Responses of rhizosphere microbial communities and resource competition to soil amendment in saline and alkaline soils

doi:10.21203/rs.3.rs-4997605/v1

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Responses of rhizosphere microbial communities and resource competition to soil amendment in saline and alkaline soils

https://doi.org/10.21203/rs.3.rs-4997605/v1

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Background and aims

Soil amendments have been widely applied in the remediation of saline soil and the improvement of crops resistance to external stresses. However, the responses of soil microbial community composition, structure, function, and resource competition strategy to soil amendment in saline and alkaline soil remain unclear.

Methods

A barrel experiment was performed in a cotton field to explore the effects of soil amendment on soil microbial life history strategies under simulated saline and alkali stresses during cotton flowering stage.

Results

The results showed that saline and alkali stresses disrupted soil microbial succession and altered rhizosphere soil micro-environment. However, after the application of amendment in saline soil, the abundance of dominant bacteria (Subgroup_17) and fungi (Mortierella, Chaetomium), soil metabolic functions (biosynthesis of amino acids and fatty acid), soil K⁺ content and Si/N ratio significantly increased, while soil Na⁺ content and electrical conductivity (EC) significantly reduced. After the application of amendment in alkaline soil, the abundance of dominant soil bacteria (Aeromicronium, Rokubacteriales, RB41) and fungi (Mycosphaeralla, Aspergillus), phenylalanine metabolise and fatty acid biosynthesis pathways soil K⁺/Na⁺ ratio, organic carbon content, total nitrogen, and Si/N ratio significantly increased, while soil Na⁺ content, pH, and Si/C ratio significantly decreased.

Conclusions

Application of soil amendment could significantly increased soil nutrient content,the formation of different life cycle strategies of soil microorganisms, so as to alleviate the saline stress and alkali stress. This study provides reference for alleviating the saline and alkaline stresses to cotton by influencing key soil microorganisms using soil amendment.

alkali stress

silicon fractions

metabolomics

microbial community

saline stress

symbiotic network

Soil salinization is an environmental issue of global concern. About 7% of the world’s soil is salinized (Wu et al., 2014a). In natural environments, salinization and alkalinization often occur simultaneously, resulting in a complex saline-alkali soil environment which severely restricts crop growth (Wang et al., 2017). In China, saline-alkali soils are widely distributed in Xinjiang Province. Studies have shown that application of soil amendment can reduce saline and alkaline stresses. For example, Zhang et al. (2019) applied silicic soil amendment in moderate saline soil, and found that it could significantly reduce soil Na⁺ content and EC and increase soil organic carbon (SOC) content, thus increasing crop yield. An et al. (2020) reported that after applying calcium lignosulfonate-based soil amendment in alkali soil, the Na⁺ content in cotton leaves significantly reduced by 18.26%, while K⁺/Na⁺ ratio significantly increased by 37.11%. Therefore, the application of soil amendment can not only reduce salinity in the plough layer, but also increase crop yield, which is of great significance for improving the productivity of saline-alkali soils in arid regions.

Soil amendment can alter soil microbial community composition, structure, function, and life history strategies under saline and alkali stresses. For example, Zhang et al. (2020) found that after the application of acid bentonite in salinized sandy soil, the dominant genus Gemmate was replaced by Pontibacter, and the nitrogen metabolism and fermentation function were improved. Liu (2019) reported that after the application of biochar in alkaline soil, soil microbial community structure was greatly altered, and diazotroph (Sinorhizobium, Bradyrhizobium, and Burkholderia) diversity and nitrogen fixation were enhanced. Yang et al. (2020) found that silicon-containing amendment could significantly improve soil microbial activity and increase stress resistance. Javaid et al. (2019) reported that Si-containing hydroponic nutrient solution could improve wheat root and stem growth, and significantly alleviate NaCl stress by reducing the absorption of Na⁺. Besides, some studies also found that application of silicate fertilizer in paddy fields could change soil microbial life history strategies, and significantly improve the soil metabolism related to organic matter decomposition (C degradation) and biogeochemical cycling (e.g., C and N fixation, nitrification, and CH₄ cycling) (Suvendu et al, 2019), promote the chelation between soil organic acids (glutamic acid, fumaric acid, etc.) and cations, and reduce soil pH(Kamran et al., 2017). Meanwhile, soil microorganisms produce organic acids, which directly affects the Na⁺ accumulation and improves the saline-alkali soil environment (Wang et al., 2020). However, the effects of silicon-containing amendment on soil microbes under saline and alkali stresses and the mechanism by which silicon-containing amendment alleviates saline and alkali stresses are unknown at present.

Cotton is the main cash crop in Xinjiang, and has strong salt tolerance. The cotton output in Xinjiang accounted for 89.5% of China's total (Hou et al., 2021). In this study, pot experiment was performed in a drip-irrigated cotton field to analyze responses of cotton rhizosphere soil physical and chemical properties, microbial community structure, and metabolic pathways to application of silicon-containing soil amendment under simulated saline stress and alkali stress, and the relationship network of soil salinity, silicon, microorganisms, and metabolites was constructed. The aims of this study were to clarify (1) the effects of soil amendment on the pH, salinity, Na⁺ content, and silicon forms of saline and alkaline soils in cotton field, (2) the effects of silicon form changes induced by the application of soil amendment on soil microbial life history strategies under saline and alkaline stresses, and (3) the mechanism of soil amendment in the remediation of saline and alkali soils. This study will deepen our understanding of soil microbial responses to soil amendment under saline and alkali stresses, and provide guidance for the remediation of saline and alkali soils in arid regions.

Experimental site

This experiment was conducted at the Experimental Station of Grape Research Institute in Shihezi City, Xinjiang Province, China (44°20′ N, 86°03′ E). The soil was desert soil. The soil pH was 7.72, organic matter content was 12.3 g·kg^− 1, alkaline hydrolyzable nitrogen content was 53.5 mg·kg^− 1, available phosphorus content was 11.5 mg·kg^− 1, and available potassium content was 215 mg·kg^− 1 (Bao 2000).

Materials and experimental design

The soil amendment (GS) used in this study was a brown liquid, mainly composed of organosilicon extract, calcium lignosulfonate, polyacrylamide, polyvinyl alcohol, zinc sulfate, iron sulfate, and manganese sulfate (mass ratio 50: 10: 5: 5: 5: 1: 1). It was prepared by rapidly stirring under high temperature. The pH of the GS was 6.25 and the electrical conductivity (EC) was 2.32 ms·cm^− 1.

Barrel experiment was conducted from April 15 to September 24, 2020. Randomized complete block design was adopted with a total of 4 treatments (three replicates per treatment). According to previous research (Wang et al., 2020) and pre-test results, NaCl and Na₂CO₃ were mixed fully with soils in barrels (50 cm in diameter, 60 cm in height) respectively to make soil salinity reach 8 g·kg^− 1, and then the barrels were buried in a cotton field. Cotton seeds (variety Xinluzao 62) were sown in early May 2020, and six seedlings were retained in each barrel after emergence. Irrigation was started on June 10, with an irrigation cycle of 10 days. A total of 9 times irrigation were carried out in the whole growth period, and the total irrigation volume was 6 000 m³·hm^− 2. Cotton and rhizosphere soil samples were collected from each treatment at the early stage of flowering and boll-forming (August 16). The rhizosphere soil samples were divided into two parts. One part was air-dried to determine soil properties, and the other part was stored at -80 ℃ for soil microbial and metabolomic analysis.

Determination of plant and soil parameters

Determination of cotton morphological parameters

Three plants were selected from each treatment and rinsed with distilled water to measure the root weight and root length, and the average value was calculated. Then, the plants were dried to constant weight to determined the dry mass and seed cotton yield.

$$\:\text{S}\text{e}\text{e}\text{d}\:\text{c}\text{o}\text{t}\text{t}\text{o}\text{n}\:\text{y}\text{i}\text{e}\text{l}\text{d}\:（\text{k}\text{g}\bullet\:{\text{h}\text{a}}^{-1}）=cotton\:density\:\left(plant\bullet\:{ha}^{-1}\right)\times\:average\:number$$

$$\:\:of\:bolls\:per\:plant\left(pieces\bullet\:{plant}^{-1}\right)\times\:single\:boll\:weight\:\left(g\right)\times\:\frac{1}{1000}$$

Determination of soil properties

Soil properties were determined according to the methods of Bao (2000). Soil K⁺ and Na⁺ contents were measured by flame photometer (AP1200, Shanghai, China). Soil pH and EC were measured by using the PHS-P acidity meter (Leici, China) (water: soil = 2.5: 1). Soil available phosphorus content was measured by the 0.5 mol·L^− 1 NaHCO₃ method. Soil TN was measured by the Kjeldahl method. Soil organic carbon content was measured by the potassium dichromate-external heating method.

Soil samples and amendment were dried and analyzed by the Fourier transform infrared spectroscopy (FTIR) (Thermo Scientific Nicolet iS5, USA), with a wavelength range of 4000 − 400 cm^− 1, 32 scans, and a resolution of 4 cm^− 1.

The extraction of various silicon forms in soil was determined by a modified chemical extraction procedure. Dried soil sample (0.7500 g) was added into 50 mL centrifuge tube, then 30 mL acetic acid-sodium acetate buffer (1.0 M, pH 4.0) was added, followed by 16-hour shaking and centrifugation. The supernatant was used to extract available silicon (EF-Si). After that, the residue was mixed with 5 mL of 30% H₂O₂, and heated at 85 ± 2 ℃ for 1 h. Acetic acid-sodium acetate buffer (30 mL, 1.0 M, pH 4.0) was then added, followed by 16-hour shaking and centrifugation. The supernatant was used to extract organic Si (ORB-Si). The residue produced in previous step was mixed with 30 mL 0.5 M NH₂OH-HCI, followed by 16-hour shaking and centrifugation. The supernatant was used to extract Fe/Mn-oxide Si (FMH-Si). The residue produced in previous step was mixed with 30 mL 0.5 M sodium hydroxide solution, followed by 1-hour ultrasonic water bath, 16-hour shaking, and centrifugation. The supernatant was used to extract amorphous silicon (AM-Si) (Yang et al., 2019).

Soil sample (5 g) was mixed with 15.0 mL of 8% sucrose solution, 5.0 mL of phosphate buffer (pH: 5.5), and five drops of toluene, followed by an incubation in an incubator (MGC-300A, Shanghai, China) at 37 ℃ for 24 h. After that, it was centrifuged at 6000 rpm for 10 min. The supernatant (1.0 mL) was used to determine sucrase activity (Lu et al., 2000).

Soil sample (5 g) was mixed with 1.0 mL of toluene in a 50 mL triangular flask, and 10 mL of 10% urea solution and 20 mL of citrate buffer (pH: 6.7) were added after 15 min. After incubating at 37 ℃ for 24 h, the supernatant (3.0 mL) was used to determine urease activity (Lu et al., 2000).

Soil sample (5 g) was mixed with 5 drops of toluene and 20 mL of 0.5% disodium phenylphosphate. The mixture was shaken and incubated at 37 ℃ for 24 h. After that, 5 mL of filtrate was used to determine alkaline phosphate activity (ALP) by colorimetry (Lu et al., 2000).

Soil sample (2 g) was mixed with 40 mL of distilled water and 5 mL of 0.3% hydrogen peroxide solution, followed by an oscillation for 20 min. Then, 5 mL of 3N sulfuric acid was added and the suspension was filtered with filter paper. After that, 0.1 N potassium permanganate solution was dropped into 25 mL of filtrate until it turned light pink. The amount of potassium permanganate consumed (mL) was recorded as B. Another tube without soil sample was taken as a control. Above procedures were performed, potassium permanganate was used to titrate 25 mL of hydrogen peroxide solution, and the potassium permanganate consumed was recorded to determine catalase activity (Lu et al., 2000).

Soil high-throughput sequencing

Genomic DNA was extracted by using the Cetyltrimethyl Ammonium Bromide (CTAB) method. The concentration, quality, and integrity of the DNA were determined using a Qubit fluorometer (Invitrogen, USA) and a NanoDrop spectrometer (Thermo Scientific, USA). Sequencing libraries were generated using the TruSeq DNA Sample Prep Kit (Illumina, USA) and Template Prep Kit (Pacific Biosciences, USA). Genome sequencing was performed by Piceno Biotechnology Co., Ltd. (Shanghai, China) using the Pacific Biosciences platform and the Illumina Novaseq platform. The bacterial 16S_V3V4 region was amplified with primers 338F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT) (Claesson et al., 2009), and the fungal ITS_V1 region was amplified with primers ITS5 (GGAAGTAAAAGTCGTAACAAGG) and ITS2 (GCTGCGTTCTTCATCGATGC) (White, 1990). In sequence analysis, Divisive Amplicon Denoising Algorithm 2 (DADA2) was used to remove data noises. The deduplicated sequences generated after DADA2 quality control were called ASVs (amplicon sequence variants). DADA2 was no longer used for clustering in similarity, only dereplication or clustering in 100% similarity was performed (Callahan et al., 2016). All downstream data analyses were performed in QIIME2 (http://qiime.org/) and R packages (version 3.2.3, http://www.r-project.org).

Soil metabolomics

Soil sample (200 mg) was mixed with 0.6 mL 2-chlorophenylalanine (4 ppm) methanol (-20 ℃) in 2 mL EP tube and vortexed for 30 s. After that, 100 mg glass beads were added and ground by a high-throughput tissue grinder (NINGBO LAWSON SMARTTECH CO., LTD) at 60 Hz for 90 s, followed by an ultrasound at room temperature for 30 min and an ice cooling for 30 min. Then, centrifugation was performed at 4 ℃ at 12000 rpm for 10 min, and the supernatant (300 µL) was filtered through 0.22 µm membrane to obtain the prepared samples for LC-MS detection. Twenty microliters were collected from each sample to prepared the quality control (QC) samples. The rest of the samples were used for LC-MS detection (Ng et al., 2012; Ponnusamy et al., 2011; Sangster et al., 2006). Five replicates were measured for each treatment.

Data analysis

One-way ANOVA and Duncan's test were performed using SPSS software (version 22.0, IBM, Armonk, NY, USA) at P < 0.05. Bacterial and fungal responders were screened by LDA analysis (linear discriminant analysis) under the condition of LDA > 3.3. Functions of soil bacteria and fungi were predicted using PICRUSt2 software (https://github.com/picrust/PICRUSt2/wiki) (MetaCyc database). Soil metabolites with VIP (Variable importance in the projection) > 1 and 0.05 < P < 0.1 were selected as differentially expressed metabolites (DEMs). The soil metabolites discovered in this study were annotated into the Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.KEGG.jp/) database to reveal the functions and interactions of the metabolites. Pearson’s correlation index was calculated using the "psych" package in R software (version 3.4.0, Origin Laboratories, Ltd., Northampton, MA, U7SA), and the correlations with a Spearman coefficient < 0.9 and P > 0.05 were excluded to better focus on strongly co-occurring interactions (Li et al., 2020). Subsequently, the co-occurrence relationships were visualized using Gephi 0.9.2 (https://Gephi.org/). Data were processed using Excel 2019 and R software. Plots were drawn using Origin software (version 2018, Origin Laboratories, Ltd, MA, USA).

Effects of soil amendment on root morphology and seed cotton yield

Cotton yield significantly increased after the application of amendment (Fig. 1). In 2019, cotton root mass, root length, and yield in GSY treatment increased by 24.6%, 20.5%, and 10.5%, respectively (P < 0.05) compared with those in CKY treatment. Cotton root mass and root length in GSJ treatment increased by 17.3% and 20.0%, respectively (P < 0.05) compared with those in CKJ treatment. Similar to in 2019, in 2020, cotton root mass, root length, and yield increased by 9.6%, 13.6%, and 6.2%, respectively (P < 0.05) compared with those in CKY treatment. Cotton root mass and root length in GSJ treatment increased by 10.4%, 18.0%, and 10.7%, respectively (P < 0.05) compared with those in CKJ treatment.

FTIR test results

The peaks at 3425 cm^− 1, 1635 cm^− 1, and 1122 cm^− 1 were attributed to the N-H stretching vibration, bending vibration, and aliphatic ether stretching vibration in soil amendment, respectively, and the peak at 2933 cm^− 1 was attributed to the diffused O-H absorption. For the soils of each treatment, the peak at 3619 cm^− 1 was mainly attributed to the O-H stretching vibration of crystal water in minerals, the peak at 1433 cm^− 1 was attributed to the v2 vibration of CO₃²⁻ in carbonate, and the peak at 1033 cm^− 1 was attributed to the v3 stretching vibration in silicate. In addition, the peaks at 1092 cm^− 1, 819 cm^− 1, 808 cm^− 1, and 798 cm^− 1 were attributed to the silicon-oxygen symmetric stretching, the v3 vibration of SiO₄²⁻, the stretching of Si-O-Si, and the = C-H nonplanar (rocking) bending vibration on the benzene ring, respectively, and the weak peaks at 519 cm^− 1 and 468 cm^− 1 were attributed to the vibration of metal oxides. The absorbance of GSY treatment decreased at 3619 cm^− 1, 1433 cm^− 1, 1033 cm^− 1, 1033 cm^− 1, 808cm^− 1, 798cm^− 1, 617cm^− 1, 519cm^− 1, and 468cm^− 1, and increased at 3455 cm^− 1 and 1122 cm^− 1, compared with that of CKY treatment. The absorbance of GSJ treatment decreased at 1033 cm^− 1, 519 cm^− 1, and 468 cm^− 1, and increased at 3619 cm^− 1, 3425cm^− 1, 1433 cm^− 1, 1122 cm^− 1, 808cm^− 1, 798cm^− 1, and 617cm^− 1 compared with that of CKJ treatment (Fig. 2).

Effects of soil amendment on the contents of different forms of silicon in the soils

Soil EF-Si content in GSY and GSJ treatments increased compared with that in CKY and CKJ treatments (P < 0.05) (Fig. 3). The contents of soil EF-Si and ORB-Si in GSY treatment increased by 27.3% and 16.6%, respectively (P < 0.05), while the FMH-Si content decreased by 11.1% (P < 0.05) compared with those in CKY treatment. The content of soil EF-Si in GSJ treatment increased by 10.1% (P < 0.05) compared with that in CKJ treatment.

Effects of soil amendment on soil physical and chemical properties and enzyme activity in cotton field

The application of soil amendment improved saline and alkali soil physicochemical properties and enzyme activities (P < 0.05), and reduced Na⁺ content (P < 0.05). Soil K⁺ content, K⁺/Na⁺ ratio, organic carbon, TN, Si/N ratio, and sucrase activity in GSY treatment increased by 13.3%, 24.7%, 26.6%, 81.6%, 96.0%, and 43.6%, respectively (P < 0.05), while soil Na⁺ content, EC, available phosphorus content, and C/N ratio reduced by 10.0%, 7.2%, 5.3%, and 43.5%, respectively (P < 0.05) compared with those in CKY treatment. Soil Na⁺ content, pH, available phosphorus content, and Si/C ratio in GSJ treatment increased by 38.1%, 10.1%, 10.0%, and 21.3%, respectively (P < 0.05), while soil K⁺/Na⁺ ratio, organic carbon content, TN, Si/N ratio, ALP, and sucrase activity reduced by 37.3%, 34.8%, 27.1%, 49.0%, 32.9%, and 66.2%, respectively (P < 0.05) compared with those in CKJ treatment (Fig. S1).

Effects of soil amendment on soil microbial community structure in cotton field

The application of soil amendment significantly affected soil microbial diversity and structure at the phylum level (Fig. S2, S3). The Chao1 index of both bacteria and fungi in GSY treatment decreased (P < 0.05), while the Pielo_e index increased (P < 0.05) compared with those in CKY treatment. The Chao1 index of bacteria and fungi and the Pielo_e index of fungi in GSJ treatment increased (P < 0.05) compared with those in CKJ treatment. The dominant bacterial phyla (relative abundance > 5%) in the soil were Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, and Gemmatimonadetes, accounting for more than 75% of the total (Fig. S2), and the dominant fungal phyla (relative abundance > 5%) were Ascomycota, Mortierellomycota, and Basidiomycota (Fig. S3).

The results of LEfSe analysis at the genus level (Fig. 4A, 4B) showed that the key soil bacterial genera were different in different treatments. The relative abundance of sixteen dominant bacteria (LDA score > 3.3) and 10 dominant fungi showed significant differences between different treatments (LDA score > 3.3). Gaiella, A4b, Longimicrobiaceae, Woeseia, S0134_terrestrial_group, Dongia, Subgroup_6, AKYG1722, Coprinellus, Fusarium, Botryotrichum, and Acrophialophora were the genera with higher relative abundance in CKY treatment. Subgroup_17, Mortierella, and Chaetomium were the genera with higher relative abundance in GSY treatment. Bacillus, Truepera, Streptomyces, JG30_KF_CM66, Metarhizium, and Gibberella were the genera with higher relative abundance in CKJ treatment. Aeromicrobium, Rokubacteriales, RB41, Mortierella, and Chaetomium were the genera with higher relative abundance in GSJ treatment. The bacterial community composition at the genus level was related to soil properties (Fig. 4C, 4D). Redundancy analysis (RDA) results showed obvious separation among treatments. Soil physical and chemical properties explained 96.25% and 78.6% of variations in bacterial and fungal communities, respectively. Soil pH and Na⁺ content were positively correlated with the relative abundance of Bacillus, Truepera, and S0134_terrestrial_group (Fig. 4C). Soil Si/C ratio, EC, and the content of AM-Si, Total Si, and EF-Si were positively correlated with the relative abundance of Streptomyces, JG30_KF_CM66, Woeseia, and Aeromicrobium. Soil FMH-Si and ORB-Si contents, SOC, Si/N ratio, and K⁺/Na⁺ ratio were negatively correlated with the relative abundance of RB41 and Subgroup_17. In terms of soil fungi (Fig. 4D), the content of soil TN, Total Si, and EF-Si were positively correlated with the relative abundance of Mycosphaerella. Soil AM-Si and K⁺ content were positively correlated with the relative abundance of Chaetomium, and soil C/N ratio and urease activity were positively correlated with the relative abundance of Fusarium.

The analysis of microbial metabolic functions (Fig. S4) showed that soil fungal metabolic functions mainly included biosynthesis, generation of precursor metabolite and energy, degradation/utilization/assimilation, and metabolic clusters. In addition to the above functions, bacterial functions also included glycan pathways and macromolecule modification.

Effect of soil amendment on microbial metabolism in cotton field

The application of soil amendment could regulate the metabolic functions of soil microorganisms. The relative abundances of 34 DEMs in GSY treatment were increased, while that of 44 DEMs were reduced, compared with those in CKY treatment. The relative abundances of 42 DEMs in GSJ treatment were increased and that of 39 DEMs were reduced compared with those in CKJ treatment (Fig. S5A). To further explore the interactions between these DEMs, VENN analysis were performed (Fig. S5B). The results showed that there were 18 DEMs in the four treatments, including: Hydroxypyruvic acid, (S)-1-Phenylethanol, 2-Pyrocatechuic acid, 2-Oxoarginene, L-Homophenylalanine, Vanillylmandelic acid, etc.

The results of KEGG enrichment analysis (Fig. S6) showed that the biosynthesis of antibiotics, glycolysis/gluconeogenesis, linoleic acid metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, glyoxylate and dicarboxylate metabolism, arginine and proline metabolism, and pyruvate metabolism/galactose metabolism were the most significant microbial metabolic functions.

To further explore how soil amendment changed the metabolic patterns of microorganisms in saline and alkaline soils, a metabolic network was visualized (Fig. 5A). In the phenylalanine, tyrosine, and tryptophan biosynthesis pathway, the abundance of Quinate in GSY treatment was reduced compared with that in CKY treatment, and the abundance of Fructose-1,6-bisphosphate in CKY treatment was also reduced compared with that in CKJ treatment. In the linoleic acid metabolism pathway, the abundance of 9(S)-HPODE in CKY treatment and GSJ treatment were increased compared with that in CKJ treatment. In the glyoxylate and dicarboxylate metabolism pathway, the abundance of Hydroxypyruvate was reduced in the four treatments. In the Arginine and proline metabolism pathway, the abundance of 2-Oxoarginine in GSY treatment was reduced, while that of 4-Guanidinobutanal was increased, compared with those in CKY treatment. The abundance of Creatinine and 2-Oxoarginine in CKY treatment were reduced, while 4-Guanidinobutanal was increased compared to those in CKJ treatment. Besides, the abundance of S-Adenosy-l-L-metioninamine and 5-Aminopentanoate in GSJ treatment were increased compared with those in CKJ treatment. In the pyruvate metabolism pathway, the abundance of Acetyl-P in GSY treatment and CKY treatment were reduced compared with that in GSJ treatment and CKJ treatment, respectively.

Heatmap analysis showed that in CKY and CKJ treatments, soil bacteria including Gaiella, Bacillus, AKYG1722, and Longimicrobiaceae promoted the accumulation of pyridinecarboxylic acids and derivatives, fatty acids and conjugates, and carbohydrates and carbohydrate conjugates. In GSY and GSJ treatments, the abundance of microorganisms were positively correlated with the abundance of dicarboxylic acids and derivatives. In CKY treatment, the abundance of soil fungi (Fig. 5B, 5D) including Fusarium and Botryotrichum were closely related to the abundance of lineolic acids and derivatives, fatty acids and conjugates, and short-chain keto acids and derivatives; and Aspergillus mainly affected alcohols and polyols in CKJ treatment. In GSY and GSJ treatments, Mortierella and Chaetomium were positively correlated with the abundance of dicarboxylic acids and derivatives and phenethylamines (Fig. 5C, 5D).

Relationships among soil microorganisms, soil properties, and soil microbial metabolites

The responses of different indicators to saline and alkali stresses were different (Fig. 4), so interactions among soil properties, key microorganisms (bacteria and fungi), and metabolites were also different. The co-occurrence network (Fig. 6) showed that in CKY treatment, bacteria A4b and Rokubacteriales were closely related to seed cotton yield, soil EC, and K⁺ content, Bacillus and Gaiella had a stable network relationships with fungi including Aspergillus, Mortierella, Acrophialophora, and Botryotrichum, which had significant effects on soil pH and Si/N ratio. In CKJ treatment, Metarhizium was closely related to most bacteria, and jointly affected the contents of soil available phosphorus and available silicon. Besides, the correlations between soil enzymes and physicochemical indicators also increased compared with those in other treatments. In GSY treatment, RB41, Rokubacteriales, Mortierella, and Chaetomium jointly affected the contents of EF-Si, FMH-Si, Total-Si, and Na⁺ content in soil, and pH was mainly affected by 4-Pyridoxic acid and Stachyose. In GSJ treatment, cotton root length was mainly affected by soil Na⁺ content, EC, and available phosphorus content. Soil bacteria promoted the change of soil physical and chemical properties, and soil fungi had a close relationship with soil microbial metabolites.

In this study, microbial interspecific cooperation, bacterial proliferation, and improvement of nutrient cycling efficiency played important roles in alleviating saline and alkaline stresses. However, after the application of soil amendment, saline and alkali stresses were alleviated by the proliferation of bacteria, metabolite and nutrient cycling, and increased metabolites. The analysis of soil microbial community abundance found that the dominant soil microorganisms (LDA > 3.3) were different in between amendment groups and non-amendment groups. This may be due to that there were differences in root exudates under saline and alkaline stresses, leading to difference in microorganisms in rhizosphere soil. This is consistent with the study results of Zhang (2020). Zhang (2020) reported that, on the one hand, microorganisms had the decomposition and energy conversion functions, and could change nutrient availability through biological processes; root exudates, on the other hand, changed with plant growth and development, thus forcing the formations of rhizosphere microbial communities with different diversity and functions.

In this study, a soil microbial community with Bacillus and Gaiella being the dominate bacteria and Botryotrichum, Acrophialophorvba, and Mortierella being the dominate fungi was formed in saline soil (CKY treatment). These microorganisms were negatively correlated with soil pH. It may be due to that the proliferation of soil microorganisms consumes a large amount of soil nutrients, which could reduce soil pH (Yi et al., 2021). Besides, it was also found that in GSY treatment, soil microbial community succession was jointly affected by key fungi (Mortierella) and bacteria (RB41, Rokubacteriates, and Subgroup_6), soil pH reduced, and the contents of soil K⁺, ORB-Si, and FMH-Si increased compared with those in CKY treatment. This is consistent with previous study results (Zhang et al., 2019). This indicates that soil amendment improve microbial resistance to saline stress by increasing soil nutrient content and reducing soil pH. Radwan et al. (1988) found that fungi could use the sodium salt contained in free fatty acids to ensure their growth, which increased soil Na⁺ content. However, in this study, with the proliferation of soil fungi, the soil Na⁺ content decreased (Fig. S1) after applying GS. This may be due to the surface complexation between benzene ring in GS and Na⁺ (Elyamine, 2018).

Under saline and alkaline stresses, different metabolites were secreted in cotton rhizosphere, resulting in different rhizosphere bacteria and fungi. In alkaline soil (CKJ treatment), cotton root exudated metabolites to attract fungi Metahizium and most bacteria (species) to the rhizosphere, promoting the accumulation of soil nutrients (Rashid et al., 2016). In CKJ treatment, soil EF-Si content was positively correlated with soil bacterial community and nutrients. This indicates that the increase of soil EF-Si content can significantly increase the relative abundance of soil bacteria (Song et al., 2020). Besides, the positive correlation between dominant microorganisms and soil nutrients and metabolites increased, and the positive correlation between dominant microorganisms and soil nutrients was weaker than that between dominant microorganisms and soil metabolites (Fig. 5). It indicates that in alkaline soil, soil microbial communities use soil metabolites as main carbon sources for their growth. However, the application of soil amendment changed the dominate microorganisms in alkaline soils. In CKJ treatment, the dominant soil microorganisms were JG30_KF_CM66 and Streptomyces. However, the dominant soil microorganisms in GSJ treatment were Rokubacteria and Aeromicrobium. Santillán (2021) showed that Rokubacteria played an important role in reducing soil pH. In this study, the application of GS also reduced soil pH. With the increase of the abundance of Mycosphaerella and Coprinellus, the activity of soil urease increased. Soil urease can decompose N in soil (Sun et al., 2019), and increase soil TN content (Fig. S1). Therefore, compared with CKY and CKJ treatments, soil amendment (GSY, GSJ) can change the composition and structure of soil microbial communities, reduce soil pH and Na⁺ content, and improve soil nutrient utilization efficiency.

In this study, soil amendment mainly regulated biogeochemical functions of soil microorganisms such as amino acid biosynthesis and fatty acid biosynthesis in saline and alkali soils (Fig. S6). This result is consistent with the predicted functions of bacteria and fungi (Fig. S4). The soil contains plant root exudates and endogenous metabolites of microorganisms. Microbes can regulate and degrade small molecular substances produced in soil metabolism, and promote the circulation and metabolism of exogenous nutrients in the soil (Li et al., 2019), thus improving the tolerance of soil microorganisms to saline and alkali stresses.

Microbes have different ecological function diversity in different soil environments (Litchman et al., 2015). Specifically, Arginine and proline metabolism, Glyoxylate and dicarboxylate metabolism, and Galactose metabolism were the most significant enrichment pathways in CKY treatment, and the metabolites 6-phosphogluconic acid and 4-pyridoxic acid produced by the above pathways could promote the accumulation of EF-Si and ORB-Si in soil (Fig. 7). Increased soil EF-Si and ORB-Si contents is beneficial for promoting cotton root elongation (He et al., 2018). The abundance of salt tolerant microorganism Bacillus significantly increased. Soil Bacillus can promote the solubilization of phosphorus and potassium and fix nitrogen, which is conducive to improving crop yields (Tao et al., 2020). In addition, other bacteria such as Longimicrobiaceae and Woeseia secreted lipids, lipid-like molecules, and organic oxygen compounds (Fig. 5). Among the exudates, lipids and lipid-like molecules can be absorbed by plant root and promote root growth (Yang et al., 2021). A4b is a key group in the rhizosphere microbiota of plants (Jiang et al., 2022) and plays a key role in resisting saline stress. In this study, after application of GS in saline soil (GSY treatment), the biosynthesis of amino acids and fatty acid biosynthesis pathways were up-regulated. Further, with the change of metabolic pathways, the dominant metabolites in soil also changed. In this study, the dominant metabolites in soil including amino acids and fat metabolites such as 2-Phospho-D-glyceric acid, phynylethylamine, sucrose, and 2-Oxoarginine in soil increased in GSY treatment, which could promote the growth of bacterial community (Kindler et al., 2009). Besides, in this study, soil amendment enhanced the interspecific cooperation of RB41, Mortierella, and Chaetomium in GSY treatment. Among them, RB41 can more efficiently use carbon sources in soil compared with other microorganisms (Liu et al., 2022), and Mortierella can chelate carbon in soil, leading to the increased content of stable organic carbon (Li et al., 2018). In this study, Mortierella and RB41 promoted the accumulation of soil organoheterocyclic compounds and organic acids (derivatives), and increased SOC (Fig. 6).

In CKJ treatment, soil bacterial community inhibited the biosynthesis of amino acids but accelerated the metabolism of hydrocarbon derivatives (Fig. S6). Dixit (2011) found that fungi can accelerate the decomposition of hydrocarbon derivatives and improve the tolerance of crops to extreme environments. In this study, the abundance of hydrocarbon derivatives and organoheterocyclic increased in CKJ treatment. The fungus Metarhizium and bacteria consumed large amounts of organoheterocyclic compounds and increased the accumulation of hydrocarbon derivatives, providing energy substances for crop growth. Further analysis found that galactose metabolism, phenylalanine metabolism, and fatty acid biosynthesis pathways were up-regulated in GSJ treatment. The differential metabolites of Fructose and Stachyose in the Galactose metabolism pathway serve as carbon sources to provide nutrients for soil microbial growth (Song et al., 2020), and soil Coprinellus is positively related to soil organic carbon and ammonium nitrogen in extreme arid environment (Duan et al., 2022). In this study, the abundance of Coprinellus increased in GSJ treatment (Fig. 5A), which could increase soil organic carbon and ammonium nitrogen content, supplying more nutrients for plant growth. Besides, Feduraev et al. (2020) found that a variety of phenolic secondary metabolites were produced in the phenylalanine metabolism, such as phenylalanine. Because phynylalanine can represent the accumulation of nitrogen in soil (Jiao et al., 2017), phynylalanine in soil could be absorbed by plant roots to promote root growth in this study. Besides, in GSJ treatment, the accumulation of soil differential metabolites phenylalanine and TN increased. This indicates that the application of amendment can increase the accumulation of soil differential metabolites, promote soil nutrient cycle, and reduce the damage of saline and alkaline stresses to cotton roots.

The application of soil amendment can reduce the pH and Na⁺ content of saline and alkaline rhizosphere soils, so as to improve the soil physical and chemical properties. Besides, by regulating the composition and structure of microbial community, changing dominant microorganisms and their uses of soil nutrients and metabolites, and optimizing the microbial symbiotic relationships, the adverse effects of saline and alkaline stresses on cotton growth and yield can be reduced. This study explored the changes of key microbial communities and soil metabonomics in saline and alkaline soils after applying soil amendment, especially the changes of soil Si forms and content, deepening our understanding of the mechanism of soil amendment alleviating saline and alkaline stresses. In the future research, based on this, the functional genes of soil microbial communities related to the resistance to saline and alkaline stresses will be screened by means of macro-genome sequencing, which is of great significance for predicting the impacts of environmental stresses on soil microbial communities with key functions.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

No data was used for the research described in the article.

Acknowledgment

This work was supported by the National Key Research and Development Program of China (grant number: 2016YFC0501406), the Innovation and Development Project of Shihezi University (CXFZ202207), and the Natural Science Foundation of Xinjiang Uygur Autonomous Region (2021D01B13). Hua F. and Wang K.Yconceptualized and conducted the experiment. Chang D.D conducted the data analysis and wrote the manuscript. Lu X.Y conducted the indoor experiment. Sun Y. assisted in conducting the experiment. All authors contributed to the manuscript and approved the submitted version.

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Responses of rhizosphere microbial communities and resource competition to soil amendment in saline and alkaline soils

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Abstract

Background and aims

Methods

Results

Conclusions

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Introduction

Materials and methods

Experimental site

Materials and experimental design

Determination of plant and soil parameters

Determination of cotton morphological parameters

Determination of soil properties

Soil high-throughput sequencing

Soil metabolomics

Data analysis

Results

Effects of soil amendment on root morphology and seed cotton yield

FTIR test results

Effects of soil amendment on the contents of different forms of silicon in the soils

Effects of soil amendment on soil microbial community structure in cotton field

Effect of soil amendment on microbial metabolism in cotton field

Relationships among soil microorganisms, soil properties, and soil microbial metabolites

Discussion

Conclusion

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