobacteria dominating in higher pH soils (Ren et al., 2018). Our data showed that the P. cuspidatum root endosphere microbiome is only significantly influenced by soil pH, but not by other soil properties and cultivation year. The cultivation year exhibited significant but small influences on the rhizosphere microbiome. Based on variation partitioning, only 3 % of variation was contributed by pure cultivation year. Crop age was reported that has significant effect on tissues (leaf, stalk, roots and rhizosphere soil)- associated microbiome in sugarcane, lettuce, wheat, maize, sweet potato, cabbage, soybean, and grapevine (Hamonts et al., 2018; Novello et al., 2017; Xiao et al., 2017a). Researchers defined crop age in different criteria relied on plant growth stages, for instance, development stage, flowering stage

It has been generally accepted that soil physicochemical properties strongly associates with the composition of the rhizosphere microbiome community (Breidenbach et al., 2015; Philippot et al., 2013; Qiao et al., 2017). In this study, although all the fields where P. cuspidatum were planted were in a 25-square-kilometer area, the soil physicochemical properties of the four separate fields were with significant differences (Table S1). The soil where the 1-year-old P. cuspidatum grown in is more alkaline than the soil where other P. cuspidatum grown in (weak acid). According to the results of CCA analyses, the compositions of the rhizosphere microbiome and bulk soil microbiome are significantly coordinated by soil pH and the content of C, N, K. Soil pH is the greatest influencing factors that driven the structure of rhizosphere microbiome (Fig. 3; Table S5: r2 = 0.95, P = 0.001) and the second-largest influencing factors of bulk soil microbiome (Fig. 3; Table S5: r2 = 0.9656, P = 0.001). Therefore, the heterogeneity of soil properties may explain the striking differences in alpha-diversity of bulk soil and rhizosphere microbiome between the first and the next years, which is consistent with previous studies. It has been well documented the importance of soil pH in structuring soil and rhizosphere microbiome (Bahram et al., 6

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the relative abundance of Bacillus (P = 0.2705). The results further suggested that the strong selection effect of roots was essential for P. cuspidatum growth, on the other hand, suggesting that P. cuspidatum harbour an invasive root system with strong adaptability. Generally, the assemblies of the root endosphere and rhizosphere microbiome of P. cuspidatum present distinct patterns. 4.2. The relationship between Stenotrophomonas and P. cuspidatum In this study, the results showed that OTUs belong to Stenotrophomonas were specifically enriched in the root endosphere of P. cuspidatum. Stenotrophomonas have been mostly isolated from the rhizosphere and the root endosphere of a variety of plant species, including cucumber, oilseed rape, potato, strawberry, alfalfa, cabbage, mustard, chili, sunflower, maize, rice, wheat, willow and poplar (Berg and Martinez, 2015; Etminani and Harighi, 2018; Mukherjee and Roy, 2016). Most of these studies suggested that Stenotrophomonas promotes the growth of plants particularly in the marginal and polluted soil through stimulating the production of the plant hormone indole acetic acid, chitinase, and siderophore, promoting the nitrogen fixation and increasing the disease resistance (An and Berg, 2018; Berg and Martinez, 2015; Mukherjee and Roy, 2016). In the highly salinized areas of Uzbekistan, Stenotrophomonas could contribute up to 180 % of plant growth promotion in crops like wheat, tomato, lettuce, sweet pepper, melon, celery and carrot (Ryan et al., 2009). Therefore, we speculated that the recruitment of Stenotrophomonas in the root endosphere may play a vital role in facilitating the growth and adaptation of P. cuspidatum. Furthermore, various Stenotrophomonas strains have been shown to produce an extensive range of organic compounds that are present in the rhizosphere, which play a vital role in phytoremediation (Lee et al., 2002; Mukherjee and Roy, 2016). For instance, S. maltophilia R551-2 could improve the growth and phytoremediation potential of poplar on the toluene contaminated soils (Mukherjee and Roy, 2016; Taghavi et al., 2005). S. maltophilia Sm777 tolerates high levels of various toxic metals, such as Cd, Pb, Co, Zn, Hg, Ag, selenite, tellurite and uranyl, contributing to the alleviation of heavy metal toxicity and supporting plant growth (Pages et al., 2008). Stenotrophomonas sp. RC5 has been shown to tolerate Al, which was isolated from the rhizosphere and the endosphere of ryegrass in the acidic Chilean volcanic soil (Mora et al., 2017). In this study, the abundance of Stenotrophomonas were relatively stable across different cultivation years and soil properties, supporting that the root endospheric Stenotrophomonas assist the growth of medicinal plant P. cuspidatum. Our results exhibited a positive relationship between the relative abundance of rhizosphere Stenotrophomonas and the content of emodin. Emodin protects plants against herbivorous insects, pathogenic microbes, competition (allelopathy), and high light intensities (Izhaki, 2002). We assumed that emodin may promote the recruitment of Stenotrophomonas in the root endosphere through either a direct way, by promoting the growth of Stenotrophomonas, or an indirect way, by inhibiting the growth of other microbes, to support the growth of P. cuspidatum (Li et al., 2016; Shan et al., 2008)).

Fig. 5. The relative abundance of genera that were significantly correlated with the contents of polydatin (a), resveratrol (b), emodin (c and d), and physcion (e).

and seed setting stage. It has been reported that plant growth stages shape the root-associated microbiome composition through root architecture and exudates (Pfeiffer et al., 2016; Philippot et al., 2013). Here, we introduced cultivation years for P. cuspidatum in this study. The root endosphere microbiome of Boechera stricta significantly varied with the host age (2, 3 and 4 years) (Wagner et al., 2016). Whereas a different pattern was observed in olive tree, which exhibited no significant variation in the relative abundance of rhizomicrobes associated with nitrogen cycling (ammonia-oxidizing archaea (AOA), bacteria (AOB), and nitrite-oxidizing bacteria (NOB)) among different ages of plantation (≤15, 15∼30 and ≥30 years) (Caliz et al., 2015). Together with our finding that the assembly of P. cuspidatum root endophytes remains relatively stable across different soil properties and cultivation years, we assumed that the stability of plant root-associated microbiome over time (cultivation years) might relate to the strong selection effect of P. cuspidatum roots. The selection effect of plantgrowth-promoting bacteria through root exudates have been intensively studied (Ankati and Podile, 2019; Berg, 2009; Feng et al., 2018; Stringlis et al., 2018; Zhou et al., 2016). Coping with this scenario, emodin and physcion in P. cuspidatum roots which were reported to exhibit a distinguished antimicrobial activity (Ma et al., 2010; Shan et al., 2008) may enhance the selection effect to maintain a relatively stable root endosphere microbiome of P. cuspidatum. Moreover, in the root endosphere, there was a positive correlation between cultivation year and the relative abundance of Bacillus, which possess the potential of plant growth promotion (r = 0.71, P = 0.0102). In the rhizosphere, no significant relationship was observed between cultivation year and

4.3. The relationships between the endosphere microbes and the contents of bioactive components In this study, significant relationships between specific endosphere microbes and the contents of bioactive compounds were observed (Fig. 5). In a previous study, the antimicrobial effect of emodin on Acinetobacter and Staphylococcus has been identified (Li et al., 2016). In line with their well-known antimicrobial activity (Li et al., 2016; Shan et al., 2008), our results agreed that the abundance of some endosphere microbes was negative correlated with the contents of emodin and physcion. Notably, our results suggested that emodin has an antimicrobial effect on Ralstonia, Erysipelatoclostridium and Phyllobacterium, while physcion has an antimicrobial effect on Micrococcus (Fig. 5). 7

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Collectively, these findings extend our knowledge of the antimicrobial spectrum of emodin and physcion. On the other hand, the relative abundance of Achromobacter is positively correlated to the content polydatin, and the relative abundance of Bacteroides, Acinetobacter, Erysipelatoclostridium, and Achromobacter is positively correlated to the content of resveratrol (Fig. 5). Previous studies have indicated that bacteria in genus Bacteroides (Ansari et al., 2017), Acinetobacter (Chaudhari Bhushan et al., 2009), and Achromobacter (Ma et al., 2009) possessed the ability of plant growth promotion, suggesting that they may be involved in the accumulation of active compounds in P. cuspidatum root. Therefore, we speculated that Bacteroides, Acinetobacter, Erysipelatoclostridium, and Achromobacter may stimulate the accumulation of resveratrol, and Achromobacter tends to promote the accumulation of polydatin in roots. In the next stage, inoculation experiments will elucidate the mechanism involved by the specific endosphere microbes in stimulating the production of particular plant secondary metabolites in P. cuspidatum.

2016QDJZR14, 2017QDJZR26, and 2018QDJZR12), the Natural Science Foundation of Hubei Provincial Department of Education (Q20182104), the Fundamental Research Funds for the Central Universities (GK201702016), Hubei Provincial Natural Science Foundation of China (2017CFB674), the Foundation of Health Commission of Hubei Province (ZY2019Q004), Open Research Fund of Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry Ministry of Education (2019005), Fund for Key Laboratory Construction of Hubei Province (2018BFC360, WLSP201905) Hubei Provincial Outstanding Young and Middle-aged Science and Technology Innovation Team Project (Grant No. T201813) and the Scientific and Technological Project of Shiyan City of Hubei Province (18Y06). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.indcrop.2020.112163.

5. Conclusion References Here, we investigated the rhizosphere and endosphere microbiome composition of the industrial plant P. cuspidatum across different cultivation years and deciphered how the microbial communities associated with the four root-derived bioactive compounds and the major soil properties. Apart from the rhizosphere microbiome, regardless of different soil physicochemical properties and cultivation years, we found that the composition of the root endosphere microbiome remains relative stable, indicating that P. cuspidatum root exhibited strong selection effect on the assembly of endosphere microbiome. Meanwhile, Stenotrophomonas in the root endosphere were specifically enriched from rhizosphere with a 15 times increase of relative abundance. Therefore, the stability of the root endosphere microbiome and the dominance of Stenotrophomonas may play a vital role in the growth of P. cuspidatum through a combining effect of emodin. The root endosphere Bacteroides, Acinetobacter, Erysipelatoclostridium, and Achromobacter may stimulate the accumulation of root resveratrol. Taken together, this study revealed a complex network among root-associated bacteria, plant secondary metabolites, and soil physicochemical properties, providing a feasible strategy to improve the industrial and pharmacological value of P. cuspidatum.

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Author contributions CL, YHZhang, XX, and GW designed the study. LZ, JZ, YZ, PH, XX, SX, JL, XH, QC, SX, CZ, YHZhao, XW, MS, XS, ZH and GW performed the research. CL, HYZhang, and XX wrote the paper. All the authors analyzed the data, discussed the results, and made comments on the manuscript. Data accessibility The 16S rDNA Illumina libraries obtained from the sequencing company were deposited at the NCBI’s small read archive (SRA) in BioProject ID: PRJNA531239. Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgments This work was funded by the National Natural Science Foundation of China (31701294, 31801210, and 31771556), the Cultivating Project for Young Scholar at Hubei University of Medicine (2016QDJZR11, 8

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