Combined application of organic material and inorganic compound fertilizer impacting on the structure and function of soil bacterial community

doi:10.21203/rs.3.rs-3630787/v1

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Combined application of organic material and inorganic compound fertilizer impacting on the structure and function of soil bacterial community

https://doi.org/10.21203/rs.3.rs-3630787/v1

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Excessive application of inorganic nitrogen fertilizers leads to soil degradation, while the application of organic materials helps to restore and maintain soil microecological balance. However, different applications of organic materials combined with inorganic fertilizers are possible to produce different influences on soil microbial communities. Therefore, field experiments of five fertilization treatments were carried out, that were: single inorganic compound fertilizer (CK), sheep manure + inorganic compound fertilizer (AF), cassava residue + inorganic compound fertilizer (PF), woody peat + inorganic compound fertilizer (MF), and monosodium glutamate waste slurry + inorganic compound fertilizer (IF). The results revealed that only the MF treatment significantly increased bacterial community richness compared to the CK. The relative abundance of Acidobacteriota was significantly lower in the treatment with combined application of organic materials and chemical fertilizers compared to the sole application of chemical fertilizers. Additionally, the relative abundance of Bacteroidota and Gemmatimonadota was significantly higher in the AF, while the relative abundance of Firmicutes was significantly higher in the IF. Soil organic carbon had the greatest impact on bacterial community structure. The IF significantly enhances soil carbon carbohydrate metabolism, while the AF significantly improves soil amino acid metabolism. The MF treatment had a higher abundance of anaerobic bacteria, while the PF treatment had a higher abundance of biofilm-forming bacteria. The IF treatment had the highest abundance of Gram-positive bacteria. The above results indicated that we can regulate the structure and function of soil bacterial communities, thus providing a favorable condition for crop production.

Biological sciences/Ecology

Earth and environmental sciences/Environmental sciences

The presence of a diverse and abundant microbial community in the soil plays a crucial role in facilitating nutrient cycling, enhancing soil structure, and improving overall soil fertility. Among these microorganisms, bacteria represent the largest and most prevalent group, responsible for decomposing mineralized organic matter and facilitating the essential cycles of carbon, nitrogen, and sulfur ¹. Their activities drive the material and energy flow within soil ecosystems, thus reflecting the soil’s health status and environmental conditions. In recent years, the excessive use of chemical fertilizers has resulted in the wastage of valuable nutrients, increased production costs, and a decline in soil biodiversity, ultimately leading to soil degradation ².To address these issues, the application of organic fertilizer has emerged as a vital strategy to restore soil biomes, enhance soil fertility, and ultimately improve soil productivity ³. This approach offers an essential initiative in regulating soil microbiomes, mitigating soil degradation, and promoting sustainable agricultural practices. The inclusion of organic materials in agricultural practices positively influences the abundance and composition of the active bacterial community in soil, leading to enhanced soil multifunctionality. This, in turn, plays a critical role in facilitating organic matter decomposition, nutrient cycling, and overall soil health ^4,5. Long-term application of organic and inorganic fertilizers has been shown to restore soil bacterial diversity and increase crop yields, which highlighted the significance of bacteria in improving crop productivity when organic and inorganic fertilizers were applied ⁶. The application of less chemical fertilizer and more organic fertilizer is conducive to maintaining and increasing the abundance and diversity of specific functional bacteria in the soil, which is in favor of protecting fragile ecological environments ⁷. Soil environmental factors, in which soil pH is a key controller of bacterial communities, have been demonstrated to indirectly shape bacterial communities by influencing soil nutrient levels ⁸.

Changes in bacterial community structure are closely associated with biological functions ⁹. The application of organic materials effectively enhances the abundance of genes associated with key metabolic pathways in bacteria, thereby facilitating bacterial flora functionality ¹⁰. The effects of different organic materials and chemical fertilizers on soil microorganisms vary due to the inherent properties of each organic material. Among them, organic matter emerges as a primary factor influencing the dynamics of soil microorganisms ¹¹. Currently, there is a wide range of organic materials derived from industrial and agricultural waste sources, which exhibit diverse characteristics and find extensive applications. There have been numerous studies on the application of manure in field experiments, while there is limited research on the effects of cassava residue, woody peat, and monosodium glutamate waste slurry when co-applied with chemical fertilizers on the community structure and functional dynamics of soil microorganisms. An impact of these organics on soil microbial communities remains unclear, necessitating further investigation.

To gain a comprehensive understanding of the impacts of different organic materials and chemical fertilizers on the structure and function of soil bacterial communities and to realize the appropriate utilization of organic materials, this study employed Illumina high-throughput sequencing technology and the PICRUSt2 analysis method ¹², while soil environmental factors were taken into account. A field experiment involving four organic materials (sheep manure, cassava residue, woody peat, and monosodium glutamate waste slurry) was conducted to investigate the changes in the structure and function of soil bacterial communities in maize fields under the influence of organic materials and chemical fertilizer application. The study of correlations between these changes and environmental factors aims to reveal the regulatory mechanisms of different organic materials on soil microorganisms. This study can provide a scientific foundation for maintaining soil health and optimizing the utilization of organic materials.

Site description

In 2022, the experiment was conducted in summer maize growing season at the experiment site of Linyi R&D Center, which is located in Hedong District, Linyi City, Shandong Province, China(35°08′N, 118°40′E), where is a temperate monsoon climate with an average annual temperature of 15.0°C, average annual precipitation of 799.9 mm, average annual sunshine hours of 2220.7 h, average annual wind speed of 3.3 m.s^− 1, and frost-free period of about 200 days. The soil texture of the site is sandy loam and the soil type is brown loam. The basic soil chemical properties at the start of the experiment in 2022 were as follows: organic matter content of 15.37 g.kg^− 1, total nitrogen content of 0.83 g.kg^− 1, total phosphorus content of 0.63 g.kg^− 1, total potassium content of 15.12 g.kg^− 1, available nitrogen content of 88.14 mg.kg^− 1, available phosphorus content of 9.40 mg.kg^− 1, available potassium content of 128.97 mg.kg^− 1, and a pH value of 8.27.

Experiment design and soil sampling

A single-factor randomized complete block design was employed with 5 treatments and 3 replications. The shape of the test plot is rectangular, with an area of 20 m²(2 m × 10 m). The organic materials used in this experiment were sheep manure, cassava residue, woody peat and monosodium glutamate waste slurry, and have been fermented and rotten, The main nutrient contents and pH values are shown in Table 1. Using chemical fertilizer alone as the control (CK), several experimental treatments of combined application of organic materials and chemical fertilizers were set up, which were sheep manure + chemical fertilizer (AF), cassava residue + chemical fertilizer (PF), woody peat + chemical fertilizer (MF), and monosodium glutamate waste slurry + chemical fertilizer (IF). The chemical fertilizer was inorganic compound fertilizer (N-P₂O₅-K₂O percentage content is 28-6-6), and the application rate was 525 kg.ha^− 1 for chemical fertilizer and 3000 kg.ha^− 1 for organic material. The wheat straws were moved out of the field, followed by farm tillage. When corn was sown, organic material and chemical fertilizer were applied to the field by strip application, with fertilization depth of 12 ~ 15 cm, and no additional fertilizer was applied later.

Table 1

Nutrient content and properties of organic materials
Organic material	OM(g.kg^− 1)	TN(g.kg^− 1)	TP(g.kg^− 1)	TK(g.kg^− 1)	pH
sheep manure	353.7	19.7	14.0	20.7	9.13
cassava residue	252.2	15.1	34.4	5.4	7.42
woody peat	554.0	6.9	1.9	0.4	4.71
monosodium glutamate waste slurry	350.0	69.6	7.0	62	5.95
OM: organic matter; TN: total nitrogen; TP: total phosphorus; TK: total potassium

The field experiment was conducted from June 15, 2022, to October 10, 2022, covering a maize growing cycle of 118 days. Before the maize harvest, topsoil samples (0 ~ 20 cm) were collected in each plot with a 5 cm diameter soil auger in an "S" shaped sampling pattern. To ensure the uniformity of sampling, samples were taken on both sides of the fertilization ditch, and the sample points were kept at the same distance (15cm) from the center of the fertilization ditch. 15 soil samples were collected, stored in ice boxes and brought back to the laboratory to be sieved through 2 mm mesh, soil samples are divided into two parts after removing roots, stones and other debris, one of which is stored in a -80°C refrigerator for soil bacterial community analysis, and the other is dried naturally and used to determine the chemical properties of the soil.

Analysis items and methods

Soil chemical property analysis

Indicators of the soil chemical properties were determined by Methods of Soil Agrochemical Analysis ¹³. Thoes are the potassium dichromate volumetric method for soil organic carbon determined, the alkaline diffusion method for soil available nitrogen determined, the sodium bicarbonate leaching and molybdenum antimony anti-colorimetric method for soil available phosphorus determined, the ammonium acetate leaching - flame photometer method for soil available potassium determined, the composite electrode at 2.5:1 water-soil ratio for soil pH determined, and the conductivity meter at 5:1 water-soil ratio for soil conductivity determined.

DNA extraction and PCR amplification

The total genomic DNA extraction from microbial communities was performed according to the instructions of E.Z.N.A.®soilDNAkit (OmegaBio-tek, Norcross, GA, U.S.), and the quality of the extracted genomic DNA was detected by 1% agarose gel electrophoresis, and the DNA concentration and purity were determined by NanoDrop2000 (ThermoScientific Inc., USA). The hypervariable region V3-V4 of the bacterial 16S rRNA gene were amplified with primer pairs 338F (5'-ACTCCTACGGGAGGCAGCAG-3') and 806R(5'-GGACTACHVGGGTWTCTAAT-3') by an ABI GeneAmp® 9700 PCR thermocycler (ABI, CA, USA). The PCR reaction mixture including 4 µL 5 × Fast Pfu buffer, 2 µL 2.5 mM dNTPs, 0.8 µL each primer (5 µM), 0.4 µL Fast Pfu polymerase, 10 ng of template DNA, and ddH2O to a final volume of 20 µL. PCR amplification cycling conditions were as follows: initial denaturation at 95 ℃ for 3 min, followed by 27 cycles of denaturing at 95 ℃ for 30 s, annealing at 55 ℃ for 30 s and extension at 72 ℃for 45 s, and single extension at 72 ℃ for 10 min, and end at 4 ℃. The microbial community structure was analyzed by sequencing using Illumina's MiseqPE300 platform (Shanghai Meiji Biomedical Technology Co., Ltd.), and three replicates of each sample were performed.

High-throughput sequencing and bioinformatics analysis

Fastp0.19.6 software was used to control the quality of the double-ended original sequencing sequences ¹⁴, and FLASH1.2.11 software was used for splicing ¹⁵. Based on the default parameters, the DADA2 plug-in in the Qiime2 process was used to denoise the optimized sequence after quality control splicing ¹⁶. The sequences after DADA2 noise reduction are commonly referred to as ASVs (i.e. amplicon sequence variants). Alpha diversity indexes (such as Chao, ACE, Shannon and Simpson indexes) were calculated using the software Mothur ¹⁷, and the Wilcoxon rank sum test was used for the inter-group variation analysis of Alpha diversity; PICRUSt2 was used for predictive analysis of soil bacterial community function, and the BugBase was used for predicting the phenotypes of soil bacterial communities ¹⁸.

Statistical analysis

Microsoft Excel 2016 was used for preliminary analysis of the data. One-way ANOVA was performed using DPS 7.05 software, and LSD test was used to test the significance of differences between the data. Different lowercase letters indicated that there was a significant difference at the P < 0.05 level. Pearson correlation analysis was performed on the data using Origin 2021 software. Redundancy analysis (RDA) was performed by Canoco 5.0 for restriction ranking to analyze the relationship between environmental factors and population classification. The relative abundance diagrams of bacterial phyla and genera, as well as the predicted functional and phenotypic analysis of bacterial communities, were drawn using Origin 2021 software.

Alpha diversity of soil bacterial communities

The ACE index of soil bacteria reflected the richness of the soil bacterial community, and the Shannon index and Simpson index reflected the diversity of the soil bacterial community. As presented in Table 2, comparisons were made between each treatment and the CK. The results indicate that all treatments exhibited increased ACE index and Shannon index values, indicating higher richness and diversity compared to the CK. Specifically, the MF treatment displayed the highest ACE index and Shannon index values. The ACE index of the MF treatment significantly exceeded that of the CK. However, no significant differences in the Shannon index and Simpson index were observed among the various treatments.

Table 2

The alpha diversity index of soil bacteria communities under different treatments
Treatment	ACE index	Shannon index	Simpson index
CK	982 ± 35b	6.51 ± 0.02a	0.0023 ± 0.0001a
AF	1045 ± 71ab	6.58 ± 0.07a	0.0020 ± 0.0001a
PF	1055 ± 39ab	6.59 ± 0.01a	0.0021 ± 0.0000a
MF	1112 ± 59a	6.62 ± 0.05a	0.0020 ± 0.0003a
IF	1062 ± 56ab	6.59 ± 0.07a	0.0021 ± 0.0003a
Note: Values (mean ± standard deviation) indicate the absolute amount of each characteristic. Different letters in column indicate significant differences (P < 0.05) between sampling sites according to Duncan’s multiple comparison.

Soil bacterial community composition

The community composition and distribution of soil bacterial phylum taxonomic levels for different treatments are shown in Fig. 1(a). The bacterial taxa with relative abundance greater than 1% for each treatment were mainly Actinobacteriota, Proteobacteria, Acidobacteriota, Chloroflexi, Firmicutes, Myxococcota, Bacteroidota, and Gemmatimonadota, with 93.18%, 95.61%, 95.23%, 94.63%, and 95.57% of the total bacterial abundance, respectively. Compared to CK, the relative abundance of Actinobacteriota, Proteobacteria, Chloroflexi, Bacteroidota and Gemmatimonadota was increased to different degrees in each treatment of organic material application, while the relative abundance of Acidobacteriota was significantly lower in all treatments. Among the treatments, the AF treatment exhibited the highest relative abundance of Actinobacteriota, Bacteroidota, and Gemmatimonadota. The PF treatment demonstrated the highest relative abundance of Proteobacteria and Myxococcota. The MF treatment exhibited the highest relative abundance of Chloroflexi, while the IF treatment showed the highest relative abundance of Firmicutes.

The relative abundance of soil bacterial genera at the taxonomic level varied in different treatments is shown in Fig. 1(b). Among the classified genera, Bacillus exhibited the highest relative abundance in each treatment, ranging from 2.25–5.21%. The abundance of Bacillus was particularly elevated in the IF treatment compared to the other treatments. The genera with relative abundance greater than 1% in each treatment were Nocardioides, Gaiella, Streptomyces, Sphingomonas, MND1, RB41, Dongia, Bryobacter, Acidibacter and Microvirga. The relative abundance of Gaiella was significantly higher in each organic material application compared to CK, and the relative abundance of Nocardioides was significantly higher in the AF compared to the other treatments.

Relationship between soil bacterial communities and environmental factors

The correlation analysis of the main soil bacterial taxa and environmental factors was performed and the results are shown in Fig. 2. The analysis revealed that soil environmental factors accounted for 52.12% of the variation in bacterial communities at the gate level. Specifically, 35.37% of the variation was explained by the first ranking axis (RDA1) and 16.75% by the second-ranking axis (RDA2). These results suggest that environmental factors contribute to the variation in bacterial communities to a certain extent, with soil organic carbon exerting the strongest influence on the bacterial community structure. As shown in Table 3, the application of organic materials influenced the soil bacterial community structure by increasing the soil organic carbon content and thus the soil bacterial community structure. Compared to the CK, the PF significantly increased soil available nitrogen content, the AF and IF treatments significantly increased soil available potassium content. Additionally, the MF and IF treatments significantly decreased soil pH. These variations in soil properties resulting from organic material application may contribute to differences in soil bacterial communities among treatments. Regarding the interrelationships between soil environmental factors and bacterial functional groups, a significant positive correlation was observed between soil Actinobacteriota and organic carbon (R² = 0.74, P < 0.05). Soil Acidobacteriota, on the other hand, showed a significant negative correlation with available phosphorus (R²=-0.52, P < 0.05) and available potassium (R²=-0.54, P < 0.05), while exhibiting a significant positive correlation with soil pH (R² = 0.54, P < 0.05). These findings indicate that soil organic carbon, available potassium, pH, and available phosphorus are the main influencing factors shaping the distribution of soil bacterial communities, while soil EC has less influence on bacterial community distribution.

Table 3

Soil environmental factors of different treatments
Treatment	SOC (g.kg^− 1)	AN (mg.kg^− 1)	AP (mg.kg^− 1)	AK (mg.kg^− 1)	pH	EC (µs.cm^− 1)
CK	8.62 ± 0.79a	99.54 ± 9.95b	10.98 ± 0.88b	119.70 ± 4.29b	8.40 ± 0.05a	102.17 ± 7.12b
AF	9.39 ± 1.11a	107.71 ± 6.54b	14.94 ± 0.60a	127.97 ± 6.54ab	8.43 ± 0.03a	102.23 ± 18.16b
PF	10.23 ± 1.34a	123.13 ± 5.07a	13.99 ± 0.64a	140.93 ± 11.47a	8.27 ± 0.08ab	114.47 ± 4.94ab
MF	9.30 ± 0.65a	101.92 ± 2.81b	13.36 ± 1.53a	121.23 ± 7.95b	8.33 ± 0.08b	99.27 ± 14.25b
IF	10.75 ± 1.78a	105.31 ± 4.40b	13.90 ± 1.38a	138.60 ± 2.52a	8.27 ± 0.06b	129.23 ± 12.65a
Note: SOC, soil organic carbon; AN, soil available nitrogen; AP, soil available phosphorus; AK, soil available potassium; EC, soil electrical conductivity. Values (mean ± standard deviation) indicate the absolute amount of each characteristic. Different letters within each column indicate significant differences (P < 0.05) between sampling sites according to Duncan’s multiple comparison.

Prediction of soil bacterial community function and phenotype

Based on the KEGG database, functional prediction analysis of bacterial communities in each treatment soil using PICRUSt2 resulted in the annotation of six primary functional metabolic pathways, 40 secondary functional metabolic pathways, and 264 tertiary functional metabolic pathways. The relative abundance of primary functional metabolic pathways in each treatment was in the order of metabolism, environmental information processing, genetic information processing, cellular processes, human diseases and organic systems (Table 4). The relative abundance of metabolism, in particular, was the highest among the primary functional metabolic pathways, ranging from 62.02–62.27%. The AF treatment exhibited the highest abundance of metabolism, significantly surpassing CK. Among the secondary functional metabolic pathways (Fig. 3), there were 18 metabolic pathways with relative abundance greater than 1.00%. Carbohydrate metabolism had the highest abundance at 12.78–13.17%, with the highest abundance observed in the IF treatment, significantly exceeding other treatments. Amino acid metabolism followed with an abundance range of 12.33–12.55%, with the AF treatment showing the highest abundance, significantly greater than the other treatments. In the environmental information processing pathway, membrane transport also exhibited higher abundance (11.35–11.82%) across all treatments, with the AF showing the highest abundance, significantly higher than the CK.

Table 4

Abundance of primary functional genes in soil bacteria under different treatments
Level one function	CK	AF	PF	MF	IF
Metabolism	62.02 ± 0.05b	62.27 ± 0.06a	62.06 ± 0.22ab	62.18 ± 0.09ab	62.04 ± 0.04ab
Environmental information processing	18.73 ± 0.09a	19.01 ± 0.11a	18.76 ± 0.13a	18.90 ± 0.16a	18.81 ± 0.27a
Genetic information processing	11.57 ± 0.02ab	11.21 ± 0.10c	11.55 ± 0.12ab	11.44 ± 0.12b	11.63 ± 0.23a
Cellular processes	4.71 ± 0.04a	4.73 ± 0.08a	4.74 ± 0.14a	4.72 ± 0.08a	4.61 ± 0.06a
Human diseases	2.07 ± 0.06a	1.93 ± 0.08b	2.00 ± 0.08ab	1.93 ± 0.02b	2.04 ± 0.02ab
Organismal systems	0.91 ± 0.12a	0.86 ± 0.07a	0.90 ± 0.02a	0.84 ± 0.08a	0.88 ± 0.06a

Phenotypic predictions were made for each treatment soil sample using BugBase, resulting in nine categories: aerobic, anaerobic, mobile element, facultatively anaerobic, biofilm-forming, Gram-negative, Gram-positive, potentially pathogenic and oxidative stress tolerant (Fig. 4). Since a species may have multiple phenotypes, this may result in a total phenotypic abundance of bacteria higher than 100% in each treatment soil. Among the nine phenotypic categories, mobile element accounted for the highest percentage of 71.02–75.58%, but there were no significant differences among different treatments. Regarding oxygen demand phenotype, aerobic phenotype was the most abundant, comprising 57.06–60.10% of the total, with no significant differences among treatments. The anaerobic phenotype was significantly higher in the MF, while facultatively anaerobic phenotype was significantly lower compared to the CK. The PF treatment had the highest relative abundance of mobile element, biofilm-forming, oxidative stress tolerance. Additionally, the relative abundance of Gram-negative was significantly higher in the PF compared to the IF. On the other hand, the IF had the highest relative abundance of Gram-positive and was significantly higher than that of the PF.

Effect of different treatments on the composition of soil bacterial communities

The application of organic materials in this study increased the abundance and diversity of soil bacterial communities. However, only the application of woody peat significantly increased the abundance of soil bacteria, probably due to the higher organic matter content of woody peat, which provides sufficient carbon source for microbial growth ¹⁹. Zhao et al. ( 2021 ) pointed out that there were no significant differences in the ability of soil nutrient-poor bacteria and nutrient-rich bacteria to obtain carbon sources and the function of microbial community after adding organic materials that are easy to use and difficult to use by soil microorganisms compared with that without the addition of organic materials ²⁰. However, there were no significant differences in soil bacterial community diversity among the treatments in our study, which may be attributed to this. Similar to the results, another study also showed no significant effect of biochar addition on soil bacterial diversity ²¹.

Our results indicate that soil organic carbon is the primary influencing the distribution of soil bacterial communities, it can be attributed to two reasons: firstly, the large amount of organic matter in organic material provides sufficient carbon source for the growth and reproduction of soil bacteria ²²; secondly, the combined form of humus rich in soil organic matter and soil mineral particles affects soil nutrient supply and soil structure, changes the soil microhabitat environment and influences the survival and reproduction of soil bacteria ¹⁸. In our study, a significant positive correlation was observed between soil organic carbon and Actinobacteriota. Actinobacteria were widely distributed in neutral to slightly alkaline soil environments and exhibited the ability to degrade cellulose, lignin, and various recalcitrant aromatic compounds ^23,24. They played a crucial role in the mineralization of soil organic matter and exhibited relatively high abundance in the various organic material treatments employed in this study. In addition, this study showed a significant positive correlation between Acidobacteria and pH, while showing a significant negative correlation with available phosphorus and available potassium in the soil. This can be attributed to the preference of Acidobacteria for acidic soil environments with lower nutrient content. Their abundance can serve as an indicator of soil fertility ^25,26. The application of organic materials increased nutrient content in the soil, which placed Acidobacteria, well-suited for low-nutrient soil, at a disadvantageous competitive position. The significant reduction in relative abundance of Acidobacteria following the application of organic materials indicates an improvement in soil health. The Chloroflexi utilize atmospheric CO₂ for photosynthesis without generating oxygen, making them competitive in soils with low organic matter content. They are also suited to survive in soils with low nutrient content, similarly, in this study, Chloroflexi had a higher abundance in the woody peat treatment with lower soil organic matter content ^27,28. The Firmicutes have been shown to secrete various enzymes crucial for nitrogen fixation and are directly involved in multiple nitrogen metabolic pathways ²⁹, The significant increase in the relative abundance of Firmicutes in soil may be attributed to the abundant nitrogen source present in monosodium glutamate waste slurry, stimulating their growth and reproduction. The Bacteroidertes is phosphate solubilizing and can secrete organic acids and phosphatases to promote the conversion of insoluble phosphorus to H₂PO₄⁻ and HPO₄²⁻ for better uptake and use by plants. In this study, the higher content of organic phosphorus and organic carbon in sheep manure promoted the growth of Bacteroidertes, significantly increasing its abundance in the treated soil. Consequently, the treated soil showed higher levels of available phosphorus ^30,31. Among the top ten soil bacterial genera in relative abundance, Bacillus emerges as the most dominant group. Bacillus, belonging to the Firmicutes phylum, comprises aerobic or partially anaerobic Gram-positive bacteria that are widely distributed in soil and water. They play a crucial role in promoting soil nitrogen fixation, phosphate solubilization, potassium mobilization, and enhancing plant growth by producing phytohormones, inducing plant resistance, and inhibiting pathogenic bacteria ^32–34. In this study, the application of monosodium glutamate waste slurry had the most significant enhancement effect on Bacillus, which can enhance crop growth and increase yield. As a plant-beneficial bacterium, Gaiella can secrete a variety of active substances to inhibit the growth of soil pathogens and promote plant growth, the results of this study showed that the relative abundance of soil Gaiella increased significantly after the application of organic materials ³⁵. The application of sheep manure in this study significantly elevated the relative abundance of soil Nocardioides, this can be attributed to the higher pH and alkalinity associated with this treatment. Nocardioides belonging to the Actinobacteria phylum, favors saline environments ³⁶.

4.2. Prediction of soil bacterial community function and phenotype

The changes in bacterial community structure caused corresponding changes of soil bacterial function, and all treatments of the organic material application increased the abundance of metabolic pathway genes in the soil bacterial community. Metabolism is the core function of soil bacterial community, soil bacteria participate in soil material cycle and transformation through metabolism, promote plant growth and increase crop yield, and active metabolic activities also ensure the survival of soil bacteria, and the enhancement of metabolic activities can promote plant root uptake of nitrogen and phosphorus ^37–39.

Within the secondary metabolic pathway, carbohydrate metabolism and amino acid metabolism are dominant. Carbohydrate metabolism is regulated by plants through processes such as photosynthesis, which govern the formation, decomposition, and conversion of carbohydrates in organisms ⁴⁰. The addition of organic materials effectively supplements soil carbon and nitrogen nutrients, thereby improving soil bacterial carbohydrate metabolism and increasing the abundance of relevant genes. Amino acid metabolism, on the other hand, is closely linked to the plant nitrogen cycle ⁴¹. Organic materials provide a large source of carbon and nitrogen to the soil, which can greatly enrich the nutrient resources required for soil bacterial metabolism, and sustains bacterial survival by soil metabolism ⁴², so that the application of organic materials increased the abundance of carbohydrate and amino acid metabolism genes. Abundant Actinobacteriota in the soil can also secrete more extracellular enzymes to degrade organic matter, both soluble and insoluble, further enhancing nutrient availability ²³. The sheep manure treatment increased the abundance of genes related to amino acid metabolism in the soil, which could be attributed to the enrichment of Nocardioides bacteria, an important microbial group involved in soil nitrogen cycling processes. On the other hand, the significant increase in carbohydrate metabolism in the monosodium glutamate waste slurry treatment may be attributed to the abundance of Bacillus.

A study using BugBase phenotype prediction revealed that the relative abundance of anaerobic bacteria with high oxygen demand was significantly higher in the woody peat treatment compared to other treatments, which might be related to the properties of organic materials. Woody peat is an organic matter accumulation layer formed by woody plant residues in an anaerobic environment, which is rich in anaerobic bacteria. Biofilm forming in cassava residue treatment was significantly higher than other organic material treatments, which indicated that its bacterial functional groups had better ecological remediation potential ^43,44. The monosodium glutamate waste slurry treatment showed the highest relative abundance of Gram-positive bacteria and the lowest relative abundance of Gram-negative bacteria, it indicated that the bacterial functional groups in this treatment were more adaptable to environmental stresses ⁴⁵. The Gram-positive bacteria tend to utilize carbon sources from soil organic matter, while Gram-negative bacteria rely more on plant residues as carbon sources. Soil microorganisms can regulate their phenotypic changes to enhance environmental adaptability utilized carbon sources mainly from plant residues ⁴⁶. It is important to note that BugBase phenotype prediction is based on ASV (amplicon sequence variant) data analysis and that a species may belong to multiple phenotypes. Therefore, it may not fully reflect changes in all phenotypes of the mycota, and further research is required to validate this prediction analysis.

In this study, an application of organic materials resulted in an increase in both the abundance and diversity of soil bacterial communities, with woody peat having the most pronounced effect. Relative abundance significantly reduced for soil Acidobacteriota and increased for soil Gaiella by the application of organic material. Specifically, the application of monosodium glutamate waste slurry increased the relative abundance of Firmicutes and Bacillus, while sheep manure application increased the relative abundance of Firmicutes and Nocardioides. Metabolism is a core function of the soil bacterial community in each treatment, with the highest abundance of genes related to carbohydrate metabolism observed in the secondary metabolic pathway, particularly in the monosodium glutamate waste slurry treatment. The bacterial community associated with cassava residue application exhibited better potential for ecological restoration, while the bacterial community associated with monosodium glutamate waste slurry application showed greater adaptability to environmental stress.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This study was funded by the Soil Health Technology and Product and Integrated Solution Development Project of Sinochem Fertilizer Co.( 072023005F).

Author Contribution

Yang: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft, Visualization, Supervision. Li: Formal analysis, Methodology, Writing - review & editing. Du: Data curation, Writing - review & editing. Wang: Data curation, Writing - review & editing, Formal analysis, Visualization. Zhou: Data curation, Writing - review & editing, Formal analysis. Zhang: Conceptualization, Methodology, Formal analysis, Data curation, Project administration, Funding acquisition. Zhu: Conceptualization, Methodology, Formal analysis, Data curation, Investigation, Writing - original draft, Supervision.

Acknowledgements

We would like to express our sincere gratitude to associate professor Dongliang Qi for his valuable guidance in the preparation of this manuscript, and also thanks to the Research and Development Center of Sinofert Linyi for providing the experimental facilities and conditions.

Data availability

All data generated or analyzed during the study are included in this published article to this article.

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Combined application of organic material and inorganic compound fertilizer impacting on the structure and function of soil bacterial community

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Abstract

Figures

Introduction

Materials and methods

Site description

Experiment design and soil sampling

Analysis items and methods

Soil chemical property analysis

DNA extraction and PCR amplification

High-throughput sequencing and bioinformatics analysis

Statistical analysis

Results

Alpha diversity of soil bacterial communities

Soil bacterial community composition

Relationship between soil bacterial communities and environmental factors

Prediction of soil bacterial community function and phenotype

Discussion

Effect of different treatments on the composition of soil bacterial communities

4.2. Prediction of soil bacterial community function and phenotype

Conclusions

Declarations

Conflict of interest

Funding

Author Contribution

Acknowledgements

Data availability

References

Additional Declarations

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