Interaction between root exudates and rhizosphere microorganisms facilitates the expansion of poisonous plant species in degraded grassland

The interaction between rhizosphere microorganisms and rhizosphere exudates is considered a ‘novel weapon’ for poisonous plants’ colonization, but the relationship between them in facilitating the expansion of poisonous plants in degraded or barren land is poorly understood. We examined this relationship in different degradation levels of alpine grasslands on the Tibetan plateau (3,700 m a.s.l) by determining the composition of root exudates, soil physical and chemical properties, rhizosphere microbial diversity and carbon metabolism of the main poisonous and non-poisonous plant species. Results Soil nutrients, including total organic carbon, total nitrogen and available phosphorous, diversity of microorganisms and microbial carbon metabolism were greater in the rhizosphere of poisonous than in non-poisonous plant species (P < 0.05). The distribution of bacteria and root exudates were plant species specic. Soil microbial communities were affected by habitat and plant species in degraded grassland, and more so for bacteria than fungi. The cell growth and death pathway for the poisonous species Ligularia virgaurea was greater than for other poisonous species (P < 0.05), and the difference increased with an increase in grassland degradation and a decrease in soil nutrients (P < 0.05), which could explain how L. virgaurea became the dominant poisonous species in degraded alpine grassland. The roots of L. virgaurea exudated such compounds as alkaloids, lupinic acid, terpenes, artemisinin, and coumarin, which were correlated positively with different bacteria in different habitats.


Introduction
Root exudates of plants and rhizosphere microorganisms alter the soil environment to aid plants compete for nutrients and to allow their offspring to be more viable [1,2,3,4,5]. The rhizosphere contains a large number of microorganisms, which participate in regulating the physiology and morphology of plants, in enhancing the growth of plants by producing phyto-hormones, and in protecting plants against pathogens [4,6]. In addition to the carbon and nitrogen substrates that represent microbial growth, root compounds have multiple effects on inter-root microbes by acting as signaling agents, inducers, stimulants, inhibitors and repellents [7], thereby regulating soil conditions for themselves and other plants, including their own offspring. The interaction between rhizosphere microorganisms and rhizosphere exudates is considered a 'novel weapon' of poisonous plant species to adapt to degraded grassland and may be an important mechanism in allowing them to spread [8,9,10,11,12,13].
The spreading of poisonous plants in degraded grassland is a global problem and is a result, at least in part, of global warming and over-grazing by livestock [25]. The problem is particularly acute on the Tibetan plateau [26, 27,28], which comprises approximately 77% of the 4504⋅10 4 ha of the degraded grassland in China [29]. In the grassland ecosystem, native poisonous plant species increase and expand aggressively with degradation and barren soil and gradually become the dominant species in the community (Additional le 1: Figure S1). The expansion of poisonous plant species is not only con ned to the natural degraded grassland, but is also evident in sown grassland on the Tibetan plateau [30,31,32,33] (Additional le 1: Figure S1).
In the grassland ecosystem, studies on poisonous plant species have focused on their high nutrient use e ciency and strong competitive ability when compared to other plant species [27,28,34], allelopathy [11], and morphological and physiological traits [35]. Poisonous plant species are more e cient in utilizing N in poor nutrient soil than sedges and grasses, which may have been their survival mechanism in alpine grassland [28]. However, during the spreading of poisonous plants, self-reinforcing is a key driving force in degraded grassland [4,8,36], with the interaction of root exudates and rhizosphere microorganisms a key factor in the process [4,24,37]. We hypothesized that the exudate from roots of poisonous plant species contain more compounds for speci c microorganisms to promote self-growth than non-poisonous plant species. To test this hypothesis, we analyzed the speci city of root exudates and rhizosphere microorganisms in poisonous and non-poisonous plant species in alpine grasslands of different levels of degradation.

Study sites and design
The study site was located at the headwater region of the Yellow River in the eastern Tibetan plateau in Marqin County, Guoluo Tibetan Autonomous Prefecture, Qinghai Province (34°28′N, 100°12′E) (Additional le 1: Figure S1). The site is 1.5 km 2 in size, approximately 3720 m a.s.l., and has a highland continental climate with no absolute frost-free days. Annually, average temperature is -0.1-1.2℃, average precipitation is 463-602 mm, evaporation is approximately 1460 mm, and total sunshine is 2272-2632 h. The grassland type is alpine meadow [32,37,38]. The dominant plant species of native grassland are Kobresia pygmaea, Stipa spp. and Kobresia humilis. Traditionally, the site is used for winter grazing of yak and sheep from December to March. We previously studied grassland degradation processes, soil nutrients and vegetation regeneration at the same site [32,37,38,39].
The study site included grasslands at different levels of degradation. In the process of degradation, small bare patches form, and poisonous plants appear in the patch [40]. With the spreading of the poisonous plants, the bare patch enlarges [40], the sward layer disappears and often only poisonous plants occupy the degraded grassland. Heavily degraded grassland is known as 'bare land' and the level of degradation is based on the ratio of bare land to living sward [33,40]. Lightly (L), moderately (M) and heavily (H) degraded native grassland, and degraded sown grassland (S) were selected (Additional le 1: Appendix S1). The degraded sown grassland was restored 'bare land' (heavy degraded grassland) more than 10 years ago, but became degraded again with the invasion and spreading of poisonous plants [38, 39].

Vegetation survey and root, soil sampling
Field sampling was done in August, 2017, and August, 2018, when alpine plants reached peak growth. Four sampling plots at each level of degradation were selected randomly. The distance between any two plots was greater than 100 m, which exceeded the spatial dependence of microbial variables [41], and thus the samples in each plot were independent. Three sub-plots, with more than 20 m between any two, were selected in each plot. Fifteen random quadrats (50 cm × 50 cm) in each sub-plot were selected to record plant cover, height and composition [42]. In some cases, there were the same poisonous plant species in different habitats (different levels of degradation) and the same habitat had different poisonous plant species.
After the vegetation survey, some plants with high frequency and coverage were selected (Additional le 1: Table S1). Rhizosphere soil was collected for Morina kokonorica in L; Aconitum pendulum, Ajuga lupulina, Euphorbia sheriana, Ligularia virgaurea, and M. kokonorica in M; A. lupulina, E. sheriana, Sphallerocarpus gracilis, L. virgaurea, M. kokonorica, Artemisia dubia, Artemisia nanschanica, and A. pendulum in H; and, L. virgaurea, M. kokonorica, Oxytropis ochrocephala, S. gracilis, and Pedicularis kansuensis in S (Additional le 1: Figure S1; Additional le 1: Table S1). In addition, bulk (nonrhizosphere) soil was collected in each habitat as control. In total 66 samples (3 replicates) in 4 habitats were collected in 2017, 6 in L, 18 in M, 27 in H and 15 in S. Rhizosphere and bulk soils were used to determine the microbial community and microbial carbon metabolism. Rhizosphere soil and root exudation were collected from L. virgaurea, M. kokonorica,and Kobresia pygmaea in L; A. pendulum and L. virgaurea in M; L. virgaurea in H; and, P. kansuensis, Elymus nutans and low (< 120 plants/m 2 ), medium (120-240 plants/m 2 ) and high (> 360 plants/m 2 ) densities of L. virgaurea in S (Additional le 1: Figure  S1; Additional le 1: Additional le 1: Table S1). In total 22 samples (3 replicates) in 4 habitats were collected in 2018, 9 in L, 6 in M, 3 in H and 15 in S. The rhizosphere soil was used to determine the microbial community.
The rhizosphere soil was collected as described by Edwards et al. [43]. In brief, the whole plant was dug up with a shovel, the soil around the root was removed by shaking, and the soil within 2 mm of the root surface was shaken into a sterile ziplock bag and mixed well. Roots and litter were removed manually, and then a small amount of soil was placed into a 3 mL sterile centrifuge tube, which was kept in liquid nitrogen, for determining the diversity of the soil microbial community. The remaining soil was divided into two parts: one was brought to the laboratory with an ice pack, and refrigerated at 4 ℃ for determination of soil microbial carbon metabolism and the other was air-dried and then put through a 2mm sieve. Nine soil core samples (3.5 cm in diameter) at a depth of 0-10 cm were collected at each sampling plot, mixed and homogenized, and three core soil samples were combined into one composite sample. This soil sample was termed 'bulk soil' and was free from the in uence of plants. Fifteen individual plants of each poisonous species were collected, the roots were rinsed with distilled water and then immersed in 500 mL distilled water for 10 h, and all extraction was placed into a 100 mL plastic bottle. The extraction was refrigerated at 4 ℃, and then the root exudates were measured as soon as possible.

Soil chemical properties
Soil pH was measured using a pH meter (Sartorius PB-10, Goettingen, Germany) in a 1:2.5 soil:water solution (w/v). Soil total N (TN) was determined by the micro-Kjeldahl method with digestion in H 2 SO 4 followed by steam distillation. Soil total phosphorous (TP) was digested with HF-HClO 4 and ammonium and nitrate were extracted by 2 mol/L potassium chloride. TN, TP, ammonium and nitrate were measured with ow injection analyzer (FIA star5000 Analyzer, Höganäs, Sweden). Soil total organic carbon (TOC) content was determined by wet digestion using the potassium dichromate method and available P (AP) was determined using the molybdenum-blue method by UV spectrophotometer (HITACHI U-2910, Tokyo, Japan) after extraction with sodium bicarbonate.

Microbial community sequencing and data processing
To extract DNA from soil samples, the E.Z.N.A. Soil DNA Kit (Omega Bio-tek, Norcross, GA, U.S.) was used according to the manufacturer's protocol. Illumina sequencing was performed by amplifying the V4/V5 region of the bacterial 16S rRNA gene using individually bar-coded forward primers 515F (5'-GTGCCAGCMGCCGCGG-3') and reverse primers 907R (5'-CCGTCAATTCMTTTRAGTTT-3') and ITS1 region of ITS using individually bar-coded forward primers ITS1F (5'-CTTGGTCATTTAGAGGAAGTAA-3') and reverse primers ITS1R (5'-GCTGCGTTCTTCATCGATGC-3'). PCR reactions were done in triplicate 20 µL mixtures containing 4 µL of 5 × FastPfu Buffer, 2 µL of 2.5 mM dNTPs, 0.8 µL of each primer (5 µM), 0.4 µL of FastPfu Polymerase, and 10 ng of template DNA. Amplicons were extracted from 2% agarose gels, puri ed according to the manufacturer's instructions and quanti ed using QuantiFluor™-ST (Promega, U.S.). The PCR conditions were as follows: 95°C for 2 min, followed by 25 cycles at 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s and a nal extension at 72°C for 5 min. Puri ed PCR products were quanti ed by Qubit®3.0 (Life Invitrogen). The pooled DNA product was used to construct an Illumina Pair-End library following Illumina's genomic DNA library preparation procedure. The amplicon library was pairedend sequenced on an Illumina HiSeq 2500 according to standard protocols.
Raw fastq les were demultiplexed and quality-ltered using QIIME (version 1.17). Operational Units (OTUs) were clustered with 97% similarity cutoff using usearch and chimeric sequences were identi ed and removed by denovo. The rarefaction curves of alpha diversity index were drawn by QIIME. The phylogenetic a liation of each 16S rRNA gene sequence was analyzed by sortmerna against the Greengene (16S rRNA) database. After classi cation, the OTU abundance table was obtained according to the number of sequences in each OTU, and subsequent analysis was done according to the OTU abundance table [44].

Microbial carbon metabolism assay
Soil microbial carbon source metabolism was determined using Biolog-Eco plates. Ten g soil were placed in a 250 mL conical bottle, 90 mL sterile saline (0.85% NaCl solution) were added, the conical bottle was sealed with sealing lm, shaken at 200 r/min at 25°C for 30 min and left to stand for 10 min. The supernatant was brought to 10 3 nal dilution before inoculation [45]. Then 150 µL of diluted supernatant were added to the microplate and placed in an incubator at 25℃ in the dark for 9 days. Absorbances at 590 nm and 750 nm were measured every 24 h with a microplate reader, and the distribution of 31 carbon sources in Biolog-Eco plates were identi ed (Additional le 1: Table S2).
The relative absorbance of each carbon source pore indicates the ability of the microbial community to utilize the carbon source. The average well color development (AWCD) of the pores re ects the average metabolic capacity of the microbial community with 31 carbon sources, indicating the overall metabolic activity of the microorganisms. The calculation of AWCD was as follows: where C i is the absorbance at 590 nm minus 750 nm of each carbon source hole, and R 0 is the absorbance of the control hole.

Root exudation determination
A liquid chromatograph mass spectrometer (Ultimate 3000LC, Q Exactive Thermo Fisher Scienti c, San Jose, CA, USA) was used to measure the composition of root exudation. Five mL of exudate were freezedried, 300 µL of methanol and 10 µL of internal standard (3 mg/mL, dichlorophenylalanine) were added, homogenized for 1 min, centrifuged at 12000 rpm for 15 min at 4 ℃, and 200 µL of supernatant were transferred into a vial. Compounds with positive and negative ion modes were determined with a Hyper Gold C18 column (100 mm × 2.1 mm, 1.9 µm). Column temperature was 45℃, the ow rate was 0.35 mL/min and mobile phase composition A was: water + 5% acetonitrile + 0.1% formic acid, and B was: acetonitrile + 0.1% formic acid. The injection volume was 10 µL and auto-sampler temperature was 4℃. The compound databases (Predicted Compositions, mzCloud Search, ChemSpider Search) were used for comparison.

Statistical analyses
One-way analysis of variance (ANOVA) for three or more treatments, or T-test for two treatments were used to test for differences among or between means (SPSS 25.0, SPSS Inc., Chicago, IL, USA). Statistical analysis and graphing were done with R 3.6.1 and Origin 2018, and principal component analysis (PCA), principal coordinates analysis (PCoA) and redundancy analysis (RDA) were done in R. Structural equation modelling (SEM) used AMOS Graphics based on the site score of the rst axis of PCoA for bacterial communities, and PCA for root exudates and AWCD. Bacterial communities were based on weighted UniFrac distances, PCA of root exudates and AWCD based on Bray-Curtis distances. Data of soil physico-chemical properties were log transformed. The initial model was simpli ed by a stepwise removal of uninformative paths, until a suitable model was generated. In addition, modi cation indices were used to identify missing paths. The χ2 test and the root mean square error of approximation (RMSEA) tested the overall goodness of t, which is indicated by a low χ2 and a high probability (P > 0.05), and a RMSEA near 0.

Network construction and visualization
The scale function standardized the original data and then the network analysis of microbial communities and root exudates were completed with weighted gene co-expression network analysis (WGCNA) in R. To reduce the redundancy of data, some values with little information were removed, and the mad function in R was used to screen the OTU/exudation (75% before the median absolute deviation and greater than 0.01). The network was constructed as an unsigned type, and the Pearson correlation coe cient was used to test for relationships. To make the constructed network conform more to the scale-free feature, the appropriate soft threshold was calculated to complete the integration of the modules. OTUs/exudations were classi ed into modules, which were represented by different colors.
Correlation analysis was employed between modules (module eigengenes, ME) and plant species after modules merged. The adjacency and colSums functions in the WGCNA package were used to calculate the connectivity of the nodes. The Pearson correlation coe cient was used to determine the relation between root exudates and microorganisms. The accepted signi cance was P < 0.05, and holm was used for multiple test adjustment. The visualization of the network was completed by Cytoscape 3.7.0 [46], which only showed the nodes and edges with signi cant correlations. The colors of nodes were consistent with the colors of the module where they were located.

16S rRNA gene amplicon analysis
Potential microbial biomarkers were obtained by the linear discriminate analysis (LDA) effect size (LEfSe) method (http://huttenhower.sph.harvard.edu/lefse/), using 16S rRNA gene sequences to calculate the metabolic cycles and pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) with picrusts (http://huttenhower.sph.harvard.edu/galaxy/picrusts/) [47]. Bray-Curtis, considered the evolutionary distance between species, was used to analyze the main coordinates of the samples and to identify the differences.

Soil microbial community carbon metabolism
The AWCD of all samples increased with incubation time (Fig. 1A) and of the rhizosphere microorganisms of poisonous plant species was higher than the bulk (non-rhizosphere) soil in the four levels of degraded grassland. This indicated that rhizosphere microorganisms of poisonous plants had higher metabolic activity and could make better use of the carbon source in the Biolog-Eco plates. The AWCD reached maximum rate within 48-96 h, and the 72 h measurements were used for PCA (Fig. 1B). The values of the rst principal component in the four degraded grasslands of S, H, M, and L were 54.2%, 50.5%, 48.5%, and 47.0%, respectively, and indicated that the microorganisms of different plant rhizospheres and bulk soil used carbon sources differently (Fig. 1B).
There were 12, 13, 11, and 13 carbon sources that were signi cantly (P < 0.05) related to principal component 1 in S, H, L, and M, respectively (Additional le 1: Table S3). Except for D-xylose, which was correlated negatively with L (P < 0.05), all were correlated positively. The microorganisms in S had greater metabolic activity for amino acids than other carbon sources. The rhizosphere microorganisms in each degraded grassland used six more types of carbon sources than bulk soils, and the utilization e ciency of amino acids by soil microbes was greater than for other carbon sources (P < 0.05) ( Table 1). In L grassland, bulk soil had a higher utilization e ciency for carbohydrates, while rhizosphere soil had a higher utilization e ciency for phenolic acids (P < 0.05) ( Table 1).   (Fig. 2). The bulk soil of L grassland had the lowest α-diversity indices of bacterial and fungal communities across all samples (Kruskal-Wallis with Kruskal.test, P < 0.05) (Fig. 3a).
If roots establish stable associations with microbial communities across different habitats, a strong hostltering effect on habitats is expected. Analysis of microbial community structure based on average Bray-Curtis distances across the 4 degraded grasslands revealed that bacterial and fungal communities in bulk soil and in rhizosphere clustered by grassland type (Figs. 3a and 3c). This pattern was corroborated by permutational multivariate analysis (PERMANOVA) of variance with Bray-Curtis distances (Adonis function in R library vegan), which indicated that species × habitat explained more of the variation in  (Fig. 3b). The bacterial community was affected to a greater extent than the fungal community by habitat and species.
PCoA ordinates based on Bray-Curtis distances revealed marked differences in soil bacterial and fungal communities in the 4 habitats. The bacterial community in M and the fungal community in S, in particular, were separated clearly from the others. These differences appeared in the same plant species in different habitats, suggesting divergence in the microbial community composition in plant rhizosphere (Fig. 3c).
Nitrate nitrogen (NO 3 -N) in L grassland was lower than the other three habitats (P < 0.05), while ammonium nitrogen (NH 4 -N) exhibited an opposite trend (Fig. 4a). The concentrations of TN, AP and TOC in bulk soil of the four habitats were lower than in the rhizosphere soil (Additional le 1: Table S4).
Redundancy analysis showed that soil physico-chemical properties explained 28.3% of the variation in rhizosphere bacterial communities (Fig. 4b) (P < 0.05), but had no effect on fungal communities. The bacterial communities were correlated positively with TP, pH and AP, but negatively with TN, TOC, NO 3 , NH 4 and WC (Fig. 4b).  Figure S2) and of L. virgaurea in the four habitats (Fig. 5c). The rhizosphere of poisonous plant species enriched more microbial taxa than bulk soil or rhizosphere of high-quality grasses (E. nutans and Kobresia pygmaea) (Additional le 1: Figure S2). Bulk soil enriched more taxa than rhizosphere in M, especially Acidobacteria, Chloro exi and Gemmatimonadetes (Fig. 5a).

Functional prediction analysis in rhizosphere microbial communities
Cell growth and death pathways of KEGG level 2 in L. virgaurea were greater than in other poisonous plant species (P < 0.05) (Fig. 6) and in H and M were greater than in S and L (P < 0.05) (Fig. 6). For the three poisonous plant species in S, except for the cell growth and death pathways, other pathways in L. virgaurea were signi cantly lower than in E. nutans and P. kansuensis (Fig. 6a). Pathway metabolism of terpenoids and polyketides in Morina kokonorica was lower than in K. pygmaea and E. nutans in L (P < 0.05). Metabolism of co-factors and vitamins in L. virgaurea was lower than in M. kokonorica and K. pygmaea (P < 0.05) in L (Fig. 6b), but of amino acids and carbohydrates were higher than in Aconitum pendulum (P < 0.05) (Fig. 6c). The cell motility and signal transduction in L. virgaurea in S was higher than in H, L and M (P < 0.05) (Fig. 6d).

Relationship of modules of root exudates and rhizosphere bacterial community
In total, 3613 effective OTUs and 1092 root exudates were obtained for network construction after screening. After the mad function removed unimportant values, the sample clustering results were consistent. There was similarity in results between OTU and root exudates, in which L. virgaurea was signi cantly different (P < 0.05) from the other poisonous plant species (Figs. 7 and S4). The rhizosphere microorganisms and root exudates of E. nutans and P. kansuensis were similar. Fifteen modules were combined in the clusterings in 16S OTUs (Additional le 1: Table S5; Additional le 1: Figure S4). A high average connection degree emerged inside the turquoise module (39.25), which contained 1769 OTUs (Additional le 1: Table S5). This module was correlated with all soil groups and had a signi cant negative correlation with L. virgaurea. The strong correlation between the module eigengenes from the WGCNA network analysis and each plant species indicated that the plant rhizosphere accumulated microorganisms/root exudation in the module. After removing the turquoise module, the OTU correlation network ltering with threshold (0.2) showed that the connectivity within the module was higher, especially in the blue, midnight blue and red modules ( Fig. 7A and C). The tan, salmon and cyan modules had few OTUs (Fig. 7C). P. kansuensis correlated with the red and tan modules (P < 0.05), S-Lv-MD with midnight blue, S-Lv-HD with green, H-Lv with black, blue and yellow, L-Lv with magenta, green yellow and pink, and M-Lv with cyan, brown, and purple (Figs. 7A, 7C, and S4).
Most root exudates contained benzene ring structures, including mainly esters, ketones, aromatic acids, alkenes, amino acids, phenols and derivatives. Poisonous plant species correlated with corresponding modules; P. kansuensis with pink (P < 0.05), M. kokonorica with green (P < 0.05), and A. pendulum with blue (P < 0.05). M-Lv correlated with black, magenta, and yellow modules (P < 0.05), L-Lv with red (P < 0.05), S-Lv-HD with brown (P < 0.05), and S-Lv-MD and S-Lv-LD with turquoise (P < 0.05) (Additional le 1: Figure S5). There was no module related to E. nutans and K. pygmaea, indicating that the content of compounds in the root system of poisonous plant species were higher than non-poisonous grasses. It was evident that root exudates were plant species speci c and each species had a unique module (Figs. 7B and 7D).
There were 12 genera, including Aureimonas, Segetibacter, Methylobacterium, and Pleomorphomonas that related signi cantly to rhizosphere exudates (P < 0.05). Most of the root exudates were insecticides with insecticidal effects and some soil microorganism inhibitors (about 60%), such as carbofuran, cycloheximide and usilazole.
For L-Lv, 11 phyla (n = 44) were included in the green yellow module, and Planctomycetes and Firmicutes accounted for 29% and 27%, respectively (Figs. 8Ac and 8C; Additional le 1: Table S6). Nineteen genera were sequenced out that promoted plant growth (Clostridium, Lactobacillus, Acidibacter) and also some pathogenic bacteria (Methylocella, Aquicella, Veillonella, Enterococcus) were included. About 80% of the exudation in the red module that related signi cantly to OTUs were intermediate metabolites, such as terpenes, alkaloids, sugars, and fatty acid conjugates.
For S-Lv, 8 and 9 phyla in the green module (OTU) correlated with the turquoise (exudate) and brown (exudate) modules, respectively, among which Proteobacteria was the main phylum and Alphaproteobacteria the main class. It contained Mycobacterium, Inquilinus, Nitrospira, Pirellula, and Singulisphaera (Figs. 8Ae and 8C; Additional le 1: Table S6). Of the compounds in the turquoise module, 80% included alkaloid, sesquiterpene, coumarin and phenolic compounds, and some compounds that inhibit the growth of mold.

Potential drivers of the variation in degraded grassland
The potential drivers of the composition of bacterial communities were assessed by a SEM approach. NH 4 -N constituted the strongest direct driver of 22 bacterial communities in the 4 habitats (Fig. 9a) and pH (Fig. 9b), TOC, NH 4 -N and TN also had signi cant effects. Soil physico-chemical properties in uenced the composition of bacterial communities and Shannon diversity, and some soil properties in uenced NH 4 -N. Additional but weak links were detected between the composition of root exudates and pH, but root exudates and AWCD did not affect rhizosphere bacterial communities (Fig. 9).

Soil physical and chemical properties and soil microbial carbon metabolism in degraded grasslands
The concentrations of TOC, TN, NH 4 -N and AP in bulk soil of L were higher than in bulk soil of more degraded grasslands (Fig. 4a; Additional le 1: Table S4) and, therefore, the degradation of grassland led to the loss of soil nutrients, which was consistent with other studies [33,48]. The concentrations of nutrients in rhizosphere soil were higher than in bulk soil, which indicated that the rhizosphere contained exudated organic matter from the plants, since no fertilizer was applied to the grassland.
Soil microorganisms could use different types of organic matter when cultivated in Biolog-Eco plates. The AWCD of rhizosphere microorganisms and, consequently, the microbial carbon metabolism activity of rhizosphere soil was greater than in bulk soil. Similar results were reported by Fang et al. [49] when examining ve grasses (Sudan grass, ryegrass, tall fescue, crested wheatgrass, and switch grass). The release of root exudates and root litter provided a substrate for microorganisms, which led to the higher carbon metabolism of microorganisms in the rhizosphere than in bulk soil. The accumulation of rhizosphere microorganisms was associated with the different types and amounts of exudates [50,51]. In support, Zhalnina et al. [51]showed that the assembly of rhizosphere microorganisms in Avena was mediated by the combined effects of root exudates and the preference of microbial substrates.

Lefse and modular analyses of rhizosphere microorganisms
The phylogenetic structure of bacteria displayed aggregation in bulk and rhizosphere soils of poisonous plant species. This suggested that each vegetation type was associated with a unique and de ned bacterial community by niche ltering, which was consistent with previous studies [52]. In addition, bacteria and fungi in the same habitat were clustered, suggesting convergence. These successful colonists in the same niche could either compete for available resources or form a stable co-existing community through mutual cooperation [53,54,55]. The Lefse analysis displayed a greater abundance of biomarker bacteria in the rhizosphere soil than in the bulk soil. During degradation, the turf layer is displaced or removed, which leads to soil nutrients being lost and oligotrophic microorganisms (e.g., Acidobacteria, Chloro exi and Gemmatimonadetes) being accumulated. However, with the invasion of poisonous plants, the roots exudate compounds [56], resulting in an increase in the proportion of eutrophic microorganisms and decrease in the proportion of oligotrophic microorganisms [57].
The rhizosphere of poisonous plant species formed a larger and more complex network than in nonpoisonous plant species (e.g., E. nutans and K. pygmaea). Modules were identi ed in the network that were likely caused by microbial-microbial interactions or cooperative mutations in response to the rhizosphere. It was reported that plant rhizosphere microbial communities differed [58, 59] due to plant species, varieties or genotypes [60]. In the present study, the modules were related to some plant species, especially in L. virgaurea and P. kansuensis, and the connectivity within the module was greater than the connectivity between modules. The bacterial community compositions of P. kansuensis and E. nutans were similar; P. kansuensis is a herb that parasitizes Gramineae [61], which could explain the similarity of their bacterial community structure.

Effect of density on root exudates and rhizosphere microorganisms
Three densities of L. virgaurea were identi ed in the present study. There was a decrease in density of L. virgaurea in high density areas due to deaths, which may have been caused by autotoxicity and/or 'selfthinning'. Autotoxicity is an allelopathy in which an individual inhibits the growth of other individuals of the same species by releasing autotoxins [62]. Some autotoxins, including phenolics, omilactone B, artemisinin, phenolic acids, and cyclic hydroxamic acids [63], inhibit or delay the germination and growth of conspeci c plants [64]. In degraded sown grassland in the present study, high-density L. virgaurea had a signi cantly related exudation module, while the middle and low densities had signi cantly related bacterial modules.

Root exudates act as potential stimulants for rhizosphere bacteria
Root exudates affect the composition of rhizosphere microorganisms, which has been labelled as the 'rhizosphere effect' [65,66], and has been observed in a large number of plant species and soil types [67,68]. However, this is not always the case. In this study, root exudates of P. kansuensis and L. virgaurea were correlated with rhizosphere microorganisms, con rming the rhizosphere effect, while roots of M. kokonorica and A. pendulum released unique compounds, but were not correlated with rhizosphere microorganisms. It was reported that Arabidopsis enriched various microbial taxa in bulk soil to colonize the rhizosphere by secreting different root exudates [59]. Plants secreted bio-active compounds to regulate rhizosphere microbiota, thereby affecting the growth and defense of the next-generation of plants [16,70]. The production and excretion of coumarin was found to be bene cial to the interaction among probiotics in plant roots and root microbiota [56, 71,72]. L. virgaurea, a perennial herb with a wide niche, had a cell growth and death of KEGG levels higher than in other plants, which may be due to differences in rhizosphere microorganisms/root exudation.
When the roots of Lupinus albus mature, organic acids are released that decrease the pH of soil to inhibit bacteria [73]. The SEM demonstrated that pH in uenced the bacterial communities directly [74], while root exudates and bacterial communities had weak effects. The speci c traits of plants in the complex degraded grasslands had no discernible effect on the composition of their rhizosphere, which was also reported in temperate grasslands [4]. In the present study, approximately 60% of the pink modules (exudates) in P. kansuensis were insecticides, disinfectants, and attractants for insects. Huang et al. [29] reported that Arabidopsis produced specialized triterpenes that maintained speci c microbiota, and could shape and customize the microorganisms within and around its roots. The content of modules for L. virgaurea contained mainly alkaloids, amino acids, phenols, aromatic organic acids and coumarin. Compared with amino acids and sugars, the phenols exudated by the root system had more signi cant correlations with Acidobacteria, Actinomycetes, Bacteroides and Cyanobacteria [75]. Flavonoids, phenolic compounds, have been studied extensively for their signaling role in plant rhizosphere [76].
The bacteria that were related to root exudates in this study were associated mainly with the nitrogen cycle; Rhizobiales (Alphaproteobacteria) in nitrogen xation, Pseudomonas (Gammaproteobacteria) and Nitrospirae [77] in nitri cation, and Rhodospirillaceae (Alphaproteobacteria) in denitri cation [78]. In addition, there were Cytophagaceae (Cytophagia) and Planctomycetales, bacteria involved in ammonia oxidation, Pirellulla, Planctomyces, and Methylobacterium in methane oxidation in the carbon cycle, Mycobacterium in decomposing organic carbon [79], and Acidibacter, in degrading protein and ingesting acidic substances.
The samples were taken in August, which was the peak time for the development of poisonous plant species. Previous studies reported that plant rhizosphere microorganisms and root exudates undergo changes during plant development [51]. M. kokonorica with green module (exudates) and A. pendulum with blue module (exudates) had high correlations; however, there was no correlation with rhizosphere microorganism, indicating that the compounds in the exudate did not affect the assembly of rhizosphere microorganisms. This may be unique to the species themselves, or it may have been caused by the sampling time.

Network analysis
Many studies on microbes have focused on identifying modules in networks due to their importance in ecology [50,80,81]. In the rhizosphere network, microbial/exudate modules related to plant species were identi ed, and different plant species corresponded to different modules. These modules play a crucial role in the abundance of plant species. The disappearance of putative taxa may lead to the disintegration of modules and networks [82,83], pointing out the importance of microorganisms/exudation in maintaining ecosystem stability [50,84].

Conclusions
Soil nutrients, including TOC, TN and AP, and microorganisms in the rhizosphere of poisonous plant species were higher than in non-poisonous plant species, which indicated that the roots of poisonous plants were better at accumulating nutrients and microorganisms in poor soils. In the process of degradation, soil nutrients were lost, and the abundance of oligotrophic microorganisms increased in the bulk soil of bare land. Habitat and plant species affected the composition of the microbial community, for bacteria more so than fungi. Bacterial and fungal microorganisms in the same habitat showed convergence. Carbon metabolism activity and modular connectivity of rhizosphere microorganisms of poisonous plants were greater than in bulk soil (P < 0.05). Poisonous plant species exudated more compounds in the rhizosphere, that were more complex and of higher connectivity than non-poisonous plant species (K. pygmaea and E. nutans) (P < 0.05). The root exudates of P. kansuensis and L. virgaurea shaped the rhizosphere microbiota; P. kansuensis released mainly insecticides and disinfectants while L. virgaureais exudated mainly secondary metabolites, including terpenes, alkaloids, sugars, coumarins and lupinic acid, that contributed to self-growth. There were signi cant positive correlations between root exudates of plant species and rhizosphere microorganisms. Poisonous plant species adapted to different habitats and promoted self-growth and offspring viability through root exudates that bene tted the rhizosphere microorganisms. Understanding the adaptations of poisonous plant species could help explain their niche space and distribution and could provide options for direct manipulation of soil microbial communities through speci c components of exudates.    degraded sown grassland (S); black: heavily degraded native grassland (H)). For each sample, community composition with class level of bacteria and fungi are indicated with bar plots, and microbial α-diversity is represented with gray bars according to the number of observed OTUs. b, Effect of compartment, habitat, species and habitat × species on bacterial and fungal community composition.