Sustained Inoculation of a Synthetic Microbial Community Engineers the Rhizosphere Microbiome for Enhanced Pepper Productivity and Quality

Abstract

The effectiveness of microbial inoculants in agriculture is often limited by their unstable colonization in dynamic soil environments. We investigated the impact of application timing and continuity of a four-member synthetic microbial community (SynCom) on pepper (Capsicum annuum L.) productivity and rhizosphere microbiome dynamics under greenhouse conditions. Four treatments were included: no inoculation (control), single inoculation at the seedling stage (T1; 5 days post-emergence), single inoculation at the potting stage (T2; 14 days post-transplant), and sustained inoculation at both stages (T3). T3 significantly enhanced plant dry weight (113.4%), root activity (267.8%), fruit sugar (43.9%), and yield (29.0%) relative to the control; and profoundly reshaped the rhizosphere microbiome, enriching functional pathways for nutrient cycling (e.g., phosphorus, nitrogen, and potassium metabolism) and phytohormone synthesis (e.g., indoleacetic acid pathway). Co-occurrence network analysis indicated a significant alteration in microbial interaction patterns, revealing a new community architecture with key taxa such as Neocosmospora, Dyella and the Rhizobium group emerging as central hubs in the T3 network. Our findings underscore that application continuity is a critical factor for optimizing bio-inoculant efficacy, providing a strategy to enhance crop productivity through microbiome engineering in sustainable agriculture.

1. Introduction

Global agriculture faces an urgent need to transition towards more sustainable agricultural practices, driven by escalating demands for food security amidst a growing global population, coupled with the profound challenges posed by climate change and persistent arable land degradation [1,2,3]. Intensive conventional farming, relying on high inputs of synthetic fertilizers and pesticides, has detrimental environmental consequences, including soil degradation, water pollution, and biodiversity loss [4,5]. In this context, harnessing the plant microbiome, the complex communities of microorganisms residing in and around plant tissues, has emerged as a promising frontier for fostering crop resilience and productivity, offering a potent, eco-friendly alternative to chemical inputs [6,7].

Plant growth-promoting microorganisms (PGPMs), predominantly bacteria and fungi, exert beneficial effects on host plants through enhancing nutrient acquisition (e.g., nitrogen fixation, phosphorus solubilization), producing phytohormones (e.g., auxins, gibberellins), synthesizing siderophores, and providing biocontrol against pathogens through competition, antibiosis, or induced systemic resistance [8,9,10,11]. Despite their immense potential, the field application of single-strain PGPM inoculants frequently yields inconsistent and unpredictable results [12,13]. This variability is largely attributed to their poor ability to establish, persist, and compete within the highly complex and often resilient native soil microbiome, which is influenced by local soil properties, nutrient profiles, and host plant developmental stage [14,15,16].

To overcome the inherent limitations of single-strain inoculants, the deliberate design and application of a synthetic microbial community (SynCom) have gained significant attention as a promising strategy in agricultural biotechnology [17,18]. SynComs, typically composed of multiple functionally complementary strains, are hypothesized to exhibit enhanced resilience, functional redundancy, and synergistic interactions among their members, leading to more robust and predictable beneficial outcomes compared to individual strains [19,20,21]. Functional redundancy within a SynCom ensures that critical ecological processes are maintained even if some members are outcompeted, while synergistic effects, such as cross-feeding of metabolites or complementary nutrient cycling, can amplify beneficial impacts on plant growth and health [22,23]. Recent research has indeed validated this paradigm, demonstrating that SynCom can more effectively promote plant growth, improve nutrient uptake, and confer enhanced resistance to biotic and abiotic stresses [5,24,25].

However, while SynCom composition is well-studied, the application strategy, specifically the timing and continuity, remains a critical, under-explored factor [26,27]. The plant–microbiome relationship is inherently dynamic and highly dependent on the plant’s developmental stage, with varying physiological demands and root exudate profiles influencing microbial recruitment and activity throughout the plant life cycle [28,29]. For instance, an early inoculation at the seedling stage might be crucial for the foundational development of a robust root system, thereby enhancing early nutrient acquisition and stress tolerance [30], an effect we previously confirmed for pepper using a single seedling-stage application of a SynCom [21]. Conversely, a later application, coinciding with high-demand flowering and fruiting stages, could be vital for sustained nutrient mobilization and yield optimization [15]. How a sustained or continuous inoculation strategy impacts the rhizosphere microbiome’s structure, functional potential, and ecological network dynamics in a major crop like pepper (Capsicum annuum L.) is not well understood.

Pepper is a horticultural crop of global economic importance [31]. In this study, we utilized the same four-member SynCom from our previous work [21], comprising Bacillus subtilis, Trichoderma harzianum, Trichoderma asperellum, and Aspergillus sp. The current study aimed to explore how the SynCom inoculation strategies, i.e., timing and continuity, impact pepper productivity and quality. We hypothesized that (1) sustained application would promote pepper productivity and quality more effectively than single-time applications, and (2) the enhanced performance would be mechanistically linked to a more profound and stable re-engineering of the rhizosphere microbiome’s composition, functional potential, and network structure. To test these hypotheses, we conducted a pot experiment, integrating plant phenotypic measurements with high-throughput amplicon sequencing, functional predictions (PICRUSt2 and FUNGuild), and co-occurrence network analysis.

2. Materials and Methods

2.1. Microbial Strains and SynCom Preparation

The synthetic microbial community used in this study comprised four microbial strains: Bacillus subtilis (GDMCC 64986), Trichoderma harzianum (GDMCC 64988), Trichoderma asperellum (GDMCC 65053), and Aspergillus sp. (GDMCC 65054). These strains were isolated from the rhizosphere of healthy pepper [21], and deposited in the Guangdong Microbial Culture Collection Center (GDMCC), Guangzhou, China. Each strain was stored at −80 °C in a 30% glycerol solution (v/v). Prior to constructing the SynCom, the four strains were confirmed to be compatible through in vitro dual culture assays.

This SynCom was constructed based on the principle of functional complementarity to achieve synergistic effects on plant health. In this specific design, Bacillus subtilis was selected for its well-characterized ability to enhance plant tolerance to biotic and abiotic stress through mechanisms such as induced systemic resistance, biofilm formation, and the production of lipopeptides [32]. The Trichoderma species, including T. harzianum and T. asperellum, were included to promote plant growth by improving nutrient solubilization, producing plant hormones and secondary metabolites, conferring abiotic stress tolerance, and colonizing plant roots [33]. Aspergillus sp. was incorporated to promote plant growth through phosphorous solubilization, the production of various secondary metabolites, and the synthesis of phytohormones like gibberellins and auxins [34]. Additionally, these strains were chosen for their known potential in disease suppression [32,33,34,35]. By combining these strains, we aimed to create a functionally diverse community capable of concurrently promoting growth, enhancing nutrient availability, and providing broad-spectrum disease suppression, thereby offering a more comprehensive and resilient benefit to the pepper plants than any single inoculant could provide. A preliminary experiment revealed that the SynCom performed best in promoting the growth of pepper seedlings than individual strains.

For inoculum preparation, fungal strains were cultured on Potato Dextrose Agar (PDA) and then in Potato Dextrose Broth (PDB) at 28 °C for 5 days. Spore suspensions were harvested, filtered, and adjusted to a final concentration of 1 × 10⁸ spores/mL. For bacterial preparation, Bacillus subtilis was cultured on Luria–Bertani (LB) agar and then in LB broth at 37 °C for 24 h. The final cell density of bacterial cultures was adjusted to approximately 1 × 10⁸ CFU/mL. The final SynCom inoculum was freshly prepared immediately before application by mixing equal volumes (1:1:1:1, v/v) of the four individual fermentation broths, resulting in a final inoculum containing approximately 2.5 × 10⁷ bacterial CFU/mL and 7.5 × 10⁷ fungal spores/mL (total of the three fungal strains). This approach ensures a high dose of each functional group while accounting for differences in propagule type and size.

2.2. Pot Experiment Design and Plant Cultivation

The pot experiment was conducted in an environment greenhouse at the Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China. The soil utilized was a typical local vegetable field soil. Pepper seeds (Capsicum annuum L. cultivar ‘Ruanpi 2307’, provided by Xiangyan Seed Co., Ltd., Changsha, China) were surface-sterilized by immersion in 75% (v/v) ethanol for 1 min, followed by 10% (v/v) sodium hypochlorite for 20 min, and then thoroughly rinsed five times with sterile distilled water. Subsequently, seeds were placed in sterile Petri dishes containing 0.5× Murashige Skoog (MS) medium and incubated in the dark at 30 °C for 36 h to promote germination. Uniformly germinated seeds were then transferred to 72-cell seedling trays filled with sterile seedling substrate (peat:vermiculite = 2:1, v/v) and cultured in a climate-controlled room under conditions of 28 °C, 80% humidity, with a 16 h light and 8 h dark cycle, and a light intensity of 300 µmol/m²/s.

The experiment was set up using a completely randomized design with four treatment groups: (1) Control (CK): no SynCom inoculation, but an equal volume of sterile culture medium liquid was applied; (2) T1: seedling-stage inoculation, i.e., SynCom was applied to the seedling substrate 5 days after seedling emergence; (3) T2: potting-stage inoculation, i.e., SynCom was applied 14 days after seedlings were transplanted into pots; (4) T3: sustained inoculation, i.e., SynCom was applied at both the seedling stage (5 days after emergence) and 14 days after seedlings were transplanted into pots.

Each treatment group comprised 20 biological replicates (one plant per pot). For application, a calculated volume of the SynCom stock suspension was uniformly irrigated into a known weight of seedling substrate or pot soil to achieve a final target concentration of approximately 1 × 10⁷ CFU/g (dry substrate/soil). After 30 days in seedling trays, seedlings were transplanted into plastic pots (20 cm diameter, 25 cm height) containing a mixture of 2.5 kg of the prepared soil and 50 g of sterile commercial organic fertilizer (organic matter ≥ 45%; N-P₂O₅-K₂O ≥ 4-2-2). Plants were watered as needed and no additional fertilizers were applied throughout the experiment. Plant growth was observed weekly, and samples were collected for analysis 45 days post-transplanting.

2.3. Plant Growth, Yield, and Fruit Quality Measurements

Forty-five days after transplanting, the height and stem diameter of the peppers were measured using a tape measure and a vernier caliper, respectively. The aboveground fresh weight was recorded, and then samples were oven-dried at 105 °C for 30 min, followed by drying at 75 °C to a constant weight to determine the dry weight [36]. The fruit shape index was the ratio of longitudinal diameter to transverse diameter of fruit. The chlorophyll content was measured using a portable chlorophyll meter (SPAD-502, Konica Minolta, Osaka, Japan) on the third fully expanded leaf from the top [37]. Root systems were carefully washed free of soil, scanned using a root scanner (SCAN-GXY-A, Hangzhou Xizhuo Instrument Co., Ltd., Hangzhou, China), and the images were analyzed using the WinRHIZO software (Version 2019a) (Regent Instruments Inc., Québec City, QC, Canada) to quantify total root length, total root surface area, and the number of root tips [38]. Root activity was assessed using the triphenyl tetrazolium chloride (TTC) reduction method [39]. This assay measures the activity of dehydrogenase enzymes, which are integral to cellular respiration. The reduction of colorless TTC to red formazan by these enzymes serves as a reliable indicator of the overall metabolic viability and vitality of the root tissues. During the fruit ripening period, the total yield per plant was recorded. The contents of cellulose, protein, soluble sugar, and vitamin C in pepper fruits were measured using commercially available assay kits (Suzhou Koming Biotechnology Co., Ltd., Suzhou, China) according to the manufacturer’s protocols.

2.4. Rhizosphere Soil Sampling, DNA Extraction and High-Throughput Sequencing

At the 45-day post-transplanting harvest, rhizosphere soil samples were collected using the root-shaking method. Briefly, bulk soil was removed by vigorous shaking, and the soil tightly adhering to the root surface (within ~2 mm) was collected as the rhizosphere sample [36]. Six replicates per treatment were included for DNA extraction and high-throughput sequencing. Total genomic DNA was extracted from 0.25 g of each soil sample using the DNeasy PowerSoil Pro Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. DNA quality and concentration were assessed via 1% agarose gel electrophoresis and a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).

The V5-V7 region of the bacterial 16S rRNA gene (primers 799F: 5′-AACMGGATTAGATACCCKG-3′/1193R: 5′-ACGTCATCCCCACCTTCC-3′) and the ITS1 region of the fungal ITS gene (primers ITS1F: 5′-CTTGGTCATTTAGAGGAAGTAA-3′/ITS2R: 5′-GCTGCGTTCTTCATCGATGC-3′) were amplified with barcoded primers. The V5-V7 region of the 16S rRNA gene was chosen as it has been shown to provide robust taxonomic resolution for diverse soil bacteria while minimizing the co-amplification of non-target host plant chloroplast and mitochondrial DNA. PCR amplification was performed in a 20 μL reaction volume containing 4 μL of 5× FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of FastPfu Polymerase, and 10 ng of template DNA. The thermal cycling conditions were: denaturation at 95 °C for 3 min, followed by 30 cycles of 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s, and a final extension at 72 °C for 10 min. Amplicons were purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) and quantified using the QuantiFluor™-ST system (Promega, Madison, WI, USA). Equimolar amounts of purified amplicons were pooled and sequenced on an Illumina MiSeq platform (2 × 250 bp paired-end). Sequencing services were provided by Shanghai Majorbio Biomedical Technology Co., Ltd. (Shanghai, China). The raw 16S rRNA sequencing data and ITS sequencing data have been deposited in the China National Center for Bioinformation (CNCB) under the accession number CRA030009 (https://ngdc.cncb.ac.cn/gsa; accessed on 18 September 2025).

2.5. Bioinformatics and Statistical Analysis

Raw sequencing data were processed using the QIIME2 pipeline [40]. Briefly, raw reads were demultiplexed and quality-filtered. Chimeras were removed using the VSEARCH plugin. The quality-filtered, non-chimeric reads were then clustered into Operational Taxonomic Units (OTUs) at a 97% similarity threshold using the open-reference clustering method within the q2-vsearch plugin. Taxonomic assignment was performed against the Silva (v138) database for 16S rRNA and the UNITE (v8.2) database for ITS sequences. Data were rarefied to an even sequencing depth.

Statistical analyses were conducted in R (version 4.2.1). Treatment effects on agronomic traits (growth indicators, root morphology, yield, and quality parameters) were evaluated using one-way analysis of variance (ANOVA), with post hoc Duncan’s multiple range tests (α = 0.05) implemented via the “agricolae” package. Microbial alpha-diversity was assessed using OTU richness (Chao1) and diversity (Shannon, Simpson) indices. Beta-diversity was visualized using principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity metrics, and statistical significance of community composition differences was determined by Permutational Multivariate Analysis of Variance (PERMANOVA) with 999 permutations using the adonis2 function in the “vegan” package. Data visualizations were generated using “ggplot2” and “ggpubr” package. The Mantel test plot was drawn using the “linkET” package in R (version 4.2.1), while the random forest model analysis was accomplished with the “randomForest” package.

Bacterial community functional potential was predicted using PICRUSt2 (v2.1.4-b) [41]. This process generated predicted metagenomes for each sample, annotating gene families as KEGG Orthologs (KO). Differential abundance analysis of KOs between the control and T3 treatments was conducted using DESeq2 package with an adjusted p-value < 0.05 as the significance threshold. Fungal ecological functions were assigned using FUNGuild (v1.2) by parsing the fungal OTU table and taxonomy [42]. The relative abundances of functional guilds were then compared across treatments.

In terms of co-occurrence network analyses, we focused the comparison on the control and the most effective treatment, i.e., T3 based on the abundances of OTU. To reduce complexity and focus on dominant taxa, only OTUs present in at least 50% of the samples within a group and with a mean relative abundance > 0.01% were retained for analysis. Spearman’s rank correlation coefficients were calculated (∣ρ∣ > 0.7, p < 0.05, after FDR correction). The resulting networks were visualized in Gephi (version 0.10.1) [43]. Key topological properties (e.g., number of nodes, number of edges, network density, average clustering coefficient, and modularity) were calculated to compare the structural properties of the control and T3 networks. Key taxa were identified as nodes with high degree and betweenness centrality values.

3. Results

3.1. Effects of SynCom Inoculation on Pepper Growth, Yield, and Quality

All SynCom inoculation treatments significantly (p < 0.05) improved pepper growth compared to the uninoculated control group (Figure 1a). The sustained inoculation (T3) treatment exerted the most significant effects, leading to significant increases in plant height (p < 0.05), stem diameter (p < 0.05), fresh weight (p < 0.05), and dry weight (p < 0.05) by 40.5%, 23.2%, 109.5%, and 113.4%, respectively, compared to the control (Figure 1b–e). For comparison, T1 and T2 treatments also significantly increased dry weight by 70.1% and 72.4%, respectively. The T3 group also exhibited the highest chlorophyll content (SPAD value), indicating an improved plant physiological status (Figure 1f).

The application of SynCom significantly (p < 0.05) promoted root system development (Figure 2a). Root activity, an indicator of root metabolic health, was significantly enhanced across all inoculated groups. The T3 group showed a 267.8% increase in root activity compared to the control, while T1 and T2 increased root activity by 87.1% and 101.6%, respectively (Figure 2b). Similarly, root morphological parameters, including total root length and the number of root tips, significantly increased in inoculated plants, with the T3 group showing the most substantial improvements (Figure 2c,d). Root surface area did not show statistically significant differences among treatments (Figure 2e).

The positive effects on plant growth translated into improved fruit quality and yield (Figure 3). No significant effect of inoculation on fruit shape index or soluble protein content was observed (Figure 3b,c). Soluble sugar content in pepper fruits was significantly elevated in T1, T2 and T3, with the T3 group showing the largest increase of 43.9% compared to the control (Figure 3d). A significant increase was also found for cellulose content under T2 (Figure 3e) or for ascorbic acid (Vitamin C) content under T1 (Figure 3f). While the average weight per single fruit did not change significantly, both the number of fruits per plant and the total yield per plant or per hectare significantly increased under T2 and T3 relative to the control (

Table 1. Effects of SynCom inoculation on pepper yield components and total productivity.

Treatment	Single Fruit Weight (g)	Number of Fruits Per Plant	Yield Per Plant (g)	Yield (kg/ha)
Control	23.3 ± 1.7 a	17.5 ± 0.5 b	407.2 ± 28.1 b	15,268.2 ± 1052.3 b
T1	24.8 ± 0.6 a	20.0 ± 1.0 a	499.2 ± 37.7 ab	18,720.0 ± 1412.6 ab
T2	25.8 ± 0.5 a	20.0 ± 1.0 a	518.2 ± 35.0 a	19,430.7 ± 1312.2 a
T3	26.2 ± 0.4 a	20.0 ± 1.0 a	525.1 ± 34.1 a	19,691.3 ± 1278.0 a

Data are presented as mean ± standard error. Different letters within the same column indicate significant differences among treatments according to Duncan’s test at p < 0.05. Control: No SynCom inoculation; T1: Seedling-stage inoculation; T2: Potting-stage inoculation; T3: Sustained inoculation. Yield per hectare was calculated from yield per plant.

), with the yield per hectare under T2 and T3 increasing by 27.3% and 29.0%, respectively, compared to the control.

3.2. Effects of SynCom Inoculation on Rhizosphere Microbial Community Structure

Alpha diversity analyses revealed distinct responses of fungal and bacterial communities to SynCom inoculation (Figure 4a–f). For fungal communities, the Shannon and Chao1 indices did not show significant differences, but the Simpson index significantly decreased in inoculated groups, indicating a reduction in community evenness and an increase in the dominance of certain fungal taxa. Conversely, for bacterial communities, the Simpson index significantly increased in all inoculated treatments, suggesting a more even and stable bacterial community structure. The bacterial Chao1 index significantly decreased in inoculated groups, implying a reduction in rare species, possibly due to selective pressures exerted by the SynCom.

Beta diversity analysis, based on Bray–Curtis dissimilarity, demonstrated that the microbial community structures of all inoculated groups were significantly different from the control group for both fungi and bacteria (p < 0.01, PERMANOVA) (Figure 4g,h). PCoA plots clearly separated the inoculated samples from the control samples along the primary axis (Figure 4g,h). Furthermore, for fungal communities, the within-group Bray–Curtis dissimilarity significantly decreased in the T1 treatment groups compared to the control, indicating that SynCom inoculation drove the rhizosphere fungal community towards a more convergent state. However, there was no significant difference in the bacterial community (Figure 4i,j).

3.3. Effects of Sustained Inoculation on Beneficial Microbial Functional Potentials

To elucidate the key mechanisms underlying the superior performance of sustained inoculation, our functional and network analyses focused on comparing the most effective treatment (T3) with the uninoculated control (CK). FUNGuild analysis of the fungal community revealed significant shifts in ecological roles between the control and T3 treatments (Figure 5a). Specifically, the T3 treatment showed a marked decrease in the relative abundance of guilds such as Dung Saprotroph-Undefined Saprotroph, Animal Pathogen-Dung Saprotroph-Endophyte-Epiphyte-Plant Saprotroph-Wood Saprotroph and Endophyte-Litter Saprotroph-Soil Saprotroph-Undefined Saprotroph, while the abundance of undefined saprotrophs and the Animal Pathogen-Endophyte-Lichen Parasite-Plant-Pathogen-Soil Saprotroph-Wood Saprotroph guild increased. PICRUSt2 analysis of the bacterial community demonstrated that the T3 treatment significantly enriched genes associated with key plant-beneficial functions compared to the control (Figure 5b). Specifically, genes related to phosphorus metabolism (e.g., alkaline phosphatase, K01077), potassium metabolism (potassium transport, K03501), auxin synthesis (tryptophan synthase, K01695, K01696) and nitrogen cycling (nitrate reductase, K00370, K00371, K00374) were significantly enriched in the T3 treatment, while nitrogenase related functions do not appear to be elevated relative to CK.

3.4. Effects of SynCom Inoculation on Rhizosphere Microbial Co-Occurrence Network

SynCom inoculation significantly altered the relative abundance of dominant microbial taxa at the genus level (Figure 6a,d). To understand how these compositional shifts affected inter-taxa interactions, we constructed co-occurrence networks (Figure 6b–f). The T3 treatment induced distinct structural changes in both the fungal and bacterial networks compared to the control. The bacterial network in the T3 treatment exhibited a less complex topology, characterized by a lower average clustering coefficient and modularity (Figure 6i,k), suggesting a more streamlined and less modular community. In contrast, the fungal network displayed a higher modularity, a topological property associated with community stability by buffering the impact of disturbances (Figure 6k). Despite these topological shifts, the total number of nodes and edges remained relatively consistent except that the number of edges in the fungal network was significantly lower in the T3 treatment (Figure 6g,h).

The analysis identified different keystone taxa in the control and T3 networks. In the T3 networks, Neocosmospora (OTU5062), Dyella (OTU10024), and the Rhizobium group (OTU9879) emerged as keystone taxa (hubs) based on their high degree of connectivity (Figure 6c,f), indicating their pivotal role as key organizers of the engineered microbiome. These taxa were not central in the control network, highlighting a fundamental restructuring of microbial interactions driven by the sustained SynCom application.

3.5. Correlation of Total Yield with Key Microbial Communities and Microbial Functions

The Mantel test and correlation analysis revealed that total yield was significantly and positively correlated with the abundances of several fungal guilds (Dung Saprotroph-Undefined Saprotroph, Undefined Saprotroph, Animal Pathogen-Dung Saprotroph-Endophyte-Epiphyte-Plant Saprotroph-Wood Saprotroph, Animal Pathogen-Endophyte-Lichen Parasite-Plant Pathogen-Soil Saprotroph-Wood Saprotroph), and with genes encoding nitrogenase and alkaline phosphatase (p < 0.05; Figure 7a). According to random forest modeling, the above variables along with tryptophan synthase were the key predictors for total yield (p < 0.05; Figure 7b).

4. Discussion

Our study provides compelling evidence that the application strategy, particularly the continuity of inoculation, is a critical determinant for the success of a SynCom in promoting plant growth and robustly engineering the rhizosphere microbiome. The superior performance of T3 highlights that persistent inoculation pressure is often required to overcome the ecological resilience of the native soil microbiome and establish a durable, functionally optimized community [44,45,46]. This sustained presence likely facilitates better colonization and provides a competitive advantage for the introduced SynCom members, enabling them to integrate into and guide the native community by adapting to the changing root exudate profiles of the plant [7,27,47].

While we acknowledge that our functional predictions are based on marker-gene inference (PICRUSt2) and database matching (FUNGuild) and do not represent direct measurements of gene expression, the clear and significant enrichment of key pathways provides strong mechanistic hypotheses. The observed enhancements in plant growth (Figure 1) are likely not merely a direct effect of the inoculant, but rather a consequence of this comprehensive re-engineering of the rhizosphere’s functional potential. The significant enrichment of genes for nutrient cycling (Figure 5b)—specifically phosphorus metabolism (alkaline phosphatase), potassium transport, and nitrogen cycling (nitrate reduction)—provides a mechanism linking to the observed improvements in plant nutritional status (higher chlorophyll content) and biomass accumulation. Specifically, the observed increase in the abundance of nitrate reduction-related genes indicates that the sustained application of the SynCom inoculant enhances the dissimilatory nitrate reduction process, thereby accelerating the turnover rate of available nitrate in the soil. Consequently, the improved nitrogen use efficiency is likely driven by the stimulated metabolism of the existing soil nitrogen pool, rather than by biological nitrogen fixation. The concurrent enhancement of nitrate reduction and alkaline phosphatase activity suggests a potential synergistic coupling between nitrogen and phosphorus cycling, which may facilitate a more balanced nutrient acquisition for the plants. Crucially, and contrary to what might be expected, biological nitrogen fixation—inferred from the abundance of nitrogenase genes—did not appear to be a primary mechanism contributing to the observed nitrogen gains. This suggests the SynCom acts as an “ecosystem engineer”, augmenting the resident community’s functional capabilities to optimize nutrient availability [48]. Furthermore, the enrichment of genes related to auxin synthesis (tryptophan metabolism) directly corroborates the observed significant improvements in root system architecture (Figure 2), as auxins are crucial for root elongation and lateral root formation [49,50].

Our study also reveals a significant restructuring of the ecological co-occurrence network following sustained SynCom inoculation (Figure 6). The bacterial network under T3 exhibited a simpler topology (reduced clustering and modularity), which could suggest a streamlining of microbial interactions toward more direct, efficient metabolic pathways beneficial for plant growth [51,52]. In contrast, the fungal network in the T3 treatment displayed higher modularity. In ecological theory, greater modular networks are theorized to be more stable, as they can contain disturbances within a single module, preventing cascading failures [53]. This dichotomy in network response between bacteria and fungi potentially reflects kingdom-specific strategies for adapting to the SynCom introduction, highlighting the complex interplay between different microbial kingdoms within the rhizosphere [54].

One key finding is that Neocosmospora, Dyella, and the Rhizobium group emerged as central hub nodes in the networks under T3 (Figure 6c,f). Their role as hubs indicates a disproportionately large influence as keystone species or community organizers, mediating a high number of interactions and thus influencing the overall network structure and function [55,56]. For instance, the prominence of the Rhizobium group correlates with the enrichment of nitrogenase genes, which are essential for biological nitrogen fixation [57]. Dyella species are known to possess various plant growth-promoting traits, including phosphate solubilization and auxin production, aligning with the observed enrichment of alkaline phosphatase and tryptophan synthase genes [57].

The case of Neocosmospora requires careful interpretation. It is important to note that this genus encompasses documented pathogens, and closely related taxa have been identified as causal agents of stem and fruit rot in Capsicum annuum under greenhouse cultivation. However, throughout our experiment, no visible symptoms of stem or fruit rot, or any other overt pathogenic phenotypes, were observed on any pepper plants. Consequently, the beneficial role we infer for Neocosmospora is based on its positive correlation with plant performance and its integration into the co-occurrence network under our specific experimental conditions, which were characterized by the absence of significant disease pressure. Its emergence as a hub in this high-performing system suggests a context-dependent, beneficial role, potentially in nutrient cycling or the induction of systemic resistance [58]. This underscores the context-dependent nature of plant-microbe interactions and highlights that the proposed beneficial roles for these hub taxa require further direct validation through re-inoculation experiments. Collectively, their central positions suggest that the SynCom’s efficacy is mediated, in part, by its ability to recruit and promote specific native taxa that act as community organizers.

An important consideration is the behavior and persistence of the inoculated strains themselves. While our amplicon sequencing was not designed to track the specific strains, the significant increase in the relative abundance of Aspergillus and Trichoderma genera in the T3 treatment (Figure 6a) strongly suggests successful colonization and proliferation. Bacillus was already abundant in the control, making its tracking difficult. The SynCom’s success may therefore stem not only from its members’ direct PGPM activities but also from their role as initiators or keystone members that catalyze the community shift, creating favorable niches for other beneficial native taxa like Rhizobium and Dyella.

While this study provides significant insights, it was conducted under controlled pot conditions. Future field trials are essential to validate the efficacy and ecological stability of this sustained inoculation strategy under more complex and variable environmental conditions [17,59]. Furthermore, long-term studies are needed to assess the impact of sustained inoculation on native microbial diversity and soil ecosystem resilience, as the introduction of robust competitors could have unintended ecological consequences over time. Additionally, future multi-omics studies (metagenomics, metatranscriptomics, and metabolomics) would provide direct evidence of the expressed functions and metabolic fluxes, further elucidating the precise molecular dialogues among the SynCom, the native microbial community, and the host plant [60,61].

5. Conclusions

This study demonstrates that sustained inoculation with a SynCom is a highly effective strategy for enhancing pepper productivity and quality under greenhouse conditions. The underlying mechanism is an effective engineering of the rhizosphere microbiome, characterized by an enrichment of functional potentials related to nutrient cycling and phytohormone synthesis, and a fundamental reconfiguration of the microbial co-occurrence network. The T3 treatment fostered a more functionally potent and interconnected microbial community, with specific native taxa like Rhizobium, Dyella, and Neocosmospora emerging as keystone species. Our work provides a clear framework for optimizing bio-inoculant application, highlighting the importance of the application strategy in microbiome management. These findings provide practical insights for developing advanced microbial application strategies, ultimately paving the way for developing more effective bio-inoculants for sustainable agricultural systems.