The Rhizosphere Microbial Community of Tobacco and Its Relationship With The Properties of Leaves and Rhizosphere Soils

Rhizosphere microbes possess important effects on plant growth and quality. Here we collected tobacco roots and leaf samples from ten places in Yunnan province to investigate the interaction of the rhizosphere microbes, the soil physicochemical characteristics, and the tobacco leaf properties. Results A high-throughput sequencing method was used to sequence the V3–V4 region of 16S rRNA genes, and the operational taxonomic units (OTUs) were clustered using QIIME under 97% identity. A total of 4571 OTUs were obtained from the 30 tobacco root samples, and the top three phyla were Proteobacteria, Acidobacteria, and Actinobacteria, while the top three annotated genera were Gp6, Gemmatimonas, and Gp4. Redundancy analysis (RDA) showed that most of the soil physicochemical properties (10 out of 17) had a signicant inuence on the rhizosphere microbial community. Both correlation analysis and RDA analysis revealed that quick potassium (K) and Acidobacteria_Gp3 had a signicant correlation with the tobacco leaf properties. The variance partitioning analysis showed that rhizosphere microbes had a bigger inuence on the tobacco leaf properties. Our results showed great differences in the rhizosphere microbial diversity of tobacco and complex interaction among the microbial diversity, soil physicochemical characteristics, and tobacco leaf properties. in ten places from Yunnan province, which is a major tobacco producing area in China. Our results revealed the rhizosphere microbial community diversity in different places. The landform, altitude, and rotation crops presented the most inuence in the tobacco rhizosphere microbial community. The top three OTUs belonged to the family Sphingomonadaceae, genus Arthrobacter, and genus Sphingomonas, while the top three genera were Gp6, Gemmatimonas, and Gp4. Most of the soil physicochemical characteristics affected the rhizosphere microbial community and K, Ca, Fe, Actinobacteria, Deltaproteobacteria, Acidobacteria_Gp4, Acidobacteria_Gp3, and Acidobacteria_Gp1 showed a signicant inuence on the tobacco leaf properties. Meanwhile the microbial community showed a larger inuence on the tobacco leaf properties than the soil physicochemical characteristics. However, most results were based on the statistical analysis and specic experiments should be designed and conducted in the future.


Background
Nicotiana tabacum is a kind of tobacco which belongs to the class Dicotyledoneac, order Tubi orae, family Solanaceae, and genus Nicotiana. Tobacco originated from America, Australia, and some islands of the South Paci c Ocean and has been planted throughout the world. It was important to the economy of Yunnan province, China [1,2]. Although it is now well known that smoking is harmful to the health, we cannot deny the medicinal value of tobacco, based on the book, National Collection of Chinese Herbal Medicine.
Rhizosphere bacteria play an important role in plant growth, in helping nutrient absorption [3,4], biotic and abiotic stress resistance [5,6], and altering the plant physiology [7]. Meanwhile, rhizosphere bacteria are also affected by the root exudates and the soil physicochemical properties [8][9][10]. Thus, the study of rhizosphere bacteria community composition and the interaction between soil, rhizosphere microbes, and the plant is of great signi cance. Although the typical culture-dependent bacteria isolation methods could provide some information on rhizosphere bacteria composition and the bacteria strains, the investigation method requires enormous amount of time and labor. Meanwhile, some of the microbes under the state of non-culturable and viable but nonculturable (VBNC) will be ignored [11]. With the development of sequencing technology, next-generation sequencing (NGS) technology has made it possible for in-depth study on the microbial communities and well understanding of the vast diversity and interaction of microbes that have existed in many natural and arti cial environmental systems. Culture-independent molecular approaches are frequently used to characterize the compositions and structures of bacterial communities as they are time-e cient and labor-saving [12]. The NGS technology is now widely used in microbial ecology study.
As a bridge to connect the soil bacteria and the bacteria above the soil, plants play important roles in microbial community changes. Diseases of plant leaves, caused by bacteria above the soil, could affect the rhizosphere bacteria community composition by altering the root exudates. In return, the altered rhizosphere bacteria community also could help the plant to resist bacterial pathogen invasion [8]. As an important economical crop, there have been many studies on the control of tobacco diseases and insect pests [13,14]. Research on the soil bacteria community of tobacco planted under different rotation patterns showed that the soil bacteria diversity decreased after tobacco cultivation, and the proportion of Proteobacteria and Planctomycetes increased, while the relative abundance of Acidobacteria and Verrucomicrobia decreased. The decreased soil microbial diversity might contribute to tobacco bacteria wilt [15]. To control the tobacco bacteria wilt caused by Ralstonia solanacearum, antagonistic bacteria were isolated from the soil and plants, and this was shown to decrease R. solanacearum in the eld experiment [16]. Thus, it is important to study the rhizosphere bacteria community of tobacco as the rhizosphere bacteria play important roles in the plant's growth and stress resistance.
Yunnan province is the largest tobacco production area and produces high-quality tobacco. Here we chose seven cities in Yunnan province to investigate the tobacco rhizosphere bacteria community diversity. In the seven cities, a total of 10 representative places with different soil types, altitudes, tobacco varieties, and intercropping crops were chosen. The main objectives of this study were to investigate (1) the bacteria community composition at different places; (2) the effects of soil physicochemical characteristics on the rhizosphere microbial community; (3) the effects of environmental factors and the rhizosphere microbial community on the quality of tobacco.

Sampling and sites description
To investigate the rhizosphere bacteria community composition and the relationship with the soil physicochemical characteristics, plant pattern, and tobacco cultivar, a total of ten representative tobacco elds were selected from seven cities in Yunnan province. The sample collection was conducted at the end of The roots of each plant at a depth of about 30 cm were dug out using a shovel. The roots were shaken vigorously, and soil shaken off the roots was collected to test the soil physicochemical characteristics, while the remaining roots were stored in sterile tubes and sent to the lab at 4 °C within 10 hours. Then the roots were placed in 0.85 NaCl solution and shaken for 1 hour. The roots were settled, and the suspension were centrifuged at 9000g for 10 min. The pellets from the same sampling point were mixed and stored at -80 °C until the DNA extraction. For each tobacco plant, three healthy leaves, about 50 cm long, were selected and roasted. The rst roasted tobacco leaves were used for the leaf physicochemical characteristics measurements.

Soil and leaf physicochemical characteristics measurement
The soils and leaves collected from the same point were also mixed, and then the mixtures were used for physicochemical characteristics measurements. The samples were sent to Yunnan Sanbiao Agriculture and Forestry Technology Co., Ltd. for physicochemical characteristics measurements. A total of 17 physicochemical characteristics (pH, organic matter (OM), hydrolysable nitrogen (SN), available phosphorus (AP), quick potassium (K), available boron (B), exchangeable magnesium (Mg), effective zinc (Zn), hydrolysable chlorine (Cl), effective copper (Cu), effective iron (Fe), effective manganese (Mn), effective sulfur (S), total nitrogen (TN), total phosphorus (TP), total potassium (TK), and exchangeable calcium (Ca)) of the soils were measured according to the national standard method. Meanwhile seven physicochemical characteristics (total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NT), potassium oxide (PO), hydrolysable chlorine (HC), and starch (ST)) of tobacco leaves were measured according to the national standard method.
DNA extraction, Illumina sequencing and data processing For DNA extraction, 0.5 g of each rhizosphere soil sample was prepared. The DNA was extracted using a MOBIO PowerSoil DNA Isolation Kit (MOBIO, USA) according to the manufacturer's instructions. The genomic DNA concentration and purity were determined using Epoch (Bioteck, USA) and 1% agarose gel electrophoresis. The nal concentration of each DNA sample was adjusted to 1.0 ng/µL using sterile distilled water. Realbio Technology Co. Ltd (Shanghai, China) were entrusted to conduct the library construction and sequencing. The DNA library was constructed using a KAPA HiFi Hotstart ReadyMix PCR kit (KAPA Biosystems, USA) for ampli cation and AxyPrep DNA Gel Extraction Kit (AXYGEN, USA) for DNA gel extraction. The products were tested and puri ed using Thermo NanoDrop 2000 (Thermo Fisher Scienti c, USA) and using 2% agarose gel electrophoresis. The Illumina sequencing was conducted using primers 341F (5'-CCTACGGGRSGCAGCAG-3') and 806R (5'-GGACTACVVGGGTATCTAATC-3') to amplify the V3-V4 region of 16S rRNA genes. Illumina HiSeq 250 platform was used to generate 2×250 bp paired-ends sequences.
The raw sequences generated from the Illumina HiSeq 250 platform were split into sample libraries based on the barcodes. The reads were trimmed using Btrim [26] with a QC threshold higher than 20 over the 5 bp window size and a minimum length of 100 bp. Forward and reverse reads were joined using Flash [27] with at least 10 bp overlap and fewer than 5% mismatches. UChime [28] was used to remove chimera from those about 425 bp long. Before operational taxonomic unit (OTU) clustering, singletons were rst removed from the reads. OTU clustering was determined using Usearch [29] at the 97% similarity level. The taxonomic assignment was conducted through the Ribosomal Database Project (RDP) classi er with an 80% minimal con dence estimate. Subsequent analyses were performed in R using the vegan package [16]. Samples were rare ed at 19,548 reads per sample.

Statistical analyses
The alpha diversity (including the observed species, the Shannon index, the Simpson index, the abundance-based coverage estimator (ACE), good-coverage, and phylogenetic distance (PD)) was calculated using QIIME [30]. The beta diversity of principal component analysis (PCA) was calculated using the vegan package in R software [31,32]. The correlations between physicochemical characteristics of tobacco leaves with environmental factors and the rhizosphere bacteria community were calculated based on Spearman correlation coe cients in R software. Redundancy analysis (RDA) was performed using the vegan package and plotted using the ggplot2 package in R software [33]. The network analysis was constructed using R software and Gephi software [34]. The analysis of similarities (Anosim) and variance partitioning analysis were conducted using R's vegan package. Functional Annotation of Prokaryotic Taxa (FAPROTAX) was used for function prediction [35].

Results
Physicochemical properties of rhizosphere soils and tobacco leaves A total of 17 physicochemical parameters at ten different tobacco elds were measured ( Table 1). The value of pH ranged from 5.23±0.16 (YX3) to 7.28±0.45 (QJ15) and all samples, except QJ15, were weakly acidic. The heatmap of the rhizosphere soil physicochemical parameters showed that the 17 parameters could be divided into four groups (Fig. 1A). pH, Mg, TN, and OM were in one group and their value (pH) and contents were higher in QJ15. Zn, Cl, and Ca were in a group and their contents were relatively high in QJ15, QJ13, and WS18. Fe, Cu, TP, Mn, and S were grouped together and their contents were high in the YX2 sample. TK, P, AP, and K made the last group and all the four parameters were high in KM1.
For tobacco leaves, seven parameters were measured and the results are shown in Table 2. The heatmap based on the seven parameters revealed three groups of the seven parameters (Fig. 1B). ST, TS, and RS formed a group, while NT and SC formed another group, and TN and PO formed the last one. ST, TS, and RS had higher contents in KM14. NT and SC had relatively higher content in YX2, while TN and PO had higher contents in BS21. For WS18 and YX3, the three repeat samples in each site were not clustered together.
The Illumina Hiseq sequencing generated a total of 692,836 clean reads with an average length of 414.6 bp. The reads number of each sample was resampled to 19,548. The OTU numbers of the 30 samples ranged from 1365 (QJ13-3) to 2034 (DL22-1) ( Table S1). The rarefaction curve based on the observed species and reads showed that the numbers of observed species for each sample were almost saturated and were su cient for microbial community analysis (Fig. S1). The mean relative abundances of the top 20 phyla in each sample site are shown in Fig. 2A. Proteobacteria possessed the highest relative abundance in all samples, ranging from 32.50% (DL21-1) to 46.81% (YX3-2) ( Table S2). The three dominate phyla were Proteobacteria, Acidobacteria, and Actinobacteria, which accounted almost 80% of the relative abundance. At the genus level, about 40% of the reads could not assigned to a speci c genus (Fig. 2B). The top ve genera were Gp6 (6.92%-26.04%), Gemmatimonas (2.69%-13.79%), Gp4 (1.91%-8.11%), Gp3 (1.95%-7.96%), and Sphingomonas (1.54%-7.42%) (Table S3). However, the most abundant genus in each sample was different.
The OTUs in each sample was compared by Venn diagram (Fig. 3). A total of 170 core OTUs were shared by all samples. CX8-1 possessed the most speci c OTUs at 15 while YX3-3 possessed no speci c OTUs. The speci c OTUs of each sample were very few and, for most of them, were lower than 10. The core OTUs and the speci c OTUs together with the OTU sequences are listed in Table S4.
The alpha diversity of all samples are listed in Table S5. The highest mean observed species was found in DL22 at 1935 ± 33.79, while the lowest was QJ13 at 1351 ± 19.61 (Fig. S2A). Similarly, DL22 had the highest PD whole tree at 100.04 ± 2.54, while QJ13 had the lowest at 82.44 ± 1.74 (Fig. S2B). All samples had a good coverage higher than 0.97, indicating that the sequence numbers were enough for each sample to perform microbial community analysis.
To illustrate the differences of the microbial communities of the ten sample sites, principal component analysis (PCA) based on the OTUs demonstrated that samples from the same site could have different microbial community pro les (Fig. 4). Samples from Yuxi city YX3 had a more similar microbial community with KM11 than YX2 while KM14 had a more similar microbial community with BS21 than KM11. YX2, QJ15, CX8, and QJ13 had a relative speci c microbial community. At the OTU level, PC1 explained 21.32% and PC2, 16.11% of the total variation (Fig. 4).

Relationship among soil properties, rhizosphere microbial communities and tobacco leaf properties
The correlation analysis based on the Spearman method between the physicochemical parameters of tobacco leaves with the soil physicochemical parameters and rhizosphere microbial community at the class level is shown in RDA analysis indicated that pH, OM, SN, TN, TP, AP, Cu, Fe, K, and Mg were signi cantly associated with microbial community diversity (forward selection with a Monte Carlo test, P < 0.05). The rst two axes explained 25.42% of the microbial community diversity information (Fig. 6A). RDA was also used to assess the relationship between the physicochemical parameters of tobacco leaves with the soil physicochemical parameters and rhizosphere bacterial microbial communities of the top 20 classes (Fig. 6B). Bacteria of Actinobacteria, Deltaproteobacteria, Acidobacteria_Gp4, Acidobacteria_Gp3, Acidobacteria_Gp1, and the soil physicochemical parameters of K, Fe, and Ca were signi cantly associated with tobacco leaf physicochemical parameters, based on the Monte Carlo test (P < 0.05). The rst two axes explained 54.95% of the total variance.
The rhizosphere microbial community similarity of different cultivars, different landforms, different soil types, different altitudes, and different rotation crops were analyzed using the ANOSIM method. The results showed that the landform, altitude, and rotation crop had a signi cant in uence in the rhizosphere microbial community, while different cultivars and different soil types showed no signi cant difference in the rhizosphere microbial community (Table 3).

Variation partitioning of tobacco leaves physicochemical parameters
To investigate the contribution of the rhizosphere microbial community and soil physicochemical characteristics to tobacco leaf property variation, variance partitioning analysis was conducted based on the RDA model and the results are shown using a variation partitioning diagram (Fig. 7). Fifteen classes of bacteria (Bacteroidetes_incertae_sedis, Thermoplasmata, Verrucomicrobiae, Armatimonadetes_gp5, BRC1_genera_incertae_sedis, Candidatus Hydrogenedens, Latescibacteria_genera_incertae_sedis, WPS-1_genera_incertae_sedis, Nitrososphaerales, and six unidenti ed class) and six soil physicochemical characteristics (pH, SN, Zn, TP, TK, and Ca) were selected as explanatory variables through a forward selection procedure. The rhizosphere microbial community and the soil physicochemical characteristics together could explain 82.68% of the variation in the tobacco leaf properties. The pure effect of the rhizosphere microbial community explained 56.99% of the variation while the pure effect of soil physicochemical characteristics explained 14.77% of the variation. We found that 10.98% of the variation could be explained by the rhizosphere microbial community and soil physicochemical characteristics simultaneously.

Discussion
Due to the important roles the rhizosphere bacteria play in plant growth and stress resistance, investigation of the rhizosphere microbial community has attracted attention. As an important economic plant in Yunnan province, China, it is meaningful to study the rhizosphere microbial community of tobacco. In this study, the rhizosphere microbial community, the soil physicochemical characteristics and tobacco leaf properties were tested and the correlations were investigated. We found that the microbial communities of different cities could be more similar than those from the same city; for instance, YX3 had a more similar microbial community with KM11 than with YX2 (Fig. 4). The rhizosphere microbial community was signi cantly affected by the soil physicochemical characteristics [9,10]. The different soil types and rotation crops might contribute to the rhizosphere microbial community diversity of YX2 and YX3.
Like other crops [17][18][19], the most dominate phylum in all samples was Proteobacteria ( Fig. 2A). Nevertheless, the most dominate annotated genus was Acidobacteria_Gp6 belonging to phylum Acidobacteria and a large proportion of the reads could not be annotated to the genus level (Fig. 2B). Similar bacterial communities were found in a study of tobacco rhizosphere microbial community [20]. In the sugarcane cultivated soils, Acidobacteria_Gp6 was also the most abundant among the Acidobacteria subgroups and the abundance of Acidobacteria_Gp6 was decreased with the addition of fertilizer N [21]. However, our results did not suggest a signi cant correlation of Gp6 and the content of SN and TN (Fig. 5). The investigation of the soil microbial community at the tobacco planting eld revealed that Acidobacteria_Gp6, Ktedonobacter, Spartobacteria_genera_incertae_sedis, Acidobacteria_Gp1, and Gemmatimonas were the top ve predominant genera, among which Acidobacteria_Gp6 and Gemmatimonas were also predominant in the rhizosphere microbial community in our study (Fig. 2B).
The high abundance of Acidobacteria_Gp6 and Gemmatimonas in both bulk soil and rhizosphere soil implied an important correlation between them and tobacco. The number of core OTUs shared by all samples was 170, accounting for 3.72% of the total OTUs (4572). The most abundant OTUs belonged to family Sphingomonadaceae, followed by the genus Arthrobacter, then genus Sphingomonas (Table S4). Sphingomonas played an important role in decomposition of toxic chemicals in the soil and maintenance of the soil nitrogen balance [22]. Despite the high abundance and important roles of Sphingomonadaceae, no signi cant correlation was found between Sphingomonadaceae (belonging to Alphaproteobacteria) with the tobacco leaf properties.
The microbial communities, the environmental factors and the plant physicochemical properties showed strong interactions with each other. K, TN, pH, Mg, Fe, and Cu showed a higher contribution to effect the rhizosphere microbial community than AP, TP, SN, and OM (Fig. 6A). Meanwhile, K showed a signi cant correlation with the tobacco leaf properties of TS, NT, PO, and ST (Fig. 5). Both RDA analysis and the correlation test showed the in uence of the rhizosphere microbial communities and the soil physicochemical characteristics on the tobacco leaf properties, similar to the results already demonstrated in other studies [23][24][25].
K, Ca, and Fe also showed signi cant in uence on the tobacco leaf properties and showed a higher in uence on the sites KM and CX, than on other sites. Actinobacteria, Deltaproteobacteria, Acidobacteria_Gp3, Acidobacteria_Gp1, and Acidobacteria_Gp4 were correlated with the tobacco leaf properties, signi cantly. Acidobacteria_Gp3, Acidobacteria_Gp1, and Acidobacteria_Gp4 possessed a synergistic effect, and they showed the opposite effect with Actinobacteria and Deltaproteobacteria. Cl showed no signi cant correlation with the tobacco leaf properties based on the RDA analysis, while showing a signi cant negative correlation with ST (R = -0.69, P < 0.001) based on the correlation analysis.
The variance partitioning analysis was used to illuminate the contribution of the rhizosphere microbes and soil physicochemical characteristics made for the tobacco leaf properties. The rhizosphere and soil physicochemical characteristics together could explain 82.68% of the tobacco leaf properties. The rhizosphere microbial communities contributed more than the soil did. As a system, the roots, rhizosphere microbes, and the soil interacted with each other. Most of the soil physicochemical characteristics showed a signi cant relationship with the rhizosphere microbial communities while only three soil physicochemical characteristics and ve microbial taxa at the class level possessed a signi cant correlation with the tobacco leaf properties, which revealed that the microbes and soils had a stronger correlation than with the tobacco leaves.

Conclusion
In this study, we investigate the rhizosphere microbial communities in ten places from Yunnan province, which is a major tobacco producing area in China. Our results revealed the rhizosphere microbial community diversity in different places. The landform, altitude, and rotation crops presented the most in uence in the tobacco rhizosphere microbial community. The top three OTUs belonged to the family Sphingomonadaceae, genus Arthrobacter, and genus Sphingomonas, while the top three genera were Gp6, Gemmatimonas, and Gp4. Most of the soil physicochemical characteristics affected the rhizosphere microbial community and K, Ca, Fe, Actinobacteria, Deltaproteobacteria, Acidobacteria_Gp4, Acidobacteria_Gp3, and Acidobacteria_Gp1 showed a signi cant in uence on the tobacco leaf properties. Meanwhile the microbial community showed a larger in uence on the tobacco leaf properties than the soil physicochemical characteristics. However, most results were based on the statistical analysis and speci c experiments should be designed and conducted in the future.

Declarations
Ethics approval and consent to participate Tables Table 1 The physicochemical parameters of rhizosphere soils for ten tobacco elds (mean ± SD, n = 3). Different small letters indicate signi cant differences between sites for that parameter. The means were compared using pairwise Adonis in R, at the P < 0.05 level.