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Article

Effects of Bacillus subtilis on Rose Growth Promotion and Rhizosphere Microbial Community Changes under Saline–Alkaline Stress

by
Meng Zou
1,2,3,
Kai Yu
1,2,3,
Hao Liu
1,2,3,
Qianqian Sheng
1,2,3,4 and
Yuanlan Zhang
5,*
1
College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
3
Digital Innovation Design Research Center, Nanjing Forestry University, Nanjing 210037, China
4
Jinpu Research Institute, Nanjing Forestry University, Nanjing 210037, China
5
College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(4), 730; https://doi.org/10.3390/agronomy14040730
Submission received: 2 March 2024 / Revised: 24 March 2024 / Accepted: 27 March 2024 / Published: 1 April 2024
(This article belongs to the Section Horticultural and Floricultural Crops)
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Abstract

:
This study investigated the impact of Bacillus subtilis on plant growth and the rhizosphere microbial community in rose cultivation under saline–alkaline stress. Saline–alkaline stress was simulated with varying salt and alkali levels. Bacillus subtilis was introduced, and 16S rRNA high-throughput sequencing was conducted to analyze the root microbial community. Introduction of Bacillus subtilis significantly promoted rose growth and mitigated saline–alkaline stress effects. Gene sequencing revealed increased abundance of microbial genera, such as Tessaracoccus, Intrasporangium, Glutamicibacter, Agrobacterium, Saccharibacteria, Falsochrobactrum, Mesorhizobium, Bacillus, Ensifer, and Ornithinicoccus, under normal and saline–alkaline conditions, while functional changes in colony abundance were observed under different environments through PICRUST2 analysis. Bacillus subtilis demonstrated potential in enhancing rose growth and stress resistance under saline–alkaline conditions, affecting the regulation of the root microbial community. This study provides insights for improving soil conditions and enhancing plant adaptability in saline–alkaline regions.

1. Introduction

Over the past two decades, soil salinization has profoundly affected ecological development in urban areas, particularly in China, where saline–alkali soil is primarily concentrated in the northwest, north, northeast, and eastern coastal regions. The total area of saline–alkali land in China is approximately 9913 × 104 hm2, accounting for about 1.03% of the country’s total land area, leading to the abandonment of roughly 1 × 105 km2 of land annually due to salinization [1,2]. Soil salinization leads to a decrease in soil organic matter content, disrupting the original ecological balance of the land and thereby triggering subsequent deterioration of the ecological environment. This results in the degradation of local agricultural economies and affects the development of related industries [3].
Soil salinization arises from the accumulation of salts in the topsoil layer, primarily due to excessive neutral salts (e.g., NaCl and Na2SO4) and alkaline salts (e.g., NaHCO3 and Na2CO3). Compared to singular salt or alkali stress, combined saline–alkaline stress poses a heightened threat to plants and soil [4,5]. This stress leads directly to elevated soil pH, decreased air permeability, and reduction in total nitrogen content, enzyme activity, and organic matter in the rhizosphere [6,7]. Research indicates that under salt–alkali conditions, quick-acting phosphorus and K+ levels decrease with soil depth, adversely affecting plant morphology and physiology. Specifically, an excess of Na+ in salt–alkali soil can impair plant cell membranes, disrupt the Na+/K+ balance, impede Ca2+ absorption, and hinder plant nutrient assimilation [5,8,9,10]. For instance, root cell membranes are compromised in high saline–alkaline environments, leading to the excretion of organic acids from the roots [11]. Concurrently, saline–alkaline stress causes a decrease in L-glutamic acid and 5-aminolevulinic acid levels involved in chlorophyll synthesis during plant growth processes [12].
To adapt to saline–alkaline stress, plants have developed various adaptive strategies, including accumulating organic osmolytes and synthesizing osmoregulatory substances such as proline, sugars, polyols, and amino acids [13,14,15]. In high-salinity environments, this osmotic regulation can protect cell structures and reduce oxidative damage to cells by reactive oxygen species. Recent research has revealed that plant growth-promoting rhizobacteria (PGPR), comprising various bacterial, fungal, and other microbial components, interact with plant roots to offer multiple benefits [16,17]. Studies indicate that PGPR enhance the plant’s nutrient absorption capacity, providing additional nitrogen, phosphorus, and other key nutrients, thereby improving crop growth and yield [18]. Moreover, they can suppress the growth of pathogenic microbes, reducing the risk of disease and decreasing pesticide dependency [19,20]. Additionally, PGPR contribute to the improvement of soil structure, increase soil water retention, counter soil erosion, and enhance the agricultural potential of soils [21,22]. For example, Bacillus subtilis can mitigate the impact of abiotic stress on lettuce growth under salt stress, significantly increasing the activities of superoxide dismutase (SOD) and catalase (CAT) while enhancing root vitality and cell membrane stability [23]. Arbuscular mycorrhizal (AM) fungi can form symbiotic relationships with most plant species, attaching to host roots and secreting beneficial substances to promote plant growth and soil nutrient cycling [24]. Under saline–alkaline conditions, chrysanthemum plants treated with Bacillus licheniformis were found to improve plant tolerance to salinity and alkalinity by regulating intracellular levels of abscisic acid (ABA) [25]. Salt-tolerant Streptomyces paradoxus D2-8 isolated from rhizosphere soil of Phragmites communis augments soybean tolerance to soda saline–alkali stress.
However, the growth of roses in highly saline–alkaline soil is significantly hindered, and the research on how plant growth-promoting rhizobacteria (PGPR) can enhance rose resistance remains inadequate. This study, utilizing 16S rRNA gene sequencing technology, elucidated the regulatory role of Bacillus subtilis in roses under high saline–alkaline stress. We aimed to investigate the potential of these biostimulants in mitigating the negative effects of high saline–alkaline stress on roses and their capability to stimulate plant growth and minimize physiological damage. The research methodology encompassed experimental design, sample collection, and multi-omics analysis to ensure the accuracy and reliability of the data. The importance of this study lies in its capacity to bolster plant resilience to high saline–alkaline stress and aid in soil remediation. By exploring the plant’s adaptive mechanisms, we can offer valuable insights for future agricultural and ecosystem management, better addressing the challenges associated with diminishing soil quality and environmental changes.

2. Materials and Methods

2.1. Materials

2.1.1. Test Strain

Bacillus subtilis (ID: ATCC6633, (Shanghai Microbiological Culture Collection Co., Ltd., Shanghai, China)). The test strain was stored in a 25% glycerol suspension at −80 °C for long-term preservation and activated at 37 °C on an LB liquid medium before use.

2.1.2. Soil Composition

The physicochemical property data of the soil substrate are as follows: organic matter—200 g/kg, total nitrogen—10.6 g/kg, total potassium—25.1 g/kg, and total phosphorus—12.7 g/kg. The primary materials include fermented distiller’s grains, bio-organic fertilizer, peat, perlite, and vermiculite.

2.2. Preparation of Bacterial Agents and Treatment of Seedlings

In the experiment, B. subtilis ATCC6633 was initially inoculated onto LB agar plates using the streak plate method, followed by incubation at 37 °C for 48 h (LB: yeast extract, malt extract, peptone, glucose, agar, distilled water). Subsequently, individual colonies were selected from the cultivated plates, inoculated into a nutrient broth medium, then incubated at 37 °C and 180 r/min for 36 h. After cultivation, the bacterial culture was processed. Initially, it was centrifuged at 8000 r/min, with the supernatant discarded. Subsequently, the bacterial pellet was washed twice with sterile water. Finally, the bacteria were resuspended, and the bacterial suspension concentration was adjusted to 1 × 108 CFU/mL.
The plant cultivation experiment was conducted in the artificial climate room for plant growth at Nanjing Forestry University on 19 October, at the coordinates of 118.816107° E longitude and 32.080836° N latitude. After slowing down the seedlings, the rose material (variety “Ruby”) was potted for cultivation. The pot cultivation was utilized with pot specifications of a 15.7 cm top diameter, 12.4 cm bottom diameter, and 16.5 cm height, holding a soil volume of 2 L. With two plants per pot repeated ten times, greenhouse conditions were set to an average daytime temperature of 26 °C to 30 °C and night-time temperature of 14 °C to 18 °C, with the relative humidity maintained between 80% to 90%. Natural sunlight provided illumination during the experimental period, following a 16:8 h light:dark cycle, using plant growth lamps. Before the experimental treatment, uniformly grown seedlings were selected and acclimatized to the greenhouse environment for two weeks. Treatments were divided into four groups: ATCC6633 treatment (ATCC0), 100 mmol·L−1 NaCl + Na2CO3 treatment (CK100), ATCC6633 + 100 mmol·L−1 NaCl + Na2CO3 treatment (ATCC100), and distilled water treatment as control (CK0). Two days after transplanting, rose plants were irrigated at the roots with 20 mL of bacterial suspension at 1 × 108 CFU/mL for each plant, while the control group was irrigated with distilled water. Sampling was conducted after 20 days of the experiment.

2.3. Measurement of Physiological Growth Indicators in Roses

Two weeks after the experimental treatment, scissors were used to sever the plants from the growth substrate. Subsequently, the height of the rose plants (the distance from the stem base to the growth point) and their fresh weight were measured. Then, the rose roots were gently pulled out, with the attached soil removed, and the roots were washed clean with running water and dried with absorbent paper before measuring the fresh weight of the roots. Afterwards, the above-ground and root parts were dried separately to constant weight and their dry weights were measured for every 6 repetitions processed.
After two weeks post-treatment, 0.3 g of fresh rose leaves per treatment were sampled, surface-cleaned, then flash-frozen in liquid nitrogen and stored at −80 °C, and every 6 repetitions processed. The chlorophyll content was determined by spectrophotometry. Superoxide dismutase (SOD) activity was measured using the SOD activity assay kit provided by Solarbio. Peroxidase (POD) activity was measured using the guaiacol method. Catalase (CAT) activity was determined by the hydrogen peroxide oxidation–reduction method. Malondialdehyde (MDA) content was measured using the thiobarbituric acid method. Soluble sugar content was determined by the anthrone method.

2.4. Root Sample Collection

The soil loosely attached to the roots was initially shaken off during the collection of the root samples. Subsequently, a small brush was used to remove gently the soil tightly bound to the roots, then the sample was sieved through a 2 mm mesh. Nitrate nitrogen content was determined using the ultraviolet spectrophotometric correction factor method, while ammonium nitrogen was determined using the KCl extraction–indophenol blue colorimetric method [26,27]. In the collection process of soil meta-samples, soil from at least three sampling points was mixed and packed into sterile 2.0 mL centrifuge tubes, with 200 mg per tube. Six replicates were set up for each group, and the collected samples were stored at −80 °C.

2.5. Root Sample DNA Extraction and High-Throughput Sequencing

Initially, five 96-well deep-well plates were prepared and added with the following solutions, respectively: for the first plate, 600 μL of magnetic bead binding solution, 20 μL of proteinase K, and 5 μL of RNase A were added; for the next three plates, 700 μL of washing solutions Wash 1, Wash 2, and Wash 3 were added respectively into the three plates; for the final plate, 100 μL of elution buffer was added. Subsequently, 100–200 mg of the sample was placed into a centrifuge tube containing grinding beads, and 1 mL of buffer ATL/PVP-10 was added. The sample was homogenized using a high-speed homogenizer and then incubated at 65 °C for 20 min to facilitate lysis. After incubation, the mixture was centrifuged at 14,000× g for 5 min, and the supernatant was transferred to a new centrifuge tube. Subsequently, 0.6 mL of buffer PCI was added and thoroughly mixed into the sample. The mixture underwent another round of centrifugation at 18,213× g for 10 min, following which the supernatant was transferred to the deep-well plate containing the magnetic bead binding solution. The Kingfisher instrument was activated, the appropriate program was selected, and each deep-well plate was positioned on the instrument, accordingly. Upon completion of the program, the DNA-containing elution buffer was transferred from the deep-well plate to a 1.5 mL centrifuge tube for storage. For library construction, 30 ng of quality-assessed genomic DNA sample and the corresponding fusion primers were used to set up the PCR reaction system. PCR parameters were adjusted for amplification. Post-amplification, the PCR products were purified using Agencourt AMPure XP beads (Shenzhen Huada Gene Technology Co., Ltd., Shenzhen, China) and resuspended in elution buffer. Tubes were labeled to finalize the library construction process. The library’s fragment range and concentration were determined using the Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). Once qualified, the libraries were sequenced on the HiSeq platform based on insert size. The DNA extraction and high-throughput sequencing procedures were carried out by BGI-Shenzhen (Shenzhen, China).

2.6. Data Processing and Bioinformatics Analysis

For sequencing 16S rRNA genes in the soil DNA samples of rose roots, we initiated the process by utilizing Cutadapt v2.6 to handle the sequencing reads. This preprocessing step aimed to eliminate sequences that matched primers and were contaminated with adapters, thereby acquiring pristine fragments of the targeted region. Subsequently, employing the window-based quality control method, we established a window length of 30 base pairs (bp) and trimmed the ends of reads where the average quality value within the window dropped below 20. Additionally, reads shorter than 75% of the original read length, and those containing ambiguous bases (N) and exhibiting low complexity, were excluded to enhance data quality.
For clustering, utilizing the Usearch method, the paired-end reads obtained from sequencing were processed using Flash software v1.2.11 to concatenate into continuous sequences by exploiting their overlap, thereby generating tags corresponding to the hypervariable regions. During this procedure, a minimum overlap length of 15 bp was enforced, with a mismatch rate of 0.1 allowed in the overlapping regions. Subsequently, the tags underwent clustering into operational taxonomic units (OTUs) using Usearch software v7.0.1090, with clustering carried out at a 97% similarity level through the UPARSE algorithm. Chimeras were eliminated using UCHIME software v4.2.40, and all tags were aligned back to the representative sequences of OTUs utilizing the Usearch_global method to produce an OTU abundance table. Regarding species annotation, the representative sequences of OTUs were annotated using the RDP Classifier software v2.2, setting a confidence threshold of 0.6. OTUs lacking annotation outcomes and those that did not meet the criteria of the analysis project were excluded from consideration. In analyzing microbial diversity in rose root systems, alpha diversity was assessed using Mothur software v.1.31.2, involving the computation of indices such as Chao1, ACE, Shannon, and Simpson. Moreover, beta-diversity analysis was conducted through QIIME software v1.80 to scrutinize disparities in species diversity among samples and compute beta-diversity metrics. Finally, the functional predictions of microbial communities were made using PICRUST2 software v2.3.0-b, establishing links between species and functions to depict an overarching functional profile of the communities.

3. Results

3.1. Growth-Promoting Effects of ATCC6633 Strain on Rose Seedlings under Saline–Alkaline Stress

To evaluate the impact of the ATCC6633 strain on the growth of rose seedlings under saline–alkaline stress, various parameters were measured, including seedling height, stem thickness, fresh weight of the above-ground part, dry weight of the above-ground part, fresh weight of the root part, and dry weight of the root part. It was found that under non-saline–alkaline stress conditions, ATCC6633 strain treatment resulted in increases in seedling height, stem thickness, fresh weight of the above-ground part, dry weight of the above-ground part, fresh weight of the root part, and dry weight of the root part by 1.3%, 23.16%, 6.79%, 31.49%, 12.54%, and 13.4%, respectively, compared to the control. Under stress conditions of 100 mmol·L−1 NaCl + Na2CO3, the ATCC6633 strain treatment led to increases in seedling height, stem thickness, fresh weight of the above-ground part, dry weight of the above-ground part, fresh weight of the root part, and dry weight of the root part by 11.56%, 16.65%, 11.67%, 1.5%, 42.86%, and 16.43%, respectively, compared to the control. Furthermore, under 100 mmol·L−1 NaCl + Na2CO3 stress, the parameters of seedling height, stem thickness, fresh weight of the above-ground part, dry weight of the above-ground part, fresh weight of the root part, and dry weight of the root part recovered to 97.3%, 112.52%, 143.05%, 139.53%, 188.58%, and 138.67%, respectively, of the CK0 (Figure 1). These results suggest that the ATCC6633 strain has a significant growth-promoting effect on rose seedlings under saline–alkaline stress conditions.

3.2. Effects of ATCC6633 Strain on Soil Nitrogen Content and Photosynthetic Pigments

The changes in soil nitrate nitrogen content under different treatments are illustrated in Figure 2a. Overall, the trend exhibited was ATCC0 < ATCC100 < CK0 < CK100. Under saline–alkaline stress, the soil nitrate-nitrogen content significantly increased by 46.11%. Furthermore, with the application of the Bacillus subtilis preparation, there was a significant reduction in nitrate-nitrogen content under both saline–alkaline and non-saline–alkaline conditions by 63.13% and 67.86%, respectively. Changes in soil ammonium-nitrogen content, as shown in Figure 2b, indicated an increase of 35.86% under non-saline–alkaline conditions, while the impact of Bacillus subtilis on soil ammonium nitrogen under saline–alkaline stress was not significant. Additionally, under both saline–alkaline and non-saline–alkaline stress conditions, inoculation with the ATCC6633 strain significantly increased the chlorophyll content in rose leaves, as shown in Figure 2c.

3.3. Effects of ATCC6633 Strain on Stress Resistance-Related Enzymatic Activities in Roses

Under saline–alkaline stress, inoculation with the ATCC6633 strain increased stress resistance-related enzyme activity in roses, as depicted in Figure 2. The activities of SOD, POD, CAT, and the contents of MDA and soluble sugars in rose leaves treated with the ATCC6633 strain were increased by 22.06%, 66.08%, 77.42%, 22.59%, and 23.41%, respectively, compared to the control. Under non-saline–alkaline conditions, inoculation with the ATCC6633 strain, on the contrary, decreased the activities of stress resistance-related enzymes in roses. Compared to plants not inoculated with ATCC6633, the activities of SOD, POD, CAT, and the contents of MDA and soluble sugars were reduced by 8.44%, 31.11%, 40.30%, 0.44%, and 19.80%, respectively, after inoculation with ATCC6633. Under 100 mmol·L−1 NaCl + Na2CO3 stress, after treatment with the ATCC6633 strain, compared to the CK0, the activities of SOD, POD, CAT, and the contents of MDA and soluble sugars were restored, respectively, to 97.55%, 111.44%, 104.52%, 113.66%, and 139.17% (Figure 2). These results indicate that under saline–alkaline stress, the ATCC6633 strain enhances the activities of stress resistance-related enzymes in rose seedlings, thereby mitigating the damage caused by saline–alkaline stress.

3.4. Characteristics of Root Microbial Community

To assess the impact of the ATCC6633 strain on the microbial community of the rhizosphere soil of roses, high-throughput bacterial 16S rRNA gene sequencing was conducted. High-quality bacterial 16S rRNA reads, numbering 1,040,787, were recovered from the samples. Post-removal of low-quality sequences from each sample was conducted, and sequences with a 97% or above similarity to the representative sequences were selected for principal coordinates analysis (PCoA). The PCoA analysis at the genus level (Figure 3a) indicated that the replicates from different treatments did not significantly segregate on the axes, suggesting that different treatments did not have a marked effect on the composition of the rhizosphere bacterial community of roses. Further analysis revealed that the first principal component (PC1) and the second principal component (PC2) accounted for 9.58% and 6.75% of the total variance, respectively, with a cumulative contribution rate of 16.32%. Additionally, bacterial α-diversity (Shannon index) and richness (Chao index) were calculated to assess the impact of ATCC6633 on the internal richness of the rose root community; the data showed that ATCC6633 did not significantly (p > 0.05) affect diversity under both saline–alkaline and non-saline–alkaline conditions. However, 1 × 108 CFU/mL bacterial solution reduced the community-level Chao index, indicating a decrease in richness (Figure 3b). At the OTU level, the four groups of samples contained 5062, 4954, 4711, and 4490 OTUs, respectively. In these different treatments, ATCC100 and CK100 shared 3850 OTUs under saline–alkaline conditions, with ATCC100 having 640 unique OTUs and CK100 having 861 unique OTUs. Moreover, ATCC0 and CK0 shared 4257 OTUs under non-saline–alkaline conditions, with ATCC0 possessing 697 unique OTUs and CK0 having 805 unique OTUs (Figure 3d).
The study results on the composition of soil bacterial communities at the genus level under different treatments (Figure 3c) showed that under saline–alkaline treatment, the top ten most abundant bacterial groups obtained after treatment with the ATCC6633 strain were Bifidobacterium, Phascolarctobacterium, Tessaracoccus, Intrasporangium, Saccharibacteria, Paracoccus, Gp16, Ornithinicoccus, Ensifer, and Mesorhizobium. Among these, compared to the CK0, the ATCC6633 strain treatment (ATCC0) showed higher relative abundances in Tessaracoccus, Intrasporangium, Glutamicibacter, Agrobacterium, Saccharibacteria, Falsochrobactrum, Mesorhizobium, Bacillus, Ensifer, and Ornithinicoccus, with increases of 385.43%, 156.47%, 563.39%, 341.09%, 63.37%, 300.27%, 56.83%, 298.38%, 48.71%, and 27.40%, respectively. Under saline–alkaline stress, compared to the saline–alkaline treatment alone (CK100), the ATCC6633 strain treatment showed higher relative abundances in Tessaracoccus, Intrasporangium, Saccharibacteria, Glutamicibacter, Falsochrobactrum, Agrobacterium, Ensifer, Bacillus, Ornithinimicrobium, and Paracoccus, with increases of 109.30%, 144.40%, 59.51%, 242.39%, 187.22%, 121.98%, 32.92%, 225.65%, 117.31%, and 13.53%, respectively. On comparing key species differences, the relative abundances of Tessaracoccus, Gp16, and G6 were significantly higher than those in the soil samples (Figure 3f). Under non-saline–alkaline conditions, compared to the distilled water control (CK0), the ATCC6633 strain treatment (ATCC0) showed significantly higher abundances of Tessaracoccus, Intrasporangium, and Saccharibacteria in soil samples, while the genus G6 was significantly reduced; in saline–alkaline conditions, compared to the CK0, the ATCC6633 strain treatment (ATCC100) resulted in significantly higher abundances of Ensifer, Saccharibacteria, and Intrasporangium in soil samples, while the genera Undibacter, G6, and Gp16 were significantly reduced (Figure 3e).

3.5. Differences in the Metabolic Pathways of Root Microbial Communities

Significant differences were observed in the abundance of 187 metabolic pathways within the bacterial communities of the rose seedling roots under different treatments, primarily encompassing cellular processes, environmental information processing, genetic information processing, metabolism, organismal systems, and other functions. The metabolism pathways were predominant, accounting for 81.37% of the relative abundance (Figure 4a). These pathways are primarily involved in the basic metabolic processes essential for cell survival, such as the metabolism of alanine, aspartate, and glutamate; arginine and proline; glycine, histidine; phenylalanine; tyrosine; and pyruvate, along with energy metabolism pathways like methane metabolism, starch, and sucrose metabolism. It also includes lipid metabolism, amino acid metabolism, nucleotide metabolism, antioxidant and detoxification metabolism, and carbohydrate metabolism. Under non-saline–alkaline stress conditions, the pathways that showed significant upregulation in abundance following ATCC6633 treatment included inositol phosphate metabolism, tyrosine metabolism, glycerolipid metabolism, retinol metabolism, phenylalanine metabolism, drug metabolism–other enzymes, nitrogen metabolism, phosphonate and phosphinate metabolism, tryptophan metabolism, and glycine, serine, and threonine metabolism (Figure 4b). Under the stress of 100 mmol·L−1 NaCl + Na2CO3, the pathways significantly upregulated after ATCC6633 strain treatment included inositol phosphate metabolism, tyrosine metabolism, phenylalanine metabolism, drug metabolism–other enzymes, tryptophan metabolism, nitrogen metabolism, phosphonate and phosphinate metabolism, porphyrin and chlorophyll metabolism, glycerolipid metabolism, and retinol metabolism (Figure 4c).

4. Discussion

4.1. Impact of ATCC6633 Strain on the Growth Physiology of Rose Seedlings

Roses are common ornamental flowers, and saline–alkaline cultivation soils can severely inhibit the normal growth of plants like tomatoes. The application of efficient and readily available microbes has become one of the most effective options to alleviate salt stress [23,28,29,30]. In this study, the effects of the ATCC6633 strain on the growth physiology of roses under NaCl + Na2CO3 stress were measured in an artificial greenhouse system. The results indicate that the ATCC6633 strain has a certain growth-promoting effect under 100 mmol·L−1 NaCl + Na2CO3 stress, and this effect is more pronounced under normal cultivation conditions for roses, suggesting that the ATCC6633 strain can effectively mitigate the inhibitory effects of saline–alkaline stress on roses. Furthermore, we found that under both saline–alkaline and non-saline–alkaline conditions, Bacillus subtilis significantly increases ammonium-nitrogen content and accelerates the reduction of NO3-N, a finding that could be attributed to the increased salinity in the soil, where lower salinity conditions accelerated nitrification rates, and higher salinity conditions reduced them [31]. The increased NH4+-N content can prevent excessive nitrogen loss, and the reduced accumulation of NO2-N can avoid toxic effects on plants. This new strategy of utilizing denitrifying bacteria to safely remediate secondary soil salinization holds significant implications, indicating its active role in the soil nitrogen cycle. This could be achieved by promoting nitrogen release or transformation, including biological processes such as nitrogen fixation and organic matter decomposition [32].
Plants possess inherent resistance mechanisms and can trigger various regulatory pathways in response to saline–alkaline stress to maintain normal growth [33,34,35]. First, facing the increased osmotic potential caused by salinization, plants adjust the osmotic concentration of the intercellular fluid by accumulating soluble substances such as proline, sucrose, and fatty acids. This helps maintain the water balance inside and outside the cell, preventing the outward movement of water [36,37]. Second, the plant’s response to ionic stress primarily involves ion exclusion mechanisms. The roots can adjust the absorption and expulsion of ions, reducing the influx of excess salts into the plant body. At the same time, plants may increase the rhizosphere soil’s osmotic potential, decreasing salt permeability and slowing the salt entry rate into the roots [38,39,40]. In this process, plants also regulate stress resistance-related enzymes, such as peroxidase, superoxide dismutase, and ascorbate peroxidase, to cope with oxidative stress. These enzymes can eliminate peroxides and free radicals caused by salt stress, alleviating oxidative damage and enhancing the plant’s stress resistance [41,42,43]. This study compared the activities of stress resistance-related enzymes (SOD, POD, CAT activity, MDA, and soluble sugar content) in roses under 100 mmol·L−1 NaCl + Na2CO3 stress with the ATCC6633 strain treatment. We observed that the activities of stress resistance-related enzymes in roses were induced after treatment with the ATCC6633 strain, indicating that enhancing the activity of stress resistance-related enzymes is one of the mechanisms by which the ATCC6633 strain enhances the salt–alkaline tolerance of roses. Simultaneously, we noted that under non-saline stress conditions, the ATCC6633 strain also exhibited a growth-promoting effect, but did not lead to an increase in the activity of stress resistance-related enzymes in rose plants. This suggests that while enhancing the activity of stress resistance-related enzymes indicates enhanced salt tolerance in tomatoes, it is not directly associated with growth promotion in roses. These findings provide important insights into understanding the regulatory mechanisms of the ATCC6633 strain on plant growth.

4.2. Impact of ATCC6633 Strain on Rhizosphere Soil Microbial Communities of Roses

Saline–alkaline stress leads to a decrease in the metabolic activity and functional diversity of soil microbes, and alters the utilization characteristics of soil microbial communities towards carbon sources. Notably, under high levels of saline–alkaline stress, the utilization of carbohydrates and amino acid carbon sources significantly declines, thereby markedly diminishing the diversity of the soil bacterial community [44]. Studies have demonstrated that adding exogenous microorganisms, such as arbuscular mycorrhizal fungi (AMF) and other beneficial bacteria, significantly impacts plant and soil rhizospheres. AMFs establish symbiotic relationships with plants, enhancing root growth and development, improving nutrient absorption efficiency, and optimizing interplant competition and overall community structure. Moreover, other microorganisms, such as nitrogen-fixing bacteria, Bacillus subtilis, and various fungi, also promote plant growth and enhance soil health through multiple mechanisms, including nitrogen fixation, growth hormone production, and pathogen growth inhibition [45,46,47,48]. Recent studies showed that while Bacillus subtilis PTS-394, an environmentally friendly plant protective agent, can optimize and improve root community relationships within a short period (3 days), its effects do not persist over the long term (30 days), aligning with the findings of this experiment [49]. In this study, we analyzed the structure of the rhizosphere microbiota of roses after 20 days of treatment with the ATCC6633 strain. The treatment of ATCC6633 strain does not significantly improve the root community, and only increases the abundance of beneficial microorganisms to a limited extent, such as Paracoccus, Ensifer, and Mesorhizobium. Some strains within the Paracoccus genus may participate in the nitrogen cycle in soil, with some members involved in nitrification, converting ammonium nitrogen into nitrite nitrogen, and impacting plant nitrogen utilization [50,51]. The genera Ensifer and Mesorhizobium, significant root nodule bacteria, form symbiotic relationships with leguminous plants, converting atmospheric nitrogen into absorbable ammonium nitrogen through nitrogen fixation, providing a usable nitrogen source for plants and promoting their growth and development. This symbiotic relationship not only aids in enhancing plant nitrogen absorption but also promotes a more effective nitrogen cycle in the soil, which is significant for maintaining the balance of soil ecosystems and plant ecological adaptation [52,53,54]. Furthermore, bacteria of the Bacillus genus are known to promote plant growth and enhance disease resistance and are widely used in biological control and for yield increase in plants [55,56]. Meanwhile, the specific roles and impacts of many other genera, such as Saccharibacteria, Ornithinicoccus, and Glutamicibacter, are not clearly defined. Predictive analyses of microbial community functions using PICRUST2 identified higher metabolic pathways, including the inositol phosphate metabolism, which is a key process within plant cells associated with cell signaling, energy metabolism, and growth regulation, affecting membrane synthesis, ion balance, and hormone signaling in plants [57]. Tyrosine metabolism is involved in producing tyrosine and its metabolites in plants, impacting plant growth and stress resistance [58]. Glycerolipid metabolism relates to membrane synthesis, energy storage, and hormone signal transduction in plants, which is crucial for maintaining cell membrane structure and function, energy balance, and stress responses [59,60]. Phenylalanine metabolism is essential for plant growth, development, and stress response, as phenylalanine is a precursor to thousands of other metabolites in plants [61]. These factors may provide explanations for the growth promotion and improved salt alkali resistance of roses, However, overall, the study found that the ATCC6633 strain does not significantly improve the microbial environment of the rose rhizosphere under both saline–alkali and non-saline–alkali conditions. Thus, further research is warranted to explore the temporal and functional effectiveness of Bacillus subtilis and other bacterial strains in future studies.

5. Conclusions

Treatment with Bacillus subtilis ATCC6633 under saline–alkaline stress conditions enhanced stress resistance-related enzymatic activities within the rose plants and improved nitrogen utilization rates in the cultivated soil. This dual effect effectively strengthened plant resilience to saline–alkaline stress. Additionally, this treatment does not significantly promote the population density and abundance of beneficial microorganisms in the rhizosphere of roses, and further exploration is needed in the future.

Author Contributions

Methodology, M.Z.; Formal analysis, M.Z.; Investigation, M.Z. and K.Y.; Data curation, M.Z. and H.L.; Writing—original draft, M.Z.; Writing—review & editing, M.Z.; Funding acquisition, Q.S. and Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Young Elite Scientist Sponsorship Program by cast in China Association for Science and Technology, grant number [YESS20220054], National Natural Science Foundation of China, grant number 32101582, Natural Science Foundation of Jiangsu Province of China, grant number [BK20210613], The Natural Science Foundation of the Jiangsu Higher Education Institutions of China, grant number [21KJB220008], Ministry of Education Humanities and Social Sciences Research “Study on the new mechanism of urban green space ecological benefit Measurement and high-quality collaborative development: A case study of Nanjing Metropolitan Area”, grant number [21YJCZH131], and Social Science Foundation Project of Jiangsu Province, grant number [21GLC002].

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The effect of Bacillus subtilis on the growth of roses under salt stress and non-salt stress. (a) Stem length, (b) stem thickness, (c) fresh and dry weight of aboveground parts, and (d) fresh and dry weight of underground parts. Data are means ± the standard deviation (n = 6). N.S., no significant, * p-value < 0.05 as determined by a two-tailed Student’s t-test, a—stature of the roses, b—sturdy stem of the roses.
Figure 1. The effect of Bacillus subtilis on the growth of roses under salt stress and non-salt stress. (a) Stem length, (b) stem thickness, (c) fresh and dry weight of aboveground parts, and (d) fresh and dry weight of underground parts. Data are means ± the standard deviation (n = 6). N.S., no significant, * p-value < 0.05 as determined by a two-tailed Student’s t-test, a—stature of the roses, b—sturdy stem of the roses.
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Figure 2. The effect of Bacillus subtilis on the physiology of roses under salt stress and non-salt stress. (a) Nitrate nitrogen content, (b) ammonium-nitrogen content, (c) chlorophyll content, (d) SOD activity, (e) POD activity, (f) CAT activity, (g) MDA content, and (h) soluble sugar content. Data are means ± the standard deviation (n = 6). * p-value < 0.05 as determined by a two-tailed Student’s t-test, a—Nitrate nitrogen content in rose soil; b—Ammonium nitrogen content in rose soil; c—Chlorophyll content in rose leaves; d—SOD activity in rose leaves.
Figure 2. The effect of Bacillus subtilis on the physiology of roses under salt stress and non-salt stress. (a) Nitrate nitrogen content, (b) ammonium-nitrogen content, (c) chlorophyll content, (d) SOD activity, (e) POD activity, (f) CAT activity, (g) MDA content, and (h) soluble sugar content. Data are means ± the standard deviation (n = 6). * p-value < 0.05 as determined by a two-tailed Student’s t-test, a—Nitrate nitrogen content in rose soil; b—Ammonium nitrogen content in rose soil; c—Chlorophyll content in rose leaves; d—SOD activity in rose leaves.
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Figure 3. The effect of Bacillus subtilis on the microbial community of rose root system of roses under salt stress and non-salt stress. (a) PCoA plots, PCoA plots are based on the weighted UniFrac metric for microbial communities. (b) Alpha diversity comparison based on the Shannon index using the 16S data; N.S. no significant. One-sided t-test; center value represents the median of Shannon index, (c) relative abundance of root microbiota in roses under different treatments, (d) Venn diagram of the microbial community in the root system of roses under different treatments at the OTU level, and (e,f) comparison of the genus abundance of root microbiota in roses under non-saline–alkali and saline–alkali stress (top 10). (* p-value < 0.05; ** p-value < 0.01; and Student’s t-test).
Figure 3. The effect of Bacillus subtilis on the microbial community of rose root system of roses under salt stress and non-salt stress. (a) PCoA plots, PCoA plots are based on the weighted UniFrac metric for microbial communities. (b) Alpha diversity comparison based on the Shannon index using the 16S data; N.S. no significant. One-sided t-test; center value represents the median of Shannon index, (c) relative abundance of root microbiota in roses under different treatments, (d) Venn diagram of the microbial community in the root system of roses under different treatments at the OTU level, and (e,f) comparison of the genus abundance of root microbiota in roses under non-saline–alkali and saline–alkali stress (top 10). (* p-value < 0.05; ** p-value < 0.01; and Student’s t-test).
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Figure 4. Comparison of metabolic functions of rose root bacteria under non-saline alkali and saline alkali stress. (a) Relative abundance of metabolic pathways in root bacterial microbiota. (b) Upregulation of metabolic pathways in the bacterial microbiota of rose roots under non-saline–alkali stress, (c) Upregulation of metabolic pathways in the bacterial microbiota of rose roots under salt–alkali stress.
Figure 4. Comparison of metabolic functions of rose root bacteria under non-saline alkali and saline alkali stress. (a) Relative abundance of metabolic pathways in root bacterial microbiota. (b) Upregulation of metabolic pathways in the bacterial microbiota of rose roots under non-saline–alkali stress, (c) Upregulation of metabolic pathways in the bacterial microbiota of rose roots under salt–alkali stress.
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Zou, M.; Yu, K.; Liu, H.; Sheng, Q.; Zhang, Y. Effects of Bacillus subtilis on Rose Growth Promotion and Rhizosphere Microbial Community Changes under Saline–Alkaline Stress. Agronomy 2024, 14, 730. https://doi.org/10.3390/agronomy14040730

AMA Style

Zou M, Yu K, Liu H, Sheng Q, Zhang Y. Effects of Bacillus subtilis on Rose Growth Promotion and Rhizosphere Microbial Community Changes under Saline–Alkaline Stress. Agronomy. 2024; 14(4):730. https://doi.org/10.3390/agronomy14040730

Chicago/Turabian Style

Zou, Meng, Kai Yu, Hao Liu, Qianqian Sheng, and Yuanlan Zhang. 2024. "Effects of Bacillus subtilis on Rose Growth Promotion and Rhizosphere Microbial Community Changes under Saline–Alkaline Stress" Agronomy 14, no. 4: 730. https://doi.org/10.3390/agronomy14040730

APA Style

Zou, M., Yu, K., Liu, H., Sheng, Q., & Zhang, Y. (2024). Effects of Bacillus subtilis on Rose Growth Promotion and Rhizosphere Microbial Community Changes under Saline–Alkaline Stress. Agronomy, 14(4), 730. https://doi.org/10.3390/agronomy14040730

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