Silver Nanoparticle Priming Enhanced Seed Germination in Bupleurum chinense and Reshaped the Fungal Community Structure, Reducing the Robustness of the Fungal Interaction

TL;DR

Silver nanoparticles improved seed germination in Bupleurum chinense and reduced mold by altering the fungal community structure.

Contribution

Demonstrates that silver nanoparticle priming enhances germination and reshapes fungal networks in a mold-prone plant species.

Findings

Seeds primed with 15 mg/L AgNPs showed a 71.67% germination rate compared to 58.90% in controls.

AgNPs reduced mold incidence to 16.46% from 31.01% and decreased fungal diversity (Shannon index 3.60 vs. 4.04).

AgNPs simplified fungal networks, reducing natural connectivity from 39.38 to 22.35 and suppressing keystone genera like Trichosporon.

Abstract

Seed germination represents the initial stage of the plant life cycle and directly affects subsequent plant establishment. Mold infestation is a major cause of reduced germination rate, yet effective and safe control methods are still lacking. Thus, developing effective strategies to ensure healthy seed germination is of critical importance. This study investigated the effect of priming with silver nanoparticles (AgNPs) on the germination rate of Bupleurum chinense seeds and on mold suppression. Additionally, we aimed to clarify the underlying microbial mechanism through high-throughput sequencing of the internal transcribed spacer (ITS) region. Seeds primed with 15 mg/L AgNPs exhibited a significantly increased germination rate of 71.67% (vs. 58.90% in control) and reduced mold incidence to 16.46% (vs. 31.01%). The ITS sequencing revealed that AgNPs significantly reduced the Shannon index to 3.60 (vs. 4.04) and decreased the abundance of potential pathogens. Co-occurrence network analysis demonstrated that AgNPs simplified the fungal network and reduced the natural connectivity to 22.35 (vs. 39.38). Topological analysis identified five keystone hub genera (e.g., Trichosporon, Podospora), whose suppression indicates their critical roles in network maintenance. This study provides evidence supporting the application of AgNPs in seed germination and offering a foundation for addressing germination challenges in mold-susceptible seeds.

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1. Introduction

Seed germination is a critical initial stage in the plant life cycle, directly determining subsequent crop yield, quality, and economic benefits [1]. However, seed mold is a major limiting factor during germination, which not only inhibits the germination process but can lead to seed or seedling death, resulting in significant economic losses [2]. Developing effective strategies to ensure healthy seed germination is of considerable practical importance.

Genetic breeding is an effective approach to improving seed germination, yet its large-scale application in the near term remains challenging due to lengthy breeding cycles, high economic costs, complex genetic backgrounds of target species, and lagging genomic research [3,4,5]. Conventional chemical treatments also present multiple limitations, including potential toxicity to radicles and plumules, environmental persistence that may lead to contamination, and the risk of fungal resistance due to their single mode of action, which reduces treatment efficacy [6,7]. Consequently, the development of novel, efficient, safe, and low-cost seed treatment technologies is urgently needed.

In recent years, nanomaterials have emerged as a promising strategy for plant growth regulation due to their high specific surface area, ease of penetration, and unique biological effects [8,9,10]. Compared to conventional chemical agents, nanomaterials offer advantages such as high efficiency, cost-effectiveness, and environmental friendliness [11]. Studies have shown that various nanomaterials, including zinc, iron, and silver, can significantly promote seed germination [11,12,13].

Mold invasion is a key factor limiting seed germination, but effective control strategies are still relatively limited. AgNPs, typically synthesized via chemical reduction or green methods, possess unique physicochemical properties (1–100 nm) that determine their biological activity: smaller particles exhibit larger surface areas, enabling efficient seed coat penetration and sustained release of Ag^+^ ions, thereby providing prolonged antifungal protection [14]. Mechanistically, AgNPs exert powerful antibacterial effects through multiple parallel pathways: generating reactive oxygen species (ROS), disrupting cell membrane integrity, damaging DNA and inhibiting protein synthesis [15,16]. Multiple studies have confirmed that AgNPs exert potent inhibitory effects on various pathogenic fungi, including Aspergillus fumigatus, Aspergillus niger, Aspeigillus flavus, Trichophyton rubrum, Candida albicans, and Penicillium [17]. For instance, quantitative analyses have shown that the MIC of biosynthesized AgNPs against Aspergillus spp. is 2.50 μg/mL, and against Candida albicans as low as 0.3 μg/mL [18,19]. These unique and powerful antibacterial properties are significantly superior to those of other nanomaterials, making AgNPs particularly suitable for solving the germination challenges of seeds characterized by prolonged germination and high mold susceptibility. Moreover, the positive effect of AgNPs on seed germination in other plant species have been fully confirmed, providing valuable benchmarks for this study. However, the application in mold-susceptible seeds and their antibacterial efficacy and mechanisms during germination remain insufficiently investigated.

Bupleurum chinense (B. chinense) is an important medicinal plant that faces significant germination challenges [20]. It is officially listed in the Chinese Pharmacopoeia as a fundamental medicinal herb, and modern pharmacological studies have demonstrated that its bioactive constituents, particularly saikosaponins, possess critical therapeutic effects including anti-inflammatory, hepatoprotective, and immunomodulatory activities. However, the increasing depletion of wild resources means that future market supply will depend largely on artificial cultivation. As a member of the Apiaceae family, it exhibits common characteristics of this family, including morphophysiological dormancy, the presence of germination inhibitors in the seed coat, and a high susceptibility to mold infestation. These intrinsic obstacles severely limit germination success. Under natural conditions, the germination rate is only 30–50%, the field emergence period may extend up to 40 days, and issues such as mold contamination and uneven seedling emergence are common, severely affecting plant establishment and the stable supply of medicinal material (Figure S1A) [21,22]. To overcome these germination barriers, exploring novel seed priming technologies is of great importance. Therefore, the objective of this study was to investigate the effect of AgNP priming on seed germination and mold suppression in B. chinense, and to elucidate the underlying microbial mechanisms through high-throughput ITS sequencing and fungal community analysis.

In this study, we used B. chinense seeds as a model system to demonstrate that AgNPs with the optimal treatment concentration can serve as an effective seed priming agent to suppress mold and improve germination performance. Using Internal Transcribed Spacer (ITS) sequencing, we compared fungal community dynamics across treatments and constructed co-occurrence networks to explore the ecological mechanisms underlying reduced mold incidence and improved germination. Notably, this study reveals for the first time in B. chinense seeds that the germination-promoting effect of nanoparticle treatment is associated not only with reduced fungal diversity and pathogen suppression, but also with the disruption of keystone taxa and simplification of fungal interaction networks. These findings provide a novel microbial ecological perspective on nanomaterial-mediated seed germination and establish a foundation for developing low-cost, efficient seed treatments applicable to other crops facing similar germination barriers.

2. Materials and Methods

2.1. Preparation of AgNPs Solution

AgNPs were purchased from Shanghai Pantian Nanomaterials Co., Ltd. (Shanghai, China). To ensure uniform dispersion and stable suspension, the stock solution was prepared as follows: 1 mg of AgNPs were added to 100 mL of deionized water and sonicated at 45 kHz for 45 min. The size and surface morphology of AgNPs were examined using transmission electron microscopy (TEM) (JEM-F200, JEOL, Tokyo, Japan). TEM images revealed that the AgNPs were spherical in shape with a size range of 19.9–36.9 nm (Figure 1C). The average particle diameter, measured by NanoMeasure software (version 1.2.5), was approximately 30 nm.

Hydrodynamic diameter and zeta potential of AgNPs dispersed in deionized water were determined using dynamic light scattering (DLS) (Zetasizer Pro, Malvern, UK). Results showed that AgNPs (2 mg/mL) exhibited a hydrodynamic diameter of 30.70 ± 0.31 nm and a zeta potential of −32.93 ± 0.23 mV (Figure 1A,B), indicating good colloidal stability.

2.2. Seed Priming Treatment

This research used B. chinense (Zhongchai No. 2) as the experimental material, which was obtained from the Institute of Medicinal Plant Development of the Chinese Academy of Medical Sciences in February 2023. After receiving them, these seeds were stored in a constant-temperature seed cabinet, with the temperature maintained at 4 °C. In May of the same year, relevant experiments for this study were conducted. Seeds were subjected to priming with AgNPs (treatment) or priming with water (control) in the Seed Physiology Laboratory, China Agricultural University, Beijing, China. The seeds were placed in deionized water and AgNPs solution at a 1:5 ratio and continuously shaken for 1 h. After priming, the seeds were rinsed three times with deionized water and air-dried at room temperature for 48 h to restore their initial moisture content, completing the seed priming process.

2.3. Determination of Seed Germination Phenotype

The seeds should be immersed in a 2% sodium hypochlorite solution for 2 min, and then thoroughly rinsed three times with deionized water. The germination test was conducted at 15 °C/25 °C with 16 h of darkness and 8 h of light. Every two days, the number of germinated seeds (with a visible radicle) was recorded. Each treatment was repeated three times, with 100 seeds per replicate, and the final germination rate was calculated. Additionally, seeds were sown in a sterilized substrate (nutrient soil:vermiculite = 1:1), and plants that emerged on the same day were selected for further growth. On the 20th day, root length and seedling dry weight were measured.

2.4. Sample Collection and DNA Extraction

To capture the dynamic changes in the microbial communities associated with seeds during the whole germination processes, four sampling points were planned: (i) before any treatment (T0), (ii) at the end of the pre-germination treatment with moist seeds (T1), (iii) after re-drying to the original moisture content (T2), and (iv) after 10 days of water uptake and reaching the “embryo root germination preparation” stage (T3). The seed samples at each sampling point need to be rinsed three times with sterile water, then rapidly frozen in liquid nitrogen and stored at −80 degrees Celsius for cryopreservation. A total of seven sample types were collected, each with three replicates, resulting in 21 DNA samples. Genomic DNA was extracted from the seeds using the VAMNE Stool/Soil DNA Extraction Kit (manufacturer: Vazyme Biotech Co., Ltd., Nanjing, China; model: DM401-C3-P2).

2.5. Sequencing

Using genomic DNA as template, the ITS1 region was amplified with barcoded primers ITS1-F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′). PCRs (10 μL) contained 2.5–4 ng DNA, 0.3 μM each primer, 5 μL KOD FX Neo Buffer, 2 μL dNTPs (2 mM each), 0.2 μL KOD FX Neo, and ddH_2_O to 10 μL. Thermal cycling: 95 °C 5 min; 25 cycles of 95 °C 30 s, 50 °C 30 s, 72 °C 40 s; final extension 72 °C 7 min. Amplicons were purified with VAHTS DNA Clean Beads at a 10:8 ratio. Indexed libraries were generated via 10-cycle index PCR (20 μL) with primers MPP1-a and MPP1-b, quantified and size-checked on a LabChip GX Touch or by agarose electrophoresis, pooled with an ECHO525 nanoliter pipetting system, further purified with an e.Z.N.A. Cycle-Pure Kit, and gel slices were purified with a Monarch DNA Gel Extraction Kit. The final libraries were sequenced on an Illumina NovaSeq 6000 platform. The sequencing data will be uploaded to the public database subsequently. ITS sequencing data have been deposited in the NCBI Sequence Read Archive under BioProject ID PRJNA1372384.

2.6. Preprocessing and Data Analysis

Raw sequencing data were processed through a standardized bioinformatics pipeline: quality filtering with Trimmomatic (v0.33), primer removal with Cutadapt (v1.9.1), and denoising, paired-end merging, and chimera removal (UCHIME, v8.1) via the DADA2 pipeline to produce high-quality sequences. Taxonomy was assigned in QIIME 2 using a Naive Bayes classifier (0.7 confidence threshold) against the UNITE database, generating taxonomic profiles and abundance tables from phylum to species.

The Shannon index was calculated to assess fungal α-diversity based on OTU abundance data obtained from ITS sequencing. Calculations were performed using the ‘diversity’ function in the picante package (version 1.8.2) within R software (version 3.1.1). The taxonomic composition was illustrated using GraPhlAn to generate circular cladograms, highlighting species with an average relative abundance exceeding 0.001%. Differentially abundant biomarkers across groups and induction stages were identified by linear discriminant analysis effect size (LEfSe) with an LDA score threshold of 2.0. Statistical significance between treatments was determined using GraphPad Prism software (version 10.0, GraphPad Software, San Diego, CA, USA). For comparisons involving multiple groups, one-way analysis of variance (ANOVA) was performed, followed by unpaired Student’s t-test for specific pairwise comparisons where applicable. Differences were considered statistically significant at p < 0.05.

Potential phytopathogenic fungi were screened at the genus level against the “List of Common Pathogenic Fungi in Chinese Agriculture” and the Animal and Plant Health Inspection Service database.

To assess differences in network topology, a Maslov–Sneppen algorithm was used to generate 100 random networks. The t-test was employed to compare topological features of the networks, including the small-world coefficient and natural connectivity. To evaluate network robustness, the natural connectivity was used as an indicator, simulating the removal of nodes in proportion to their importance. Three attack strategies were applied: (1) random attack; (2) intentional attack based on node degree; and (3) intentional attack based on node betweenness.

The cluster_fast_greedy algorithm was used to identify communities. Nodes were classified into four categories based on the module internal connectivity (Zi) and inter-module connectivity (Pi): (1) peripheral nodes (Zi ≤ 2.5, Pi ≤ 0.62); (2) connectors (Zi ≤ 2.5, Pi > 0.62); (3) module hubs (Zi > 2.5, Pi ≤ 0.62); and (4) network hubs (Zi > 2.5, Pi > 0.62).

3. Results

3.1. Effect of AgNP Priming on Seed Germination

Seeds of B. chinense were primed with AgNPs solutions at different concentrations (0, 5, 10, 15, 20, 25, 30, 35, 40, and 80 mg/L). AgNP priming significantly affected both seed germination rate and mold incidence (p ≤ 0.05) across the tested concentrations. Further analysis confirmed a clear dose-dependent effect of AgNPs on seed germination and mold incidence. Within the range of 0–15 mg/L, the germination rate increased with rising AgNPs concentration; however, when the concentration exceeded 15 mg/L, the germination rate gradually declined, while mold incidence exhibited the opposite trend. Notably, 15 mg/L AgNPs was the optimal concentration, increasing the germination rate from 58.90% to 71.67% and reducing mold incidence from 31.01% to 16.46% (Figure 1D and Table S1). In addition, AgNP priming showed no significant impact on subsequent seedling root length or dry weight (p > 0.05) (Figure S1B), indicating that the treatment promotes seed germination without adversely affecting seedling growth.

Beyond concentration, the temporal dynamics of AgNP priming were critical. During the first 8 days of imbibition, germination dynamics showed no significant differences between AgNP-primed and hydroprimed seeds. A significant advantage for AgNP priming emerged only on day 10, suggesting that day 9 marks the critical time point when the promotive effect of AgNPs begins (Figure 1E).

3.2. Overview of All Sequencing Data and Taxonomy Assignments

To investigate the microbiological mechanisms by which AgNP priming reduces mold incidence in B. chinense seeds, we selected four key time points for ITS sequencing: dry seeds (T0), after priming but before re-drying (T1), after re-drying (T2), and on the 9th day of imbibition (T3) (Figure 1F). A total of 1,678,934 raw read pairs were obtained. After stringent quality control and denoising, 1,420,083 high-quality read pairs remained, which were clustered into 4036 operational taxonomic units (OTUs) (Table S2). The rarefaction curves (Figure S2) indicated that the sequencing depth was adequate to capture the full spectrum of species diversity present in the samples, supporting the reliability of subsequent analyses. Taxonomic classification revealed that the 4036 OTUs belonged to 15 phyla, 99 orders, 226 families, and 451 genera (Table S3). At the phylum level, Ascomycota and Basidiomycota were the predominant fungal lineages. At the genus level, Didymella, Alternaria, and Filobasidium, were the three most abundant genera (Figure S3A–C).

3.3. Diversity Analysis of Fungal Communities

α diversity is a key metric for assessing the richness, evenness, and overall diversity of fungal communities. Compared to hydropriming, AgNP priming significantly reduced the Shannon diversity index but only slightly decreased the number of OTUs (Figure 2A,D), indicating a more pronounced inhibition of community diversity than of richness. Comparison between treatment and control groups at each time point revealed that at T3, the number of OTUs in the control group was significantly higher than that in the treatment group. In contrast, at both T1 and T3, the Shannon index of the control group was significantly greater than that of the AgNP-primed group (Figure 2B,E). Overall, AgNP priming significantly reduced both the diversity and richness of fungal communities in B. chinense seeds. This suppression was particularly evident at T1 and T3 for diversity, whereas the reduction in richness was mainly observed at T3.

3.4. Composition of Fungal Communities

Following the characterization of AgNP priming effects on overall fungal diversity, we further examined compositional shifts within the communities. At the phylum level, Ascomycota exhibited significantly higher relative abundance and species diversity than Basidiomycota (Figure 3A,B). At the genus level, the ten most abundant fungal genera were Didymella, Alternaria, Filobasidium, Coniothyrium, Papiliotrema, Fusarium, Lectera, unclassified_Pleosporales, and Cladosporium (Figure 3C,D). From stage T0 to T3, as seed germination progressed, the relative abundance of Basidiomycota gradually decreased, whereas that of Ascomycota increased (Figure 3B), suggesting distinct ecological roles of these two phyla during the germination of B. chinense seeds. LefSe analysis further identified 81 genera that varied significantly across time points and 20 genera that responded differentially to priming treatments. Among these, the genera Curvularia and Pseudaleuria showed significantly higher relative abundance in the treatment group compared to the control (Figure S3D,E and Supplementary Table S4). Collectively, the germination of B. chinense seeds was accompanied by dynamic shifts in fungal community composition, which responded distinctively to different priming treatments.

3.5. Composition of Possible Plant Pathogens

To further elucidate the mechanism by which AgNP priming reduces seed mold incidence, we cross-referenced the identified fungi with previous literature to identify potential pathogens. In the hydroprimed group, 195 genera (relative abundance ≥ 0.0001%) were identified, of which 50 were classified as potential pathogens. In the AgNP-primed group, 201 genera met the abundance threshold, with 46 classified as potential pathogens, indicating that AgNP priming moderately reduced the number of pathogenic genera (Figure 4A,B and Supplementary Table S5). Notable among these were genera such as Alternaria, Aspergillus, Cercospora, Bipolaris, and Curvularia, which are known to cause seed rot or inhibit germination through mycotoxin production during germination. Furthermore, several fungi—including Cladosporium, Fusarium, Stemphylium, Colletotrichum, and Diaporthe—have been documented as causal agents of typical plant diseases such as leaf spot, rot, and wilt.

Analysis of the fungal community dynamics revealed a progressive increase in potential pathogens during germination, with a peak at the T3 stage that coincided precisely with the maximal germination rate difference between the two treatments (Figure 4A). Notably, 61.67% of the potential pathogenic genera exhibited significantly lower relative abundance in the AgNP-primed group compared to the hydroprimed group, including common pathogens such as Fusarium and Bipolaris (Figure 4A). Together, our results demonstrate that AgNP priming effectively reduces both the diversity and relative abundance of potential fungal pathogens in B. chinense seeds, which may represent a key mechanism underpinning the observed reduction in mold incidence and enhancement of germination rate.

3.6. The Fungal Interaction Network in the Seeds of B. chinense

The internal microorganisms of seeds do not exist in isolation but commonly form interactive associations. To dissect how AgNP priming reshapes the ecological relationships within the seed mycobiome, we constructed co-occurrence networks for Hydroprimed and AgNP-primed seeds (filtering criteria: relative abundance > 0.001, prevalence > 50% of samples; Spearman |r| > 0.80). The results revealed that, compared to the control group (118 nodes and 1123 edges), the treatment group exhibited 76 nodes and 339 edges, representing reductions of 36% and 70%, respectively. The proportion of positive correlations also decreased from 70.26% to 63.72% (Table 1 and Figure 5A,B). These findings indicate that AgNP priming not only markedly simplified the structure of the fungal community but may also have directly suppressed certain keystone taxa and shifted the network interactions from facilitative to more inhibitory relationships.

Natural connectivity is a key topological metric for quantifying the global connectedness and disturbance resistance of a network, directly reflecting the stability of its ecological function. We found that the natural connectivity of the control group (39.384) was significantly higher than that of the treatment group (22.352) (Table 1). Under both random attack (Figure 5C) and targeted attack based on node degree (Figure 5D), the natural connectivity of the hydroprimed network remained higher than that of the AgNP-primed network until 48% and 92% of nodes were removed, respectively; beyond these thresholds, the two networks converged. Similarly, under degree based targeted attack, the natural connectivity of both groups declined as the proportion of removed nodes increased, with periods of relative stability observed in specific intervals (control: 20–32%; treatment: 14–26%) (Figure 5). In summary, the fungal interaction network of the control exhibited greater complexity and robustness, indicating a more stable structure. In contrast, AgNP priming simplified the fungal network and compromised its stability, likely by disrupting microbial cooperation to suppress pathogens and promote germination.

To further dissect the topological characteristics of the fungal interaction networks, we compared the node-level topological roles between the treatment and control groups (Figure 6A,B). The results revealed that the vast majority of fungal genera were classified as peripheral nodes (Hydropriming: 95.76%; AgNP priming: 100%), with most connections confined to their own modules. Notably, 98.68% of peripheral nodes in the AgNP-primed group lacked inter-module connections, a higher proportion than that observed in the hydroprimed group (97.35%). These findings indicate that the network under AgNP priming exhibits a more fragmented and less integrated architecture than that under hydropriming.

Further analysis identified four connector nodes (Podospora, Trichosporon, unclassified_Agaricomycetes, unclassified_Mycosphaerellaceae) and one module hub (Humicola) in the hydroprimed group. These five keystone taxa all exhibited lower relative abundance in the treatment group compared to the control (Figure 6C). Moreover, their peak abundance at T3 coincides with the critical period of germination rate divergence, strongly supporting their role as core microbial taxa responsible for maintaining the structural and functional stability of the fungal network in hydroprimed seeds.

4. Discussion

Seed germination is conventionally regarded as a physiological process initiated by endogenous metabolic activity [1]. However, in seeds harboring rich endophytic and epiphytic microbial communities, successful completion of germination also depends on the ecological pressures exerted by the microbiota on the host. In this study, priming with AgNPs enhanced the germination rate of B. chinense seeds while concurrently reducing the incidence of mold contamination, suggesting that the underlying mechanism may involve modification of the seed’s microecological structure. Although previous studies have demonstrated that AgNPs can promote germination in various crop species, their explanations have predominantly focused on changes in physiological indices [23,24]. This study, however, further reveals an association between community-level shifts and germination success.

Following AgNP treatment, the overall abundance and alpha diversity of the seed-associated fungal community decreased. Nanomaterials can exert antifungal activity by inducing oxidative damage and disrupting cellular structures [25]. During early germination, fungal invasion often accompanies reserve consumption and tissue damage. Research has indicated that fungal infection can significantly reduce seed germination rates due to competitive utilization of nutrients [26]. Therefore, a reduction in fungal load may alleviate resource competition, enabling the seed to prioritize allocation of stored reserves toward critical processes such as radicle elongation and testa rupture. This shift provides an ecological explanation for the observed increase in germination rate.

Compositional shifts are also significant. Several potentially pathogenic genera, including Aspergillus, Cercospora, and Bipolaris, decreased in abundance following treatment. Previous studies indicate that these taxa can produce mycotoxins or secrete cell wall-degrading enzymes, thereby damaging host tissues [27,28]. Their suppression implies a concurrent decrease in both toxin exposure and the risk of tissue disruption, contributing to lower mold incidence.

At the level of community interactions, node number and connectivity within the network decreased after treatment, leading to diminished overall robustness. Ecological theory suggests that highly connected structures are typically associated with greater stability [29]. However, in communities harboring potential pathogens, high connectivity may also maintain structures conducive to synergistic infection. Reduced robustness implies that the community is more prone to disintegration upon disturbance, thereby weakening its persistent infectivity [30,31,32]. Consequently, AgNPs may attenuate synergistic relationships among fungi by disrupting community organization.

Furthermore, certain taxa occupying topologically central positions (such as Podospora, Trichosporon, and members of the Mycosphaerellaceae family) exhibited declines in both centrality and abundance after treatment. According to network theory, nodes with high within-module connectivity and high participation coefficients play crucial roles in maintaining overall structural stability [33]. These groups include potentially pathogenic members, and their altered structural status may weaken inter-modular connections, thereby triggering network simplification [34,35,36,37]. Due to amplification effects associated with keystone nodes, such changes can have cascading effects on community function.

In summary, AgNPs reshape the seed’s microecological structure through multiple mechanisms: reducing fungal abundance and diversity, diminishing potentially pathogenic taxa, and weakening community connectivity and keystone node influence. As the community transitions from a relatively connected state to a more simplified configuration, its capacity for resource competition and synergistic infection likely diminishes. Consequently, the microbial pressure experienced by the seed during germination is alleviated. This study extends the mechanistic understanding of AgNP-mediated germination promotion to encompass microecological regulation, providing a theoretical basis for understanding the ecological effects of nanomaterials in seed treatment.

5. Conclusions

This study demonstrates that AgNP priming effectively overcomes the germination barriers in B. chinense, a medicinal species constrained by morphophysiological dormancy and high mold susceptibility. At the optimal concentration of 15 mg/L, AgNPs treatment achieved over 70% germination while reducing mold incidence to below 20%, representing a substantial improvement over conventional methods. By integrating high-throughput sequencing and microbial interaction network analysis, we elucidated the ecological mechanisms underlying this enhancement. Our results demonstrated that AgNPs not only directly suppressed total fungal load, diversity, and potential pathogen abundance but, more importantly, simplified the fungal network structure, reduced its robustness, and selectively eliminated keystone taxa such as Mycosphaerellaceae and Podospora, thereby disrupting the cooperative infection capacity of the fungal community. This finding provides a new perspective for understanding how AgNPs regulate the seed microbiome and germination outcomes.

Future research should focus on the following directions. First, functional characterization is required for the five keystone genera identified through network analysis, particularly Trichosporon and Podospora, to elucidate whether they act as direct pathogens or facilitate infection by other fungi. Targeted isolation and re-inoculation assays using cultures derived from B. chinense seeds could resolve their specific roles. Second, it remains to be determined whether the efficacy of AgNP priming extends to other Apiaceae species or to other seeds characterized by prolonged germination cycles and high mold susceptibility, addressing this question will clarify the universality of this approach. Third, the influence of nanoparticle morphology (e.g., size, shape, surface properties) on germination outcomes and antifungal efficacy warrants systematic evaluation, as different morphological features may modulate seed penetration, ion release kinetics, and microbial interactions. Fourth, while AgNPs effectively suppressed Fusarium and Alternaria during germination, it remains unknown whether this suppression persists during seedling establishment; further research is needed to assess post-germination disease resistance. Addressing these questions will not only refine our understanding of how nanomaterials interact with seed microbiomes but also guide the development of targeted, microbiome-informed seed treatments for other economically important species facing similar germination challenges.