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Article

Responses of Rhizospheric Microbial Communities to Brevibacillus laterosporus-Enhanced Reductive Soil Disinfestation in Continuous Cropping Systems

by
Risheng Xu
1,2,3,†,
Haijiao Liu
2,†,
Yafei Chen
2,
Zhen Guo
1,
Juan Liu
2,
Yue Li
3,
Jingyi Mei
3,
Tengfei Ma
2,* and
Yanlong Chen
3,*
1
Key Laboratory of Degraded and Unused Land Consolidation Engineering, The Ministry of Natural Resources, Xi’an 710075, China
2
Peanut Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
3
School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710129, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(8), 1775; https://doi.org/10.3390/agronomy15081775
Submission received: 27 June 2025 / Revised: 15 July 2025 / Accepted: 17 July 2025 / Published: 24 July 2025
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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Versions Notes

Abstract

Reductive soil disinfestation (RSD) significantly alters soil characteristics, yet its combined effects with bacterial inoculation on subsequent rhizospheric microbial community composition remains poorly understood. To address this knowledge gap, we investigated the effects of RSD and endophytic Brevibacillus laterosporus inoculation on the composition, network, and predicted function of peanut rhizospheric bacteria and fungi. Our results demonstrated that RSD and B. laterosporus inoculation substantially increased rhizospheric bacterial diversity while reducing fungal diversity. Specifically, B. laterosporus-enhanced RSD significantly reshaped the bacterial community, resulting in increased relative abundances of Chloroflexi, Desulfobacterota, and Myxococcota while decreasing those of Firmicutes, Gemmatimonadota, and Acidobacteriota. The fungal community exhibited a more consistent response to RSD and B. laterosporus amendment, with reduced proportions of Ascomycota and Gemmatimonadota but an increase in Chytridiomycota. Network analysis revealed that B. laterosporus inoculation and RSD enhanced the bacterial species complexity and keystone taxa. Furthermore, canonical correspondence analysis indicated strong associations between the soil bacterial community and soil properties, including Eh, EC, NO3−-N, and SOC. Our findings highlight that the shifts in bacterial taxa induced by B. laterosporus inoculation and RSD, particularly the keystone taxa identified in the network, may contribute to the suppression of soil-borne pathogens. Overall, this study provides a novel insight into the shifts in rhizospheric bacterial and fungal communities and their ecological functions after bacteria inoculation and RSD treatment.

1. Introduction

The complex etiology of continuous cropping challenges involve multifaceted interactions among crops, soil, and microorganisms [1,2]. Their primary manifestations include (1) deterioration of soil physicochemical properties; (2) accumulation of phytotoxic allelochemicals; and (3) imbalance of soil microbial communities. For example, at certain concentrations, toxic allelopathic substances can suppress peanut seedling growth and damage cell membrane integrity, while also inducing the deterioration of soil microbial communities. In turn, the imbalanced microbial community further leads to the accumulation of toxic allelopathic substances and a reduced rate of soil nutrient transformation [1]. Microorganisms play vital roles in crop health and serve as key indicators of soil quality [3]. However, root exudates from crops such as peanut can significantly stimulate the sporulation and spore germination of soil-borne pathogenic fungi, which occurs at the expense of beneficial soil bacteria [4]. In fact, the transition from a bacterial-dominated, disease-suppressive community structure to a fungal-dominated, disease-conducive community structure is widely regarded as a fundamental driver of continuous cropping obstacles [1,2]. Consequently, suppressing soil-borne pathogens and enhancing beneficial microbial populations is critical for mitigating continuous cropping obstacles.
Reductive soil disinfestation (RSD) is a pre-planting agricultural practice where easily decomposable organic materials are incorporated into the soil, followed by irrigating to saturation and covering with plastic film for 2–4 weeks (the duration being climate-dependent). For example, Soil temperatures of 16–30 °C significantly reduce plant pathogen viability under RSD treatment [5]. This process rapidly creates a strongly reducing soil environment that effectively eliminates soil-borne pathogens and restores degraded soils [6]. Extensive field applications have demonstrated that RSD significantly alleviates continuous cropping obstacles in various vegetable crop and ornamental flower production systems [5]. However, the reducing soil environment created by RSD was broad-spectrum, while the beneficial microorganisms were also depleted. Thus, the routine application of bio-inoculants following RSD treatment has become standard practice to restore the soil microbial community structure and establish an environment conducive to crop planting [7]. Despite these advances, significant knowledge gaps remain regarding the potential of microbial-inoculation-enhanced RSD for managing soil-borne diseases of the crop rhizosphere in continuous cropping systems.
Previous studies have demonstrated that the application of exogenous Bacillus velezensis XC1 can promote the growth of beneficial soil microorganisms while simultaneously suppressing soil-borne pathogens, thereby mitigating continuous cropping problems [8]. Moreover, the enhanced effect of RSD exhibited a positive correlation with the diversity of applied exogenous bio-inoculants, suggesting the combined application of the beneficial inoculants and RSD leveraged the synergistic advantages of both technologies [8]. Meanwhile, sequestration of organic carbon sources by RSD treatment modified the soil conditions for colonization and functional expression of beneficial microbes [9]. On the other hand, during RSD treatment, members of the phylum Firmicutes, which use straw as a substrate, rapidly proliferated and became the dominant microbial population [9]. Indeed, a dramatic increase in Firmicutes abundance serves as a key microbial indicator during RSD treatment [9,10]. Coincidentally, Bacillus spp. within the Firmicutes phylum represent a key group of beneficial bacteria depleted in both soil and plant tissues after the continuous cropping of peanut [11]. Thus, Bacillus species are widely recognized as an effective microbial agent for mitigating peanut continuous cropping obstacles. Compared to Bacillus velezensis XC1, Brevibacillus laterosporus inoculants exert multiple protective mechanisms, including (1) degradation of the phytotoxic compounds accumulated in continuously cropped soils and (2) competitive exclusion of pathogens via nutrient and spatial competition [2,11]. However, the synergistic effects of B. laterosporus inoculation combined with RSD treatment on alleviating peanut continuous cropping obstacles, as well as the underlying mechanisms, remain unclear.
The objective of this study was to reveal the synergistic effects of inoculation with B. laterosporus and RSD treatment on (1) the rhizospheric microbial community structure and function, and (2) key soil property determinants. The rhizospheric bacterial and fungal communities were investigated with 16S rRNA Miseq high-throughput sequencing. We hypothesized that inoculation with B. laterosporus could further strengthen the effects of RSD regarding suppressing the pathogenic fungi related to consecutive cropping and that this improved the association with beneficial bacteria and the soil properties. The present study provides a theoretical foundation for mitigating the replanting risks induced by soil-borne pathogenic fungi through microbial inoculants, as well as for optimizing RSD technology and developing complementary measures.

2. Materials and Methods

2.1. Soil Samples for Pot Experiment

The soil used for the pot experiment was from the continuous peanut cropping around abandoned mines located in MianXian Town (33°15′35″ N, 106°67′32″ E), HanZhong, Shanxi Province, China. The field was characterized by low fertility and soil-borne disease. Prior to soil sampling, the experimental field had been cultivated with peanut during the preceding growing season, where yield suppression occurred due to Fusarium oxysporum infection. The initial soil properties were pH 5.81, soil organic carbon (SOC) 5.86 g kg−1, NH4+-N 1.60 mg kg−1, and NO3−-N 205.23 mg kg−1. The collected soil samples were thoroughly sieved, homogenized, and subdivided for the pot experiments.

2.2. Experimental Treatment

Four treatments were set up for pot experiment: (1) control soil (CK); (2) water flooding treatment without straw addition; (3) water flooding treatment with straw addition (RSD); and (4) co-treatment application of Brevibacillus laterosporus amendment into RSD-treated soil (YB). A complete randomized design was arranged in this experiment (4 treatment × 3 replicates = 12 pots). Each experimental treatment comprised 3 flowerpots (30 cm × 15 cm × 15 cm) that contained 3.0 kg soil and two peanut plantlets. The pot experiment was carried out in a glasshouse in MianXian Town.

2.3. Plant Materials and Microbial Strains

Seeds of the peanut were obtained from the Henan Academy of Agricultural Sciences (Henan, China), surface-sterilized in a 1% NaOCl solution for 5 min, rinsed five times with sterile double-distilled water, and sown in pots.
Brevibacillus laterosporus was isolated from rice roots and characterized by our laboratory. This strain showed a soil-borne pathogen suppression effect in various conditions. We grew the B. laterosporus strain on Luria-Bertani (LB) agar (10 g bacto tryptone, 5 g yeast extract, 10 g NaCl, 20 g agar, 1.0 L distilled water) and cultured it on a shaker (200 rpm, 25 °C) for 48 h [7]. Following centrifugation for 10 min, the bacterial cells were harvested and the suspension concentration was adjusted to an optical density of OD600 = 1 (equivalent to 1 × 108 cfu mL−1) [7]. After peanut seedling emergence, the topsoil surrounding the plant stem base was gently exposed and a 10 mL uniformly mixed aqueous suspension of B. laterosporus (prepared by dilution with water) was applied directly to the base of the plant stem via irrigation. Following irrigation, the exposed soil was backfilled.
The B. laterosporus was applied twice: once at the 2nd true leaf stage and again at the 4th true leaf stage of the seedlings. The seedlings were cultivated for 120 days in natural conditions and irrigated as needed to maintain soil moisture. Rhizospheric soil samples (0–15 cm depth) were collected from two soil cores per replicate using the root shaking method and then stored at 4 °C for physicochemical property analysis and at −20 °C for subsequent DNA extraction.

2.4. Determination of Soil Properties

Soil chemical properties, including pH, electrical conductivity (EC), soil redox potential (Eh), soil organic carbon (SOC), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and available phosphorus (AP) were analyzed using methods described in [12].

2.5. Genomic DNA Extraction and High-Throughput Sequencing

DNA was extracted using the FastDNA™ Spin Kit for Soil (MP Biomedicals, Solon, OH, USA) following the manufacturer’s protocol. Briefly, 0.5 g of the 12 soil samples was subjected to DNA extraction. The extracted DNA was quantified and assessed for quality using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA). The V4 region of the bacterial 16S rRNA gene was amplified using the primers 515F (5′-GTGCCAGCMGCCGCGG-3′) and 907R (5′-CCGTCAATTCCTTTGAGTTT-3′) [12]. The fungal internal transcribed spacer (ITS) regions were amplified using the primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′) [13]. PCR (Polymerase Chain Reaction) amplification was performed in a GeneAmp® 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA), with specific cycling conditions for 16S rRNA and ITS genes adapted from published protocols [10]. The purification of PCR products was conducted with the AxyPrep™ DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), followed by quantification using the QuantiFluor™-ST Fluorometer (Promega, Madison, WI, USA). Subsequent library preparation, cluster generation, and 250 bp paired-end sequencing were performed on an Illumina MiSeq platform (Illumina, San Diego, CA, USA) by Genesky Biotechnologies Inc. (Shanghai, China) [10]. The following experimental procedures, including sequence data analysis and network analysis, are detailed in the Supplementary Methods.

2.6. Statistical Analysis

Significant differences in soil and microbial properties were analyzed using one-way ANOVA followed by Duncan’s multiple range test (p < 0.05 or p < 0.01). When data did not meet ANOVA assumptions, a t-test was applied. All analyses were performed in SPSS 18.0 (SPSS Inc., Chicago, IL, USA). Microbial community differences were analyzed using principal coordinates analysis (PCoA) and visualized using Canoco 5.0 (Microcomputer Power, Ithaca, NY, USA). Further analyses, including canonical correspondence analysis (CCA) and Mantel tests, were also conducted in Canoco 5.0. The treatment-specific clustering patterns of bacterial and fungal abundances were visualized through heatmaps using the R package heatmap3 (1.0.3). Potential microbial biomarkers (from phylum to genus level) were identified using linear discriminant analysis effect size (LEfSe) analysis (http://www.majorbio.com, accessed on JUN 2025), with an LDA score threshold of 2.0. The functional prediction methods are detailed in the Supplementary Methods.

3. Results

3.1. Soil Physicochemical Properties

The results showed that RSD treatment significantly altered the soil physicochemical properties, with decreasing soil EC, pH, Eh, and NO3−-N content and increasing SOC, NH4+-N, and AP levels (Table 1). Notably, the combined application of RSD with B. laterosporus inoculation showed the most pronounced effects: it reduced soil EC, pH, Eh, and NO3−-N content by 70%, 9%, 121%, and 58%, respectively, compared to CK. Conversely, this treatment yielded the highest increases in SOC (70%), NH4+-N (80%), and AP (41%) levels among all treatments.

3.2. Microbial Alpha Diversity

We found that the bacterial and fungal diversity of microbial communities exhibited differences after the various treatments. In terms of bacteria, the results showed that B. laterosporus inoculation and RSD treatments had a significant impact, increasing the Chao1, Dominance, Pielou_e, Shannon, and Simpson indices (Figure 1a). Conversely, the opposite trends were true for fungi in these indices, except for the Dominance index (Figure 1b).

3.3. Microbial Community Composition

For bacteria, the RSD and YB treatments decreased the proportions of Firmicutes, Gemmatimonadota, and Acidobacteriota but increased those of Chloroflexi, Desulfobacterota, and Myxococcota compared to under CK treatment (Figure 2a and Figure S2a). At the genus level, the abundance of bacterial genera such as Anaerolinea and Anaeromyxobacter increased in the RSD and YB treatments, whereas that of Gemmatimonas, Sphingomonas, and Bacillus showed the opposite trends compared to CK (Figure 2b). Moreover, the YB treatment further increased the proportions of the phylum Desulfobacterota and the genus Anaeromyxobacter compared to RSD alone. The results of PCoA showed that the samples from the RSD and YB treatments clustered together and were separated from the CK and WF treatments (Figure S1a). For fungi, the WF, RSD, and YB treatments sequentially decreased the proportions of Ascomycota and Gemmatimonadota but increased those of Chytridiomycota compared to the CK treatment (Figure 2c and Figure S2b). At the genus level, we found that the species in the microbial communities of the RSD and YB treatments versus the CK and WF treatments differed. The abundance of fungal genera such as Cladosporium increased in the RSD and YB treatments, whereas that of Rhizopus, Ustilaginoidea, and Talaromyces showed the opposite trends compared to CK (Figure 2d). Moreover, YB treatment further increased the proportions of phylum Chytridiomycota and the genus Cladosporium. In terms of fungi, results of the PCoA were similar those readging bacteria (Figure S1b).

3.4. LEfSe Analysis of Microbial Communities

LEfSe analysis revealed significant treatment-dependent variations in bacterial and fungal community composition (Figure 3). The bacterial community exhibited the most pronounced response to different treatments, with 222, 289, 196, and 100 significantly differentially enriched taxonomic groups identified in the CK, WF, RSD, and YB treatments, respectively. In contrast, fungal communities showed more modest responses, with 189, 25, 52, and 87 significantly enriched groups detected in the corresponding treatments.

3.5. Microbial Network Properties

To identify the effect of B. laterosporus inoculation and RSD treatments on potential bacteria–bacteria and fungi–fungi interactions, bacterial or fungal co-occurrence networks were constructed using data from before and after RSD (Figure 4). The results showed that B. laterosporus inoculation and RSD increased bacterial and fungal network species complexity but decreased the average degree and triangle counts. Multiple network topological metrics (e.g., positive and negative links) consistently supported this difference in the bacterial and fungal co-occurrence patterns. However, the modularity_class values in B. laterosporus inoculation and RSD treatments were consistently higher than those of CK and WF for both the bacterial and fungal networks.
The Zi-Pi plot showed that the Proteobacteria, Chloroflexi, and Ascomycota phyla were the most abundant keystone (connectors or module hubs) taxa for bacteria and fungi, respectively (Figure S3). In the co-occurrence networks for CK and YB, 6 and 12 bacterial genera and 8 and 2 fungal genera were defined as keystone taxa, respectively, indicating that B. laterosporus inoculation and RSD increased the presence of the bacterial keystone taxa responsible for network construction. In contrast, the number of fungal keystone species in the network was lower in the YB soil than in the CK soil.
Natural connectivity analysis was conducted to evaluate the impacts of B. laterosporus inoculation combined with RSD treatment on microbial network stability (Figure S4). The results showed that B. laterosporus inoculation and RSD soil had higher bacterial values than CK soil. In contrast, the fungal networks demonstrated an opposite response pattern, showing consistently lower connectivity values throughout the evaluated range in treated versus control soils.

3.6. Relationships Between Soil Properties and Bacterial Communities

Canonical correspondence analysis (CCA) combined with Mantel tests revealed that the soil’s physicochemical properties explained 91% of the observed variation in bacterial community structure (Figure 5a and Table S1). Among these parameters, redox potential (Eh) emerged as the dominant factor, accounting for 67% of the total variation (p < 0.01). Additional significant contributors included electrical conductivity (EC, 15%), nitrate nitrogen (NO3−-N, 4%), and soil organic carbon (SOC, 3%).
Furthermore, B. laterosporus inoculation and RSD notably affected the relative abundances of bacterial metabolic functional properties (Figure 5b). B. laterosporus inoculation and RSD upregulated the bacterial metabolism of the superpathway of methanogenesis, glycolysis V, and isoprene biosynthesis II. Specifically, B. laterosporus inoculation further enriched these pathways of metabolism.

4. Discussion

4.1. Brevibacillus Laterosporus Inoculation Improved the Soil Environment

Our results demonstrate that the application of RSD and B. laterosporus inoculation significantly altered soil chemical properties (Table 1). The combined treatment exhibited pronounced synergistic effects, particularly in reducing soil pH and electrical conductivity (EC). Notably, we observed the lowest NO3−-N concentrations coupled with the highest NH4+-N levels in soils receiving both RSD and B. laterosporus treatments compared to CK. These results indicate that post-RSD bacterial inoculation acts as a potentiator of RSD [13]. In addition, combined bacteria treatment also further increased soil nutrients such as the SOC and AP contents. This may be attributed to the accelerated degradation of straw under this treatment, which releases mineral elements and promotes organic carbon accumulation. It has been reported that B. laterosporus secretes ligninolytic enzymes and exhibits a strong capacity for organic matter decomposition [14,15].

4.2. Influence of Brevibacillus laterosporus Inoculation and RSD on Bacterial and Fungal Community Diversity and Compositions in Rhizosphere Soil

Our results demonstrate the distinct effects of RSD and B. laterosporus treatments on soil microbial α-diversity (Figure 1), with RSD-induced soils and B. laterosporus amendments showing significantly higher bacterial Pielou’s evenness and diversity indices (Shannon and Simpson) in the peanut rhizosphere, consistent with previous findings in cucumber and tomato systems [7,16]. These bacterial community enhancements likely contribute to pathogen suppression and ecological stability [7]. Conversely, both fungal population (observed features) and diversity indices were markedly reduced following RSD treatments, particularly with B. laterosporus amendment, potentially due to the anaerobic conditions unfavorable for aerobic pathogenic fungi [6,9]. Importantly, the combined B. laterosporus–RSD treatment showed superior pathogen control, significantly reducing Fusarium spp. abundance compared to RSD alone. These microbial community shifts, characterized by increased bacterial diversity and abundance coupled with decreased fungal diversity, appear to underlie the enhanced disease suppression observed in peanut plants, highlighting the potential of this integrated approach for sustainable soil-borne pathogen management.
The bacterial community compositions were significantly altered by B. laterosporus inoculation and RSD treatment (Figure 2a). Previous studies have documented that changes in bacterial community composition are closely related to RSD [7,9]. However, our findings provide novel insights by demonstrating that post-RSD B. laterosporus inoculation potentiates these RSD-induced changes through two pathways: (1) B. laterosporus inoculation further increased the proportions of the phylum Desulfobacterota and the genus Anaeromyxobacter following the baseline RSD treatment [10]; and (2) the enhanced anaerobic functionality of bacteria under the combined treatment (bacterial inoculation + RSD) compared to RSD alone further corroborates this finding (Figure 5b).
The composition of the bacterial community after B. laterosporus inoculation and RSD was also significantly affected by Eh, which is consistent with several published reports [17,18]; Eh influences microbial survival by regulating the availability of inorganic electron acceptors [17]. Furthermore, the increased proportions of the bacterial phyla Proteobacteria and Chloroflex in the B. laterosporus inoculation and RSD soil were closely associated with soil nutrients such as SOC. This suggests that the increased SOC after RSD treatment supports the growth of key bacteria, since the soil organic matter is one of the most important energy sources for microbial growth [12,19].

4.3. Effect of B. laterosporus-Enhanced RSD on Microbial Network Keystone Taxa, Complexity, and Stability

The observed shifts in keystone taxa in RSD compared to CK suggest that RSD affected keystone taxa [20,21]. For bacteria, few keystones were observed before RSD, whereas prominent keystone taxa such as Proteobacteria and Chloroflexi were increased to 12 after RSD treatment, which may increase the complexity of bacterial network within the network. These increased taxa also disproportionately influence ecosystem functioning [22]; Spearman correlation analysis revealed that most of the bacterial keystone ASVs that appeared after RSD were negatively associated with ASVs that belonged to Fusarium sp. at genus level (Figure S5), suggesting that RSD-mediated soil-borne disease suppression may operate through keystone taxa reorganization. In addition, Chloroflexi may bloom in pools with high N and P concentrations in soil, providing nutrients for other beneficial microorganisms [23]. However, the decreased fungal network species complexity coincided with the decreased numbers of keystones belonging to the Ascomycota phylum after RSD; this may be related to RSD’s non-selective killing of fungi.
Network analysis further revealed that RSD treatment fundamentally altered microbial community stability metrics. In the present study, RSD enhanced the species complexity, stability, and modularity of the bacterial community, indicating that the increased modularity and complexity of the network were closely associated with drastically reduced network stability after RSD [13]. This effect was further exacerbated by the higher modularity, potentially contributing to an increase in network stability (Figure 4c).

5. Conclusions

The combined application of B. laterosporus inoculation and RSD treatment induced significant alterations in peanut rhizosphere microbial communities, primarily mediated through modifications in soil nutrient status. Specifically, bacterial community composition demonstrated strong environmental filtering, with key phyla including Chloroflexi, Desulfobacterota, and Myxococcota exhibiting significant correlations with fundamental soil parameters (Eh, EC, NO3−-N, and SOC). In contrast, fungal communities showed progressive reductions with water flooding, RSD, and combined B. laterosporus in the relative abundance of dominant phyla such as Ascomycota and Gemmatimonadota. Network topology analysis revealed that the integrated treatment enhanced both bacterial network complexity and the prevalence of keystone taxa, which were also associated with enhanced suppression of soil-borne pathogens, particularly Fusarium spp., suggesting a potential mechanistic basis for soil-borne disease control efficacy.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15081775/s1, Figure S1: Principal coordinates analysis (PCoA) of bacterial (a) and fungal (b) communities at the ASV level. CK: no RSD; WF: Water flooding; RSD: water flooding treatment with straw addition; YB: co-treatment application of B. laterosporus amendment into RSD-treated soil; Figure S2: Hierarchical clustering of samples by bacterial (a) and fungal (b) composition at genus level. The cell colors of the heatmap indicated the relative abundances of each genus in each sample, with blue corresponding to the minimum and red to the maximum value; Figure S3: Classification of nodes to identify potential keystone species within the correlation network, with Pi > 0.62 or Zi > 2.5 indicating potential keystone species. The bacterial (a and b) and fungal (c and d) keystone before and after B. laterosporus inoculation and RSD; Figure S4: The stability of co-occurrence networks before and after B. laterosporus inoculation and RSD; Figure S5: Spearman correlations represented interacitions between Fusarium ASVs and bacterial keystone after B. laterosporus inoculation and RSD Significance levels were indicated by * (p < 0.05); Table S1: Mantel tests of bray-curtis distances of bacterial communities and their relationships with soil properties and the p values of percentage contribution [24,25,26,27,28].

Author Contributions

Conceptualization, R.X., Y.C. (Yanlong Chen) and Y.C. (Yafei Chen); methodology, R.X. and T.M.; software, R.X. and J.L.; validation, R.X., Y.L. and J.L.; investigation, H.L., Y.C. (Yafei Chen), Y.C. (Yanlong Chen), Z.G., and J.L.; resources, Y.C. (Yanlong Chen); data curation, Y.L., J.M., and T.M.; writing—original draft preparation, H.L., Y.L., T.M. and R.X.; writing—review and editing, H.L., T.M., R.X., and Y.C. (Yafei Chen); project administration, Z.G.; funding acquisition, R.X., Z.G. and Y.C. (Yanlong Chen) All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Key laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural Resources (SXDJ2024-12); the Major Emergency Response Project for Agricultural Production in Henan Province, grant number 2024ZDYJ001; the Henan Province Science and Technology Research Project 252102111087; Independent Innovation Project of Henan Academy of Agricultural Sciences 2025ZC16; and the earmarked fund for CARS-13.

Data Availability Statement

Data will be made available upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The α-diversity of bacterial (a) and fungal (b) communities across all treatments after B. laterosporus inoculation and RSD. Different lowercase letters above bars indicate statistically significant differences between treatments (t-test, p < 0.05).
Figure 1. The α-diversity of bacterial (a) and fungal (b) communities across all treatments after B. laterosporus inoculation and RSD. Different lowercase letters above bars indicate statistically significant differences between treatments (t-test, p < 0.05).
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Figure 2. Community composition of rhizospheric bacteria and fungi. Relative abundance of soil bacteria ((a) phylum level; (b) genus level) and fungi ((c) phylum level; (d) genus level). Groups with <0.01 relative abundance were merged into the “others” group.
Figure 2. Community composition of rhizospheric bacteria and fungi. Relative abundance of soil bacteria ((a) phylum level; (b) genus level) and fungi ((c) phylum level; (d) genus level). Groups with <0.01 relative abundance were merged into the “others” group.
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Figure 3. Linear discriminant analysis effect size (LEfSe) analysis of the microbial taxa ((A): bacteria; (B): fungi) significantly enriched across all treatments after B. laterosporus inoculation and RSD. CK: no RSD; WF: water flooding; RSD: water flooding treatment with straw addition; YB: co-treatment application of B. laterosporus amendment into RSD-treated soil.
Figure 3. Linear discriminant analysis effect size (LEfSe) analysis of the microbial taxa ((A): bacteria; (B): fungi) significantly enriched across all treatments after B. laterosporus inoculation and RSD. CK: no RSD; WF: water flooding; RSD: water flooding treatment with straw addition; YB: co-treatment application of B. laterosporus amendment into RSD-treated soil.
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Figure 4. Co-occurrence networks of soil bacteria ((a) CK and WF; (b) RSD and YB) and fungi ((d) CK and WF; (e) RSD and YB). The size of each node is proportional to the number of connections (degree). The red edges indicate positive interactions between two nodes, while green edges indicate negative interactions. The nodes (at the genus level) are colored according to bacterial or fungal phyla. N, EN, and EP in the networks represent nodes, positive interactions, and negative interactions of edges, respectively. The degree, modularity_class (a metric that quantifies the strength of network or graph partitioning into modules), and triangles (any three randomly selected nodes in the network form a closed triangular loop) of the network after B. laterosporus inoculation and RSD are shown in (c) or (f). Different lowercase letters above bars indicate statistically significant differences between treatments (t-test, p < 0.05).
Figure 4. Co-occurrence networks of soil bacteria ((a) CK and WF; (b) RSD and YB) and fungi ((d) CK and WF; (e) RSD and YB). The size of each node is proportional to the number of connections (degree). The red edges indicate positive interactions between two nodes, while green edges indicate negative interactions. The nodes (at the genus level) are colored according to bacterial or fungal phyla. N, EN, and EP in the networks represent nodes, positive interactions, and negative interactions of edges, respectively. The degree, modularity_class (a metric that quantifies the strength of network or graph partitioning into modules), and triangles (any three randomly selected nodes in the network form a closed triangular loop) of the network after B. laterosporus inoculation and RSD are shown in (c) or (f). Different lowercase letters above bars indicate statistically significant differences between treatments (t-test, p < 0.05).
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Figure 5. Canonical correspondence analysis (CCA) for bacterial (a) communities (at ASV level) and soil properties. Volcano plot of bacterial predicted functional properties (b). Red (blue) points indicated significantly higher (lower) abundances of bacterial predicted functions in treatments compared with the control (p < 0.05).
Figure 5. Canonical correspondence analysis (CCA) for bacterial (a) communities (at ASV level) and soil properties. Volcano plot of bacterial predicted functional properties (b). Red (blue) points indicated significantly higher (lower) abundances of bacterial predicted functions in treatments compared with the control (p < 0.05).
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Table 1. Soil physicochemical properties across all treatments.
Table 1. Soil physicochemical properties across all treatments.
ECpHEhSOCNO3−NH4+AP
CK500.3 ± 11.6 a 18.5 ± 0.1 a510.7 ± 7.5 a5.9 ± 0.3 a212 ± 4.7 a1.7 ± 0.1 a51 ± 3.5 a
WF448.7 ± 10.4 b8.3 ± 0.1 a−55.3 ± 3.2 b5.7 ± 0.4 a135 ± 5.1 b2.5 ± 0.2 a53 ± 3.5 ab
RSD168 ± 9.2 c8.0 ± 0.1 b−85.7 ± 4.1 c9.4 ± 0.1 b127.3 ± 4.6 b2.9 ± 0.1 b67 ± 6.4 bc
YB144 ± 6.8 c7.7 ± 0.1 c−107.3 ± 3.3 d10.1 ± 0.2 b89.3 ± 4.7 c3.0 ± 0.1 c71.67 ± 4.5 c
1 Values are means ± standard error (n = 3). Different lowercase letters indicate significant differences at p < 0.05 among all treatments (one-way ANOVA, p < 0.05). CK: no RSD; WF: water flooding; RSD: water flooding treatment with straw addition; YB: co-treatment application of B. laterosporus amendment into RSD-treated soil. EC: soil electric conductivity; Eh: soil redox potential; NO3−: nitrate ion; NH4+: ammonium ion; AP, available phosphorus; SOC, soil organic carbon.
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MDPI and ACS Style

Xu, R.; Liu, H.; Chen, Y.; Guo, Z.; Liu, J.; Li, Y.; Mei, J.; Ma, T.; Chen, Y. Responses of Rhizospheric Microbial Communities to Brevibacillus laterosporus-Enhanced Reductive Soil Disinfestation in Continuous Cropping Systems. Agronomy 2025, 15, 1775. https://doi.org/10.3390/agronomy15081775

AMA Style

Xu R, Liu H, Chen Y, Guo Z, Liu J, Li Y, Mei J, Ma T, Chen Y. Responses of Rhizospheric Microbial Communities to Brevibacillus laterosporus-Enhanced Reductive Soil Disinfestation in Continuous Cropping Systems. Agronomy. 2025; 15(8):1775. https://doi.org/10.3390/agronomy15081775

Chicago/Turabian Style

Xu, Risheng, Haijiao Liu, Yafei Chen, Zhen Guo, Juan Liu, Yue Li, Jingyi Mei, Tengfei Ma, and Yanlong Chen. 2025. "Responses of Rhizospheric Microbial Communities to Brevibacillus laterosporus-Enhanced Reductive Soil Disinfestation in Continuous Cropping Systems" Agronomy 15, no. 8: 1775. https://doi.org/10.3390/agronomy15081775

APA Style

Xu, R., Liu, H., Chen, Y., Guo, Z., Liu, J., Li, Y., Mei, J., Ma, T., & Chen, Y. (2025). Responses of Rhizospheric Microbial Communities to Brevibacillus laterosporus-Enhanced Reductive Soil Disinfestation in Continuous Cropping Systems. Agronomy, 15(8), 1775. https://doi.org/10.3390/agronomy15081775

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