Biocontrol Potential of Bacillus subtilis SV108 Against Aspergillus carbonarius and Botrytis cinerea of Grapevine

Biocontrol Potential of Bacillus subtilis SV108 Against Aspergillus carbonarius and Botrytis cinerea of Grapevine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biocontrol Potential of Bacillus subtilis SV108 Against Aspergillus carbonarius and Botrytis cinerea of Grapevine Simin Sabaghian, Giacomo Braschi, Davide Gottardi, Lorenzo Siroli, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8535314/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract The increasing restriction of chemical fungicides has intensified the search for environmentally sustainable alternatives for grapevine disease management. In this study, we evaluated the biocontrol potential of Bacillus subtilis SV108, an endophytic strain isolated from grape berries, against major grapevine fungal pathogens. The antifungal activity of SV108 cell-free supernatant (CFS) was assessed in vitro against a panel of phytopathogenic fungi, revealing strong and concentration-dependent inhibition, particularly against Botrytis cinerea and Aspergillus carbonarius . These pathogens were further evaluated using a detached grape berry assay, where SV108 treatment significantly reduced lesion development compared with untreated controls, confirming efficacy under fruit-based conditions. To elucidate the mechanisms underlying antifungal activity, volatile organic compounds (VOCs) produced by SV108 during pathogen interaction were analyzed using SPME-GC-MS. SV108 emitted a complex blend of bioactive VOCs, including alcohols, aldehydes, ketones, organic acids, phenols, and pyrazines, many of which are known for their antimicrobial properties. Principal component analysis demonstrated distinct VOC profiles between bacterial strains and fungal pathogens, with SV108 showing similarities to the established biocontrol strain Bacillus amyloliquefaciens AG1. Qualitative proteomic analysis of the active antifungal fraction identified peptides homologous to non-ribosomal peptide synthetases associated with iturin and mycosubtilin biosynthetic pathways, as well as proteins linked to siderophore production and secondary metabolite biosynthesis. The results indicate that B. subtilis SV108 suppresses fungal growth through a multi-modal mechanism involving both soluble antifungal metabolites and volatile emissions. These findings support the potential application of SV108 as a sustainable biocontrol agent for grapevine disease management, particularly in postharvest and integrated disease control strategies. Bacillus subtilis Grapevine antifungal activity volatile organic compounds Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Due to increasing concerns over the adverse effects of chemical fungicides on human health and the environment, many of these compounds are being progressively restricted or banned (Deresa & Diriba, 2023 ). Consequently, research efforts have increasingly focused on developing natural and environmentally sustainable alternatives (Grzegorczyk et al., 2017 ). Among these, the use of biocontrol agents has emerged as a promising and eco-friendly strategy, with their efficacy extensively documented in the literature in managing grapevine pathogens (Altieri et al., 2023 ; Carmona-Hernandez et al., 2019 ). Biocontrol agents offer two main advantages over traditional chemical approaches for managing grapevine fungal diseases: (i) they can be isolated from the same ecological niche as crop pathogens without negatively impacting the safety or quality of the final product; and (ii) their use can reduce the development of pathogen resistance to synthetic agents commonly used in crop disease management. Most biocontrol agents produce antibacterial, antifungal, and other secondary metabolites that inhibit the growth of plant pathogens such as bacteria and molds (Keswani et al., 2020 ). Among the various biocontrol agents tested for managing fungal diseases, Bacillus subtilis has emerged as a particularly promising solution for in-field control of grapevine and other crop diseases (Ongena & Jacques, 2008 ). B. subtilis strains are known for their diverse metabolic capabilities, environmental adaptability, and effectiveness in suppressing both bacterial and fungal pathogens, as demonstrated in vitro and field trials (Pertot et al., 2017 ). Approximately 4–5% of the Bacillus genome is dedicated to genes involved in the production of antimicrobial compounds. These genes are primarily associated with the biosynthesis of antifungal compounds, including bioactive antimicrobial lipopeptides, volatile organic compounds (VOCs), polyketides, and bacteriocins. Such compounds can directly inhibit the growth of plant pathogens by disrupting their cell membranes and/or by eliciting plant defense responses against infections (Farace et al., 2015 ) The antimicrobial lipopeptides produced by B. subtilis are generally classified into three major families: surfactins, fengycins, and Iturins (Ongena & Jacques, 2008 ). These lipopeptides share a conserved backbone structure comprising a cyclic heptapeptide, with the Iturin family (including Iturins A, B, and C) exhibiting particularly strong in vitro antifungal activity against a broad spectrum of fungi and yeasts due to their membrane-permeabilizing effects (Ongena & Jacques, 2008 ). However, the specific antimicrobial profile of B. subtilis varies depending on the strain and environmental or process-related conditions. This research evaluated a Bacillus subtilis strain SV108, isolated from grape berries, for its potential as a biocontrol agent against two major grapevine fungal pathogens. The objectives were to assess the antagonistic potential of SV108 through in vitro assays, characterize the volatile organic compounds (VOCs) emitted during bacterium-fungus interactions, and analyze the CFS to identify key bioactive compounds associated with mycelial growth inhibition. Also, a proteomic analysis was performed to uncover the presence of antimicrobial peptides and explore secondary metabolite biosynthetic pathways. 1. Materials and methods 1.1 Strain and culture conditions Bacillus subtilis (Cohn 1872) strain SV108, obtained from the microbial collection of the Department of Agricultural and Food Sciences, University of Bologna (Italy), isolated from the experimental vineyard of the University of Bologna (Faenza, Italy), was used in this study. This strain was selected as the most effective among various biocontrol agents previously tested against grapevine fungal pathogens (unpublished data). B. subtilis SV108 was re-cultured on Malt Extract Agar (MEA; Oxoid, Thermo Fisher, Milan, Italy) and incubated overnight at 37°C. Bacillus amyloliquefaciens ( B. amyloliquefaciens) strain AG1, provided by the Department of Scienze Agrarie e Forestali, University of Palermo (Italy), was used as a positive control (Alfonzo et al., 2012 ). Antagonism assays were performed against a panel of grapevine fungal pathogens included Botrytis cinerea and Phaeomoniella chlamydospora ( P. chlamydospora) (provided by the Department of Integrated Pest Management of Mediterranean Fruit trees and Vegetable Crops, CIHEAM Bari, Italy) Fusarium oxysporum ( F. oxysporum) (isolated from the grapevine rhizosphere), Alternaria alternata ( A. alternata ) (obtained from grapevine leaves), Verticillium dahliae ( V. dahliae ) (isolated from decayed grapevine tissue), and Aspergillus carbonarius (A. carabonarius) and Aspergillus ochraceus ( A. ochraceus ) (both isolated from grapes). All fungal isolates were maintained on MEA and incubated at 25°C for two weeks before use. 1.2 Antifungal Activity of Bacillus subtilis SV108 Cell-Free Supernatant The antifungal activity of B. subtilis SV108 CFS against B. cinerea , P. chlamydospora , F. oxysporum , A. alternata , A. carbonarius , and A. ochraceus was evaluated in vitro using the dual-culture method described by Zhang et al., 2017. Briefly, fungal colonies were grown on MEA plates at 25°C for 7 days. Spores were harvested with 5 mL of 0.9% NaCl, yielding ~ 100–120 spores/mL. For each species, 1 mL of spore suspension was mixed with 14 mL of molten MEA (40°C) in a sterile Petri dish and gently agitated. After solidification, a 5 mm well was punched in the center and filled with 50 µL of B. subtilis SV108 CFS. The CFS was prepared following the extraction protocol described by(Leelasuphakul et al., 2008 , with slight modifications. In this method, Pure colonies of B. subtilis SV108 grown on MEA at 30°C for 24 h were used to inoculate 300 mL Malt Extract Broth. After incubation, cultures were filtered (0.2 µm) to obtain CFS, which was extracted twice with ethyl acetate (1:1, v/v). The combined organic phases were dried over anhydrous Na₂SO₄, evaporated under vacuum at 40°C, washed with hexane, redissolved in DMSO, and stored at -80°C. Extraction yield was determined after drying and expressed as mg/mL of the original supernatant. MEA plates were incubated at 25°C for the antifungal assay for 6 days. After incubation, the antifungal activity of B. subtilis SV108 was assessed by measuring the inhibition radius (IR, in mm) using a caliper. Results were expressed in arbitrary units (AU/mL) according to the formula proposed by Alfonzo et al. ( 2012 ). AU/mL = \(\:\frac{IR\:\left(mm\right)}{well\:capacity\:\left(mL\right)}\times\:free\:supernatant\:concentration\:(mg/mL)\) Where: IR (mm) = Inhibition Radius in millimeters (mm), Well capacity (mL) = Volume of supernatant added, and CFS concentration (mg/mL) = Concentration of extract dissolved in DMSO. Each antifungal test was conducted in triplicate against all selected grapevine fungal pathogens. Negative controls consisted of plates inoculated with 0.9% (w/v) NaCl saline solution without bacterial supernatant. Based on the results of the in vitro plate assays, B. cinerea and A. carbonarius exhibited the greatest sensitivity to SV108, as evidenced by markedly larger inhibition zones and higher inhibition rates compared with the other tested pathogens. These two fungi were therefore selected for subsequent, more detailed evaluations, including quantitative inhibition analyses and detached grape berry assays, to assess the biocontrol efficacy of SV108 under fruit-based conditions. To evaluate concentration-dependent antifungal activity, SV108 CFS was tested as a two-fold serial dilution series prepared in the same solvent system as the extract (DMSO). Treatments corresponded to the following dilution levels: 1/64 (treatment 1), 1/32 (treatment 2), 1/16 (treatment 3), 0× solvent-only negative control (treatment 4), 1/8 (treatment 5), 1/4 (treatment 6), and undiluted CFS (1×; treatment 7). For each plate, 50 µL of the corresponding dilution was added to the central well. Each treatment–pathogen combination was tested in triplicate (n = 3). The negative control consisted of the solvent used for dilutions (treatment 4) without SV108 CFS. Data are presented as mean ± SD. Differences among treatments were assessed by one-way ANOVA followed by Tukey’s HSD test (p < 0.05). 1.3 Detached Berry Antifungal Assay The antagonistic activity of B. subtilis SV108 against A. carbonarius and B. cinerea was evaluated using a detached grape berry assay adapted from Pantelides et al. (2015), with modifications. Briefly, SV108 was grown in Malt Extract Broth (Oxoid, Thermofisher, Milan, Italy) (or an equivalent bacterial growth medium) at 30°C for 24–48 h. Bacterial cultures were adjusted to approximately 10⁸ CFU/mL prior to application. Mature grape berries (cv. Red Globe) were detached from bunches and surface-disinfected using 1% commercial sodium hypochlorite for 15 min, followed by rinsing with sterile deionized water and air-drying under sterile conditions. Berries were then immersed in the SV108 culture for uniform coating. After 4 h incubation at 25°C, berries were air-dried, and a standardized wound (~ 2 mm diameter) was made on each berry using a sterile needle. For pathogen inoculation, each wound was spot-inoculated with 20 µL of a conidial suspension of either A. carbonarius (≈ 10⁶ conidia/mL) or B. cinerea (≈ 10⁵–10⁶ conidia/mL). Inoculated berries were placed in humid chambers (e.g., sealed boxes with moist sterile paper) to maintain high relative humidity and incubated under pathogen-favorable conditions (25°C for A. carbonarius for 10 days; 20–22°C for B. cinerea for 5–7 days, or until clear symptom development in controls) (Fig. 1 ). Disease development was monitored daily. Antifungal efficacy was quantified by measuring lesion/mycelial growth diameter (ø, mm) using a digital caliper. Each treatment consisted of three biological replicates, and the experiment was repeated as necessary. One-way ANOVA analyzed data, and mean comparisons were performed using Tukey’s HSD test (p < 0.05). 1.4 Volatile Organic Compounds (VOCs) Samples were initially prepared by incubating B. subtilis SV108 and B. amyloliquefaciens AG1, alone and in combination with B. cinerea and A. carbonarius , for 48 h at 25°C in MEB. The two species of fungi were selected due to their strong inhibition by SV108. The composition of VOCs was analyzed on the headspace of the vials using solid-phase microextraction combined with GC-MS (SPME-GC-MS), as described by Gottardi et al. ( 2023 ). A 75 µm CAR/PDMS fiber was used for VOC collection. Five milliliters of culture were incubated at 45°C, and the fiber was exposed to the headspace for 30 minutes. Desorption occurred at 250°C for 10 minutes. VOCs were analyzed with an Agilent 6890N GC-MS using a J&W CP-Wax 52 column, with helium as the carrier gas. Compounds were identified via the NIST 11 database and quantified using 4-methyl-2-pentanol (final concentration: 6 mg/L) as the internal standard, reported in ppm equivalents. All experiments were run in triplicate. 1.5 Protein Extraction and SDS-PAGE Protein extraction and separation were performed using tricine-sodium dodecyl sulphate-polyacrylamide gel electrophoresis (tricine-SDS-PAGE) as described by Cao et al. ( 2013 ), optimized for high-resolution separation of low-molecular-weight peptides. First, gel pieces were soaked in 50 µL ultrapure water for 30 min, cut into 1–2 mm fragments, and transferred to microcentrifuge tubes. For decolorization, 1 mL of 50 mM NH₄HCO₃:acetonitrile (1:1, v/v) was added, vortexed for 10 s, incubated at 37°C for 30 min, then centrifuged and dried. To dehydrate, 500 µL acetonitrile was added until the gel turned white, and tubes were air-dried under a clean bench for 10 min. For reduction, gel pieces were covered with 10 mM DTT (1 M DTT:25 mM NH₄HCO₃ = 1:100) and incubated at 56°C for 1 h. After cooling, the solution was replaced with 55 mM IAM (0.55 M IAM:25 mM NH₄HCO₃ = 1:10), incubated at room temperature for 45 min in the dark. Gels were then washed twice with 500 µL decolorizing solution and once with 500 µL acetonitrile, vortexed for 5 min, centrifuged, and dried. Trypsin (0.01 µg/µL in 25 mM NH₄HCO₃) was prepared and kept on ice for 30 min. Gel pieces were rehydrated in this solution and incubated overnight at 37°C. The next day, peptides were extracted with five volumes of 50% ACN, vortexed for 5 min, and centrifuged at 5,000 × g for 1 min. The supernatant was transferred and centrifuged at 25,000 × g for 5 min. Peptides were freeze-dried, reconstituted in mobile phase A (2% ACN, 0.1% formic acid), centrifuged, and injected for analysis. 1.5.1 Protein Gel Strips Identification High-performance liquid chromatography (HPLC) was conducted using a Shimadzu LC-20AD nano-LC system (Hsieh et al., 2008 ). Peptides were desalted in a trap column and separated on a C18 analytical column (75 µm ID, 3 µm, 15 cm) at 300 nL/min using a gradient of mobile phase B (98% ACN, 0.1% formic acid). Eluted peptides were analyzed with a TripleTOF 5600 mass spectrometer equipped with a NanoSpray III source. MS1 scans (350–1,500 Da) were acquired with a 250 ms accumulation time. Up to 30 ions (> 150 cps) were selected for MS2 (350–1,250 Da, 100 ms) with charge states 2 + to 5+, dynamic exclusion (12 s), and optimized collision energy for iTRAQ. 1.6 Statistical and Bioinformatic Analysis Antifungal activity data of B. subtilis SV108 against grapevine pathogens were analyzed, and VOC profile differences were visualized through PCA. Protein identification was performed using MS/MS spectra aligned with NCBI reference sequences. Raw MS data were converted to peak lists and searched against databases. Results were filtered using Percolator 3.0 with a peptide-spectrum match FDR ≤ 1%. Protein inference was conducted according to parsimony principles, and functional annotation was performed using the GO, COG/KOG. Accurate database selection is essential for reliable protein identification in mass spectrometry-based analyses; therefore, the NCBI RefSeq database was chosen for this study. Protein identification was performed using Mascot software (version 2.3.02) (Wang et al., 2018 ), with Mascot Generic Format (mgf) files used as input. Database searches were performed against a pre-constructed reference library, and the specific search parameters applied are detailed in Table 1 . Table 1 Mascot search parameters Search Engine Mascot v2.3 Enzyme Trypsin Peptide Mass Tolerance 0.05Da Fragment Mass Tolerance 0.1Da Fixed modifications Carbamidomethyl (C) Variable modifications Oxidation (M); Gln->pyro-Glu (N-term Q); Deamidated (NQ) Max Missed Cleavages 1 Ccnnn ESI-QUAD-TOF Database uniprot-taxonomy_1423.fasta (82874 sequences) 2. Results 2.1 Bacillus subtilis SV108 CFS Antifungal Activities The antifungal activity of the B. subtilis SV108 CFS was assessed in vitro against a range of grapevine fungal pathogens. As shown in Fig. 2 , the supernatant exhibited varying degrees of inhibitory effects across the tested species. The highest levels of inhibition were observed against B. cinerea and A. carbonarius , with inhibition values of 16,536 and 15,808 AU/mL, respectively (Table 1 ). A significant inhibitory effect was also observed against P. chlamydospora , which recorded 10,920 AU/mL. By contrast, the antifungal effect was considerably lower against F. oxysporum , A. alternata , V. dahliae , and A. ochraceus . These pathogens exhibited moderate to weak sensitivity to the B. subtilis SV108 CFS. Negative control plates, treated with sterile 0.9% NaCl solution instead of bacterial extract, showed no inhibition zones. The antifungal activity of Bacillus subtilis SV108 cell-free supernatant (CFS) was evaluated against Botrytis cinerea and Aspergillus carbonarius using a well diffusion assay with a two-fold serial dilution series. SV108 CFS exhibited a clear concentration-dependent inhibitory effect against both pathogens (Table 2 ). Table 2 Antifungal activity of Bacillus subtilis SV108 cell-free supernatant against B. cinerea and A. carbonarius in a plate assay. Treatment SV108 two-fold serial dilution series (v/v) Botrytis cinerea Inhibition zone (mm) Aspergillus carbonarius Inhibition zone (mm) 1 1/64 1.2 * ± 0.2 e ** 1.0 ± 0.3 e 2 1/32 1.3 ± 0.3 e 1.6 ± 0.4 d 3 1/16 1.9 ± 0.4 e 1.2 ± 0.5 c 4 0× (Control) 0.0 ± 0.0 f 0.0 ± 0.0 f 5 1/8 1.8 ± 0.5 e 1.4 ± 0.7 b 6 1/4 1.4 ± 0.6 e 1.1 ± 0.8 ab 7 1× (Undiluted) 8.6 ± 0.7 a 14.6 ± 0.9 a * Values are mean ± SD (n = 3). ** Different normal letters within the same column indicate significant differences among treatments at p < 0.05 (Tukey’s HSD). Treatment 4 represents the solvent-only negative control. Low SV108 concentrations (1/64 − 1/16; treatments 1–3) produced only small inhibition zones, indicating limited antifungal activity. No inhibition was observed in the solvent-only negative control (treatment 4). Increasing inhibition was detected at higher SV108 concentrations (1/8 and 1/4; treatments 5 and 6), whereas the undiluted preparation (1×; treatment 7) resulted in the largest inhibition zones for both pathogens. For B. cinerea , inhibition zones increased progressively with concentration and reached a maximum at the undiluted SV108 treatment, which was significantly greater than all diluted treatments and the negative control (p < 0.05). A similar trend was observed for A. carbonarius , which exhibited overall greater sensitivity to SV108, as reflected by larger inhibition zones and higher inhibition rates at comparable concentrations (Fig. 3 ). 2.2 Detached berry antifungal assay The detached berry assay confirmed the ability of B. subtilis SV108 to suppress disease development caused by A. carbonarius and B. cinerea on grape berries (Fig. 4 ). Compared with the untreated control, SV108-treated berries exhibited significantly reduced lesion/mycelial growth diameter (p < 0.05), indicating effective antagonistic activity under fruit-based conditions. In the control berries, A. carbonarius produced extensive colonization, reaching a mean growth diameter of approximately 18.5 mm by day 10. In contrast, berries treated with SV108 showed a markedly lower growth diameter, demonstrating strong inhibition of fungal development. A similar trend was observed for B. cinerea , where SV108 treatment significantly reduced lesion expansion relative to the control, consistent with a protective effect on wounded berry tissue. 2.3 Pathogen inhibition and volatile profiles Visual assessment of mycelial growth in MEB showed inhibitory effects of both B. subtilis SV108 and B. amyloliquefaciens AG1 on A. carbonarius and B. cinerea (Fig. 5 ). The inhibitory activity of B. amyloliquefaciens AG1 against several grapevine pathogens has already been demonstrated (Alfonzo et al., 2009 , 2012 ). A clear reduction in the mycelial growth of A. carbonarius was observed in the presence of SV108 and AG1, respectively, compared to the dense mycelial mat seen in the negative control. Similarly, B. cinerea growth was markedly inhibited in the presence of SV108 and AG1, while the untreated control displayed extensive fungal proliferation. These findings suggest that B. subtilis SV108 exhibits comparable antifungal activity to B. amyloliquefaciens AG1, visibly suppressing the target pathogen’s growth in liquid culture conditions (Fig. 5 ). The VOC profiles after 6 days of incubation at 25°C of B. subtilis SV108, B. amyloliquefaciens AG1, Botrytis cinerea , Aspergillus carbonarius , and their combinations were qualitatively and quantitatively analysed using headspace solid-phase microextraction coupled with GC-MS-SPME. The PCA biplot displays the distribution of samples based on their VOC emission profiles along two principal components: Factor 1 (explaining 38.00% of variance) and Factor 2 (15.73%). The positioning of the samples in the plot indicates distinct metabolic responses depending on microbial interactions. B. subtilis SV108 and B. amyloliquefaciens AG1 clustered separately on the right side of the plot, suggesting that the two bacilli presented similar VOC profiles, having documented antimicrobial activities against grapevine pathogens (Alfonzo et al., 2009 ). The target pathogenic molds ( B. cinerea and A. carbonarius ) showed specific VOC profiles that were well separated from those of the bacilli. The addition of the two strains of bacilli determined two different behaviours. The addition of strain SV108 determined a mild modification in the VOC profiles of the two pathogenic molds since they were present in the same quadrant, while the addition of strain AG1 determined a shift to the lower left quadrant, showing a distinct, pathogen-specific VOC profile (Fig. 6 ). VOCs identified included alcohols, aldehydes, ketones, esters, organic acids, phenols, and pyrazines. B. subtilis SV108 produced high levels of alcohols, including ethanol (1.15 ppm eq.), 1-butanol, and phenylethyl alcohol. Ethanol production increased when co-cultured with A. carbonarius (2.35 ppm eq.) and B. cinerea (3.42 ppm eq.). Similarly, the positive control B. amyloliquefaciens AG1, endowed with antimicrobial activities against several grapevine pathogens, produced ethanol (1.22 ppm eq.), with a slight decrease in the presence of both pathogens which led to reduced ethanol production due to antimicrobial activity against fungi, which were unable to produce the same metabolites as under optimal conditions, such as B. cinerea (3.42 ppm eq.). Similarly, the positive control B. amyloliquefaciens AG1, known for its antimicrobial activity against several grapevine pathogens, produced 1.22 ppm eq. of ethanol, with a slight decrease observed in the presence of both pathogens (Table 3 ). Table 3 Volatile organic compounds classified as alcohols, aldehydes, and ketones were emitted by Bacillus subtilis SV108 and grapevine pathogenic molds after 48 h of incubation at 25°C. Data are expressed as equivalent parts per million (ppm eq.) and represent the mean of three replicates. The standard deviation observed is 5%. Alcohol (ppm*) Aldehyde (ppm) Ketone (ppm) Ethanol 1-Butanol Phenylethyl Alcohol Nonanal Benzaldehyde 2-Butanone 4-Heptanone SV108 1.15 0.49 0.17 0.2 0.29 0.15 0.29 SV108 + A. c 2.35 0.16 0.92 0.14 0.1 0.1 0.1 SV108 + B. c 3.42 0.1 0.28 0.1 0.13 - 0.1 AG1 1.17 0.35 - ** - 0.1 0.33 0.65 AG1 + A. c 1.25 0.1 0.11 0.1 0.14 - 0.1 AG1 + B. c 1.22 0.1 0.12 0.1 0.11 - 0.1 B. c 4.09 0.13 3.04 - - 0.12 0.14 A. c 3.14 0.12 0.69 0.11 0.14 - 0.21 * ppm: Parts per million equivalent. ** Compounds below the detection limit (< 0.1 ppm eq..) are marked with “–”. According to Table 4 , the production of organic acids increased during the interaction between A. carbonarius and the biocontrol strain SV108, including acetic acid (0.21 ppm eq.), 2-methylpropanoic acid (0.19 ppm eq.), and hexanoic acid (0.75 ppm eq.). Notably, these acids are commonly associated with antimicrobial action through mechanisms such as a drop in intracellular pH, which can cause cytoplasmic acidification and membrane-associated mechanisms (Koilybayeva et al., 2023 ). Additionally, substantial levels of esters and phenols were also detected in the two biocontrol, notably acetic acid ethenyl ester (0.39 ppm eq.) and 2-methoxyphenol (0.17 ppm eq.), both of which are recognized for their antimicrobial potential (Orlo et al., 2021 ), further enriching the chemical diversity of the B. subtilis SV108 VOC profile (Table 4 ). Table 4 Volatile organic compounds classified as esters, organic acids, and phenols were emitted by Bacillus subtilis SV108 and grapevine pathogenic molds after 48 h of incubation at 25°C. Data are the mean of three replicates. The standard deviation observed is 5%. Compounds below the detection limit (< 0.1 ppm eq.) are marked with “–”. ppm: Parts per million equivalent. Ester (ppm * ) Acetic acid Acid (ppm) Hexanoic acid Phenol (ppm) Acetic acid ethenyl ester Propanoic acid, 2-methyl- Phenol, 2-methoxy- SV108 0.39 0.14 0.16 0.11 0.17 SV108 + A.c - ** 0.21 0.19 0.75 0.1 SV108 + B.c - - 0.06 - - AG1 0.15 0.12 0.1 - 0.1 AG1 + A. c - - 0.11 - 0.12 AG1 + B. c - - 0.22 - - B. c - - 0.28 - - A. c - - - - - * ppm: Parts per million equivalent. ** Compounds below the detection limit (< 0.1 ppm eq.) are marked with “–”. Nonanal and benzaldehyde were the main aldehydes detected in SV108 cultures, with respective concentrations of 0.2 and 0.29 ppm eq. These compounds have well-established antifungal effects due to their membrane-disruptive and cytotoxic properties (Li et al., 2021 ). Among the ketones, acetoin showed increased production during co-cultivation with the pathogens (0.79 ppm eq. with A. carbonarius and 0.61 ppm eq. with B. cinerea ) (Table 5 ). Acetoin was also notably elevated during interactions of fungal pathogens with strain SV108 (0.79 and 0.61 ppm eq. instead of 0.51 ppm eq.), and strain AG1 (1.84 and 1.82 ppm eq., instead of 0.26 ppm eq.). As shown in Table 5 , B. subtilis SV108 produced high levels of various pyrazines, including 2, dimethyl-, trimethyl-, and 3-ethyl-pyrazines, which are known antifungal compounds produced by Bacillus spp. (Guevara-Avendaño et al., 2020 ). Among them, 2-dimethyl-pyrazine was the most abundant, reaching 6.77 ppm in B. subtilis SV108 and 7.38 ppm in the positive control B. amyloliquefaciens AG1. Furthermore, two nitrogen-containing heterocyclic compounds were detected: 1H-imidazole (0.21 ppm eq.) and 1H-pyrrole, which was especially elevated in co-culture with B. cinerea (1.53 ppm eq.). Table 5 Volatile organic compounds classified as pyrazines and heterocyclic aromatic compounds were emitted by B. subtilis SV108 and grapevine pathogenic molds after 48 h of incubation at 25°C. Data are the mean of three replicates. The standard deviation observed is 5%. Organic compound (ppm*) 2,3-Butanedione Acetoin Pyrazine, 2,dimethyl- Pyrazine, trimethyl- Pyrazine, 3-ethyl- 1H-Imidazole 1H-Pyrrole 2-Methylisoborneol 2-Acetylthiazole Mequinol SV108 - ** 0.51 6.77 1.04 1.22 0.21 - - 0.19 - SV108 + A. c 0.12 0.79 - - - 0.13 - 0.31 - - SV108 + B. c 0.1 0.61 - - - - 1.53 0.11 - 0.32 AG1 - 0.26 7.38 1.37 1.61 0.37 - - 0.17 - AG1 + A. c 0.37 1.84 - - - - - 0.41 - - AG1 + B. c 0.48 1.82 - - - - 1.91 0.1 - - B. c - - - - - - - - - - A. c - - - - - - - - - - * ppm: Parts per million equivalent. ** Compounds below the detection limit (< 0.1 ppm eq.) are marked with “–”. 2.4 Proteomic Profiling of Bacillus subtilis SV108 Due to the gel-based nature of the proteomic workflow and the limited number of identified proteins, the proteomic analysis was used primarily for qualitative confirmation of biosynthetic potential rather than quantitative pathway mapping. The mass spectrometer Triple TOF 5600 was used to analyze and identify possible proteins and peptides associated with B. subtilis SV108's antifungal activity. A total of 38,034 spectra were obtained from the sample group. According to Mascot 2.3.02 search engine, 108 spectra were confidently matched, leading to the identification of 49 proteins and 53 peptides. The molecular weights of the identified proteins were used as a reference for statistical analyses, showing a broad distribution consistent with the diversity of functional proteins. Peptide mass distribution analysis revealed that most peptides fell within the 5–19 kDa range, with the highest frequency observed between 6–10 kDa. Furthermore, peptide sequence coverage analysis indicated that most identified proteins had good sequence representation, supporting the reliability of the dataset. To correlate these findings with antifungal activity, a gel stained with Coomassie blue was used to locate the zone of inhibition. A single prominent band, corresponding to an approximate molecular weight of 70–80 kDa, aligned with the active antifungal zone (Fig. 7 ). Peptides within this band were matched against the NCBI RefSeq database using Mascot, and the sorting of Mascot scores highlighted several relevant substances. Among these, two peptides, lnmmtk and sstldhk, were particularly abundant. These peptides showed homology to conserved regions of non-ribosomal peptide synthetases associated with the Iturin and Mycosubtilin biosynthetic clusters. In addition to ItuB and MycA, several other proteins with potential antimicrobial functions were identified, such as non-ribosomal peptide synthetase DhbF, associated with the siderophore. 2.5 Gene ontology (GO) annotation, KOG classification, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping GO, KOG, and KEGG annotations were therefore interpreted cautiously and used only as contextual support rather than as evidence of statistically significant functional mapping. Among the 49 identified proteins, several were annotated within functional categories related to secondary metabolite biosynthesis and lipid transport and metabolism, which are associated with lipopeptide production. Proteins are also mapped to “translation,” “protein turnover,” and “post-translational modification” pathways, which may support biosynthetic regulation. However, broader GO terms like “metabolic process” and “catalytic activity” were frequently observed and provided a limited specific understanding of antifungal functionality. As such, these annotations were used as supportive rather than central evidence in interpreting the proteomic profile of SV108. The results revealed that 50% of the annotated proteins were assigned to KEGG-defined metabolic pathways, supporting their biological annotation. These were primarily presented in general metabolic pathways (ko01100) and biosynthesis of secondary metabolites (ko01110). 3. Discussion Species within the Bacillus genus have long been applied for plant disease management, as well as to produce industrial enzymes and antibiotics. Their mechanism of action involves the synthesis of various enzymes, antibiotics, and plant growth-promoting hormones, emission of VOCs, and the induction of systemic resistance in host plants (Chowdhury et al., 2015 ). While the role of VOCs in the biocontrol activity of Bacillus spp. has been well documented (Carmona-Hernandez et al., 2019 ). In this study, we provide an integrated characterization of the phenotypic, volatilomic, and qualitative proteomic properties of Bacillus subtilis SV108, an endophytic strain isolated from grape berries, in interaction with major grapevine fungal pathogens. Specifically, the cell-free supernatant (CFS) of B. subtilis SV108 exhibited notable antimicrobial activity against fungal pathogens, particularly A. carbonarius and B. cinerea , by significantly inhibiting their mycelial growth. These results align with the findings of Alfonzo et al. ( 2009 , 2012 ), who reported strong in vitro antifungal activity of B. amyloliquefaciens AG1 against multiple phytopathogenic fungi. Based on its established efficacy, B. amyloliquefaciens AG1 was included in the present study as a positive control. The reduced inhibitory activity observed at lower SV108 concentrations is consistent with a threshold-dependent antifungal response, in which crude bacterial supernatants must reach a minimum effective level to suppress fungal growth. Similar observations have been widely reported for Bacillus spp., where dilution of culture filtrates or antagonistic preparations results in diminished or absent inhibition, whereas undiluted or concentrated preparations exhibit strong antifungal activity (Ongena and Jacques, 2008 ; Cawoy et al., 2011 ). This behavior is consistent with general antimicrobial principles, in which inhibitory effects are only observed once a minimum effective concentration is exceeded (Wiegand et al., 2008 ). Importantly, the detached grape berry assay confirmed that SV108-mediated inhibition extends beyond artificial media. Treatment with SV108 significantly reduced lesion development caused by both A. carbonarius and B. cinerea on wounded berries, demonstrating protective efficacy under fruit-based conditions. For example, Arrebola et al. 2010 demonstrated that in vitro inhibition translated to fruit-level protection, with significant reductions in decay incidence and lesion size on citrus fruit, comparable to the reduced lesion development observed on detached grape berries treated with SV108. The effectiveness of SV108 in the detached berry assay aligns with previous studies demonstrating that Bacillus spp. can significantly reduce lesion development and fungal colonization on grape berries, highlighting their potential for postharvest disease management (Pantelides et al., 2015; Pertot et al., 2017 ). Volatilomic analysis revealed that SV108 produces a complex blend of VOCs, including alcohols, aldehydes, ketones, organic acids, phenols, and pyrazines. Principal component analysis demonstrated that the VOC profile of SV108 clustered closely with that of the established biocontrol strain B. amyloliquefaciens AG1, while remaining distinct from those of the fungal pathogens. This suggests that SV108 shares a conserved antimicrobial volatile signature characteristic of effective Bacillus biocontrol strains. A total of 21 VOCs were identified from B. subtilis SV108 and B. amyloliquefaciens AG1, including alcohols, aldehydes, ketones, esters, acids, phenols, and other organic compounds. Many of these VOCs are recognized for their antifungal properties. Notably, pyrazine derivatives, identified as the most abundant VOCs in this study, are well-documented for their antifungal activity. Janssens et al. ( 2019 ) reported their ability to inhibit fungal mycelial growth, while Yuan et al. ( 2012 ) demonstrated their inhibitory activity specifically against B. cinerea . Similarly, Guevara-Avendaño et al. ( 2020 ) found that pyrazines produced by rhizobacteria exhibited strong antifungal activity against Fusarium kuroshium . Among the aldehydes detected in SV108 cultures, nonanal and benzaldehyde were predominant; both compounds possess well-established antifungal effects, primarily due to their membrane-disrupting and cytotoxic properties (Li et al., 2021 ). On the other hand, it is widely reported that stress conditions both in prokaryotic and eukaryotic organisms result in the accumulation of Reactive oxygen species (ROS), and the inability to manage ROS load leads in living cell to oxidative stress and cell damage. The oxidative stress is coupled with cell membrane lipid peroxidation. This process can generate a broad range of aldehydes, most of which are highly reactive and toxic. Aldehydes produced through the lipoxygenase pathway by the wounded tissues are pivotal for the plant resistance to pathogenic species, and their antimicrobial and antifungal activities in model and real systems (including food products) are widely proven by other literature (Lanciotti et al., 2004 ; 2023; Siroli et al., 2019 ). Another prominent VOC detected was acetoin, whose production increased during interactions with B. cinerea and A. carbonarius . While acetoin has limited direct antifungal activity, it plays an important role in promoting plant growth and inducing systemic responses, potentially explaining its increased synthesis during fungal interactions (Wu et al., 2019 ). In general, ketones such as Diacetyl, 2,3-butanedione, and less extent, acetoin are endowed with strong antimicrobial activities due mainly to reactivity of their keto group, causing damage to DNA, proteins, and cytoplasmic membrane (Cesselin et al., 2021 ;Lanciotti et al., 2003 ). In addition to pyrazines and acetoin, both B. subtilis SV108 and B. amyloliquefaciens AG1 produced heterocyclic compounds such as 1H-pyrrole and 1H-imidazole, which are known for their antimicrobial activities. In particular, 1H-pyrrole has been reported to exhibit antifungal activity (Bhardwaj et al., 2015 ). Its production was significantly elevated in the presence of B. cinerea by both bacterial strains. Furthermore, 1H-imidazole, a carbazole-based azole derivative, has been reported to possess antimicrobial activity. Its structural feature, particularly the six-carbon chain spacer, may enhance its bioactivity (Zhang et al., 2017). The observed antifungal activity likely results from the combined effects of soluble metabolites present in the CFS and volatile organic compounds emitted during microbial interaction, rather than a single dominant inhibitory factor. The production of antifungal compounds is a key mechanism by which Bacillus species inhibit fungal pathogens, offering broad-spectrum antifungal activity. Previous research in grapevines has shown that mycosubtilin, a lipopeptide produced by Bacillus , acts as a potent activator of innate immunity, triggering the plant defense system and inducing localized resistance to fungal infections (Farace et al., 2015 ). Iturins, another class of lipopeptides, can induce programmed cell death in fungal pathogens by generating reactive oxygen species (ROS) and upregulating NADPH oxidase genes (Cao et al., 2011 ). The antifungal action of both Mycosubtilin and Iturins is associated with their amphiphilic nature. Lipopeptides like Iturin A are known to reduce surface tension and disrupt the integrity of fungal biofilms and membranes (Zhao et al., 2017 ). Mycosubtilin, an isoform of Iturin A, specifically targets ergosterol in fungal membranes, allowing Bacillus species to inhibit a wide range of fungal pathogens (Nasir & Besson, 2012). Notably, peptides that contribute to antifungal activity have been identified in multiple Bacillus species, including B. subtilis , B. clausii , B. cereus , B. anthracis , and B. amyloliquefaciens (H. Cao et al., 2013 ; Jeong & Son, 2021 ). In line with previous findings, the antifungal potential of B. subtilis SV108 is likely mediated through both lipopeptide synthesis and VOCs emission. The increase of aldehydes and short-chain fatty acids such as nonanal, as well as ketones, suggests a key role of lipid metabolism and cell membrane oxidative disruption (mediated by ROS production) in the action mechanisms of B. subtilis SV108. Also, the proteomic study showed that significant expression was observed for proteins involved in lipid metabolism. Among the identified proteins in Bacillus subtilis SV108, one of particular interest was MYCA-BACIU (Mycosubtilin synthase subunit A), which was annotated within the lysine biosynthesis pathway, specifically through the α-aminoadipate route. This enzyme is functionally linked to non-ribosomal peptide synthetase activity and α-aminoadipate metabolism, both of which are central to the biosynthesis of lysine and antimicrobial lipopeptides. As illustrated in the KEGG pathway map (Online resource 1), this protein is closely associated with the enzyme EC 1.2.1.95, a key component in converting aminoadipate semialdehyde to aminoadipate, a precursor in the lysine biosynthesis route. The presence of MYCA-BACIU further supports the proteomic findings of B. subtilis SV108’s capacity to produce antimicrobial metabolites, not only via volatile compounds and Iturin-family peptides but also through amino acid-derived bioactive molecules. These findings reinforce the hypothesis regarding the potential of B. subtilis SV108 as a multi-modal biocontrol agent with complex antimicrobial biosynthetic machinery. Moreover, the identification of peptides corresponding to Iturin A synthetase B (ItuB) and Mycosubtilin synthetase A (MycA) in this study reinforces the established role of non-ribosomal lipopeptides in mycelial inhibition. Similar antifungal mechanisms were demonstrated by B. subtilis KS1, where the disruption of Iturin biosynthetic genes completely abolished antifungal activity against B. cinerea and C. gloeosporioides (Furuya et al., 2011 ). Furthermore, B. amyloliquefaciens AG1 has been shown to produce bioactive peptides stable across a range of pH and enzymatic conditions, with in-gel digestion and mass spectrometry supporting the presence of cyclic antifungal peptides like subtilisin BPN′ (Alfonzo et al., 2012 ). These results support the involvement of protein-based mechanisms in SV108’s antifungal activity. Proteomic analysis revealed peptides homologous to non-ribosomal peptide synthetases, while GC/MS-SPME analysis identified volatile antimicrobial metabolites. ItuB is one of the four open reading frames (ituA, ituB, ituC, and ituD) associated with the biosynthesis of Iturin A, a lipopeptide with strong antifungal properties (Ongena & Jacques, 2008 ). ItuB contains an amino acid activation domain associated with the production of bacillomycin D-related peptides. Alfonso et al. (2012) also identified two cyclic peptides related to the N-terminal sequence of Subtilisin BPN, further supporting the association of these biosynthetic genes with the antifungal activity of B. subtilis SV108. In addition to ItuB and MycA, several other proteins with potential antimicrobial roles were identified, including enzymes linked to secondary metabolite biosynthesis and cell wall assembly. Among them, DhbF, a non-ribosomal peptide synthetase, participates in the synthesis of bacillibactin, a catecholate-type siderophore in Bacillus subtilis . This enzyme catalyzes the formation of a trimeric iron-chelating compound from threonine and 2,3-dihydroxybenzoate, enabling iron acquisition under limiting conditions and contributing to microbial competition through iron sequestration (May et al., 2001 ). Mycosubtilin synthase (MYCA-BACIU) was mapped to the secondary metabolite biosynthesis pathway (ko01110), suggesting that it might be involved in the production of antifungal lipopeptide. Lipopeptides produced by Bacillus species are known to suppress plant disease progression by disrupting specific fungal processes (Palanisamy, 2008 ). B. subtilis SV108 activates a wide array of metabolic and regulatory pathways, supporting its strong antifungal potential. Several identified proteins are functionally linked to processes such as protein folding, sorting, degradation, replication, repair, and transcription, as well as in amino acid and nucleotide metabolism, lipid metabolism, genetic information processing, and peroxisomal function. These findings suggest that B. subtilis SV108 may enhance its antagonistic capacity by improving oxidative stress response pathways and cell membrane disruption. Moreover, increased competition for space and nutrients, along with elevated protein synthesis activity, could facilitate the production of antifungal metabolites and cell wall-degrading enzymes (Cao et al., 2013 ). 4. Conclusion Bacillus subtilis SV108 showed strong biocontrol potential against grapevine fungal pathogens, with the greatest activity against Botrytis cinerea and Aspergillus carbonarius . Its cell-free supernatant inhibited fungal growth in a clear dose-dependent manner, and the detached berry assay confirmed significantly reduced lesion development on fruit. VOC profiling revealed a diverse antimicrobial volatile blend (notably pyrazines, aldehydes, ketones, and organic acids), while qualitative proteomics supported biosynthetic potential for antifungal lipopeptides (iturin or mycosubtilin-related NRPS signatures) and competitive traits such as siderophore production. Overall, SV108 likely suppresses fungi through combined soluble metabolites and VOCs, supporting its promise as an eco-friendly alternative to chemical fungicides; next steps include targeted metabolite confirmation, genomic validation, formulation/stability testing, and field/postharvest trials. Declarations Competing interests The authors declare that they have no competing interests. They have no relevant financial or non-financial interests to disclose and no financial or proprietary interests in any material discussed in this article. Research involving Human Participants and/or Animals This study did not involve human participants or vertebrate animals. All experiments were conducted using microbial cultures and plant-associated in vitro or laboratory assays. Therefore, ethical approval from a human or animal ethics committee was not required. Funding The authors did not receive support from any organization for the submitted work. No external funding was received for conducting this study, and no external funds, grants, or other support were received. 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Supplementary Files Acknowledgements.pdf Onlineresource1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 08 Apr, 2026 Reviewers agreed at journal 22 Jan, 2026 Reviewers invited by journal 22 Jan, 2026 Editor invited by journal 21 Jan, 2026 Editor assigned by journal 20 Jan, 2026 First submitted to journal 13 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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09:24:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":379136,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/dab62b7f1a41b2503bbd5ba2.jpg"},{"id":101297032,"identity":"fc5f6990-02e8-4929-a75b-cb18142eaec1","added_by":"auto","created_at":"2026-01-28 09:24:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":460918,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/62f8648e91d9be86f8a2cd96.jpg"},{"id":101259433,"identity":"e22c1e70-31f5-456a-b4d4-47ebca11584b","added_by":"auto","created_at":"2026-01-27 19:59:13","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":551626,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/60e2e434e29170018f92d2cd.jpg"},{"id":101259436,"identity":"6371c6ee-9053-4de0-9d03-ae5c17d49f6d","added_by":"auto","created_at":"2026-01-27 19:59:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":935593,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/b25e12d1a962db186f8f140f.jpg"},{"id":101259431,"identity":"7adc5c0b-925b-4f2e-8eee-d55791e9c4e9","added_by":"auto","created_at":"2026-01-27 19:59:13","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":408226,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/f01cf2d8d7b22f9cbeb2f705.jpg"},{"id":101259432,"identity":"4c7c8993-0bcf-4aba-a0b3-49619da3f5cd","added_by":"auto","created_at":"2026-01-27 19:59:13","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":239079,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Collectionoffigures7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/964d6d12b61a6d8846818150.jpg"},{"id":101299485,"identity":"643acd6e-6192-4cff-b368-fe577eef6d75","added_by":"auto","created_at":"2026-01-28 09:42:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5169156,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/86dd70b8-aee8-4d72-9862-249409307199.pdf"},{"id":101298057,"identity":"04eda112-7ee8-40f9-88ba-64b7062948e8","added_by":"auto","created_at":"2026-01-28 09:30:01","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":90050,"visible":true,"origin":"","legend":"","description":"","filename":"Acknowledgements.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/13a91daa1db6d16627405b15.pdf"},{"id":101259435,"identity":"0ab8d3d4-cd09-4a3c-8912-c5a70dd7777d","added_by":"auto","created_at":"2026-01-27 19:59:13","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":161303,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineresource1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8535314/v1/fefc5b73671c2e6db518b009.pdf"}],"financialInterests":"","formattedTitle":"Biocontrol Potential of Bacillus subtilis SV108 Against Aspergillus carbonarius and Botrytis cinerea of Grapevine","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDue to increasing concerns over the adverse effects of chemical fungicides on human health and the environment, many of these compounds are being progressively restricted or banned (Deresa \u0026amp; Diriba, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, research efforts have increasingly focused on developing natural and environmentally sustainable alternatives (Grzegorczyk et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Among these, the use of biocontrol agents has emerged as a promising and eco-friendly strategy, with their efficacy extensively documented in the literature in managing grapevine pathogens (Altieri et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Carmona-Hernandez et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiocontrol agents offer two main advantages over traditional chemical approaches for managing grapevine fungal diseases: (i) they can be isolated from the same ecological niche as crop pathogens without negatively impacting the safety or quality of the final product; and (ii) their use can reduce the development of pathogen resistance to synthetic agents commonly used in crop disease management. Most biocontrol agents produce antibacterial, antifungal, and other secondary metabolites that inhibit the growth of plant pathogens such as bacteria and molds (Keswani et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the various biocontrol agents tested for managing fungal diseases, \u003cem\u003eBacillus subtilis\u003c/em\u003e has emerged as a particularly promising solution for in-field control of grapevine and other crop diseases (Ongena \u0026amp; Jacques, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). \u003cem\u003eB. subtilis\u003c/em\u003e strains are known for their diverse metabolic capabilities, environmental adaptability, and effectiveness in suppressing both bacterial and fungal pathogens, as demonstrated \u003cem\u003ein vitro\u003c/em\u003e and field trials (Pertot et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Approximately 4\u0026ndash;5% of the \u003cem\u003eBacillus\u003c/em\u003e genome is dedicated to genes involved in the production of antimicrobial compounds. These genes are primarily associated with the biosynthesis of antifungal compounds, including bioactive antimicrobial lipopeptides, volatile organic compounds (VOCs), polyketides, and bacteriocins. Such compounds can directly inhibit the growth of plant pathogens by disrupting their cell membranes and/or by eliciting plant defense responses against infections (Farace et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe antimicrobial lipopeptides produced by \u003cem\u003eB. subtilis\u003c/em\u003e are generally classified into three major families: surfactins, fengycins, and Iturins (Ongena \u0026amp; Jacques, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). These lipopeptides share a conserved backbone structure comprising a cyclic heptapeptide, with the Iturin family (including Iturins A, B, and C) exhibiting particularly strong \u003cem\u003ein vitro\u003c/em\u003e antifungal activity against a broad spectrum of fungi and yeasts due to their membrane-permeabilizing effects (Ongena \u0026amp; Jacques, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). However, the specific antimicrobial profile of \u003cem\u003eB. subtilis\u003c/em\u003e varies depending on the strain and environmental or process-related conditions.\u003c/p\u003e \u003cp\u003eThis research evaluated a \u003cem\u003eBacillus subtilis\u003c/em\u003e strain SV108, isolated from grape berries, for its potential as a biocontrol agent against two major grapevine fungal pathogens. The objectives were to assess the antagonistic potential of SV108 through \u003cem\u003ein vitro\u003c/em\u003e assays, characterize the volatile organic compounds (VOCs) emitted during bacterium-fungus interactions, and analyze the CFS to identify key bioactive compounds associated with mycelial growth inhibition. Also, a proteomic analysis was performed to uncover the presence of antimicrobial peptides and explore secondary metabolite biosynthetic pathways.\u003c/p\u003e"},{"header":"1. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Strain and culture conditions\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBacillus subtilis\u003c/em\u003e (Cohn 1872) strain SV108, obtained from the microbial collection of the Department of Agricultural and Food Sciences, University of Bologna (Italy), isolated from the experimental vineyard of the University of Bologna (Faenza, Italy), was used in this study. This strain was selected as the most effective among various biocontrol agents previously tested against grapevine fungal pathogens (unpublished data). \u003cem\u003eB. subtilis\u003c/em\u003e SV108 was re-cultured on Malt Extract Agar (MEA; Oxoid, Thermo Fisher, Milan, Italy) and incubated overnight at 37\u0026deg;C. \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e (\u003cem\u003eB. amyloliquefaciens)\u003c/em\u003e strain AG1, provided by the Department of Scienze Agrarie e Forestali, University of Palermo (Italy), was used as a positive control (Alfonzo et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Antagonism assays were performed against a panel of grapevine fungal pathogens included \u003cem\u003eBotrytis cinerea\u003c/em\u003e and \u003cem\u003ePhaeomoniella chlamydospora\u003c/em\u003e (\u003cem\u003eP. chlamydospora)\u003c/em\u003e (provided by the Department of Integrated Pest Management of Mediterranean Fruit trees and Vegetable Crops, CIHEAM Bari, Italy) \u003cem\u003eFusarium oxysporum\u003c/em\u003e (\u003cem\u003eF. oxysporum)\u003c/em\u003e (isolated from the grapevine rhizosphere), \u003cem\u003eAlternaria alternata\u003c/em\u003e (\u003cem\u003eA. alternata\u003c/em\u003e) (obtained from grapevine leaves), \u003cem\u003eVerticillium dahliae\u003c/em\u003e (\u003cem\u003eV. dahliae\u003c/em\u003e) (isolated from decayed grapevine tissue), and \u003cem\u003eAspergillus carbonarius (A. carabonarius)\u003c/em\u003e and \u003cem\u003eAspergillus ochraceus\u003c/em\u003e (\u003cem\u003eA. ochraceus\u003c/em\u003e) (both isolated from grapes). All fungal isolates were maintained on MEA and incubated at 25\u0026deg;C for two weeks before use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Antifungal Activity of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 Cell-Free Supernatant\u003c/h2\u003e \u003cp\u003eThe antifungal activity of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 CFS against \u003cem\u003eB. cinerea\u003c/em\u003e, \u003cem\u003eP. chlamydospora\u003c/em\u003e, \u003cem\u003eF. oxysporum\u003c/em\u003e, \u003cem\u003eA. alternata\u003c/em\u003e, \u003cem\u003eA. carbonarius\u003c/em\u003e, and \u003cem\u003eA. ochraceus\u003c/em\u003e was evaluated \u003cem\u003ein vitro\u003c/em\u003e using the dual-culture method described by Zhang et al., 2017.\u003c/p\u003e \u003cp\u003eBriefly, fungal colonies were grown on MEA plates at 25\u0026deg;C for 7 days. Spores were harvested with 5 mL of 0.9% NaCl, yielding\u0026thinsp;~\u0026thinsp;100\u0026ndash;120 spores/mL. For each species, 1 mL of spore suspension was mixed with 14 mL of molten MEA (40\u0026deg;C) in a sterile Petri dish and gently agitated. After solidification, a 5 mm well was punched in the center and filled with 50 \u0026micro;L of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 CFS. The CFS was prepared following the extraction protocol described by(Leelasuphakul et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, with slight modifications.\u003c/p\u003e \u003cp\u003eIn this method, Pure colonies of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 grown on MEA at 30\u0026deg;C for 24 h were used to inoculate 300 mL Malt Extract Broth. After incubation, cultures were filtered (0.2 \u0026micro;m) to obtain CFS, which was extracted twice with ethyl acetate (1:1, v/v). The combined organic phases were dried over anhydrous Na₂SO₄, evaporated under vacuum at 40\u0026deg;C, washed with hexane, redissolved in DMSO, and stored at -80\u0026deg;C. Extraction yield was determined after drying and expressed as mg/mL of the original supernatant. MEA plates were incubated at 25\u0026deg;C for the antifungal assay for 6 days. After incubation, the antifungal activity of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 was assessed by measuring the inhibition radius (IR, in mm) using a caliper. Results were expressed in arbitrary units (AU/mL) according to the formula proposed by Alfonzo et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eAU/mL\u003c/em\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{IR\\:\\left(mm\\right)}{well\\:capacity\\:\\left(mL\\right)}\\times\\:free\\:supernatant\\:concentration\\:(mg/mL)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWhere: IR (mm)\u0026thinsp;=\u0026thinsp;Inhibition Radius in millimeters (mm), Well capacity (mL)\u0026thinsp;=\u0026thinsp;Volume of supernatant added, and CFS concentration (mg/mL)\u0026thinsp;=\u0026thinsp;Concentration of extract dissolved in DMSO. Each antifungal test was conducted in triplicate against all selected grapevine fungal pathogens. Negative controls consisted of plates inoculated with 0.9% (w/v) NaCl saline solution without bacterial supernatant.\u003c/p\u003e \u003cp\u003eBased on the results of the in vitro plate assays, \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e exhibited the greatest sensitivity to SV108, as evidenced by markedly larger inhibition zones and higher inhibition rates compared with the other tested pathogens. These two fungi were therefore selected for subsequent, more detailed evaluations, including quantitative inhibition analyses and detached grape berry assays, to assess the biocontrol efficacy of SV108 under fruit-based conditions.\u003c/p\u003e \u003cp\u003eTo evaluate concentration-dependent antifungal activity, SV108 CFS was tested as a two-fold serial dilution series prepared in the same solvent system as the extract (DMSO). Treatments corresponded to the following dilution levels: 1/64 (treatment 1), 1/32 (treatment 2), 1/16 (treatment 3), 0\u0026times; solvent-only negative control (treatment 4), 1/8 (treatment 5), 1/4 (treatment 6), and undiluted CFS (1\u0026times;; treatment 7). For each plate, 50 \u0026micro;L of the corresponding dilution was added to the central well. Each treatment\u0026ndash;pathogen combination was tested in triplicate (n\u0026thinsp;=\u0026thinsp;3). The negative control consisted of the solvent used for dilutions (treatment 4) without SV108 CFS. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Differences among treatments were assessed by one-way ANOVA followed by Tukey\u0026rsquo;s HSD test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Detached Berry Antifungal Assay\u003c/h2\u003e \u003cp\u003eThe antagonistic activity of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 against \u003cem\u003eA. carbonarius\u003c/em\u003e and \u003cem\u003eB. cinerea\u003c/em\u003e was evaluated using a detached grape berry assay adapted from Pantelides et al. (2015), with modifications. Briefly, SV108 was grown in Malt Extract Broth (Oxoid, Thermofisher, Milan, Italy) (or an equivalent bacterial growth medium) at 30\u0026deg;C for 24\u0026ndash;48 h. Bacterial cultures were adjusted to approximately 10⁸ CFU/mL prior to application.\u003c/p\u003e \u003cp\u003eMature grape berries (cv. Red Globe) were detached from bunches and surface-disinfected using 1% commercial sodium hypochlorite for 15 min, followed by rinsing with sterile deionized water and air-drying under sterile conditions. Berries were then immersed in the SV108 culture for uniform coating. After 4 h incubation at 25\u0026deg;C, berries were air-dried, and a standardized wound (~\u0026thinsp;2 mm diameter) was made on each berry using a sterile needle.\u003c/p\u003e \u003cp\u003eFor pathogen inoculation, each wound was spot-inoculated with 20 \u0026micro;L of a conidial suspension of either \u003cem\u003eA. carbonarius\u003c/em\u003e (\u0026asymp;\u0026thinsp;10⁶ conidia/mL) or \u003cem\u003eB. cinerea\u003c/em\u003e (\u0026asymp;\u0026thinsp;10⁵\u0026ndash;10⁶ conidia/mL). Inoculated berries were placed in humid chambers (e.g., sealed boxes with moist sterile paper) to maintain high relative humidity and incubated under pathogen-favorable conditions (25\u0026deg;C for \u003cem\u003eA. carbonarius\u003c/em\u003e for 10 days; 20\u0026ndash;22\u0026deg;C for \u003cem\u003eB. cinerea\u003c/em\u003e for 5\u0026ndash;7 days, or until clear symptom development in controls) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDisease development was monitored daily. Antifungal efficacy was quantified by measuring lesion/mycelial growth diameter (\u0026oslash;, mm) using a digital caliper. Each treatment consisted of three biological replicates, and the experiment was repeated as necessary. One-way ANOVA analyzed data, and mean comparisons were performed using Tukey\u0026rsquo;s HSD test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Volatile Organic Compounds (VOCs)\u003c/h2\u003e \u003cp\u003eSamples were initially prepared by incubating \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, alone and in combination with \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e, for 48 h at 25\u0026deg;C in MEB. The two species of fungi were selected due to their strong inhibition by SV108. The composition of VOCs was analyzed on the headspace of the vials using solid-phase microextraction combined with GC-MS (SPME-GC-MS), as described by Gottardi et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A 75 \u0026micro;m CAR/PDMS fiber was used for VOC collection. Five milliliters of culture were incubated at 45\u0026deg;C, and the fiber was exposed to the headspace for 30 minutes. Desorption occurred at 250\u0026deg;C for 10 minutes. VOCs were analyzed with an Agilent 6890N GC-MS using a J\u0026amp;W CP-Wax 52 column, with helium as the carrier gas. Compounds were identified via the NIST 11 database and quantified using 4-methyl-2-pentanol (final concentration: 6 mg/L) as the internal standard, reported in ppm equivalents. All experiments were run in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e1.5 Protein Extraction and SDS-PAGE\u003c/h2\u003e \u003cp\u003eProtein extraction and separation were performed using tricine-sodium dodecyl sulphate-polyacrylamide gel electrophoresis (tricine-SDS-PAGE) as described by Cao et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), optimized for high-resolution separation of low-molecular-weight peptides. First, gel pieces were soaked in 50 \u0026micro;L ultrapure water for 30 min, cut into 1\u0026ndash;2 mm fragments, and transferred to microcentrifuge tubes. For decolorization, 1 mL of 50 mM NH₄HCO₃:acetonitrile (1:1, v/v) was added, vortexed for 10 s, incubated at 37\u0026deg;C for 30 min, then centrifuged and dried. To dehydrate, 500 \u0026micro;L acetonitrile was added until the gel turned white, and tubes were air-dried under a clean bench for 10 min. For reduction, gel pieces were covered with 10 mM DTT (1 M DTT:25 mM NH₄HCO₃ = 1:100) and incubated at 56\u0026deg;C for 1 h. After cooling, the solution was replaced with 55 mM IAM (0.55 M IAM:25 mM NH₄HCO₃ = 1:10), incubated at room temperature for 45 min in the dark. Gels were then washed twice with 500 \u0026micro;L decolorizing solution and once with 500 \u0026micro;L acetonitrile, vortexed for 5 min, centrifuged, and dried. Trypsin (0.01 \u0026micro;g/\u0026micro;L in 25 mM NH₄HCO₃) was prepared and kept on ice for 30 min. Gel pieces were rehydrated in this solution and incubated overnight at 37\u0026deg;C. The next day, peptides were extracted with five volumes of 50% ACN, vortexed for 5 min, and centrifuged at 5,000 \u0026times; g for 1 min. The supernatant was transferred and centrifuged at 25,000 \u0026times; g for 5 min. Peptides were freeze-dried, reconstituted in mobile phase A (2% ACN, 0.1% formic acid), centrifuged, and injected for analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e1.5.1 Protein Gel Strips Identification\u003c/h2\u003e \u003cp\u003eHigh-performance liquid chromatography (HPLC) was conducted using a Shimadzu LC-20AD nano-LC system (Hsieh et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Peptides were desalted in a trap column and separated on a C18 analytical column (75 \u0026micro;m ID, 3 \u0026micro;m, 15 cm) at 300 nL/min using a gradient of mobile phase B (98% ACN, 0.1% formic acid). Eluted peptides were analyzed with a TripleTOF 5600 mass spectrometer equipped with a NanoSpray III source. MS1 scans (350\u0026ndash;1,500 Da) were acquired with a 250 ms accumulation time. Up to 30 ions (\u0026gt;\u0026thinsp;150 cps) were selected for MS2 (350\u0026ndash;1,250 Da, 100 ms) with charge states 2\u0026thinsp;+\u0026thinsp;to 5+, dynamic exclusion (12 s), and optimized collision energy for iTRAQ.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e1.6 Statistical and Bioinformatic Analysis\u003c/h2\u003e \u003cp\u003eAntifungal activity data of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 against grapevine pathogens were analyzed, and VOC profile differences were visualized through PCA. Protein identification was performed using MS/MS spectra aligned with NCBI reference sequences. Raw MS data were converted to peak lists and searched against databases. Results were filtered using Percolator 3.0 with a peptide-spectrum match FDR\u0026thinsp;\u0026le;\u0026thinsp;1%. Protein inference was conducted according to parsimony principles, and functional annotation was performed using the GO, COG/KOG.\u003c/p\u003e \u003cp\u003eAccurate database selection is essential for reliable protein identification in mass spectrometry-based analyses; therefore, the NCBI RefSeq database was chosen for this study. Protein identification was performed using Mascot software (version 2.3.02) (Wang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), with Mascot Generic Format (mgf) files used as input. Database searches were performed against a pre-constructed reference library, and the specific search parameters applied are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMascot search parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSearch Engine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMascot v2.3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnzyme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrypsin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeptide Mass Tolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05Da\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFragment Mass Tolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1Da\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed modifications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbamidomethyl (C)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable modifications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOxidation (M); Gln-\u0026gt;pyro-Glu (N-term Q); Deamidated (NQ)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax Missed Cleavages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCcnnn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-QUAD-TOF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDatabase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003euniprot-taxonomy_1423.fasta (82874 sequences)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.1 \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 CFS Antifungal Activities\u003c/h2\u003e \u003cp\u003eThe antifungal activity of the \u003cem\u003eB. subtilis\u003c/em\u003e SV108 CFS was assessed \u003cem\u003ein vitro\u003c/em\u003e against a range of grapevine fungal pathogens. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the supernatant exhibited varying degrees of inhibitory effects across the tested species. The highest levels of inhibition were observed against \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e, with inhibition values of 16,536 and 15,808 AU/mL, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A significant inhibitory effect was also observed against \u003cem\u003eP. chlamydospora\u003c/em\u003e, which recorded 10,920 AU/mL. By contrast, the antifungal effect was considerably lower against \u003cem\u003eF. oxysporum\u003c/em\u003e, \u003cem\u003eA. alternata\u003c/em\u003e, \u003cem\u003eV. dahliae\u003c/em\u003e, and \u003cem\u003eA. ochraceus\u003c/em\u003e. These pathogens exhibited moderate to weak sensitivity to the \u003cem\u003eB. subtilis\u003c/em\u003e SV108 CFS. Negative control plates, treated with sterile 0.9% NaCl solution instead of bacterial extract, showed no inhibition zones.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe antifungal activity of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 cell-free supernatant (CFS) was evaluated against \u003cem\u003eBotrytis cinerea\u003c/em\u003e and \u003cem\u003eAspergillus carbonarius\u003c/em\u003e using a well diffusion assay with a two-fold serial dilution series. SV108 CFS exhibited a clear concentration-dependent inhibitory effect against both pathogens (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntifungal activity of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 cell-free supernatant against \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e in a plate assay.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSV108 two-fold serial dilution series (v/v)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eBotrytis cinerea\u003c/em\u003e\u003c/p\u003e \u003cp\u003eInhibition zone (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAspergillus carbonarius\u003c/em\u003e\u003c/p\u003e \u003cp\u003eInhibition zone (mm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003csup\u003e*\u003c/sup\u003e \u0026plusmn; 0.2 e\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026times; (Control)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0 f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0 f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026times; (Undiluted)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eValues are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003cp\u003e \u003csup\u003e**\u003c/sup\u003eDifferent normal letters within the same column indicate significant differences among treatments at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Tukey\u0026rsquo;s HSD). Treatment 4 represents the solvent-only negative control.\u003c/p\u003e \u003cp\u003eLow SV108 concentrations (1/64\u0026thinsp;\u0026minus;\u0026thinsp;1/16; treatments 1\u0026ndash;3) produced only small inhibition zones, indicating limited antifungal activity. No inhibition was observed in the solvent-only negative control (treatment 4). Increasing inhibition was detected at higher SV108 concentrations (1/8 and 1/4; treatments 5 and 6), whereas the undiluted preparation (1\u0026times;; treatment 7) resulted in the largest inhibition zones for both pathogens.\u003c/p\u003e \u003cp\u003eFor \u003cem\u003eB. cinerea\u003c/em\u003e, inhibition zones increased progressively with concentration and reached a maximum at the undiluted SV108 treatment, which was significantly greater than all diluted treatments and the negative control (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A similar trend was observed for \u003cem\u003eA. carbonarius\u003c/em\u003e, which exhibited overall greater sensitivity to SV108, as reflected by larger inhibition zones and higher inhibition rates at comparable concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Detached berry antifungal assay\u003c/h2\u003e \u003cp\u003eThe detached berry assay confirmed the ability of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 to suppress disease development caused by \u003cem\u003eA. carbonarius\u003c/em\u003e and \u003cem\u003eB. cinerea\u003c/em\u003e on grape berries (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCompared with the untreated control, SV108-treated berries exhibited significantly reduced lesion/mycelial growth diameter (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating effective antagonistic activity under fruit-based conditions.\u003c/p\u003e \u003cp\u003eIn the control berries, \u003cem\u003eA. carbonarius\u003c/em\u003e produced extensive colonization, reaching a mean growth diameter of approximately 18.5 mm by day 10. In contrast, berries treated with SV108 showed a markedly lower growth diameter, demonstrating strong inhibition of fungal development. A similar trend was observed for \u003cem\u003eB. cinerea\u003c/em\u003e, where SV108 treatment significantly reduced lesion expansion relative to the control, consistent with a protective effect on wounded berry tissue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Pathogen inhibition and volatile profiles\u003c/h2\u003e \u003cp\u003eVisual assessment of mycelial growth in MEB showed inhibitory effects of both \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 on \u003cem\u003eA. carbonarius\u003c/em\u003e and \u003cem\u003eB. cinerea\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The inhibitory activity of \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 against several grapevine pathogens has already been demonstrated (Alfonzo et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A clear reduction in the mycelial growth of \u003cem\u003eA. carbonarius\u003c/em\u003e was observed in the presence of SV108 and AG1, respectively, compared to the dense mycelial mat seen in the negative control. Similarly, \u003cem\u003eB. cinerea\u003c/em\u003e growth was markedly inhibited in the presence of SV108 and AG1, while the untreated control displayed extensive fungal proliferation. These findings suggest that \u003cem\u003eB. subtilis\u003c/em\u003e SV108 exhibits comparable antifungal activity to \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, visibly suppressing the target pathogen\u0026rsquo;s growth in liquid culture conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe VOC profiles after 6 days of incubation at 25\u0026deg;C of \u003cem\u003eB. subtilis\u003c/em\u003e SV108, \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, \u003cem\u003eBotrytis cinerea\u003c/em\u003e, \u003cem\u003eAspergillus carbonarius\u003c/em\u003e, and their combinations were qualitatively and quantitatively analysed using headspace solid-phase microextraction coupled with GC-MS-SPME. The PCA biplot displays the distribution of samples based on their VOC emission profiles along two principal components: Factor 1 (explaining 38.00% of variance) and Factor 2 (15.73%). The positioning of the samples in the plot indicates distinct metabolic responses depending on microbial interactions. \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 clustered separately on the right side of the plot, suggesting that the two bacilli presented similar VOC profiles, having documented antimicrobial activities against grapevine pathogens (Alfonzo et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The target pathogenic molds (\u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e) showed specific VOC profiles that were well separated from those of the bacilli. The addition of the two strains of bacilli determined two different behaviours. The addition of strain SV108 determined a mild modification in the VOC profiles of the two pathogenic molds since they were present in the same quadrant, while the addition of strain AG1 determined a shift to the lower left quadrant, showing a distinct, pathogen-specific VOC profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVOCs identified included alcohols, aldehydes, ketones, esters, organic acids, phenols, and pyrazines. \u003cem\u003eB. subtilis\u003c/em\u003e SV108 produced high levels of alcohols, including ethanol (1.15 ppm eq.), 1-butanol, and phenylethyl alcohol. Ethanol production increased when co-cultured with \u003cem\u003eA. carbonarius\u003c/em\u003e (2.35 ppm eq.) and \u003cem\u003eB. cinerea\u003c/em\u003e (3.42 ppm eq.). Similarly, the positive control \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, endowed with antimicrobial activities against several grapevine pathogens, produced ethanol (1.22 ppm eq.), with a slight decrease in the presence of both pathogens which led to reduced ethanol production due to antimicrobial activity against fungi, which were unable to produce the same metabolites as under optimal conditions, such as \u003cem\u003eB. cinerea\u003c/em\u003e (3.42 ppm eq.). Similarly, the positive control \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, known for its antimicrobial activity against several grapevine pathogens, produced 1.22 ppm eq.\u0026nbsp;of ethanol, with a slight decrease observed in the presence of both pathogens (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVolatile organic compounds classified as alcohols, aldehydes, and ketones were emitted by \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 and grapevine pathogenic molds after 48 h of incubation at 25\u0026deg;C. Data are expressed as equivalent parts per million (ppm eq.) and represent the mean of three replicates. The standard deviation observed is 5%.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAlcohol (ppm*)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAldehyde (ppm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eKetone (ppm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEthanol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1-Butanol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhenylethyl Alcohol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNonanal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBenzaldehyde\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2-Butanone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4-Heptanone\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eppm: Parts per million equivalent.\u003c/p\u003e \u003cp\u003e \u003csup\u003e**\u003c/sup\u003eCompounds below the detection limit (\u0026lt;\u0026thinsp;0.1 ppm eq..) are marked with \u0026ldquo;\u0026ndash;\u0026rdquo;.\u003c/p\u003e \u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the production of organic acids increased during the interaction between \u003cem\u003eA. carbonarius\u003c/em\u003e and the biocontrol strain SV108, including acetic acid (0.21 ppm eq.), 2-methylpropanoic acid (0.19 ppm eq.), and hexanoic acid (0.75 ppm eq.). Notably, these acids are commonly associated with antimicrobial action through mechanisms such as a drop in intracellular pH, which can cause cytoplasmic acidification and membrane-associated mechanisms (Koilybayeva et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, substantial levels of esters and phenols were also detected in the two biocontrol, notably acetic acid ethenyl ester (0.39 ppm eq.) and 2-methoxyphenol (0.17 ppm eq.), both of which are recognized for their antimicrobial potential (Orlo et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), further enriching the chemical diversity of the \u003cem\u003eB. subtilis\u003c/em\u003e SV108 VOC profile (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVolatile organic compounds classified as esters, organic acids, and phenols were emitted by \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 and grapevine pathogenic molds after 48 h of incubation at 25\u0026deg;C. Data are the mean of three replicates. The standard deviation observed is 5%. Compounds below the detection limit (\u0026lt;\u0026thinsp;0.1 ppm eq.) are marked with \u0026ldquo;\u0026ndash;\u0026rdquo;. ppm: Parts per million equivalent.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEster (ppm\u003csup\u003e*\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAcetic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcid (ppm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHexanoic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhenol (ppm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcetic acid ethenyl ester\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePropanoic acid, 2-methyl-\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhenol, 2-methoxy-\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eA.c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eB.c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eppm: Parts per million equivalent.\u003c/p\u003e \u003cp\u003e \u003csup\u003e**\u003c/sup\u003eCompounds below the detection limit (\u0026lt;\u0026thinsp;0.1 ppm eq.) are marked with \u0026ldquo;\u0026ndash;\u0026rdquo;.\u003c/p\u003e \u003cp\u003eNonanal and benzaldehyde were the main aldehydes detected in SV108 cultures, with respective concentrations of 0.2 and 0.29 ppm eq.\u0026nbsp;These compounds have well-established antifungal effects due to their membrane-disruptive and cytotoxic properties (Li et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among the ketones, acetoin showed increased production during co-cultivation with the pathogens (0.79 ppm eq.\u0026nbsp;with \u003cem\u003eA. carbonarius\u003c/em\u003e and 0.61 ppm eq.\u0026nbsp;with \u003cem\u003eB. cinerea\u003c/em\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Acetoin was also notably elevated during interactions of fungal pathogens with strain SV108 (0.79 and 0.61 ppm eq.\u0026nbsp;instead of 0.51 ppm eq.), and strain AG1 (1.84 and 1.82 ppm eq., instead of 0.26 ppm eq.).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, B. \u003cem\u003esubtilis\u003c/em\u003e SV108 produced high levels of various pyrazines, including 2, dimethyl-, trimethyl-, and 3-ethyl-pyrazines, which are known antifungal compounds produced by \u003cem\u003eBacillus\u003c/em\u003e spp. (Guevara-Avenda\u0026ntilde;o et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among them, 2-dimethyl-pyrazine was the most abundant, reaching 6.77 ppm in \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and 7.38 ppm in the positive control \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1. Furthermore, two nitrogen-containing heterocyclic compounds were detected: 1H-imidazole (0.21 ppm eq.) and 1H-pyrrole, which was especially elevated in co-culture with \u003cem\u003eB. cinerea\u003c/em\u003e (1.53 ppm eq.).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVolatile organic compounds classified as pyrazines and heterocyclic aromatic compounds were emitted by \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and grapevine pathogenic molds after 48 h of incubation at 25\u0026deg;C. Data are the mean of three replicates. The standard deviation observed is 5%.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eOrganic compound (ppm*)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,3-Butanedione\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcetoin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePyrazine, 2,dimethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePyrazine, trimethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePyrazine, 3-ethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1H-Imidazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1H-Pyrrole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2-Methylisoborneol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2-Acetylthiazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMequinol\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV108\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG1\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. c\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eppm: Parts per million equivalent.\u003c/p\u003e \u003cp\u003e \u003csup\u003e**\u003c/sup\u003eCompounds below the detection limit (\u0026lt;\u0026thinsp;0.1 ppm eq.) are marked with \u0026ldquo;\u0026ndash;\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Proteomic Profiling of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108\u003c/h2\u003e \u003cp\u003eDue to the gel-based nature of the proteomic workflow and the limited number of identified proteins, the proteomic analysis was used primarily for qualitative confirmation of biosynthetic potential rather than quantitative pathway mapping. The mass spectrometer Triple TOF 5600 was used to analyze and identify possible proteins and peptides associated with \u003cem\u003eB. subtilis\u003c/em\u003e SV108's antifungal activity. A total of 38,034 spectra were obtained from the sample group. According to Mascot 2.3.02 search engine, 108 spectra were confidently matched, leading to the identification of 49 proteins and 53 peptides.\u003c/p\u003e \u003cp\u003eThe molecular weights of the identified proteins were used as a reference for statistical analyses, showing a broad distribution consistent with the diversity of functional proteins. Peptide mass distribution analysis revealed that most peptides fell within the 5\u0026ndash;19 kDa range, with the highest frequency observed between 6\u0026ndash;10 kDa. Furthermore, peptide sequence coverage analysis indicated that most identified proteins had good sequence representation, supporting the reliability of the dataset. To correlate these findings with antifungal activity, a gel stained with Coomassie blue was used to locate the zone of inhibition. A single prominent band, corresponding to an approximate molecular weight of 70\u0026ndash;80 kDa, aligned with the active antifungal zone (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePeptides within this band were matched against the NCBI RefSeq database using Mascot, and the sorting of Mascot scores highlighted several relevant substances. Among these, two peptides, lnmmtk and sstldhk, were particularly abundant. These peptides showed homology to conserved regions of non-ribosomal peptide synthetases associated with the Iturin and Mycosubtilin biosynthetic clusters. In addition to ItuB and MycA, several other proteins with potential antimicrobial functions were identified, such as non-ribosomal peptide synthetase DhbF, associated with the siderophore.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.5 Gene ontology (GO) annotation, KOG classification, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGO, KOG, and KEGG annotations were therefore interpreted cautiously and used only as contextual support rather than as evidence of statistically significant functional mapping. Among the 49 identified proteins, several were annotated within functional categories related to secondary metabolite biosynthesis and lipid transport and metabolism, which are associated with lipopeptide production. Proteins are also mapped to \u0026ldquo;translation,\u0026rdquo; \u0026ldquo;protein turnover,\u0026rdquo; and \u0026ldquo;post-translational modification\u0026rdquo; pathways, which may support biosynthetic regulation. However, broader GO terms like \u0026ldquo;metabolic process\u0026rdquo; and \u0026ldquo;catalytic activity\u0026rdquo; were frequently observed and provided a limited specific understanding of antifungal functionality. As such, these annotations were used as supportive rather than central evidence in interpreting the proteomic profile of SV108. The results revealed that 50% of the annotated proteins were assigned to KEGG-defined metabolic pathways, supporting their biological annotation. These were primarily presented in general metabolic pathways (ko01100) and biosynthesis of secondary metabolites (ko01110).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eSpecies within the \u003cem\u003eBacillus\u003c/em\u003e genus have long been applied for plant disease management, as well as to produce industrial enzymes and antibiotics. Their mechanism of action involves the synthesis of various enzymes, antibiotics, and plant growth-promoting hormones, emission of VOCs, and the induction of systemic resistance in host plants (Chowdhury et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile the role of VOCs in the biocontrol activity of \u003cem\u003eBacillus\u003c/em\u003e spp. has been well documented (Carmona-Hernandez et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In this study, we provide an integrated characterization of the phenotypic, volatilomic, and qualitative proteomic properties of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108, an endophytic strain isolated from grape berries, in interaction with major grapevine fungal pathogens. Specifically, the cell-free supernatant (CFS) of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 exhibited notable antimicrobial activity against fungal pathogens, particularly \u003cem\u003eA. carbonarius\u003c/em\u003e and \u003cem\u003eB. cinerea\u003c/em\u003e, by significantly inhibiting their mycelial growth. These results align with the findings of Alfonzo et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), who reported strong \u003cem\u003ein vitro\u003c/em\u003e antifungal activity of \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 against multiple phytopathogenic fungi. Based on its established efficacy, \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 was included in the present study as a positive control.\u003c/p\u003e \u003cp\u003eThe reduced inhibitory activity observed at lower SV108 concentrations is consistent with a threshold-dependent antifungal response, in which crude bacterial supernatants must reach a minimum effective level to suppress fungal growth. Similar observations have been widely reported for Bacillus spp., where dilution of culture filtrates or antagonistic preparations results in diminished or absent inhibition, whereas undiluted or concentrated preparations exhibit strong antifungal activity (Ongena and Jacques, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Cawoy et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This behavior is consistent with general antimicrobial principles, in which inhibitory effects are only observed once a minimum effective concentration is exceeded (Wiegand et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, the detached grape berry assay confirmed that SV108-mediated inhibition extends beyond artificial media. Treatment with SV108 significantly reduced lesion development caused by both \u003cem\u003eA. carbonarius\u003c/em\u003e and \u003cem\u003eB. cinerea\u003c/em\u003e on wounded berries, demonstrating protective efficacy under fruit-based conditions. For example, Arrebola et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e demonstrated that in vitro inhibition translated to fruit-level protection, with significant reductions in decay incidence and lesion size on citrus fruit, comparable to the reduced lesion development observed on detached grape berries treated with SV108. The effectiveness of SV108 in the detached berry assay aligns with previous studies demonstrating that \u003cem\u003eBacillus\u003c/em\u003e spp. can significantly reduce lesion development and fungal colonization on grape berries, highlighting their potential for postharvest disease management (Pantelides et al., 2015; Pertot et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eVolatilomic analysis revealed that SV108 produces a complex blend of VOCs, including alcohols, aldehydes, ketones, organic acids, phenols, and pyrazines. Principal component analysis demonstrated that the VOC profile of SV108 clustered closely with that of the established biocontrol strain \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, while remaining distinct from those of the fungal pathogens. This suggests that SV108 shares a conserved antimicrobial volatile signature characteristic of effective \u003cem\u003eBacillus\u003c/em\u003e biocontrol strains. A total of 21 VOCs were identified from \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1, including alcohols, aldehydes, ketones, esters, acids, phenols, and other organic compounds. Many of these VOCs are recognized for their antifungal properties. Notably, pyrazine derivatives, identified as the most abundant VOCs in this study, are well-documented for their antifungal activity. Janssens et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported their ability to inhibit fungal mycelial growth, while Yuan et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) demonstrated their inhibitory activity specifically against \u003cem\u003eB. cinerea\u003c/em\u003e. Similarly, Guevara-Avenda\u0026ntilde;o et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that pyrazines produced by rhizobacteria exhibited strong antifungal activity against \u003cem\u003eFusarium kuroshium\u003c/em\u003e. Among the aldehydes detected in SV108 cultures, nonanal and benzaldehyde were predominant; both compounds possess well-established antifungal effects, primarily due to their membrane-disrupting and cytotoxic properties (Li et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, it is widely reported that stress conditions both in prokaryotic and eukaryotic organisms result in the accumulation of Reactive oxygen species (ROS), and the inability to manage ROS load leads in living cell to oxidative stress and cell damage. The oxidative stress is coupled with cell membrane lipid peroxidation. This process can generate a broad range of aldehydes, most of which are highly reactive and toxic. Aldehydes produced through the lipoxygenase pathway by the wounded tissues are pivotal for the plant resistance to pathogenic species, and their antimicrobial and antifungal activities in model and real systems (including food products) are widely proven by other literature (Lanciotti et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; 2023; Siroli et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Another prominent VOC detected was acetoin, whose production increased during interactions with \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eA. carbonarius\u003c/em\u003e. While acetoin has limited direct antifungal activity, it plays an important role in promoting plant growth and inducing systemic responses, potentially explaining its increased synthesis during fungal interactions (Wu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In general, ketones such as Diacetyl, 2,3-butanedione, and less extent, acetoin are endowed with strong antimicrobial activities due mainly to reactivity of their keto group, causing damage to DNA, proteins, and cytoplasmic membrane (Cesselin et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e;Lanciotti et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to pyrazines and acetoin, both \u003cem\u003eB. subtilis\u003c/em\u003e SV108 and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 produced heterocyclic compounds such as 1H-pyrrole and 1H-imidazole, which are known for their antimicrobial activities. In particular, 1H-pyrrole has been reported to exhibit antifungal activity (Bhardwaj et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Its production was significantly elevated in the presence of \u003cem\u003eB. cinerea\u003c/em\u003e by both bacterial strains. Furthermore, 1H-imidazole, a carbazole-based azole derivative, has been reported to possess antimicrobial activity. Its structural feature, particularly the six-carbon chain spacer, may enhance its bioactivity (Zhang et al., 2017). The observed antifungal activity likely results from the combined effects of soluble metabolites present in the CFS and volatile organic compounds emitted during microbial interaction, rather than a single dominant inhibitory factor. The production of antifungal compounds is a key mechanism by which \u003cem\u003eBacillus\u003c/em\u003e species inhibit fungal pathogens, offering broad-spectrum antifungal activity. Previous research in grapevines has shown that mycosubtilin, a lipopeptide produced by \u003cem\u003eBacillus\u003c/em\u003e, acts as a potent activator of innate immunity, triggering the plant defense system and inducing localized resistance to fungal infections (Farace et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Iturins, another class of lipopeptides, can induce programmed cell death in fungal pathogens by generating reactive oxygen species (ROS) and upregulating NADPH oxidase genes (Cao et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The antifungal action of both Mycosubtilin and Iturins is associated with their amphiphilic nature. Lipopeptides like Iturin A are known to reduce surface tension and disrupt the integrity of fungal biofilms and membranes (Zhao et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Mycosubtilin, an isoform of Iturin A, specifically targets ergosterol in fungal membranes, allowing \u003cem\u003eBacillus\u003c/em\u003e species to inhibit a wide range of fungal pathogens (Nasir \u0026amp; Besson, 2012). Notably, peptides that contribute to antifungal activity have been identified in multiple \u003cem\u003eBacillus\u003c/em\u003e species, including \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eB. clausii\u003c/em\u003e, \u003cem\u003eB. cereus\u003c/em\u003e, \u003cem\u003eB. anthracis\u003c/em\u003e, and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e (H. Cao et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Jeong \u0026amp; Son, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In line with previous findings, the antifungal potential of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 is likely mediated through both lipopeptide synthesis and VOCs emission. The increase of aldehydes and short-chain fatty acids such as nonanal, as well as ketones, suggests a key role of lipid metabolism and cell membrane oxidative disruption (mediated by ROS production) in the action mechanisms of \u003cem\u003eB. subtilis\u003c/em\u003e SV108. Also, the proteomic study showed that significant expression was observed for proteins involved in lipid metabolism. Among the identified proteins in \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108, one of particular interest was MYCA-BACIU (Mycosubtilin synthase subunit A), which was annotated within the lysine biosynthesis pathway, specifically through the α-aminoadipate route. This enzyme is functionally linked to non-ribosomal peptide synthetase activity and α-aminoadipate metabolism, both of which are central to the biosynthesis of lysine and antimicrobial lipopeptides. As illustrated in the KEGG pathway map (Online resource 1), this protein is closely associated with the enzyme EC 1.2.1.95, a key component in converting aminoadipate semialdehyde to aminoadipate, a precursor in the lysine biosynthesis route. The presence of MYCA-BACIU further supports the proteomic findings of \u003cem\u003eB. subtilis\u003c/em\u003e SV108\u0026rsquo;s capacity to produce antimicrobial metabolites, not only via volatile compounds and Iturin-family peptides but also through amino acid-derived bioactive molecules. These findings reinforce the hypothesis regarding the potential of \u003cem\u003eB. subtilis\u003c/em\u003e SV108 as a multi-modal biocontrol agent with complex antimicrobial biosynthetic machinery. Moreover, the identification of peptides corresponding to Iturin A synthetase B (ItuB) and Mycosubtilin synthetase A (MycA) in this study reinforces the established role of non-ribosomal lipopeptides in mycelial inhibition. Similar antifungal mechanisms were demonstrated by \u003cem\u003eB. subtilis\u003c/em\u003e KS1, where the disruption of Iturin biosynthetic genes completely abolished antifungal activity against \u003cem\u003eB. cinerea\u003c/em\u003e and \u003cem\u003eC. gloeosporioides\u003c/em\u003e (Furuya et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Furthermore, \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e AG1 has been shown to produce bioactive peptides stable across a range of pH and enzymatic conditions, with in-gel digestion and mass spectrometry supporting the presence of cyclic antifungal peptides like subtilisin BPN\u0026prime; (Alfonzo et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These results support the involvement of protein-based mechanisms in SV108\u0026rsquo;s antifungal activity. Proteomic analysis revealed peptides homologous to non-ribosomal peptide synthetases, while GC/MS-SPME analysis identified volatile antimicrobial metabolites. ItuB is one of the four open reading frames (ituA, ituB, ituC, and ituD) associated with the biosynthesis of Iturin A, a lipopeptide with strong antifungal properties (Ongena \u0026amp; Jacques, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). ItuB contains an amino acid activation domain associated with the production of bacillomycin D-related peptides. Alfonso et al. (2012) also identified two cyclic peptides related to the N-terminal sequence of Subtilisin BPN, further supporting the association of these biosynthetic genes with the antifungal activity of \u003cem\u003eB. subtilis\u003c/em\u003e SV108. In addition to ItuB and MycA, several other proteins with potential antimicrobial roles were identified, including enzymes linked to secondary metabolite biosynthesis and cell wall assembly. Among them, DhbF, a non-ribosomal peptide synthetase, participates in the synthesis of bacillibactin, a catecholate-type siderophore in \u003cem\u003eBacillus subtilis\u003c/em\u003e. This enzyme catalyzes the formation of a trimeric iron-chelating compound from threonine and 2,3-dihydroxybenzoate, enabling iron acquisition under limiting conditions and contributing to microbial competition through iron sequestration (May et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Mycosubtilin synthase (MYCA-BACIU) was mapped to the secondary metabolite biosynthesis pathway (ko01110), suggesting that it might be involved in the production of antifungal lipopeptide. Lipopeptides produced by \u003cem\u003eBacillus\u003c/em\u003e species are known to suppress plant disease progression by disrupting specific fungal processes (Palanisamy, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). \u003cem\u003eB. subtilis\u003c/em\u003e SV108 activates a wide array of metabolic and regulatory pathways, supporting its strong antifungal potential. Several identified proteins are functionally linked to processes such as protein folding, sorting, degradation, replication, repair, and transcription, as well as in amino acid and nucleotide metabolism, lipid metabolism, genetic information processing, and peroxisomal function. These findings suggest that \u003cem\u003eB. subtilis\u003c/em\u003e SV108 may enhance its antagonistic capacity by improving oxidative stress response pathways and cell membrane disruption. Moreover, increased competition for space and nutrients, along with elevated protein synthesis activity, could facilitate the production of antifungal metabolites and cell wall-degrading enzymes (Cao et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003e \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108 showed strong biocontrol potential against grapevine fungal pathogens, with the greatest activity against \u003cem\u003eBotrytis cinerea\u003c/em\u003e and \u003cem\u003eAspergillus carbonarius\u003c/em\u003e. Its cell-free supernatant inhibited fungal growth in a clear dose-dependent manner, and the detached berry assay confirmed significantly reduced lesion development on fruit. VOC profiling revealed a diverse antimicrobial volatile blend (notably pyrazines, aldehydes, ketones, and organic acids), while qualitative proteomics supported biosynthetic potential for antifungal lipopeptides (iturin or mycosubtilin-related NRPS signatures) and competitive traits such as siderophore production. Overall, SV108 likely suppresses fungi through combined soluble metabolites and VOCs, supporting its promise as an eco-friendly alternative to chemical fungicides; next steps include targeted metabolite confirmation, genomic validation, formulation/stability testing, and field/postharvest trials.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests. They have no relevant financial or non-financial interests to disclose and no financial or proprietary interests in any material discussed in this article.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eResearch involving Human Participants and/or Animals\u003c/h2\u003e \u003cp\u003eThis study did not involve human participants or vertebrate animals. All experiments were conducted using microbial cultures and plant-associated in vitro or laboratory assays. Therefore, ethical approval from a human or animal ethics committee was not required.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors did not receive support from any organization for the submitted work. No external funding was received for conducting this study, and no external funds, grants, or other support were received.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eConceptualization: R.L., F.P., S.S.; Methodology: S.S., G.B., D.G., L.S., A.A.; Investigation: S.S.; Data analysis: S.S., G.B., L.S.; Resources: T.E., A.A.; Writing-original draft: S.S., G.B.; Writing-review and editing: all authors; Supervision: R.L., F.P.; All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArrebola, E., Sivakumar, D., \u0026amp; Korsten, L. (2010). Effect of volatile compounds produced by Bacillus strains on postharvest decay in citrus. \u003cem\u003eBiological control\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(1), 122\u0026ndash;128.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlfonzo, A., Conigliaro, G., Torta, L., Burruano, S., \u0026amp; Moschetti, G. 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(2012). Antifungal activity of \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e NJN-6 volatile compounds against Fusarium oxysporum f. Sp. Cubense. \u003cem\u003eApplied and Environmental Microbiology\u003c/em\u003e, \u003cem\u003e78\u003c/em\u003e(16), 5942\u0026ndash;5944.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang (2017). Isolation and identification of antifungal peptides from \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e W10. Environmental Science and Pollution Research, 24, 25000\u0026ndash;25009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, H., Shao, D., Jiang, C., Shi, J., Li, Q., Huang, Q., Rajoka, M. S. R., Yang, H., \u0026amp; Jin, M. (2017). Biological activity of lipopeptides from \u003cem\u003eBacillus\u003c/em\u003e. \u003cem\u003eApplied Microbiology and Biotechnology\u003c/em\u003e, \u003cem\u003e101\u003c/em\u003e, 5951\u0026ndash;5960.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-plant-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpp","sideBox":"Learn more about [European Journal of Plant Pathology](http://link.springer.com/journal/10658)","snPcode":"10658","submissionUrl":"https://www.editorialmanager.com/ejpp/default2.aspx","title":"European Journal of Plant Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Bacillus subtilis, Grapevine, antifungal activity, volatile organic compounds","lastPublishedDoi":"10.21203/rs.3.rs-8535314/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8535314/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe increasing restriction of chemical fungicides has intensified the search for environmentally sustainable alternatives for grapevine disease management. In this study, we evaluated the biocontrol potential of \u003cem\u003eBacillus subtilis\u003c/em\u003e SV108, an endophytic strain isolated from grape berries, against major grapevine fungal pathogens. The antifungal activity of SV108 cell-free supernatant (CFS) was assessed in vitro against a panel of phytopathogenic fungi, revealing strong and concentration-dependent inhibition, particularly against \u003cem\u003eBotrytis cinerea\u003c/em\u003e and \u003cem\u003eAspergillus carbonarius\u003c/em\u003e. These pathogens were further evaluated using a detached grape berry assay, where SV108 treatment significantly reduced lesion development compared with untreated controls, confirming efficacy under fruit-based conditions. To elucidate the mechanisms underlying antifungal activity, volatile organic compounds (VOCs) produced by SV108 during pathogen interaction were analyzed using SPME-GC-MS. SV108 emitted a complex blend of bioactive VOCs, including alcohols, aldehydes, ketones, organic acids, phenols, and pyrazines, many of which are known for their antimicrobial properties. Principal component analysis demonstrated distinct VOC profiles between bacterial strains and fungal pathogens, with SV108 showing similarities to the established biocontrol strain \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e AG1. Qualitative proteomic analysis of the active antifungal fraction identified peptides homologous to non-ribosomal peptide synthetases associated with iturin and mycosubtilin biosynthetic pathways, as well as proteins linked to siderophore production and secondary metabolite biosynthesis. The results indicate that \u003cem\u003eB. subtilis\u003c/em\u003e SV108 suppresses fungal growth through a multi-modal mechanism involving both soluble antifungal metabolites and volatile emissions. These findings support the potential application of SV108 as a sustainable biocontrol agent for grapevine disease management, particularly in postharvest and integrated disease control strategies.\u003c/p\u003e","manuscriptTitle":"Biocontrol Potential of Bacillus subtilis SV108 Against Aspergillus carbonarius and Botrytis cinerea of Grapevine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-27 19:59:08","doi":"10.21203/rs.3.rs-8535314/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2026-04-08T12:07:02+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-01-22T11:43:13+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-22T08:51:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"European Journal of Plant Pathology","date":"2026-01-22T03:56:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-21T02:18:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Plant Pathology","date":"2026-01-13T11:13:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-plant-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpp","sideBox":"Learn more about [European Journal of Plant Pathology](http://link.springer.com/journal/10658)","snPcode":"10658","submissionUrl":"https://www.editorialmanager.com/ejpp/default2.aspx","title":"European Journal of Plant Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b6ed23e0-63d1-4fd3-8318-9072728c1923","owner":[],"postedDate":"January 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T17:12:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-27 19:59:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8535314","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8535314","identity":"rs-8535314","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}