Microbial Divergence and Degradative Capacity During Straw Enrichment

Abstract

Whether consecutive annual incorporation of rice straw can enrich straw-decomposing microorganisms, and what common and distinct dominant straw-degrading microbial populations exist in soils under long-term rice straw incorporation across different regions of Fujian Province, remain relatively unexplored. To address this, soil samples were collected from rice cultivation areas with consecutive straw incorporation located in different geographical directions within Fujian Province. A straw burial pot experiment was conducted, and high-throughput sequencing was employed to analyze the bacterial and fungal community compositions in these soils. Furthermore, the degradation potential of the soil microbial communities towards rice straw was determined. The results revealed that the dominant bacterial phyla associated with straw degradation across the four treatments were Proteobacteria, Actinobacteriota, Firmicutes, and Chloroflexi, while the dominant fungal phyla were Ascomycota and Basidiomycota. At the genus level, the relative abundance of the dominant bacterial genus, Bacillus, showed a positive correlation with the straw degradation rate but a negative correlation with soil pH. In contrast, the dominant fungal genera, Zopfiella and Chaetomium, were positively correlated with both the straw degradation rate and soil pH. Furthermore, a strain designated PC1 was isolated and screened from the PC treatment samples. Sequencing of the rDNA-ITS region identified PC1 as Chaetomium sp. The degradation rate of rice straw by strain PC1 reached 49.13%, which was higher than the degradation rate observed in the PC treatment in the pot burial experiment. This finding provides a theoretical foundation for the potential application of efficient lignin-degrading fungi in field-scale straw degradation.

1. Introduction

China, as one of the world’s most abundant sources of crop straw, faces significant importance in the rational and highly efficient utilization of this resource for sustainable agricultural development. Straw return to fields leads to improvements in comprehensive soil ecological factors, subsequently enhancing soil microbial activity [1,2,3,4,5,6]. This increase in microbial activity and intensified microbial actions inevitably accelerate the decomposition and decay of straw, which further ameliorates the soil environment. Consequently, an improved soil environment enhances microbial activity and actions again [7,8,9], forming a mutually reinforcing positive cycle. Soil fungi and bacteria constitute the main body of soil microbial biomass and respond differently to straw incorporation due to their distinct nutritional preferences [10,11]. Qiu P. et al. [12], through a 30-year long-term straw incorporation experiment, found that compared to non-straw application, straw return increased the abundance of Gram-negative bacteria by 11.6% and fungi by 68.2%. Some studies have identified key microbial taxa, such as Pseudomonas, Pannonibacter, Thauera, Ruminofilibacter, and Anaerocolumna, as playing significant roles during straw decomposition, the response of soil microbiota also varies at different decomposition stages [13]. Li Peng et al. [14], investigating the succession of soil fungal communities over different straw incorporation periods, reported significant changes in fungal abundance and diversity with prolonged incorporation time. Furthermore, Tan Zhoujin et al. [15], tracking soil microbes throughout the straw plowing process, observed that after straw return during the late rice growth period, soil microbial biomass initially increased significantly and then gradually decreased. Soil fungi and bacteria can synergistically degrade lignin by secreting various oxidases, including laccase and peroxidase [16]. Laccases are widely present in both fungi and bacteria and can directly oxidize phenolic lignin during lignin degradation. Fungal laccases generally exhibit higher redox potential and stronger catalytic activity compared to bacterial laccases [17].

Straw degradation is a core process in the agricultural ecosystem carbon cycle, requiring the collaborative activity of cellulose-degrading, hemicellulose-degrading, and lignin-degrading microorganisms, along with other microbes that utilize intermediate metabolites. The effectiveness of straw return varies significantly across regions, partly due to differences in microbial communities. These regional variations in microbiota directly influence both the rate and pathway of carbon turnover [18,19]. Abiotic factors-such as temperature, humidity, soil pH, and soil type-exert strong selective pressures, leading to compositional differences in microbial communities across different geographical areas [20]. While functional redundancy ensures that certain degradation processes are carried out by multiple microbial groups, some microorganisms become uniquely adapted to local conditions, emerging as region-specific, highly efficient keystone species or core microbiota. Identifying these locally adapted, highly efficient degraders is essential for developing effective microbial inoculants [21]. This study addresses the following questions: How does continuous rice straw incorporation affect the soil microbial community structure in different regions of Fujian Province? What shared core microorganisms with straw degradation potential exist across these regions? Nevertheless, a knowledge gap persists concerning this particular issue within Fujian Province’s primary rice cultivation zones. Soil samples were collected from four long-term rice straw return sites located in the northern, central, and southern parts of Fujian Province. A pot-based straw burial experiment was conducted, and high-throughput sequencing was used to analyze the straw-enriched bacterial and fungal communities. We investigated how microbial composition and straw degradation potential respond to environmental factors. By exploring these regional microbial differences, this work enables the targeted selection of high-efficiency indigenous microbial strains tailored to local climatic and soil conditions. The results provide a scientific basis for developing composite microbial agents with direct practical application, enhancing the efficiency of in situ straw return or off-site composting. This approach offers a precise technological tool for promoting green agriculture and enabling efficient recycling of agricultural waste resources.

2. Materials and Methods

2.1. Experimental Soil

Soil samples were collected from representative rice planting areas with continuous annual straw return practices in different regions of Fujian Province. The specific sampling sites were as follows: BS Treatment: Located at the Ministry of Agriculture and Rural Affairs Fujian Scientific Observing and Experimental Station of Cultivated Land Conservation, Xitou Village, Baisha Town, Minhou County, Fuzhou City (119°04′10″ E, 26°13′31″ N). LY Treatment: Located at Zhongfang Village, Lufeng She Ethnic Township, Shanghang County (116°28′30″ E, 24°59′37″ N). JO Treatment: Located at Zhangtun Village, Dongyou Town, Jian’ou City (118°37′55″ E, 27°14′93″ N). PC Treatment: Located at Rui’an Village, Fuling Town, Pucheng County (118°61′04″ E, 27°86′47″ N).

The general natural characteristics of each study area are provided in

Table 1. General situation of the study area.

Natural Condition		BS	LY	JO	PC
Annual sunshine hours (h)		1812.5	1704	1612	1635
Mean annual temperature (°C)		19.5	17.8	19.3	17.6
Annual precipitation (mm)		1350.9	1550	1700	1755
Soil physicochemical property	pH	4.78	5.1	5.3	5.1
	Organic matter (g/kg)	24.4	44.6	20.5	28.7
	Total nitrogen (g/kg)	1.23	2.86	1.13	1.82
	Total phosphorus (g/kg)	0.60	1.1	1.46	0.83
	Total potassium (g/kg)	13.3	14.7	12.6	28
	Alkaline hydrolysis nitrogen (mg/kg)	171.6	115.3	95.3	139.0
	Available phosphorus (mg/kg)	13.5	43.4	143.4	50.2
	Available potassium (mg/kg)	83.4	251	351	242

.

All study sites implemented an annual practice of returning crushed rice straw to the field. The specific fertilization regimes for each treatment were as follows:

BS Treatment: Nitrogen, phosphorus, and potassium were applied as urea, calcium superphosphate, and potassium chloride, respectively. All phosphorus fertilizer was applied as basal fertilizer. For nitrogen and potassium fertilizers, 60% was applied as a basal dose, with the remaining 40% top-dressed at the tillering stage. The rice straw return rate was 4.5 t·ha⁻¹.

LY Treatment: Basal fertilizer consisted of 350 kg·ha⁻¹ compound fertilizer (N:P₂O₅:K₂O = 15:15:15) and 100 kg·ha⁻¹ urea. An additional 100 kg·ha⁻¹ urea was top-dressed at the tillering stage. The rice straw return rate was 5 t·ha⁻¹.

JO Treatment: Basal fertilizer consisted of 400 kg·ha⁻¹ compound fertilizer (N:P₂O₅:K₂O = 15:15:15) and 150 kg·ha⁻¹ urea. An additional 150 kg·ha⁻¹ urea was top-dressed at the tillering stage. The rice straw return rate was 5 t·ha⁻¹.

PC Treatment: Basal fertilizer application was 350 kg·ha⁻¹ compound fertilizer (N:P₂O₅:K₂O = 15:15:15). A top-dressing of 300 kg·ha⁻¹ compound fertilizer (N:P₂O₅:K₂O = 18:18:18) was applied at the tillering stage, followed by another top-dressing of 150 kg·ha⁻¹ of the same compound fertilizer (N:P₂O₅:K₂O = 18:18:18) at the booting stage. The rice straw return rate was 6 t·ha⁻¹.

Soil samples were collected from paddy fields under consecutive years of rice straw return in different regions. In each region, five sampling points were arranged in a quincunx pattern to collect topsoil (0–20 cm depth) with three replicates. After removing impurities, 200 g of soil was air-dried in shaded conditions for physicochemical analysis. The remaining soil was air-dried and sieved (10-mesh) for pot experiments with straw amendment.

2.2. Soil Physical and Chemical Properties Determination

Soil pH, soil organic matter, total nitrogen, alkali-hydrolyzable nitrogen, total phosphorus, available phosphorus, total potassium, and available potassium were determined using the following methods: the potentiometric method (soil-to-water ratio of 2.5:1), the potassium dichromate oxidation-external heating method, the Kjeldahl method, the alkali hydrolysis-diffusion method, the alkali fusion-molybdenum antimony anti-colorimetry method, the molybdenum antimony anti-colorimetry method (HCl-NH₄F extraction), the alkali fusion-flame photometry method, and the flame photometry method (NH₄Ac extraction), respectively [22].

2.3. Lignin Degradation Strains Isolation

(The culture media were prepared in our laboratory, and all chemical reagents were purchased from Sinopharm Chemical Reagent Co., Ltd. Fuzhou China) Lignin Screening Medium: Lignin powder (10.0 g), peptone (10.0 g), NaCl (10.0 g), guaiacol (0.4%), agar powder (18.0 g), distilled water (1000 mL); pH unadjusted. The cultures were incubated at a constant temperature of 30 °Cfor 3 days. Colonies surrounded by a dark red zone, indicative of laccase production, were selected and repeatedly streaked for isolation.

Straw Liquid Medium: MgSO₄·7H₂O (0.1 g), K₂HPO₄ (1.0 g), FeSO₄·7H₂O (0.1 g), MnSO₄ (0.01 g), peptone (2.0 g), rice straw (10.0 g), distilled water (1000 mL); pH unadjusted. The seed suspension of the strain was inoculated into an Erlenmeyer flask containing 8% (w/v) straw liquid medium and incubated in a rotary shaker at 28 °Cand 120 rpm. After 30 days of cultivation, the straw degradation rate was determined using the same method described in Section 2.4.

2.4. Straw Degradation Rate Determination

Four distinct treatments were established in the straw burial pot experiment, corresponding to soil samples from four different regions: BS, LY, JO, and PC treatments. For each treatment, 5 kg of sieved field soil was weighed and transferred into 11 L capacity pots. Each treatment group consisted of three replicate pots. Dried rice straw (5 g) was cut into 5 cm segments and placed into nylon mesh bags (80 mesh). Two bags were buried in each pot at a depth of 10 cm. Soil moisture was adjusted to 60% of the field maximum water holding capacity and maintained throughout the incubation period using the weight-based watering method, with measurements taken every two days.

After a two-month incubation period (July to September 2023), all nylon mesh bags were retrieved. One bag from each pot was used for DNA extraction and subsequent amplicon sequencing via the MiSeq platform. The other bag was used to determine the straw degradation rate. Soil removal was performed according to established protocols: straw contained within the nylon bags was transferred to a 100-mesh sieve and gently rinsed with deionized water under low flow rate until the effluent became clear, ensuring the removal of adhering soil particles [23,24]. The cleaned straw was then oven-dried at 80 °Cuntil constant weight was achieved.

The straw degradation rate (D) was calculated as follows:

D = [(W₀ − W_t)/W₀] × 100%

where W₀ represents the initial dry weight of the straw (g), and W_t denotes the dry weight of the straw after incubation time t (g).

2.5. Soil DNA Extraction and Microbial Community Structure Analysis

2.5.1. Genomic DNA Extraction and PCR Amplification

Genomic DNA was extracted from soil samples using the E.Z.N.A.^® Soil DNA Kit (Omega Bio-tek, Inc., Norcross, GA, USA) according to the manufacturer’s instructions. For each extraction, 0.5 g of soil was used. Three biological replicates were processed per treatment. The quality of the extracted DNA was assessed by 1% agarose gel electrophoresis, and its purity and concentration were measured using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Inc., USA). DNA samples were stored at –20 °C for further analysis.

The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified with the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) using an ABI GeneAmp^® 9700 PCR system (Applied Biosystems, USA). The PCR reaction mixture (20 μL) contained: 4 μL of 5× TransStart FastPfu buffer, 2 μL of 2.5 mmol/l dNTPs, 0.8 μL each of the forward and reverse primers (5 μmol/l), 0.4 μL of TransStart FastPfu DNA polymerase, and 10 ng of template DNA, with the final volume adjusted to 20 μL using sterile ddH₂O. The amplification program consisted of initial denaturation at 95 °Cfor 3 min; 27 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s; followed by a final extension at 72 °C for 10 min.

2.5.2. Library Preparation and Sequencing

PCR products were processed using the NEB Next Ultra II DNA Library Prep Kit (New England Biolabs, Inc., Ipswich, MA, USA). Briefly, amplicons from each sample were pooled in equimolar ratios based on electrophoresis quantification. The pooled library was size-selected using 2% agarose gel electrophoresis, and its concentration was quantified with a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Inc., Waltham, MA, USA). End repair and adenylation were performed by adding 10 μL of End Repair & A-Tailing Mix, followed by adapter ligation using 33.5 μL of Ligation Mix. The ligated products were purified and subjected to PCR enrichment on an ABI 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA) to construct the final sequencing library.

Library concentration was measured using a Nanodrop 2000, and fragment size distribution was assessed with an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Quantitative PCR was performed on an ABI StepOnePlus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) for precise quantification. Sequencing was carried out on the Illumina MiSeq PE300 platform (Shanghai Meiji Biomedical Technology Co., Ltd., Shanghai, China). Raw sequencing data have been deposited in the NCBI SRA database under accession number PRJNA1128743.

2.5.3. Bioinformatic Analysis

Raw paired-end sequencing reads were processed using fastp (version 0.19.6) [25] for quality control and FLASH (version 1.2.11) [26] for merging. The specific steps were as follows: (1) Quality Control with fastp: Reads were trimmed by removing bases from the 3′ end with a quality score below 20. A 50-bp sliding window was applied; if the average quality within any window dropped below 20, the trailing portion of the read from that window onward was truncated. Reads shorter than 50 bp after trimming, as well as reads containing any ambiguous bases (‘N’), were discarded. (2) Read Merging with FLASH: Paired-end reads were assembled into single contiguous sequences by overlapping their respective ends, with a minimum overlap length of 10 bp required for merging. (3) Mismatch Filtering: To ensure overlap fidelity, a maximum mismatch ratio of 0.2 was permitted within the overlapping region. Any merged sequences that exceeded this mismatch threshold were filtered out and excluded from downstream analysis. (4) Demultiplexing and Orientation: Samples were demultiplexed and sequences were oriented based on their unique barcodes and primers. The barcode sequence was required to be an exact match (0 mismatches allowed), while a maximum of 2 mismatches was permitted in the primer region.

Quality control of raw sequences was performed using Fastp (v0.20.0), and paired-end reads were merged with FLASH (v1.2.7). Sequences were clustered into operational taxonomic units (OTUs) at 97% similarity using UPARSE (v7.1), and chimeric sequences were removed. The most abundant sequence within each OTU was selected as the representative sequence (Clustering sequences into operational taxonomic units (OTUs) at a 97% similarity threshold is not an absolute standard; however, it is widely adopted as a rational choice that balances biological relevance, computational efficiency, and data quality [27]). Taxonomic annotation of OTUs was conducted using the RDP classifier (v2.2) against the SILVA 16S rRNA database (v138) with a confidence threshold of 70%. To minimize the influence of varying sequencing depths on subsequent alpha- and beta-diversity analyses, all samples were rarefied to the minimum sequence count of 53,685. Following this rarefaction, the average sequence coverage across all samples remained high at 99.73%, ensuring robust community representation. Functional prediction of the 16S rRNA gene data was performed using PICRUSt2, and OTU tables were compared with the COG (Clusters of Orthologous Groups) database to infer functional gene profiles.

2.6. Data Analysis

The original data were processed using Excel 2022 and are presented as means ± standard deviations. Prior to conducting analysis of variance (ANOVA), the data were subjected to and met the necessary assumptions of normality and homogeneity of variances. One-way ANOVA was performed using SPSS 24.0 to assess the effects of different treatments on the alpha diversity of bacterial communities and the values of predicted functional genes. Multiple comparisons were conducted using the least significant difference (LSD) method at a significance level of α= 0.05. Principal component analysis (PCA) based on the Bray–Curtis distance matrix was employed to evaluate the similarities and differences in bacterial community structure (beta diversity) among the treatments. STAMP software 2.1.3 was used to examine differences in taxonomic abundance between groups, with a specific focus on changes in bacterial abundance at the genus level. False discovery rate (FDR) correction was applied for multiple testing. Redundancy analysis (RDA) was performed under a linear model to elucidate the relationships between soil bacterial communities and environmental factors.

3. Results and Analysis

3.1. Diversity of Straw-Enriched Microbial Community

The α-diversity indices of bacterial and fungal communities enriched by straw under different regional soil treatments are presented in Table 1. The library coverage exceeded 99% for all tested soil samples, indicating a high probability of sequence detection and faithfully representing the in situ soil microbial communities. As shown in

Table 2. Alpha diversity index of straw-enriched bacterial and fungal communities under different regional soil treatments.

Microorganism	Treatment	Ace Index	Chao1 Index	Shannon Index	Coverage/%
Bacteria	BS	1743.92 ± 160.96 a	1719.65 ± 152.67 a	6.10 ± 0.05 a	99.77 ± 0.05 a
	JO	1529.22 ± 106.25 a	1507.13 ± 103.61 a	5.76 ± 0.17 a	99.71 ± 0.12 a
	LY	1577.53 ± 267.23 a	1558.99 ± 254.65 a	5.60 ± 0.25 a	99.81 ± 0.14 a
	PC	1575.41 ± 243.76 a	1550.92 ± 231.51 a	5.66 ± 0.06 a	99.64 ± 0.25 a
Fungi	BS	110.20 ± 11.58 a	109.76 ± 11.76 a	2.09 ± 0.16 a	99.99 ± 0.01 a
	JO	92.32 ± 10.74 a	92.33 ± 10.73 a	2.13 ± 0.57 a	1 ± 0.00 a
	LY	100.36 ± 9.14 a	99.93 ± 9.42 a	2.17 ± 0.03 a	1 ± 0.00 a
	PC	128.84 ± 26.65 a	128.58 ± 27.22 a	2.12 ± 0.15 a	99.98 ± 0.01 a

Note: BS, soil samples were collected from the Fujian Cultivated Land Conservation Scientific Observation Experimental Station of the Ministry of Agriculture and Rural Affairs of Xitou Village, Baisha Town, Minhou County, Fuzhou City; JO, soil samples were collected from Zhangtun Village, Dongyou Town, Jian’ou City, where rice straw was returned to the field for years; LY, soil samples were collected from the rice straw returning planting area in Zhongfang Village, Lufeng She Nationality Township, Shanghang County; PC, soil samples were collected from the rice straw returning planting area in Rui’an Village, Fuling Town, Pucheng County. Different lowercase letters in the same row indicate significant difference (n = 3, p < 0.05) between treatments.

, for fungal communities, the Ace and Chao1 indices followed the order: PC treatment > BS treatment > LY treatment > JO treatment. Conversely, the Shannon index exhibited a different pattern: LY treatment > JO treatment > PC treatment > BS treatment.

For the fungal community, the Ace and Chao1 indices followed the order: PC treatment > BS treatment > LY treatment > JO treatment, indicating that the PC treatment resulted in the highest fungal richness. The Shannon index, however, exhibited a different trend: LY treatment > JO treatment > PC treatment > BS treatment. It is noteworthy that the differences in Shannon index among treatments did not reach statistical significance.

3.2. PCA of Straw-Enriched Microbial Community

The Principal Component Analysis (PCA) results revealed distinct clustering patterns for both bacterial and fungal communities at the genus level. As shown in Figure 1A, the bacterial communities of the four treatments were clearly separated. Principal component 1 (PC1) and principal component 2 (PC2) explained 18.69% and 14.34% of the total variance, respectively. This clear separation indicates a significant difference in the bacterial community structure among the treatments (R = 0.9198, p = 0.001). In Figure 1B, for the fungal communities, the cumulative variance explained by PC1 and PC2 was 28.95%. The PC treatment was distinctly separated from the others, suggesting its fungal community structure was significantly different (R = 0.2747, p = 0.036). In contrast, the BS, JO, and LY treatments showed overlapping clusters, indicating a degree of similarity in their fungal community compositions at the genus level.

3.3. Microbial Community Composition and Its Correlation with Environmental Factors

3.3.1. Composition Differences at the Phylum and Genus Levels of Straw-Enriched Bacteria

The composition of straw-enriched bacterial communities under different regional soil treatments was shown in Figure 2A, at the phylum level. Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, Chloroflexi, Acidobacteriota, Myxococcota, Patescibacteria, Verrucomicrobiota, Planctomycetota and Bdellovibrionota accounted for more than 1% of soil bacterial abundance in each treatment. A total of 97.90–98.47% of the relative abundance of soil samples at the phylum level. Fibrobacter bacteria can decompose complex organic substances, can efficiently degrade and utilize cellulose, and play a vital role in the global carbon cycle. It can be seen from Figure 3 that the relative abundance of Fibrobacterota in JO treatment is higher than that in other treatments.

At the genus level (Figure 2B). Bacillus, Allorhizobium-Neorhizobium- Pararhizobium-Rhizobium, Streptomyces, Chitinophaga, Devosia, JG30-KF-CM45, Pseudolabrys, Sphingomonas, A4 b, Steroidobacter accounted for the top 10 of soil bacterial abundance in each treatment. A total of 31.22–34.26% of the relative abundance of soil samples at the genus level.

3.3.2. Differences in Fungal Composition at the Phylum and Genus Levels in Straw-Enriched Fungi

The composition of fungal communities enriched in straw under different soil treatments in different regions is shown in Figure 4A. At the phylum level, Ascomycota, k-Fungi and Basidiomycota, which accounted for more than 1% of the relative abundance of soil fungi in each treatment, accounted for 97.90–98.47% of the relative abundance of soil samples at the phylum level. At the genus level (Figure 4B), Aspergillus, Echria, Zopfiella, Arnium, Thielavia, Chaetomium, Coniochaeta, Hormographiella, Westerdykella and Curvularia accounted for the top 10 of soil fungal abundance in each treatment. A total of 33.51–80.19% of the relative abundance of fungal genera in soil samples. Through multiple groups of comparative analysis, it was found that the relative abundance of Zopfiella in PC treatment group was significantly higher than that in other treatment groups (Figure 5). The genus Zopfiella exhibits biological activities such as antagonism against plant pathogens, cellulose degradation, and antioxidant effects [28]. The relative abundance of the genus Chaetomium was higher than that of other treatments. Chaetomium is a widely distributed filamentous ascomycete with strong cellulase and hemicellulase activities. The core enzyme system of Chaopefinium for lignin degradation primarily includes laccases and peroxidases. Many species of Chaetomium can secrete highly active laccases, and their activity can be induced by various aromatic compounds and metalions [29].

3.3.3. Correlation Analysis Between Straw-Enriched Bacteria and Fungi (Genus Level) and Environmental Factors

In the straw buried pot experiment, the straw degradation rates of BS treatment, LY treatment, JO treatment and PC treatment were 35.2%, 47.6%, 35% and 46.27%, respectively. The straw degradation rates of LY treatment and PC treatment were higher than other treatments. In order to further explore the relationship between soil environmental factors, bacterial and fungal community composition (genus level) and straw degradation potential, redundancy analysis (RDA), a multivariate statistical analysis method, was used. According to the analysis results of Figure 6A, the two axes of RDA1 and RDA2 jointly explained 59.79% of the difference in bacterial community structure. Monte Carlo test showed that there was a significant correlation between soil pH and bacterial community structure (p < 0.01). Specifically, the relative abundance of Bacillus was positively correlated with soil electrical conductivity (EC), total nitrogen (TN) and total carbon (TC), but negatively correlated with soil pH and total phosphorus (TP). These results indicate that straw enrichment can effectively increase the relative abundance of Bacillus, thereby increasing the degradation rate of straw. Similarly, the analysis of fungal community structure (Figure 6B) showed that the two axes of RDA1 and RDA2 jointly explained 50.25% of the difference in fungal community structure. The results of Monte Carlo test showed that there was a significant correlation between soil pH and fungal community structure (p < 0.05). Among them, the relative abundance of Aspergillus, k _ Fungi and other fungal genera was positively correlated with soil pH and TP, but negatively correlated with EC, TN and TC. In addition, the study also found that straw enrichment can increase the relative abundance of Thielavia, Chaetomium, Sordariales, Coniochaeta, Arnium, Lasiosphaeriaceae, Zopfiella, Echria and other fungal genera, thus playing a positive role in promoting the improvement of straw degradation rate.

3.3.4. Prediction and Analysis of PICRUSt Function Under Soil Treatment in Different Regions

In order to deeply analyze the functional characteristics of straw-enriched bacteria in soil treatment in different regions, PICRUSt analysis tool and COG (Cluster of Orthologous Groups) database were used to comprehensively classify and predict their functions. As shown in Figure 7, among the top 23 functional genes in relative abundance, different treatments showed significant differences. The abundance of five functional genes, including “Cell wall/membrane/envelope biogenesis”, “Intracellular trafficking /secretion/vesicular transport”, “Posttranslational modification/protein turnover/chaperones”, “Cytoskeleton” and “Extracellular structures”, in BS treatment group were significantly higher than those in other treatment groups. This result indicates that bacteria under BS treatment have unique functional advantages in cell structure construction and maintenance, intracellular material transport and signal transmission. The abundance of four functional genes, “Carbohydrate transport and metabolism”, “Amino acid transport and metabolism”, “Nucleotide transport and metabolism” and “Coenzyme transport and metabolism”, in LY treatment group was significantly higher than that in other treatment groups, indicating that bacteria under LY treatment showed outstanding performance in the functions related to material metabolism and energy conversion, and may play a key role in the recycling of various nutrients in soil. In addition, the abundance of “Translation/ribosomal structure and biogenesis” functional genes in BS treatment group and JO treatment group was significantly higher than that in other treatment groups, indicating that the bacteria in these two treatment groups had stronger ability in physiological processes related to protein synthesis, which may have an important impact on the growth, reproduction and ecological function of soil microbial community.

3.4. Isolation and Identification of Dominant Strains and Straw Degradation Effect

In order to further explore the microbial mechanism of straw degradation, lignin screening medium was used to systematically isolate and screen PC-treated samples, and strain PC1 was successfully obtained (Figure 8). Subsequently, the rDNA-ITS sequence of strain PC1 was compared and analyzed by Blast in GenBank. The results showed that the sequence homology between the strain and the strain with the highest similarity was 99%. The strain PC1 was identified as Chaetomium (https://www.iapt-taxon.org/nomen/main.php accessed on 26 September 2024). In order to further evaluate the degradation ability of strain PC1 on rice straw, the degradation rate of rice straw was measured. The experimental data showed that strain PC1 had a significant degradation effect on rice straw, and the degradation rate reached 49.13% (Figure 9). It is worth noting that the degradation rate value is higher than the straw degradation rate of PC treatment in the straw pot experiment. These results indicate that strain PC1 has unique advantages in the process of rice straw degradation, and it is expected to play an important role in the utilization of agricultural waste resources and the material cycle of soil ecosystem, which provides a solid theoretical basis and data support for the subsequent in-depth study of its degradation mechanism and practical application.

4. Discussion

Straw burial experiment with four soil samples from different regions with consecutive rice straw incorporation. The straw-enriched bacterial communities were dominated by the phyla Proteobacteria and Firmicutes, which are key bacterial groups driving straw decomposition. These phyla contain numerous strains capable of producing extracellular enzymes that degrade complex plant polymers in straw [30]. The phylum Actinobacteria promotes straw decay and can decompose recalcitrant organic compounds. It becomes a dominant group during the middle and late stages of straw decomposition, marking the transition of the decomposition process from a rapid phase to a slow and stable humification stage [31,32,33]. The straw-enriched fungal communities were dominated by the phyla Basidiomycota and Ascomycota, which include a large number of saprophytic fungi. These fungi decompose the plant cell wall by secreting a series of enzymes such as lignin peroxidase, manganese peroxidase, and laccase, thereby accelerating the straw degradation process and leading to more thorough decomposition [34,35,36,37]. Among the straw-enriched dominant bacterial genera across the four treatments, Bacillus is a group effective in degrading cellulose and promotes the rapid decomposition of cellulose in straw [38]. Jiang Gaofei et al. [39] used rice straw as the sole carbon source and screened two strains, B-7 and B-11, with high cellulase activity, identified as Bacillus pumilus and Bacillus stearothermophilus, respectively. Wang, X. et al. [40] conducted a field microplot experiment by inoculating soil with Bacillus amyloliquefaciens. The results showed that inoculation significantly increased the abundance of Bacillus in the soil, accelerated the degradation rate of wheat straw, and enhanced the activities of cellulase and β-glucosidase in the soil. The genus Streptomyces can effectively degrade cellulose. Li Linchao et al. [41] screened two strains of Streptomyces, C31 and C37, from corn stover that efficiently degrade cellulose. Zhao, S. et al. [42] demonstrated that an increase in Streptomyces abundance positively correlated with lignin degradation rate, cellulose degradation rate, and related enzyme activities. Using Streptomyces alone effectively degraded corn stover, but the effect was enhanced when combined with Trichoderma. In the four treatments, the relative abundance of the straw-enriched fungal genus Zopfiella in the PC treatment was significantly higher than in the other treatments. Zopfiella can secrete corresponding enzyme systems to decompose cellulose and hemicellulose in straw. Hassa, J. et al. [43] found that in biogas reactors using straw as substrate, Zopfiella was frequently detected with high abundance. In strictly anaerobic fermentation environments, the sustained high abundance of Zopfiella was directly related to the stable operation of the system and straw degradation efficiency. During straw degradation, a clear succession of microbial communities occurs. The early stage is dominated by bacteria such as Firmicutes, which rapidly utilize readily decomposable carbon sources, while the later stage shifts towards Actinobacteria and Ascomycota, which decompose complex lignin [44].

The composition, diversity, and function of soil microbial communities are not randomly distributed but are systematically shaped by soil physicochemical parameters (e.g., pH, nutrients, moisture) and climatic differences (e.g., temperature, precipitation) [45,46]. Among these, soil pH is considered the most important factor predicting soil microbial community structure and diversity [47]. In this study, the relative abundance of Bacillus positively correlated with the straw degradation rate and negatively correlated with pH. In contrast, the dominant fungal genera Zopfiella and Chaetomium positively correlated with both the straw degradation rate and pH. Different organic inputs significantly alter the soil microbial community. Straw incorporation typically specifically enriches cellulolytic and ligninolytic members of Firmicutes, Actinobacteria, and Ascomycota, and this enrichment effect is strongly regulated by native soil properties such as pH and nitrogen content [48]. The relative abundances of Bacillus, Zopfiella, and Chaetomium all showed positive correlations with soil EC, TN, and TC. This indicates that increased soil nutrients can promote the growth of straw-degrading dominant microorganisms, thereby accelerating the decomposition of rice straw.

The relative abundance of the straw-enriched dominant fungal genus Chaetomium in the PC treatment was higher than in the other treatments. Chaetomium is a saprophytic fungus. Its degradation of lignin primarily relies on a secreted lignin-modifying enzyme system, mainly comprising laccases and various peroxidases. Laccase uses molecular oxygen as the final electron acceptor to catalyze the single-electron oxidation of phenolic lignin subunits (such as guaiacyl and syringyl phenols), forming phenoxy radicals. These radicals are highly unstable and undergo a series of non-enzymatic reactions, leading to the partial depolymerization and degradation of the lignin macromolecule. Chaetomium can further transform lignin degradation products into humus, which not only removes intermediates that might inhibit enzymatic reactions but also enhances soil fertility, forming a positive ecological cycle [49]. Zhuang Peiwen et al. [50] isolated a strain of Chaetomium (CS1) from seawater that could grow using lignin as the sole carbon source. This strain showed potential to secrete various extracellular lignin-degrading enzymes, capable of decolorizing aniline blue and producing a brown-red oxidation zone with guaiacol. Infrared spectroscopy analysis revealed that strain CS1 primarily degraded lignin by attacking the aromatic skeleton, the C-O bonds of β-O-4 linkages, and the O-H groups at the β or γ positions. In this study, the straw degradation rate in the PC treatment of the straw burial experiment was relatively high. Strain PC1, isolated and screened from the PC treatment samples, was identified via ITS gene sequencing as belonging to Chaetomium. Using strain PC1 to degrade rice straw resulted in a degradation rate of 49.13%, which is higher than the 46.27% degradation rate observed in the PC treatment burial experiment, and the degradation time was shorter. Liu Shuang [51] conducted a pot-simulated experiment of direct straw incorporation under low-temperature conditions and found that a combined inoculum of Fusarium oxysporum DSH2-3 and Chaetomium sp. YSH3-3 provided better degradation effects on rice and corn straw, achieving a weight loss rate of up to 69%. Chaetomium possesses both a lignin-modifying enzyme system (laccase, MnP) and a powerful polysaccharide hydrolase system (cellulase, hemicellulase), enabling synergistic decomposition of lignocellulose. It serves as a crucial bridge connecting plant residue decomposition with soil carbon sequestration [52] and shows great potential for agricultural applications such as composting and bioremediation. Future experiments could consider scientifically formulating a composite microbial inoculant by combining Chaetomium with other efficient, in situ screened straw-degrading strains. This aims to simultaneously achieve waste treatment, soil fertilization, disease prevention, and increased crop yield.

5. Conclusions

• The predominant bacterial phyla enriched in the straw-amended soils across the four regions were Proteobacteria, Actinobacteriota, Firmicutes, and Chloroflexi. The dominant fungal phyla enriched under straw degradation were Ascomycota and Basidiomycota. These phyla encompass a substantial number of fungi and bacteria that play leading roles in straw decomposition.
• In the straw-enriched soils from the four regions, the relative abundance of the dominant bacterial genus, Bacillus, showed a positive correlation with the straw degradation rate but a negative correlation with pH. In contrast, the dominant fungal genera, Zopfiella and Chaetomium, exhibited positive correlations with both the straw degradation rate and pH. The enrichment of these two genera facilitates the rapid decomposition of straw.
• A Chaetomium strain, designated PC1, was isolated and screened from the PC-treated samples. Determination of its degradation capability revealed that strain PC1 achieved a rice straw degradation rate of 49.13%, which is higher than the 46.27% degradation rate observed in the pot-burial experiment under PC treatment. This result provides a theoretical foundation for screening indigenous high-efficiency microbial strains and developing compound microbial inoculants with direct practical application value.