Dual-functionality of Nocardiopsis alba B57 in biocontrol and plant growth: a metabolomic approach to agricultural sustainability

Abstract

The increasing incidence of fungal phytopathogens poses a significant challenge to agricultural sustainability, necessitating the development of environmental alternatives to synthetic fungicides and mitigating their ecological impact. This study explores the efficiency of Nocardiopsis alba B57 to produce secondary metabolites with antifungal and plant growth-promoting properties. Untargeted metabolomics using ultra-high-performance liquid chromatography (UPLC-MS/MS) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified key metabolites (e.g., carbapenem, menaquinone, and fumiquinazoline) in the co-culture environment with fungal pathogens. Additionally, principal component analysis and OPLS-DA differentiated monoculture and co-culture metabolic profiles, revealed carbapenem biosynthesis as a highly enriched pathway. The comprehensive metabolomics data and the statistical analysis of the identified metabolites confirmed that co-culturing of B57 and fungal strains showed upregulated metabolites (e.g., carbapenem and menaquinone). However, other metabolites (e.g., mupirocin) were downregulated and significantly suppressed. These changes in metabolic activity reflect the organism’s adaptive and competitive responses during the co-culture conditions with fungal pathogens and influence plant hormone signaling (e.g., auxin and cytokinin), promoting plant growth and disease resistance. These findings underscore B57’s adaptive biosynthetic response to co-culture conditions, supporting its use as a sustainable biocontrol agent and boosting crop productivity.

Introduction

Environmental sustainability has become a critical issue of the 21^st century, necessitating a balance between economic growth, social equity, and ecological preservation to mitigate the adverse impacts of human activities on ecosystems^1,2. With the global population projected to reach ~10 billion by 2050³, the agricultural sector faces unprecedented challenges, including urban expansion, declining soil quality, climate variability, and increasing pathogen resistance to conventional treatments⁴. Plant diseases alone cause substantial crop losses, exacerbating food insecurity. To address these issues, many agricultural practices have relied heavily on chemical pesticides and fungicides, such as dimetachlone^5,6 and mancozeb^7,8. While effective in the short term, their overuse presents significant environmental and health risks, including soil and water contamination, reduced biodiversity, and chemical residues in food⁹. Moreover, the reliance on these chemical agents undermines sustainability goals by harming beneficial soil microorganisms and contributing to environmental degradation.

Fungal pathogens (e.g., Fusarium spp. and Verticillium spp.) exemplify the challenges to agricultural productivity and sustainability. Fusarium species alone account for an estimated 14% reduction in annual crop yields¹⁰, while Verticillium dahliae can cause yield losses of up to 50% in susceptible crops such as potatoes and cotton¹¹. Managing these pathogens often necessitates increased use of chemical fungicides, further exacerbating environmental issues. Effective alternative strategies, including integrated pest management, crop rotation, biopesticides, and the development of disease-resistant plant varieties, are urgently needed to reduce chemical dependency and foster sustainable agricultural practices^12,13. Recent research emphasizes the use of biological antagonists, such as endophytic bacteria, as eco-friendly biocontrol agents to combat plant diseases. These bacteria establish symbiotic relationships with host plants and produce bioactive compounds that enhance plant survival while suppressing pathogens¹⁴. For instance, Thymus roseus, a medicinal plant, has been identified as a source of endophytic actinobacteria such as with broad-spectrum antimicrobial properties, offering promising solutions for sustainable crop protection^1,15,16. Musa et al.¹⁵ found that Streptomyces polyantibioticus isolated from T. roseus showed fungal inhibition ratios of up to 67.1%, 64.2%, and 70.6% against Alternaria solani, Valsa malicola, and Valsa mali, respectively. Additionally, Abdelshafy Mohamad et al.¹ successfully isolated Streptomyces albidoflavus from T. roseus with antifungal activity against Fusarium spp.

Emerging biotechnologies and metabolomics have revolutionized the discovery of novel biocontrol agents. Metabolomics provides a comprehensive framework for identifying and profiling metabolites, offering insights into biochemical interactions between plants and pathogens¹⁷. Metabolomics has facilitated the development of biopesticides derived from bacterial strains (e.g., Streptomyces spp.), which produce bioactive compounds and secondary metabolites with antifungal properties^15,18. Commercial products (e.g., Actinovate, Mycostop, and Streptomycin) demonstrated the potential of these biocontrol agents to manage soil-borne pathogens and promote plant health^19,20. Moreover, advanced metabolomics techniques enable the identification of novel bioactive compounds that enhance plant resilience and suppress pathogens. By leveraging these tools, researchers can pave the way for innovative, sustainable strategies to control plant diseases, reduce chemical pesticide usage, and ensure agricultural productivity in the face of growing global challenges.

Endophytic bacteria, such as Nocardiopsis alba B57, can produce secondary metabolites as reported in our previous study¹⁵, which possess the potential to control fungal pathogens and promote plant growth. Therefore, this study aims to explore the ability and underlying mechanisms of N. alba B57 to promote plant growth and mitigate plant diseases. Specifically, this study sought to comprehensively elucidate the metabolite composition of B57 and their dynamic variations in response to antagonistic interactions with specific fungal phytopathogens, employing cutting-edge untargeted metabolomics analysis. Furthermore, the growth-promoting and biocontrol efficacy of B57 crude extract was systematically evaluated. This research provides the first scientific basis for an untargeted metabolomics approach to exploring the antagonistic activity of crude extracts from B57. In addition, this investigation is significant because it represents a pioneering application of untargeted metabolomics to unveil the antagonistic properties of B57, offering novel insights into its potential as a sustainable biocontrol agent and plant growth enhancer, contributing to sustainable agriculture, and enhancing productivity within ecosystems.

Results and discussion

Comparative analysis of metabolomic profiles in N. alba B57

Microorganisms possess the ability to produce a wide range of metabolites in response to varying ecological conditions^1,21. In this study, B57 was subjected to metabolomics evaluation to detect metabolic changes and provide a detailed understanding of the complex interactions between N. alba and fungal pathogens, leading to the development of effective, sustainable, and eco-friendly biocontrol strategies. The interactions between B57 and plant pathogens (F1, F2, F3, and F4) encoded as (B-Fungi) were analyzed using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS), which employs comprehensive specific metabolomics in negative and positive ionization modes. The heatmap illustrates the Spearman rank correlation (SRC) coefficients between B-Fungi compared to fungi groups as a control, as shown in Fig. 1. The correlation values range from 0.5 to 1.0, with darker blue shades indicating stronger positive monotonic relationships. The diagonal values, which represent self-correlations, are consistently 1.000.

Fig. 1

Spearman rank correlation coefficient analysis between Nocardiopsis alba B57 and various plant fungal pathogens.

The significant strong correlations that occurred within the B-Fungi showed notable correlation values, such as 0.652 between B57 and F1-57, and 0.835 between F1-57 and F3-57, suggesting a significant interdependency among these strains, as shown in Fig. 1. This analysis indicates that the robust interactions between N. alba and fungal strains. Conversely, the correlations between B-Fungi and the control group were insignificant. Spearman’s rank correlation further clarified B57’s antagonistic impact on the tested fungi, revealing a strong positive association between B57 and F1, F2, F3, and F4 at 0.652, 0.674, 0.623, and 0.654, respectively (Fig. 1). Network correlation analysis underscored specific, highly repeatable microbial interactions with each fungal species.

Ghosh et al.²², stated that the metabolomics assay assists in the monitoring of chemical variations in the biosystems’ metabolome, presenting a deep understanding of the effect of fungal interactions on the diverse metabolite profile of actinobacteria (e.g., N. alba). This was aligned with Mohamed et al.¹⁶, who found that actinobacteria can generate different plant growth-promoting (PGP) traits, including phosphate solubilization (24%), auxin (88%), siderophore production (94%), and ammonia (96%) with 45% and 26% inhibition effect against Fusarium oxysporum and for Verticillium dahlia, respectively. This could be because microbial interactions can activate antimicrobial compound production as a defense strategy. In addition, activates different biosynthetic gene clusters (BGCs) depending on the presence of competing organisms²³. Moreover, Rutledge and Challis²⁴ highlighted the role of interspecies interactions in awakening silent gene clusters, often via cross-species signaling or stress-induced pathways.

This study leverages metabolomics and bioinformatics to investigate the links between microbial metabolites and their interactions with phytopathogens. Metabolomics can track chemical variations within the metabolome of B57 and provide insights into its fungal interaction mechanism¹.

Multivariate statistical analysis of metabolomic interactions between N. alba B57 and fungal pathogens

The multivariate statistical analyses in Fig. 2 offer a detailed exploration of the metabolic interactions between B57 and the tested fungal pathogens. These analyses utilize principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) to uncover metabolic variations and relationships between N. alba B57 and fungal strains. The PCA score plot revealed distinct clustering patterns, with PC1 and PC2 explaining 20.61 and 18.43% of the variance, respectively (Fig. 2A). A clear variation was observed between the B-Fungi group (co-culture samples) and the fungi group (monoculture samples). The B-Fungi group forms a compact cluster, while the fungi group showed wider dispersion, suggesting high variability in their metabolic profiles. Within the B-Fungi cluster, samples F1-57, F2-57, F3-57, and F4-57 exhibited close clustering, indicating metabolic consistency in their interactions with B57. B57 is distinctly positioned along the PC2 axis, signifying a unique metabolic profile that may reflect specialized biosynthetic activity. This distinctiveness highlights the organism’s potential influence of organisms on metabolite production during co-culture.

Fig. 2: Multivariate statistical analysis of B57 with the tested fungal strains.

PCA illustrates the clustering of B57 and the fungal pathogens based on their metabolic profiles. The ellipses represent 95% confidence intervals, with the B-Fungi subgroup in red and the fungi group in green (A). OPLS-DA scores demonstrated strong separation between the B-Fungi and fungi group as a control, indicating distinct metabolic characteristics and relationships. The model performance metrics (R2X, R2Y, Q2Y, and RMSEE) are displayed, indicating the robustness and reliability of the analysis (B).

The PCA analysis for co-cultured and monoculture samples suggests that B57 may produce specific metabolites (e.g., carbapenem, menaquinone, and fumiquinazoline) against fungal pathogens. The general description of compact clustering of the B-Fungi group (Fig. 2A) indicates a consistent metabolic response when interacting with multiple fungal strains, which could point to a robust defense mechanism that could be harnessed for developing resistant plant varieties or natural fungicides. The PCA results align with the data obtained by Ma et al.²⁵, who reported distinct clustering between co-culture and monoculture samples, indicating that unique chemical compositions are driven by microbial interactions. Similarly, Shi et al.²⁶ observed clear metabolite differentiation between co-culture and monoculture groups, further supporting the role of chemically mediated interactions in modulating biosynthetic pathways and enhancing secondary metabolite production. The obtained data in this study collectively underscore the influence of B57 in shaping metabolite profiles through its interactions with fungal pathogens, emphasizing its potential ecological and biotechnological relevance.

The OPLS-DA further substantiates these findings through a supervised approach, enhancing the separation between predefined groups (Fig. 2B). The OPLS-DA plot distinctly differentiates the B-Fungi group (clustered in the bottom-left quadrant) from the fungi group (clustered in the top-right quadrant), highlighting strong discriminatory metabolites between these categories. The model demonstrates robust reliability, as evidenced by high-performance metrics: R²X = 0.323, R²Y = 0.999, and Q²Y = 0.648. These values indicate excellent model fitness and predictive power. Additionally, the tight clustering of samples within each group suggested consistent metabolite profiles, while the clear separation between B-Fungi and fungi emphasized unique metabolic interactions with B57. Strong discriminatory metabolite identification through OPLS-DA highlights potential targets for further research into bioactive compounds produced by B57. Understanding how microbial metabolites are produced in response to fungal pathogens could lead to the development of biopesticides or other agricultural products that mimic these natural defenses²⁷ providing an eco-friendly alternative to synthetic fungicides.

Collectively, the PCA and OPLS-DA analyses revealed that B57 exhibited significant metabolic correlations with the co-culture (B-Fungi) group compared to the fungi group (control group). This suggests a more effective influence or interaction at the metabolite level. The distinct positioning of B57 in the PCA plot underscores its unique metabolomic profile, due to specialized metabolite production in response to fungal pathogens. The successful discrimination of groups achieved by the OPLS-DA model provides a solid foundation for exploring specific metabolic pathways and compounds responsible for these interactions. From a biological perspective, the obtained data highlight the potential of B57 as a biocontrol agent against pathogenic fungal strains. The clear metabolic distinctions and interactions observed suggest promising applications in agricultural settings. Further investigation into the specific pathways and metabolomic profiles of B57 could uncover the mechanisms underlying its specificity, potentially leading to the development of more effective and targeted biocontrol strategies in agriculture.

An in-depth analysis of differential metabolites between monoculture and co-culture reveals quantitative variations, highlights significant metabolites, and visualizes their overall changes based on fold change (FC) values, as illustrated in Fig. 3. The bar plot highlights the top 10 upregulated and top 10 downregulated metabolites, expressed as log2FC values. Among the upregulated metabolites, carbapenem (C20821), menaquinone, and (3S,4R)-3,4-dihydroxycyclohexa-1,5-diene-1,4-dicarboxylate showed the highest FCs, with log2FC values of 6.7, 6.11, and 5.65, respectively, as shown in Fig. 3. These metabolites may represent compounds whose production is enhanced due to specific interactions in the co-culture. In contrast, among the downregulated metabolites, PS(18:1(11Z)/16:1(9Z)), ethylglyoxalbis(guanylhydrazone), and mupirocin were the most significantly suppressed, with log2FC values of −4.24, −3.74, and −3.46, respectively. These shifts suggest changes in metabolic activity, reflecting the organism’s adaptive or competitive responses during co-culture conditions.

Fig. 3: Comparative fold change analysis of the changes in the quantitative data of the main upregulated and downregulated metabolites in N. alba B57 and fungi co-culture system.

The fold change highlights the differential expression of metabolites, emphasizing the impact of co-cultivation on the metabolic profile of B57. Each bar represents the magnitude of change, providing insights into the specific metabolites that are significantly influenced by the co-culture environment.

The variations in the expression of metabolites by plotting their log2 fold change (log2FC) values against their statistical significance (-log10(p-value)), as shown in the volcano plot Fig. 4A. This analysis identified unchanged metabolites (n = 3792) and key metabolites that undergo significant changes in abundance during co-culture. The upregulated metabolites (n = 19), such as 12-keto-leukotriene B4 and Lys-Val-Gly, are positioned prominently on the right side of the plot, indicating substantial increases in their abundance. These metabolites also display high variable importance in projection (VIP > 1.4) values, emphasizing their strong contribution to the metabolic distinctions between co-culture and monoculture conditions. Conversely, downregulated metabolites, such as lubiprostone (RU-0211) and phosphatidylserine (PS(16:1(9Z)/17:0)), appeared on the left, reflecting significant decreases in abundance. Their elevated VIP scores further validated their critical role in distinguishing metabolic states. Most metabolites, represented in gray, cluster around the center of the plot with log2FC values near zero and low VIP scores, indicating their stability across the experimental conditions. Together, the volcano plot highlights a subset of metabolites with both high statistical significance and biological relevance.

Fig. 4: Metabolic profile variations in Nocardiopsis alba.

A The volcano plot revealed variations in metabolites at (p < 0.01). B Spider chart of the top ten metabolites ranked by log2FC values.

The spider chart complements (Fig. 4B) the volcano plot by showcasing the proportional abundance of the top 10 metabolites with the top absolute log2FC values. Upregulated metabolites, such as menaquinone and (3S,4R)-3,4-dihydroxycyclohexa-1,5-diene-1,4-dicarboxylate, exhibit significant positive log2FC values and high VIP values, suggesting enhanced biosynthetic activity in secondary metabolism pathways. These metabolites may contribute to increased antimicrobial or competitive capabilities under co-culture conditions. Notably, carbapenem showed strong upregulation, reinforcing its potential role in antibiotic production. In contrast, downregulated metabolites such as mupirocin and PS(18:1(11Z)/16:1(9Z)) (phosphatidylserine; C₄₀H₇₄NO₁₀P) display considerable suppression, which may reflect adaptive strategies to reduce antagonistic interactions and promote co-culture synergy. Kenis et al.²⁸ stated that the phosphatidylserine upregulation at the cell surface functions as an “eat me” flag toward phagocytes and is a part of the membrane dynamics of apoptosis. Thus, in this study, phosphatidylserine downregulation refers to the survival and adaptability of the bacterial cells.

By providing a comparative view of metabolite abundance, the spider chart underscores the dynamic regulation of specific metabolic pathways in response to co-culture conditions. The results showed that metabolites associated with B57 and their differential expression during co-culture conditions play crucial roles in both antifungal activity and plant growth promotion. One of the prominent metabolites, carbapenem (β-lactam antibiotic), is recognized for its broad-spectrum antimicrobial properties, particularly against Gram-negative bacteria and certain fungi. The observed upregulation of carbapenem in co-culture conditions indicates its potential to enhance the plant’s defense mechanisms against fungal pathogens by effectively inhibiting their growth and proliferation.

This characteristic positions carbapenem as a significant player in the plant’s biochemical arsenal against infections. Therefore, the metabolomic analysis, as shown in Fig. 5, illustrated the intricate biosynthetic pathway of carbapenem antibiotics, emphasizing the pivotal roles of amino acids such as arginine and proline in the synthesis process. This pathway involves a cascade of enzymatic reactions and metabolic intermediates, showcasing the biochemical complexity underlying the production of carbapenems. Carbapenem biosynthesis is initiated through metabolic precursors, particularly L-glutamate and L-proline, which are derived from the metabolism of arginine and proline. These amino acids serve as fundamental building blocks, linking basic metabolic pathways to the specialized biosynthesis of carbapenems. This reliance on essential amino acid pathways highlights the evolutionary efficiency of microbial systems in repurposing primary metabolites for secondary metabolite production.

Fig. 5

Different carbapenems biosynthesis pathways and the integrated enzymes and genes in B57.

A series of specialized enzymes catalyze critical transformations throughout the pathway. Key enzymes such as carboxymethylproline synthase (CarDE, CarB), and thienamycin genes (ThnE) play essential roles, particularly in modifying L-proline to generate carbapenem-specific intermediates, such as (2S, 5S)-trans-carboxymethylproline. These enzymatic steps ensure the structural specificity required for the bioactivity of carbapenems. Additionally, the involvement of enzymes such as ThnF and ThnG, which regulate subsequent modifications, demonstrates the complexity and precision of this biosynthetic process. The pathway features a variety of intermediates, including L-glutamyl-P, L-glutamate 5-semialdehyde, and diverse thienamycin derivatives such as 2,3-dihydrothienamycin and N-acetylthienamycin. These intermediates signify systematic assembly and progressive modifications that culminate in the formation of the carbapenem core structure. The presence of multiple thienamycin derivatives underscores the substrate variability and the potential to generate bioactive compounds with distinct pharmacological profiles. Such modifications may influence the spectrum and potency of the resulting antibiotics.

The enzymatic activities within this pathway are subject to sophisticated regulatory mechanisms, including feedback inhibition and environmental modulation. For instance, the activity of key enzymes may be fine-tuned by the cellular metabolic state or external stimuli, optimizing antifungal production under varying conditions. Understanding these regulatory networks could provide insights into how microbial systems adapt biosynthetic outputs to meet survival demands. The detailed enzymatic and metabolic insights revealed by this pathway pave the way for synthetic biology innovations. By engineering microbial strains or manipulating biosynthetic enzymes, researchers can potentially enhance antibiotic yields or create new antibiotics with improved efficacy and stability.

Carbapenem antibiotics are among the most effective agents against multidrug-resistant bacterial infections, making them indispensable in different applications. Also, FDA-approved lipopeptides daptomycin and dalbavancin, and novel carbapenems, such as thienamycin, are precursors of antifungals such as nystatin and candicidin²⁹. A deeper understanding of their biosynthesis could facilitate bioengineering approaches to enhance production efficiency or design novel derivatives capable of overcoming different plant pathogens. Another metabolite, menaquinone (Vitamin K2), is involved in various biological processes, including electron transport in bacteria³⁰. Menaquinones play a significant role in the growth and development of plants. This vitamin K2 variant is primarily synthesized by certain bacteria and has implications for plant health and nutrient cycling. Menaquinone is involved in the electron transport chain, which is crucial for cellular respiration in plants to facilitate energy production by acting as an electron carrier, thus enhancing the efficiency of photosynthesis and respiration processes³¹. Menaquinones are known to regulate calcium levels within plant cells. This regulation is vital for various physiological processes, including cell division, elongation, and overall growth³¹. Proper calcium levels contribute to the structural integrity of plant cells and influence nutrient uptake. Environmental stressors such as salinity or drought can negatively impact plant growth. Menaquinone has been shown to enhance stress tolerance by modulating metabolic pathways that help plants adapt to adverse conditions. For instance, studies indicate that the synthesis of MK-7 can be stimulated under stress conditions, leading to improved resilience^31,32. Menaquinones are not produced by plants themselves; instead, they are synthesized by certain bacteria that can be found in the soil or associated with plant roots. The presence of beneficial bacteria such as Bacillus subtilis can enhance the availability of MK-7 to plants, thereby promoting their growth and health^31,32.

Mupirocin, which is primarily recognized for its antibacterial properties, showed downregulation in co-culture settings. This reduction suggests a strategic adaptation that may minimize certain defensive responses that could inhibit beneficial interactions with co-cultured organisms. By downregulating mupirocin, plants may foster a more synergistic relationship with other microbes, promoting overall plant health and resilience against pathogens. However, (3S,4 R)-3,4-dihydroxycyclohexa-1,5-diene-1,4-dicarboxylate has limited specific studies available. However, similar metabolites are often associated with antimicrobial properties. This compound may indicate enhanced metabolic pathways that bolster antifungal activity or facilitate plant defense responses during co-culture conditions. Its role underscores the complexity of metabolic interactions that occur within these environments. In addition to their antifungal roles, several metabolites also contribute to plant growth promotion. Siderophores chelate iron from the environment, increasing its bioavailability to plants. This enhanced iron uptake supports plant growth and improves resilience against environmental stressors by ensuring a sufficient nutrient supply³³. The upregulation of metabolites such as menaquinone is indicative of enhanced secondary metabolism pathways that can lead to increased production of growth-promoting substances or antimicrobial compounds beneficial for plants³⁴. This dynamic regulation of metabolic pathways reflects the adaptability and responsiveness during co-culture conditions.

The differential expression of metabolites during co-culture highlights their dual roles in antifungal activity and plant growth promotion, demonstrating the adaptive biosynthetic versatility of B57. The upregulation of compounds such as menaquinone and carbapenem suggests enhanced secondary metabolism, contributing to pathogen inhibition and microbial interactions, while simultaneously supporting plant health through growth-promoting activities. A deeper understanding of their biosynthesis could facilitate bioengineering approaches to enhance production efficiency or design novel derivatives capable of overcoming different plant pathogens. Conversely, the downregulation of metabolites (e.g., mupirocin) may reflect a strategy to minimize antagonism, fostering a cooperative environment within the metabolic interaction systems. These findings underscore the potential of B57 as a bioinoculant for sustainable agriculture, offering innovative solutions for disease management and crop productivity enhancement. The identified metabolites, particularly those with high VIP and log2FC values, could serve as biomarkers for metabolic shifts and as leads for novel antibiotic discovery¹. Moreover, the dynamic regulation of these metabolites points to promising applications in microbial consortia optimization, where metabolic engineering could amplify desired traits, ultimately contributing to more resilient and efficient agricultural systems capable of thriving under challenging conditions.

KEGG metabolic pathways

Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways, metabolic pathway analysis was conducted to interpret the biological relevance of significantly altered metabolites detected through untargeted metabolomics. This approach enabled the identification of enriched biosynthetic and signaling pathways involved in antifungal activity and plant growth promotion. Different metabolic pathways and plant hormone signal transduction were specifically explored using MetaboAnalyst 5.0 and KEGG Mapper to visualize the functional roles of B57-derived metabolites under monoculture and co-culture conditions.

The investigation of detailed metabolomic comparison of B-Fungi and fungi was performed using a combination of Z-score analysis and hierarchical clustering. The analysis highlights the metabolic differences between these groups, identifying specific metabolites and their relative abundances. The individual metabolites are plotted with their corresponding Z-scores (Fig. 6A), differentiating the metabolomic profiles of the B-Fungi (red) and fungi group (blue). A clear distinction in metabolite abundance was observed. For example, metabolites such as ethylglyoxalbis (guanylhydrazone), menaquinone, and veratramine were more abundant in the B-Fungi group, with significantly elevated Z-scores. Several other metabolites, including canthaxanthin and butyric acid, were more abundant in the control group than in the B-Fungi group. The Z-score distribution reflects significant metabolic variation, indicating distinct biochemical processes or environmental adaptations between the two groups. This visualization underscores the role of specific metabolites in differentiating these two fungal-related groups, potentially concerning their metabolic pathways or ecological niches.

Fig. 6: Heatmap analysis of the detected compounds in B57 versus co-culture.

Hierarchical clustering of the detected 48 metabolites (A). The standardized quantitative value of the Z-score for each metabolite classified all metabolic spectra (B). Ordered main matrix heatmap of upregulated compounds across tested groups (C).

The heatmap in Fig. 6B provides a comprehensive visualization of the metabolomic profiles of the two groups. Each column represents a sample, and each row corresponds to a metabolite. The color spectrum provides insights into the expression levels and clustering patterns. Cluster analysis revealed a distinct grouping of B-Fungi and fungi, emphasizing metabolic dissimilarities. The clear separation suggests robust differences in metabolome composition. Metabolites are clustered based on co-expression patterns, with some metabolites consistently expressed at relatively high levels in B-Fungi, while others are predominantly elevated in the fungi group. High variance in metabolite levels reflects biochemical diversity, potentially influenced by genetic, environmental, or functional differences between the two fungal-related groups. The obtained data demonstrates the comparative analysis of KEGG metabolic pathways in B57 under monoculture and co-culture growth conditions, focusing on the top metabolites with the highest number of differential annotations, which could influence plant growth promotion and pathogen inhibition.

The ordered main matrix heatmap showed that B57 generates distinct metabolites under different antagonistic conditions when co-cultured with fungal pathogens, as shown in Fig. 6C. The levels of metabolites vary significantly depending on the interaction type (monoculture vs. co-culture with specific fungi). Many metabolites, such as tryptophyl-Lysine, zeatin, 13,14-dihydro-15-keto-PGF2α, and 1,7-diphenyl-4-hepten-3-one, are present at significantly higher levels in co-culture (e.g., F1-57, F2-57, F3-57, F4-57) compared to monoculture of B57 and individual fungal strains. For instance, tryptophan-lysine and 1,7-diphenyl-4-hepten-3-one were increased in F4-57 co-culture. Also, zeatin drastically increased in F3-57. Certain metabolites that are absent or present in negligible quantities in monoculture conditions appear under co-culture. C20821 (involved in carbapenem biosynthesis), this metabolite showed a massive upregulation in co-culture, particularly in F3-57, compared to negligible levels in monoculture, showing its production is stimulated by fungal interaction. Similarly, C20823 (involved in carbapenem biosynthesis), this compound is not detected in B57 monoculture but is upregulated across co-culture conditions, indicating its inducible production. Menaquinone, which contributes to plant growth and pathogen defense, is highly produced in monoculture but decreases during co-culture. However, its levels remain substantial, particularly in F3-57, indicating its dual role. Some metabolites are downregulated in co-culture, possibly to modulate antagonistic interactions or focus resources on critical antifungal activities. Mupirocin was almost absent in co-culture, suggesting that it may not be critical for fungal suppression in the case of this study. Lumichrome was also significantly reduced in co-culture compared to monoculture, as listed in Supplementary data Table S1 and Fig. S1. The interactions with specific fungi influence metabolite profiles. The 13,14-dihydro-15-keto-PGF2α peak in F4-57 indicates that this metabolite is strongly induced by V. dahlia interactions. However, the content of Tryptophyl-Lysine increased in F3-57, reflecting a tailored metabolic response. B57 adapts its metabolic profile based on the fungal species it interacts with, producing different bioactive metabolites with antifungal or plant-growth-promoting properties. These findings suggest that fungal interactions act as a trigger for the biosynthesis of key secondary metabolites, such as carbapenem, menaquinone, and tryptophyl-Lysine, enhancing the strain’s biocontrol potential of the strain.

Several studies have highlighted the diverse roles of bacterial metabolites as biofungicides, demonstrating their varying effectiveness against different fungal pathogens in antagonistic relationships^12,13,35. For instance, Bacillus velezensis produces lipopeptides (e.g., fengycin and iturin), which have shown significant activity against pathogens such as Ralstonia solanacearum and Fusarium oxysporum³⁶. The mechanisms through which these bacterial metabolites exert their antifungal effects include competition for resources, the production of hydrolytic enzymes, and the secretion of secondary metabolites that inhibit fungal growth^37,38.

Studies have demonstrated that different fungal pathogens exhibit different sensitivity to bacterial metabolites. For instance, Kiesewalter et al.³⁹ concentrated on differences in antifungal metabolites (nonribosomal peptides) produced by B. subtilis isolated from the soil against three phytopathogens (F. oxysporum, F. graminearum, and Botrytis cinerea). The authors found that isolates from the same soil showed different activities against the test fungi and could generate distinct secondary metabolites with chemical variations of B. subtilis in the environment. The results of intraspecies interactions between isolates that coexist in nearby microenvironments point to the influence of accessory biosynthesis gene clusters on the sensitivity to secondary metabolites and their inhibitory potential. The potential for using these bacterial metabolites as biocontrol agents is significant because they inhibit the growth of specific fungal pathogens and promote plant health by enhancing resistance mechanisms within the host plants^35,40. Hence, the effectiveness of bacterial metabolites as biofungicides varies significantly depending on the specific fungal pathogens involved, highlighting the need for tailored approaches in biocontrol strategies.

Tryptophan and arginine metabolism pathways play a pivotal role in the synthesis of secondary metabolites, including indole acetic acid and polyamines, which are important for promoting plant growth and improving stress resilience (Fig. 7). Additionally, bioactive compounds, including alkaloids and flavonoids (8.12%), play roles in plant hormone signaling and pathogen inhibition. The co-culture environment seems to catalyze the production of these defense-related metabolites due to interspecies microbial competition and plant-microbe exchanges. For instance, Anjum et al.⁴¹ identified a total of 73 metabolites in resistant and susceptible tomato plant samples, revealing extensive physiological re-modulations in response to F. oxysporum infection. The functional categorization of these metabolites indicated the activation of signaling pathways and the overproduction of precursor molecules in various carbon cycles upon pathogen perception. These precursor metabolites were predominantly redirected into hormone biosynthesis, phenylpropanoid, and alkaloid biosynthesis pathways. Consequently, the resistant tomato variety produced significantly higher levels of defense-related compounds, including phenolics, terpenoids, and alkaloids, upon pathogen attack. This upregulation of defense-associated metabolic pathways was integral to the tomato plant’s resistance against Fusarium wilt disease.

Fig. 7

Analysis of KEGG metabolic pathways in B57 showing top-generated compounds with the maximum number of differential annotations.

Additionally, tropane, piperidine, and pyridine biosynthesis (1.9%) was a notable presence among the analyzed pathways (Fig. 7). These compounds are known for their antibacterial and antifungal properties⁴², indicating B57’s potential to bolster plant immunity by suppressing pathogens in co-culture settings. Regarding energy and lipid metabolism, arachidonic acid metabolism and methane metabolism pathways (4.14%) were enriched, reflecting enhanced energy-related processes. Arachidonic acid is a known precursor for signaling molecules that mediate plant defense responses⁴³. The metabolic activity in these pathways signals energy allocation toward plant protection and growth under co-culture conditions. However, terpenoid and polyketide metabolism pathways, such as carotenoid biosynthesis, Type II polyketide products, and diterpenoid biosynthesis (7.9%) are significantly represented, reflecting the involvement of B57 in synthesizing biomolecules with antimicrobial and growth-enhancing properties. These compounds support the ability of plants to suppress pathogens and increase stress tolerance and plant developmental processes⁴⁴. With respect to the nucleotide and membrane transport pathways, the purine metabolism (2.1%), and ABC transporter (3.1%) pathways indicate that regulatory activity is essential for microbial nutrient exchange and metabolite secretion between B57 and plants. The nutrient exchange favors the production and transport of bioactive secondary metabolites crucial for plant health.

Pathway enrichment analysis highlighted the metabolic versatility of B57, demonstrating its capacity to produce metabolites involved in both biocontrol and plant growth promotion. Key metabolites mapped to these pathways exhibited significant FCs, underscoring the diverse roles of B57’s metabolic activity (Fig. 8). KEGG pathway enrichment analysis identified carbapenem biosynthesis as a highly enriched pathway, exhibiting a highly rich factor and large marker size, indicating its central role in the metabolic processes of B57, as shown in Fig. 8A. Carbapenems are potent antimicrobial agents that inhibit bacterial and fungal development. Their role in suppressing pathogens is significant, demonstrating B57’s potential as a biocontrol agent. However, enriched glutathione-related pathways indicate the production of metabolites that detoxify reactive oxygen species (ROS) in both bacteria and plants. This phenomenon enhances plant stress resilience and promotes plant-pathogen defense capacity. The activity of the butanoate metabolism pathway may be linked to the synthesis of precursors for plant growth-enhancing metabolites and stress regulators. This highlights B57’s involvement in optimizing conditions for plant development.

Fig. 8: KEGG metabolic pathways analysis for monoculture and co-culture of B57 and the tested fungal strains.

KEGG pathway enrichment analysis (A); fold change (FC) of the top five metabolites (B).

Additionally, pathways supporting plant growth and protection, and the breakdown of fatty acids, support energy production and the biosynthesis of cellular components, indirectly aiding plant growth. Regarding Carbohydrate Digestion and Absorption, this enrichment indicates metabolic adaptations to optimize nutrient utilization, fostering symbiotic microbial and plant interactions. Additionally, the plant hormone signal transduction pathway suggests possible modulation of plant hormonal responses, such as those involving auxins and cytokinins, which are critical for plant development and disease resistance.

On the other hand, metabolite fold change analysis (FCA) revealed that carbapenem biosynthesis was particularly active under co-culture conditions, as evidenced by the upregulation of metabolites, such as tabtoxin biosynthesis intermediate one (carbapenem biosynthesis pathway), which exhibited a positive FC (Fig. 8B). This upregulation supports the production of carbapenem antibiotics, a major contributor to pathogen suppression. Also, in glutathione metabolism, the metabolites Glutathionyl amino propylcadaverine and L-Ornithine exhibit significant upregulation. These findings indicate that increased antioxidant activity during stress-induced or pathogen-exposed conditions helps plants mitigate oxidative damage. However, during fatty acid degradation, palmitaldehyde demonstrated downregulation, suggesting that it is consumed as a substrate to support energy-demanding metabolic processes during co-culture.

In the butanoate metabolism pathway, the presence of up- and downregulated metabolites, including (R)-3-((R)-3-Hydroxybutanoyloxy)butanoate and butyric acid, suggests a dynamic pathway activity that may be associated with providing precursors for the biosynthesis of bioactive compounds. In carbohydrate digestion and absorption, metabolites such as butyric acid are upregulated, demonstrating the importance of energy metabolism in co-culture conditions. Thus, differential changes in metabolite levels reflect metabolic flexibility, enabling B57 to respond to the added demands of co-culture or rhizospheric interactions, which include nutrient competition, signaling, and pathogen suppression. Pathways such as carbapenem biosynthesis and glutathione metabolism highlight the production of antimicrobial and stress-resilience compounds. Carbapenems inhibit critical cellular processes in pathogens⁴⁵, while glutathione supports plant immune responses⁴⁶.

Additionally, enriched pathways such as plant hormone signal transduction, carbohydrate metabolism, and fatty acid degradation reinforce B57’s ability to enhance plant primary and secondary metabolism. These pathways regulate the growth, stress tolerance, and nutrient availability of plants. The differential expression of metabolites in co-culture conditions reflects B57’s capacity to dynamically modify its metabolism to support its role in promoting plant health and suppressing pathogens. Consequently, the enrichment of pathways linked to biocontrol (e.g., carbapenems and fatty acid degradation) and growth promotion (e.g., glutathione and butanoate metabolism) underscores B57’s potential as a bioinoculant. These findings suggest that it can reduce the reliance on synthetic agrochemicals while supporting plant productivity and health.

The enrichment of pathways such as carbapenem biosynthesis, glutathione metabolism, and butanoate metabolism highlights the metabolic flexibility and bioactive potential of B57, as depicted in Fig. 8B, reflecting its dual role in both pathogen inhibition and plant growth enhancement. The identification of differentially expressed metabolites further highlights the ability of this organism to adapt to co-culture conditions, demonstrating its promise as a sustainable and environmentally friendly agricultural biocontrol agent. The data indicated substantial differences in metabolic pathway expression. In co-culture, B57 appears to enhance its metabolic potential by redirecting resources toward pathways synthesizing antimicrobial compounds, strengthening the plant’s ability to inhibit pathogens. Boosting the biosynthesis of compounds involved in plant growth promotion, such as plant hormones and siderophores. These findings suggest that microbial interactions in co-culture promote physiological adaptability and stimulate synergistic effects to protect plants and promote sustainable growth. The KEGG pathway analysis underscores the metabolic versatility of B57 under co-culture conditions. Its enhanced activity in secondary metabolite biosynthesis, amino acid metabolism, and terpenoid/polyketide biosynthesis pathways highlights its potential as a powerful biocontrol agent against plant pathogens and a promoter of plant growth. Several metabolic shifts in co-culture reflect B57’s adaptability and its ability to interact beneficially to improve plant health, making it a valuable candidate for sustainable agricultural practices. These results align with recent studies by Ma et al.²⁵ and Wang et al.⁴⁷, further supporting the relevance of metabolic pathway activation in microbial interactions.

Effects of N. alba B57 metabolites on plant pathogens

In this study, the inhibitory effects of B57 metabolites on four plant fungal pathogens (designated as F1, F2, F3, and F4) were evaluated. The obtained results revealed that the crude extracts of B57 exhibited varying degrees of antifungal activity against the tested pathogens, achieving an average growth inhibition of 30.27% compared with that of the negative control (Fig. 9). Notably, the crude extracts completely inhibited spore germination in all fungal pathogens and induced significant morphological alterations in fungal conidia, underscoring their potent antifungal properties. Similar findings were reported by Cha et al.⁴⁸, who found that Streptomyces S4-7 isolated from Korean soil showed suppressiveness antifungal activity against Fusarium wilt disease. Metabolomic analysis revealed 35 biosynthetic-related gene clusters to produce putative antimicrobial agents. Newitt⁴⁹ found that 17 Streptomyces spp. isolated from wheat roots produce specific metabolites that inhibit Gaeumannomyces tritici (wheat take-all fungus). The authors reported that the genomes of two Streptomyces strains with exceptionally potent antifungal activity were sequenced and that putative antifungal gene clusters were identified.

Fig. 9: Intelligent live digital imaging of the antifungal activity of Nocardiopsis alba metabolites against four fungal pathogens.

Fusarium oxysporum (A), Fusarium moniliforme (B), Fusarium graminearum (C), and Verticillium dahliae Kleb (D) compared to control.

The metabolomic analysis of B57, as shown in Fig. 10, highlighted the biosynthesis of secondary metabolites in B57. These secondary metabolites contribute to essential agricultural processes (e.g., pathogen-inhibiting bioactive molecules). The dityrosine biosynthesis pathway is initiated from D-fructose-6-phosphate and involves intermediates leading to the final product, (-)-Dityrosylphenaline, through the action of DtpA, DtpB, and DtpC enzymes. Ditryptophenaline is an alkaloid metabolite that showed antifungal properties by inhibiting the germination of fungal sclerotia⁵⁰. Additionally, the fumiquinazoline (antifungal agent) pathway incorporates phenylalanine and tryptophan as precursors to complex molecules, such as fumiquinazoline F, C, and D. Their mechanism involves disrupting key fungal metabolic processes, such as inhibition of Na⁺/K⁺-ATPase⁵¹, making them potential candidates for use in agricultural settings to control fungal diseases⁵².

Fig. 10

The metabolomic analysis of the biosynthesis of various secondary metabolites in B57.

Although paerucumarin was reported to be produced by different types of bacterial strains, such as Pseudomonas aeruginosa⁵³. The metabolomic analysis showed that paerucumarin can also be generated by B57 through a series of enzymatic processes originating from tyrosine and transformed into intermediates by specific enzymes, eventually leading to the formation of paerucumarin (Fig. 10). Paerucumarin has antifungal properties and can promote plant growth by producing various growth-promoting substances, such as indole-3-acetic acid (IAA) and gibberellic acid, which increase root development and overall plant vigor. Additionally, it exhibits antifungal activity against several plant pathogens, improving crop yields through dual action⁵⁴.

Staphyloferrins are synthesized via pathways involving precursors including serine, glutamate, and ornithine. The conversion of these compounds involves multiple enzymes such as L-2,3-diaminopropionate synthase and various aminotransferases, which are modified by hydroxylation and cyclization. These reactions produce siderophores (iron-chelating compounds), such as L-2,3-diaminopropionate and ultimately Staphyloferrin A and Staphyloferrin B. The biosynthesis of Staphyloferrin A utilizes 2-oxoglutarate and glutamate and produces NS-Citryl-D-ornithine, illustrating the strain’s continued emphasis on iron acquisition and pathogen suppression. Staphyloferrin is a siderophore that plays a crucial role in iron acquisition for bacteria. While primarily known for its role in microbial iron transport, it may also indirectly promote plant growth by increasing the availability of iron in the soil, which is essential for many physiological processes in plants⁵⁵. Its direct antifungal properties are less well documented but may contribute to overall soil health and plant resilience against fungal pathogens.

Moreover, cyclooctatin is produced through cyclohexanone biosynthesis pathways involving precursors (e.g., cyclooctat-9-en-7-ol). Cyclooctatin is a cyclic peptide that is an important plant growth regulator and antimicrobial agent, providing dual benefits of enhancing plant development while suppressing pathogen activity⁵⁶. However, lovastatin biosynthesis showcases another aspect of B57’s antimicrobial potential. The pathway utilizes malonyl-CoA to produce lovastatin, a known polyketide that can inhibit fungal growth by targeting critical metabolic processes. Lovastatin is a statin that acts by inhibiting 3-hydroxy-3-methylglutaryl-coenzyme A reductase (a rate-limiting enzyme of the mevalonate pathway), as well as other statins have activity towards several pathogens⁵⁷. These findings further emphasize the strain’s role in biological control.

The pathway for grixazone B biosynthesis incorporates aspartate and leads to metabolites that possess antioxidant properties, as depicted in Fig. 10. These compounds may help mitigate oxidative stress during the fungal attack, bolstering plant resilience. Le Roes-Hill et al.⁵⁸ reported that the grixazones produced by Streptomyces griseus subsp. griseus is divided into grixazone A, which has an aldehyde at position 8, and grixazone B, which has a carboxyl group. Few reports have discussed the bioactivity of grixazone in general. However, grixazone B has antifungal, antiviral, antihelminthic, and lipooxygenase inhibitory activities⁵⁸. While there are no studies on its role as a plant growth promoter, its effectiveness in controlling fungal pathogens suggests that it could indirectly support plant health by minimizing disease impact.

L-B-ethynylserine biosynthesis is another important pathway featured in the metabolomic analysis of B57. This pathway uses lysine as a precursor, leading to the production of 4-chloro-L-lysine before resulting in L-B-ethynylserine. L-B-ethynylserine is noteworthy due to its potential effects on microbial communication and stress responses. LB-ethynylserine is a non-proteinogenic L-α-amino acid that is L-propargylglycine, which carries a hydroxy group at the 3R position. It has a role as an antimetabolite, an antimicrobial agent. It is a terminal acetylenic compound and a non-proteinogenic L-α-amino acid. It is functionally related to L-propargylglycine. It is a tautomer of an LB-ethynylserine zwitterion⁵⁹. However, more research is needed to fully understand its mechanisms and efficacy as a plant growth promoter. Lastly, the biosynthesis of aerobactin, which uses lysine as a precursor, results in compounds that increase nutrient availability while inhibiting competition from pathogens. Aerobactin is a siderophore that facilitates iron uptake in bacteria and may improve soil fertility by increasing the bioavailability of iron to plants⁶⁰. Its role as an antifungal agent is not well established, but it could contribute to overall soil health and support plant growth. Thus, these compounds exhibit significant potential both as antifungal agents and as plant growth promoters through various mechanisms, including nutrient solubilization, pathogen inhibition, and the enhancement of beneficial microbial activity in the rhizosphere. Further research into their specific mechanisms will help optimize their use in agricultural practices.

The study highlighted the remarkable ability of N. alba B57 to produce a diverse range of antibiotics (Fig. 11) through well-defined biosynthetic pathways, showcasing its potential as a producer of bioactive compounds for agricultural and antimicrobial applications. These antibiotics are synthesized from various metabolic precursors, including glucose, pyruvate, and amino acids such as tyrosine and serine, reflecting the metabolic versatility of the strain. The study emphasizes the strain’s capacity to combat bacterial, fungal, and protozoal pathogens through its diverse antimicrobial arsenal. Among the key biosynthetic pathways, kanosamine biosynthesis is initiated by intermediates such as 3-dehydro-D-glucose, catalyzed by enzymes like transaminase (EC 2.6.1.104) and phosphatase (EC 3.1.3.92). Kanosamine is an effective antibiotic that inhibits fungal strains, including Saccharomyces cerevisiae and human pathogenic fungi⁶¹. Similarly, aurachins A-D, synthesized from D-fructose-6-phosphate through the intermediate anthranilate, act as inhibitors of bacterial electron transport chains by targeting cytochrome enzymes, significantly disrupting energy metabolism. Aurachins also exhibit antifungal and antiprotozoal activity, showcasing their broad-spectrum potential⁶².

Fig. 11

The metabolomic analysis of the biosynthesis of antibiotics by B57.

Another critical pathway is bacilysin biosynthesis, which begins with pyruvate and involves intermediates such as 4-hydroxy-3-hexaprenoyl-AMP. Bacilysin disrupts bacterial cell wall synthesis, granting B57 a competitive advantage in microbial environments⁶³. Likewise, puromycin biosynthesis utilizes tyrosine as a precursor to produce highly bioactive compounds such as N-acetyl-O-methyl-puromycin⁶⁴. Singh et al.⁶⁵ reported that puromycin disrupts microbial protein synthesis and is effective against resistant strains, including Escherichia coli, Klebsiella pneumoniae, and Staphylococcus spp. Dapdiamide biosynthesis is another notable pathway in B57, producing dapdiamides A, B, and C from serine and glutamate. These compounds, derived through catalytic steps involving enzymes such as transferase (EC 2.5.1.140), exhibit antibacterial activity, particularly against Erwinia amylovora⁶⁶. Similarly, fosfomycin biosynthesis starts with phosphoenolpyruvate and glyceraldehyde-3-phosphate and involves enzymes like isomerase (EC 5.4.2.5). Fosfomycin irreversibly inhibits MurA, a critical enzyme in bacterial cell wall synthesis, making it highly effective against Gram-positive pathogens⁶⁷. Additionally, the study identifies the biosynthesis of cremomycin and pentalenolactone. Cremomycin is synthesized through nitro intermediates, although its bioactivity remains underexplored. Pentalenolactone, on the other hand, targets microbial energy metabolism through its epoxylactone moiety, demonstrating activity against bacteria, fungi, and protozoa⁶⁸. Furthermore, roseoflavin production in B57 utilizes FMN as a precursor, a compound previously reported only in Streptomyces davawensis and Streptomyces cinnabarinus, with significant potential as a broad-spectrum antibiotic⁶⁹. Lastly, cycloserine biosynthesis involves the conversion of arginine and ornithine into intermediates that disrupt bacterial peptidoglycan synthesis⁷⁰

These diverse biosynthetic pathways underscore B57’s metabolic adaptability and its capacity to produce clinically and agriculturally valuable antibiotics. Compounds such as kanosamine, fosfomycin, and puromycin target critical bacterial processes such as the cell wall and protein synthesis, whereas other compounds, including aurachins and cremomycin, extend their activity to fungal and protozoal pathogens. Its ability to upregulate multiple pathways in response to environmental stress makes B57 a promising candidate for biotechnological applications, particularly in addressing antibiotic resistance and enhancing sustainable agricultural practices.

Effects of N. alba B57 metabolites on plant growth

To investigate the effects of N. alba B57 metabolites on plant growth, this study evaluated their impact on Lolium perenne (monocot) and Amaranthus retroflexus (dicot) at varying concentrations (100, 500, 1000, and 2000 µg/mL). Growth parameters, including root length (RL) and shoot length (SL), were measured to assess species-specific and concentration-dependent responses (Fig. 12).

Fig. 12: Effect of different concentrations of B57 metabolites on plant growth.

A Growth response of Lolium perenne. B Root and shoot length variations in Amaranthus retroflexus compared to control (CK).

In L. perenne, B57 metabolites significantly enhanced RL and SL compared to the control (p = 0.0262 and p = 0.0341, respectively). At 100 µg/mL, RL and SL increased to 4.13 cm and 3.75 cm, respectively, compared to the control values of 3.62 cm (RL) and 3.17 cm (SL). The highest growth stimulation was observed at 1000 µg/mL, with RL and SL reaching 4.74 cm and 4.20 cm, respectively (Fig. 12A). However, at 2000 µg/mL, both RL and SL decreased slightly, suggesting a threshold beyond which the stimulatory effects diminished, possibly due to metabolite-induced phytotoxicity or osmotic stress. This dose-dependent response aligns with the hormesis model, where low to moderate concentrations promote growth, while higher concentrations may inhibit it.

In contrast, A. retroflexus exhibited a different response pattern. At 100 µg/mL, RL and SL increased to 1.64 cm and 1.57 cm, respectively, compared to the control values of 1.40 cm (RL) and 1.42 cm (SL). Growth peaked at 500 µg/mL, with RL and SL reaching 2.11 cm and 1.88 cm, at P = 0.0127 and P = 0.0256, respectively (Fig. 12B). However, at higher concentrations (1000 and 2000 µg/mL), RL and SL declined, indicating potential allelopathic inhibition due to toxic metabolite accumulation or metabolic disruption. Comparative analysis revealed that L. perenne exhibited greater tolerance to higher concentrations of B57 metabolites than A. retroflexus. For instance, at 2000 µg/mL, L. perenne maintained RL and SL values of 4.62 cm and 4.19 cm, respectively, while A. retroflexus showed significantly lower values (1.91 cm RL and 1.90 cm SL). These species-specific responses highlight the varying tolerance levels of target plants and the specificity of allelopathic interactions. The findings suggest that B57 metabolites could serve as natural growth regulators with applications in sustainable agriculture, such as weed control or crop enhancement.

Several pathways involved in plant hormone signal transduction in N. alba B57 were illustrated in Fig. 13, providing a comprehensive overview of multiple pathways that regulate plant growth, stress response, and metabolic adaptations. Each pathway is associated with specific plant hormones that initiate biochemical cascades, leading to gene expression changes and physiological changes. Auxin is a plant growth regulator and plays a role in almost every aspect of plant growth and development. IAA is the most abundant natural auxin and can execute the majority of auxin-related regulatory actions in plants⁷¹. Metabonomic analysis showed that B57 auxin signal transduction pathways can play a central role in regulating cell enlargement and overall plant growth. B57’s auxin is synthesized from tryptophan metabolism and is transported into cells via the AUX1 receptor. The downstream signaling steps involve interactions with TIR1 receptors and ARFs (auxin response factors), which activate the transcription of auxin-related genes (e.g., GH3 and SAUR) necessary for plant growth.

Fig. 13

The signaling pathways in B57 involved in plant hormone signal transduction that regulate plant growth and metabolic adaptations.

Cytokinin signaling, as shown in Fig. 13, can regulate cell division and shoot development through a two-component signaling system. The cytokinin receptor (CRE1), upon ligand (zeatin) binding, activates Arabidopsis histidine phosphotransfer protein (AHP), which is translocated to the nucleus and activates B-ARR (type-B response regulators). The transcription of target genes by A-ARR (type-A ARR) controls critical developmental processes. Cytokinins also interact antagonistically with auxins to maintain root-shoot balance. Also, gibberellins (GAs) are vital for stem elongation and germination. Additionally, gibberellin binds to the Gibberellin Insensitive Dwarf1 (GID1) receptor, resulting in the degradation of the DELLA (domain family of proteins), which is a growth suppressor⁷². This degradation releases transcription factors that promote plant growth-related gene expression. Ubiquitin-mediated proteolysis ensures the removal of DELLA when gibberellin levels rise, providing an efficient regulatory mechanism to modulate plant height and developmental transitions⁷². Similarly, the abscisic acid (ABA) pathway, where ABA regulates stomatal closure and seed dormancy, occurs, particularly under stress conditions (e.g., drought). ABA binds to PYR/PYL receptors, leading to the inhibition of PP2C phosphatases. This allows the activation of SnRK2 kinases, which phosphorylate transcription factors, such as ABF (ABA-responsive element binding factors), triggering the expression of stress-response genes. This pathway plays a critical role in plant survival under adverse conditions.

The metabolomic analysis showed that ethylene signaling involves ETR1 and downstream components such as EIN2 and ERF1/2, controlling processes like fruit ripening, senescence, and environmental adaptability⁷³. The pathway also integrates environmental and mechanical stress, emphasizing its role in environmental adaptability and developmental regulation. Additionally, N. alba B57 metabolic analysis showed that brassinosteroids influence cell elongation and division through the receptor kinase proteins BRI1 and BAK1. Upon ligand binding, a cascade involving BSU1 phosphatase and BIN2 kinase leads to the dephosphorylation and activation of transcription factors, such as BZR1/2. These transcription factors regulate genes responsible for elongation and division, contributing to enhanced growth⁷⁴. Additionally, the metabolomic analysis (Fig. 13) showed that jasmonic acid primarily mediates stress responses and senescence and regulates secondary metabolite production. Jasmonoyl–isoleucine (JA–Ile) conjugate binds to COI1 receptors, which target JAZ repressors to facilitate stress responses, defense, and secondary metabolite production⁷⁵. Moreover, salicylic acid (SA), a key player in plant immunity, regulates systemic acquired resistance (SAR) by activating NPR1 and TGA transcription factors to induce pathogenesis-related proteins. It also enhances photosynthesis and redox homeostasis while modulating hormonal crosstalk with JA, ethylene, and ABA to improve stress tolerance^76,77. These pathways, triggered by pathogen invasion, drive SA synthesis and subsequent conjugation into biologically active or inactive forms⁷⁸.

The findings highlight the critical role of N. alba B57 in regulating plant hormone signaling pathways, which are essential for plant development. Through intricate signaling networks, N. alba B57 facilitates plant bioprocesses to ensure a balanced and adaptive response to environmental challenges while promoting healthy plant development. The ability of N. alba B57 to modulate these hormone pathways underscores its potential as a valuable tool in sustainable agriculture. Thus, N. alba B57 can contribute to improving crop yield and environmental sustainability. Further research into these pathways can unlock innovative applications in agriculture, such as developing stress-tolerant crops and optimizing plant performance under changing climatic conditions.

In conclusion, this study highlights the potential of Nocardiopsis alba B57 as an effective biocontrol agent and plant growth promoter, capable of producing antifungal and growth-enhancing metabolites. Metabolomic analyses revealed its ability to modulate key pathways under co-culture conditions, leading to the synthesis of bioactive compounds that suppress pathogens and enhance plant resilience. These findings support B57 as a sustainable alternative to chemical fungicides, with future research needed to optimize its application and assess long-term impacts on soil and crop health.

Methods

Nocardiopsis alba B57 crude extract preparation and fermentation

The endophytic actinobacterial strain N. alba B57 (Accession No. MN688677) was isolated and identified in our previous study¹⁵ from T. roseus obtained from Xinjiang, China. To prepare B57 for fermentation, a single colony was cultured in the International Streptomyces Project-2 (ISP2) broth medium. The cultures were incubated in 500 mL flasks under continuous shaking at 28 °C and 200 rpm for 21 days⁷⁹. Similarly, fungal pathogens were cultured individually on potato dextrose agar (PDA) for 6 days. A 5 mm mycelial disc from each fungal culture was then transferred into a fresh ISP2 medium, where they were incubated for 21 days under the same conditions. For co-culture experiments, B57 was first pre-cultured in a modified liquid ISP2 medium for 24 h. Subsequently, a 5 mm mycelial disc from each fungal strain was introduced into 500 mL flasks containing the modified ISP2 medium. These co-culture flasks were continuously incubated for 21 days at 200 rpm and 28 °C.

In large-scale fermentation setups, the fermentation broth was filtered using Whatman No. 1 filter paper to separate the biomass, and the filtrate was then centrifuged for 15 min at 10,000 rpm. To extract bioactive metabolites, the supernatant was subjected to a three-step liquid-liquid extraction process using ethyl acetate (1:1; v/v). The produced extracts were filtered under reduced pressure using a rotary vacuum evaporator (N-1300, EYELA, Ailang Instrument Co., Ltd., Shanghai, China) at 40 °C to be concentrated, following Zhang et al.³⁸. The crude extracts were subsequently stored for further analysis.

Nocardiopsis alba B57 metabolite extraction

Nocardiopsis alba B57 metabolites were extracted and analyzed using a Waters Acquity I-Class PLUS ultra-high-performance liquid chromatography (UPLC) system coupled with a Waters Xevo G2-XS QTOF high-resolution mass spectrometer. The separation process was achieved using a Waters Acquity UPLC HSS T3 column (1.8 μm, 2.1 × 100 mm) at 35 °C, with a 0.3 mL/min flow rate. For positive ion mode, mobile phase A consisted of 0.1% formic acid in water, while mobile phase B was a mixture of acetonitrile and 0.1% formic acid. The same mobile phases were used for the negative ion mode. The gradient elution program was designed as follows: the initial phase (30 s) consisted of 90% mobile phase A. This condition was maintained until 7 min, after which phase A was reduced to 0% between 7- and 8.5 min. Re-equilibration to 90% phase occurred between 8.6 and 10 min. A volume of 1 μL as the injection volume of each sample was set to ensure process accuracy⁴⁷.

Nocardiopsis alba metabolites identification

The liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis was conducted by a high-resolution mass spectrometer (Waters Xevo G2-XS QTOF) operating in MSe mode. The low collision energy was adjusted at 2 V, and the high collision energy was adjusted from 10 to 40 V. A scanning frequency of 0.2 s per mass spectrum ensured comprehensive data collection. Data acquisition was managed and performed via MassLynx v4.2 software provided by Waters Corporation. The electrospray ionization (ESI) source parameters included a capillary voltage of +2000 V for positive ion mode and −1500 V for negative ion mode. The cone voltage was set at 30 V, with the ion source temperature at 150 °C. For desolvation, the gas temperature was held at 500 °C, with desolvation and backflush gas flow rates of 800 and 50 L/h, respectively. The obtained data were interpreted via Progenesis QI software (v3.0). This software facilitated peak extraction, alignment, and other data processing tasks. Metabolite identification was conducted by referencing the METLIN database and Biomark’s custom-built library. To ensure accuracy, theoretical fragment matches and mass deviations were validated within a threshold of 100 ppm. This rigorous approach ensured the reliable identification of the metabolites present in the samples.

Metabolomic and pathway analyses

The original peak area data were normalized to the total peak area to ensure consistent and comparable analysis. Subsequently, advanced statistical methods, including PCA and SRC analysis, were applied to evaluate sample repeatability within groups and the quality control samples. The identified metabolites were classified and mapped to metabolic pathways using the KEGG database. Grouping information was utilized to calculate FC, and t-tests were carried out to detect the statistical significance (p-value) of changes in compound abundance. PCA was implemented following methodologies described in previous studies^21,79,80. Multivariate statistical analysis, including PCA and hierarchical clustering, was carried out using MetaboAnalyst 5.0. Heatmaps and SRC coefficient matrices were generated to visualize the relationships among samples. For supervised analysis, OPLS-DA modeling was applied using the R package ropls (v3.19). The reliability of the OPLS-DA model was verified through 200 permutation tests. VIP scores were determined using multiple cross-validation methods. Differentially abundant metabolites were selected using a comprehensive approach that incorporated fold changes (FC >1), statistical significance (p < 0.01), and VIP scores (VIP >1).

Enriched pathways for these metabolites were identified using KEGG, with significance determined via a hypergeometric distribution test. Potential biomarkers were identified, and associated pathways were analyzed using MetaboAnalyst 4.01 to further explore metabolic insights. In addition, Spearman’s correlation analysis was employed to investigate metabolite relationships, providing deeper insights into the underlying metabolic networks⁸¹.

Antimicrobial activity of crude extracts against fungal pathogens

To evaluate the antifungal potential of crude extracts from B57, four fungal pathogens served as representative organisms for evaluating antifungal activity, as listed in Table 1. B57 crude extract inhibitory effects on the spore germination of fungal pathogens were tested using a modified protocol reported by Abdelshafy Mohamad et al⁸². Briefly, the fungal strains were grown on PDA for 6 days to ensure adequate mycelial development. A 5 mm mycelial disc was positioned at the center of a fresh PDA plate (6 cm). Sterile filter paper discs, 5 mm in diameter, were autoclaved at 121 °C for 30 min. These discs were loaded with bioactive metabolites-containing crude extracts and placed equally on each plate. The plates were sealed with parafilm to maintain humidity and incubated at 26 ± 2 °C for 7 days. The morphological response of Fusarium spp. and Verticillium dahliae Kleb was observed under a laser microscope (Olympus SZX2-ILLT, Japan) at different magnifications. Plates with pathogenic fungi alone served as a control.

Table 1 Plant fungal pathogens were used to assess the antifungal potential of B57 crude extract in the present study

Fungal growth inhibition was observed and quantified by calculating the inhibition zone (IZ) diameter according to the following Eq. (1)⁸³

$$\mathrm{Inhibition\; percentage}\,\left( \% \right)=\frac{\mathrm{CD}-\mathrm{Ct}}{\mathrm{CD}-{\rm{D}}0}{\rm{X}}100$$

(1)

where CD is the diameter of the control fungal colony, Ct is the diameter of the tested fungal colony, and D0 is the disc diameter (5 mm).

Growth-promoting effects of N. alba B57 crude extracts

The allelopathic potential of B57 crude extracts was assessed on L. perenne (monocot) and A. retroflexus (dicot) seedlings. Seeds were surface sterilized with 0.5% HgCl₂ to eliminate contaminants. Crude extracts of B57 were dissolved in ethyl acetate to prepare concentrations of 100, 500, 1000, and 2000 μg/mL. Petri dishes lined with filter paper were treated with these solutions, followed by complete evaporation of the solvent. Subsequently, 2 mL of distilled water was added to each dish, and 10 seeds of either L. perenne or A. retroflexus were placed on the moistened filter paper. Controls were treated with distilled water under identical conditions. All dishes were incubated in darkness at 25 °C for 5 days to facilitate seedling growth. Shoot and root lengths were measured to assess the growth-promoting effects of the extracts. Each treatment was performed in triplicate, analyzing 30 seeds per condition (n = 30), providing valuable insights into the biostimulant potential of B57 extracts.