Plant Growth-Promoting Bacillus Strains Modulate Early Soybean Development via Proteome Remodelling

Plant Growth-Promoting Bacillus Strains Modulate Early Soybean Development via Proteome Remodelling | 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 Plant Growth-Promoting Bacillus Strains Modulate Early Soybean Development via Proteome Remodelling Haleema Tariq, Pierre Dutilleul, Jennifer Geddes-McAlister, Anja Geitmann, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7602726/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Dec, 2025 Read the published version in BMC Plant Biology → Version 1 posted 12 You are reading this latest preprint version Abstract Plant adaptation to environmental stress involves tightly regulated cellular, molecular, and biochemical responses. Among these, microbe-assisted strategies have gained attention, particularly the role of the plant microbiome (phytomicrobiome) in promoting growth and stress resilience. Soybean (), a major agricultural crop, actively recruits beneficial microbes through root-secreted secondary metabolites, fostering symbiotic interactions with endophytic bacteria. However, the direct and indirect impacts of root-associated endophytes on plant development remain incompletely understood. In this study, we investigated three strains (HT1, HT2, and HT3) isolated previously from the soybean root microbiome for their potential plant growth-promoting and biocontrol activities. -HT1 and HT2 significantly enhanced soybean seed germination, while -HT3 promoted leaf area expansion significantly compared to the control, indicating strain-specific developmental effects. To elucidate the molecular basis of these effects, we conducted shotgun proteomic profiling of soybean leaves. Enrichment analysis revealed distinct functional signatures, with HT1 and HT2 associated with pathways linked to cellular component organization, microtubule dynamics, and organelle function, and -HT3 inducing broader enrichment of photosynthesis, chloroplast organization, and biosynthetic processes. These findings suggest that HT1 and HT2 promote early developmental transitions, while HT3 enhances vegetative growth through large-scale metabolic reprogramming. Notably, proteins such as anthranilate synthase and proteasome subunit alpha type were differentially abundant, pointing to the potential involvement of auxin biosynthesis and ubiquitin–proteasome–mediated regulation but, the actual roles of these pathways remain to be validated. These findings provide mechanistic insights into how specific strains modulate soybean development at the molecular level and highlight their potential for use as bio-inoculants to enhance crop productivity and resilience under stress conditions. Soybean microbiome Label-free proteomics Endophyte-host interaction Bacillus strains Proteomic reprogramming Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Due to their sessile nature, plants cannot avoid exposure to numerous stressors that threaten their survival [ 1 ]). Plants use adaptation tactics to deal with environmental stress on a cellular, molecular, and biochemical level. One such approach is the use of microbial species associated with the plant known as the plant microbiome or phytomicrobiome, which is often referred to as the second genome, and which plays an important role in the health of the plant [ 2 ][ 3 ][ 4 ]. The presence of microbes in every part of the plant plays an important role in the development and reproduction of the plant. As a result of these interactions, plants develop, grow, and become adapted to a stressful environment, establishing the basis for the Holobiont theory, which considers plants and their microorganisms to be one evolutionary unit rather than separate entities[ 5 ][ 6 ][ 7 ]. Microbiomes can be greatly influenced by a variety of host-based factors, such as plant species, genotype, developmental stage, canopy type, and metabolite production. Soybean is an important agricultural crop due to its high protein and oil content. As a model plant, it is also useful for exploring the associated phytomicrobiome since the plant produces secondary metabolites that are released into the soil-root environment to attract beneficial bacteria [ 8 ][ 9 ][ 10 ]For instance, isoflavonoids are biologically active specialized metabolites synthesized by legumes through the phenylpropanoid pathway, and soybean roots produce large amounts of these compounds that influence the rhizosphere microflora with spatiotemporal variations [ 11 ]. Root exudates from legume species contain a combination of flavonoids that serve as selective agents for compatible symbiotic organisms. Flavonoids, such as medicarpin, are produced by Trifolium and Medicago species and inhibit the growth of bacterial strains that are incompatible with these species [ 12 ][ 13 ]. The antimicrobial activity of plant-derived coumarins is limited to pathogenic bacteria and does not affect endophytic bacteria [ 14 ]. Furthermore, rhizobacteria have developed resistance to the toxic structural mimic of arginine (cotinine) produced by legumes, allowing them to thrive in the rhizosphere [ 15 ]. Plant metabolites, such as polyamine amino acids, organic acids, or sugars, can also be used by symbionts to identify their host plants [ 16 ]. Therefore, plants selectively recruit beneficial endophytes from complex microbial communities by secreting specific signals, including nutrients, antimicrobial compounds, and secondary metabolites. These metabolic signals likely play a key role in shaping symbiotic associations between host plants and endophytes, ultimately, facilitating the colonization of plant tissues by beneficial bacteria. Upon colonizing the host tissues, endophytic bacteria establish an intimate relationship with plants. For instance, some bacteria affect the growth of plants by producing phytohormones, aminocyclopropane-1-carboxylase-deaminase, and antibiotic compounds, as well as by fixing nitrogen, solubilizing phosphate, or suppressing pathogens through the competence of invasion sites [ 17 ][ 18 ][ 19 ] found that the endophytic bacteria in soybean plants can produce siderophore, indole acetic acid, promote nitrogen fixation, and inhibit the specific to pathogenic fungi. These metabolites mediate the growth-promoting effects of endophytic bacteria on soybean seedlings. Soybean seed endophytes protect seeds from seed-borne pathogens, promote plant growth, and suppress diseases, all of which support their use in crop protection and growth [ 20 ]. As described in the literature above, root endophytes of soybean plants form a selectively beneficial and diverse community that needs to be studied further to determine their direct effects on the plant. This study explores the beneficial effects of members of the soybean endophyte community on the soybean phenotype. Soybean-associated Bacillus endophytes influence host development by reprogramming leaf proteomes at the mid-vegetative stage. Through modulation of signaling, metabolic, and structural pathways, these endophytes differentially enhance seed germination, vegetative growth, or defense responses, thereby shaping soybean phenotypes under both optimal and controlled conditions. In our previous study [ 21 ], we used an LC-MS/MS-based untargeted metabolomics workflow to profile secondary metabolites produced by Bacillus strains HT1, HT2 and HT3 used in the present study. MS²-guided annotation indicated that HT1 and HT2 secrete multiple putative antifungal compounds that attribute to their anti-fungal activity against Fusarium oxysporum , whereas HT3 lacks these features. Motivated by these findings, we tested the direct effects of these plant growth-promoting bacteria on soybean and sought to elucidate their mechanisms of action. In this study, we analyzed the soybean leaf proteome to signalling pathways associated with elucidating the mechanisms of plant growth that are modulated by inoculation with Bacillus species. This approach provides a comprehensive understanding of the molecular interactions between soybean endophytes and their host, offering new insights into plant-microbe symbiosis. 2. Material and Methods 2.1. Bacteria Culture Propagation and Inoculation Bacillus -HT1 (Accession No. PV534845), Bacillus- HT2 (Accession No. PV534846), and Bacillus -HT3 (Accession No. PV534847) were preselected from the microbiome of soybean roots grown in Sainte-Anne-de-Bellevue, Quebec, Canada, previously by the author [ 21 ]. The cultures of these three bacteria were grown from glycerol stock in TSB (Tryptic Soy broth) medium for 48 h incubated at 25°C and 150 rpm. The cultures were harvested by centrifugation at 5,000xg for 10 min at room temperature (AwelTM MF 48-R, NuAire, United States) and the supernatant was discarded. The pellet was resuspended in 10 mM MgSO 4 , and three different cell concentrations were prepared. The optical density of the cultures was adjusted to three different concentrations i.e., 10 6, 10 7 and 10 8 colony forming unit (CFU) using a spectrophotometer (Ultraspec 4300 pro UV/Visible Spectrophotometer, Biochrom) at absorbance A 600nm . The three different concentrations of Bacillus- HT1, HT2 and HT3 strains were prepared in 10 mM MgSO 4 to screen the best concentration for germination. 2.2. Screening for Optimal Bacterial Concentration A screening test was performed to select optimal concentrations for in-planta application. Three different concentrations (10 6 , 10 7 and 10 8 CFU) of Bacillus -HT1, HT2 and HT3 strains were prepared in 10 mM MgSO 4 . The soybean germination experiments were carried out in a phytorium located at the Macdonald Campus of McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada. Seeds of soybean ( Glycine max L. var B088Y1) were used for the study. Per sample, ten soybean seeds were surface sterilized using 2% sodium hypochlorite for 2 mins, rinsed with sterilized distilled water five times, and placed in Petri dishes (Cat. no. 431760, sterile 100 × 15 mm polystyrene Petri dish, Fisher Scientific Co., Whitby, Ontario, Canada), lined with filter paper (09-795D, QualitativeP8, porosity coarse, Fisher Scientific Co., Pittsburgh, PA, United States). Bacillus suspension (5 mL) was added to each Petri dish for a total of 9 treatments (3 bacterial strains administered at 3 different concentrations each). Control seeds were treated with 10 mM MgSO 4 . Each Petri plate contained 10 seeds, and each treatment was replicated 10 times, and the experiment was repeated two times. The Petri plates were sealed with parafilm and incubated in a phytorium set at 25°C with a relative humidity of 70% and 24h darkness. Seeds were considered germinated when their radicle was about 2 mm long; data were collected at 24, 30, 36 and 48h. Data analysis Seed germination percentages were first calculated for each replicate of each treatment. These percentage data were then submitted to the arcsine-square-root transformation and analyzed by one-way analysis of variance (ANOVA) with PROC GLM (SAS Version 9.4). In particular, differences between the treatments and control were assessed using Dunnett's test after the treatment main effects had been found significant with the ANOVA F -test. Differences with a p -value < 0.05 were considered statistically significant. 2.3. Soybean growth condition and sample collection Based on their optimal effects on soybean germination, a concentration of 10 7 CFU was used for all bacterial strains for the investigation of their effects on soybean vegetative growth. There were three bacterial treatments (10⁷ CFU of each strain) and one control (10 mM MgSO₄). Pots (15.25 cm diameter) filled with vermiculite (Perlite Canada Inc., Laval, QC, Canada) were supplied with 300 mL of water. After two hours, 5 seeds were placed in each pot. Each seed in a pot was treated with 500 µL of bacterial suspension and covered with vermiculite. The pots were placed under greenhouse conditions at 25 ± 2°C and 50% relative humidity. After seedling emergence, the plants were thinned to one seedling per pot. The plants were irrigated with 300 mL water twice a week (every 3–4 days) and sampled on the 28th day after planting. Above-ground plant growth variables, including plant height, leaf area, shoot fresh weight and dry weight were measured. Intact roots were harvested, placed on a 30 × 40 cm plastic plate, and submerged in deionized water. The roots were scanned (Modified Epson Expression 10000XL, Regent Instruments Inc., Québec, QC, Canada) and the output images were analyzed using WinRhizo software (Regent Instruments Inc.). Several root parameters were measured, including root length, root projection area, root surface area, and dry root weight. The experiment was repeated three times with three treatments and six replicates per treatment each time. Three replicates were allocated for measuring growth variables and three replicates were allocated for protein extraction. Data analysis Growth data were analyzed in SAS Version 9.4. One-way ANOVA and Dunnett's test were used to determine differences between each treatment and the control. The level of significance was set at 0.05. 2.4. Label free proteomics analysis Shotgun proteomics analysis was performed on soybean plants grown from seeds coated with Bacillus strains HT1, HT2, and HT3 at a concentration of 10⁷ CFU per seed prior to germination. Trifoliate leaves harvested after 28 days of planting were flash frozen in liquid nitrogen. A biological replicate was constructed by pooling the three technical replicates from each experiment. The collected leaf samples were dried in a lyophilizer and the total protein was extracted using a plant total protein extraction kit (Sigma-Aldrich, St. Louis, MO, USA). Approximately 100 mg of the fine powder was placed in sterile Eppendorf tubes and 1 mL of ice-cold methanol-protease cocktail inhibitor (Cat. No. 15468-7, Sigma-Aldrich Co., St. Louis, MO, USA) was added; the resulting mix was vortexed, incubated at -20°C for 2 h and centrifuged for 10 mins at 4°C (Micro12, Fisher Scientific, Denver Instrument Co., USA). Following the removal of the supernatant, ice-cold methanol was added and incubated overnight at -20°C, followed by centrifugation at 13,000 rpm for 10 mins, followed by incubation in ice-cold methanol again for 1 h and centrifugation at the same speed. A similar incubation in acetone was performed to remove phenolics and secondary metabolites that might interfere with the LC-MS/MS (liquid chromatography tandem mass spectrometry) analysis. Following the removal of acetone from the samples, wash buffer solution (RW4) was added, vortexed for 30 s, and incubated for 30 mins at room temperature (22°C). The samples were centrifuged at 13,000 rpm for 10 minutes, and the supernatants were carefully collected in sterile tubes, which constituted the total proteins from leaves. Proteins were quantified using the Lowry method [ 21 ] and a sample of 10 µg of proteins in 20 µL of 1M urea were analyzed for untargeted proteomics at the Institute de Recherches Cliniques de Montréal (IRCM) for label-free shotgun proteomics. Total extracted proteins from trifoliate leaves were tryptic digested before analyses by LC-MS/MS on a Velos Orbitrap instrument (Thermo Fisher Scientific, Waltham, MA, USA). Proteins were solubilized in 20 µL of 8 M urea buffer. Reduction was performed by adding 10 µL of 45 mM dithiothreitol (DTT) in 100 mM ammonium bicarbonate, followed by incubation for 30 min at 37°C. Alkylation was carried out with 10 µL of 100 mM iodoacetamide in 100 mM ammonium bicarbonate, and samples were incubated for 30 min at 24°C in the dark. To remove nucleic acids, 50 units of benzonase were added in the presence of 2 mM MgCl₂ and incubated for 1 h at 37°C. Protein Aggregation Capture (PAC) digestion was then performed using hydroxyl-functionalized magnetic beads (ReSyn Biosciences). Ten µL of pre-washed beads were added to each sample, and proteins were precipitated by adjusting the acetonitrile concentration to 50%. Samples were incubated for 20 min at room temperature with agitation (1,000 RPM), placed on a magnetic rack for 2 min, and the supernatant was discarded. Beads were washed three times with 70% ethanol. For digestion, beads were resuspended in 100 µL of trypsin solution (0.0005 µg/µL Promega trypsin in 50 mM ammonium bicarbonate), sonicated in a water bath for 1 min, and incubated overnight at 37°C with shaking (700 RPM). Following digestion, peptides were recovered by placing samples on a magnetic rack, transferring the supernatant to Eppendorf LoBind tubes, and rinsing beads with 25 µL of 50 mM ammonium bicarbonate. The rinses were pooled with the corresponding digests. Samples were dried in a SpeedVac and stored at − 20°C until analysis. Before LC-MS/MS, peptides were reconstituted in 11 µL of 2% acetonitrile / 1% formic acid with agitation for 15 min. Separation was performed on a 75 µm i.d. × 150 mm self-packed C18 column using an Easy-nLC II system (Proxeon Biosystems) with a binary buffer system: buffer A (0.2% formic acid in water) and buffer B (90% acetonitrile, 0.2% formic acid). Peptides were eluted at 250 nL/min with a three-step gradient: 2–34% B over 120 min, 34–42% B over 14 min, and 42–80% B over 5 min. The LC system was coupled to an LTQ Orbitrap Velos mass spectrometer (Thermo Scientific) via a Nanospray Flex Ion Source. Data-dependent acquisition employed a 17-scan cycle: one full MS scan in the Orbitrap (resolution 60,000 at m/z 400) followed by MS/MS of the 16 most intense ions in the linear ion trap. MS scans were acquired over m/z 360–1600 with a target value of 1 × 10⁶ charges. MS/MS scans were collected from one-third of the parent ion m/z up to m/z 2000 with a target value of 10,000 charges. Maximum ion fill times were 100 ms, with one microscan per spectrum. Dynamic exclusion was set to 8 s. 2.5. Mass spectrometry data analysis and protein quantification Raw mass spectrometry (MS) data were processed using MaxQuant software (version v2.6.7.0). The spectra were searched against the Glycine max (85,130 sequences; accessed on June 2025 ) database from UniProtKB ( http://www.uniprot.org/ ). An initial precursor mass tolerance of 15 ppm was applied. Trypsin was specified as the digestion enzyme, allowing up to two missed cleavages and a fragment ion mass tolerance of 20 ppm. Carbamidomethylation of cysteine was set as a fixed modification, while N-terminal acetylation and methionine oxidation were treated as variable modifications. A global false discovery rate (FDR) threshold of < 1% was applied for both peptide-spectrum matches (PSMs) and protein identifications. Only proteins identified by at least two unique peptides and consistently detected in at least two of three replicates per sample were considered confidently identified and selected for downstream analysis. Protein quantification was carried out using LFQ based on peptide intensities. Match-between-runs functionality was enabled to align quantification data across replicates. Subsequent analysis of the MaxQuant-processed output (specifically the “proteinGroups.txt” file) was conducted in Perseus (v2.1.4.0). Reverse database hits, potential contaminants, and proteins identified solely by modified peptides were excluded from the dataset. Label-free quantification (LFQ) intensities were log-transformed, and proteins detected in all three replicates within at least one experimental group were retained for further analysis (valid-value filter = 3 in at least one group). Missing values were imputed using a normal distribution, applying a downshift of 1.8 and a width of 0.3 standard deviation to simulate low abundance. Significant differences were evaluated with Student’s t test (significance level = 0.05) with the multiple-hypothesis testing correction of Benjamini-Hochberg FDR = 0.05 with S 0 = 1) and the post hoc test used to identify pairwise group differences. The variability and associations in the data table were summarized into a small number of principal components (PC) using the multivariate statistical method of principal-component analysis (PCA). Proteins with a fold change greater than 1.5 and a p -value < 0.05 were identified as differentially abundant proteins (DAPs) compared to the control.SRplot (SRplot - Science and Research online plot) was used for visual representation of the data and results (e.g., PCA biplots). For pairwise comparisons, Student’s t -tests were performed in Perseus. Volcano plots were generated using a permutation-based FDR of 0.05 with an S₀ parameter of 1 to balance statistical significance with effect size. Annotation enrichment analysis was performed in Perseus using the 1D annotation enrichment function. The Benjamini–Hochberg procedure was applied to control the FDR, and a stringent significance threshold of FDR < 0.001 was used to identify significantly enriched annotations. Enrichment plots were generated in RStudio (R Core Team, version 4.5.1) using the ggplot2 package. 3. Results 3.1. Determining the optimal concentration of bacterial cultures based on their effect on seed germination Three Bacillus strains were tested for their potential to positively affect the seed germination of soybean. To this end, seeds were inoculated with three concentrations of Bacillus -HT1, Bacillus -HT2 and Bacillus -HT3 and seed germination was scored (Figs. 1 A-D). In addition, seed germination rates were determined revealing that the administration of Bacillus -HT1 at 10 7 CFU increased the seed germination rate of soybean in statistically significant manner compared to the uninoculated control and. However, this effect was not detectable until 48h after administration of the treatment (Fig. 2 A). Bacillus -HT2, 10 7 CFU increased seed germination significantly at all tested time points compared to the control (Fig. 2 B). However, none of the concentrations of Bacillus -HT3 tested showed any statistically significant effect on soybean seed germination (Fig. 2 C). Based on these results, 10 7 CFU was chosen as the working concentration for Bacillus -HT1 and Bacillus- HT2 for subsequent experiments to assay for plant growth promotion at the vegetative stage. While not generating any positive effect on seed generation, we nevertheless decided to test Bacillus -HT3 at 10 7 CFU for potential growth stimulating effects at the vegetative stage. 3.2. Effects of Bacillus strains on soybean plant growth at the vegetative stage Based on the screening test results described above, 10 7 CFU was chosen as a suitable concentration for testing the effect of Bacillus -HT1, Bacillus -HT2 and Bacillus -HT3 on soybean at the vegetative stage. At the age of 28 days, plants produced from the soybean seeds coated with Bacillus -HT1, HT2 and HT3 were tested for change in fresh and dry biomass, plant height, chlorophyll content, and leaf area (Figs. 3 A-E). The results showed that only Bacillus -HT3 showed a pronounced effect on leaf area whereas Bacillus -HT1 and Bacillus -HT2 did not lead to any changes in plant traits at the concentrations tested (Fig. 3 D). Plant roots were analyzed for changes in root length, root surface area, root weight, and root projection area. None of the bacterial strains led to any changes in root parameters (Figs. 4 A-D). 3.3. Protein profiling Comparative analysis of total proteins extracted from leaves from plants treated with Bacillus -HT1, HT2, and HT3 revealed distinct changes in protein abundance patterns. Label-Free Quantification (LFQ) intensities and corresponding spectral annotations are provided in Supplementary sheet-Table 1. 3.3.1. Multivariate analysis On a global scale, the PCA demonstrates clear clustering patterns among the treatments and the control, indicating treatment-specific proteomic shifts (Fig. 5 A). The PCA biplot (Fig. 5 ) revealed that the three replicates in each treatment group, including the control, were similarly dispersed, suggesting comparable degrees of variability within groups. Notably, the replicates of the control clustered near the center of the biplot, indicating a proteomic profile that represents the dataset’s centroid. In contrast, replicates of Bacillus -treated samples were positioned farther from the center, consistent with treatment-specific proteomic shifts. The profile plot (Fig. 5 B) derived from the post hoc test highlights a unique protein production pattern in Bacillus -HT3-treated plants, distinct from both Bacillus -HT1, HT2, and the control group. This indicates that Bacillus -HT3 induces a unique proteomic response, likely linked to enhanced metabolic and stress-related processes. 3.3.2. Univariate analysis Figure 5 illustrates the number of significantly higher and lower abundance proteins across all three treatments compared to the control. In the present study, no proteins with significantly differential abundance were identified in the leaves of plants treated with Bacillus -HT1 or HT2 compared to the control. In the case of Bacillus -HT3 treatment, the abundance of 10 proteins was lower than in the control, while a group of 10 different proteins was significantly more abundant. Supplementary sheet 1 (Table 2) provides detailed information on the 20 differentially abundant proteins, ranked by their abundance difference. The abundant proteins in the leaves of Bacillus -HT3-treated plants included important proteins like glucan endo-1,3-beta-D-glucosidase, methionine adenosyl transferase and 20 kDa chloroplastic chaperonin. Proteins with increased abundance in Bacillus -HT3-treated plants were primarily associated with ion transmembrane transport, ATPase activity, protein folding, signal transduction, and biosynthetic and catabolic processes. These proteins are localized to diverse subcellular structures, including the cytoplasm, nucleus, ribosome, proteasome, and membrane complexes. In contrast, proteins more abundant in Bacillus -HT3-treated plants were enriched in peptidase activity, cytoskeleton organization, and regulatory functions such as enzyme inhibition and protein modification. This contrast suggests that Bacillus -HT3 treatment reprograms key cellular processes toward energy metabolism, protein synthesis, and signalling, while untreated plants maintain higher levels of structural and regulatory proteins. These findings suggest that Bacillus -HT3 induces distinct proteomic changes in the host plant, potentially reflecting a stronger or more specific interaction compared to Bacillus -HT1 and HT2. 3.3.3. Enrichment analysis Functional enrichment analysis revealed treatment-specific reprogramming of soybean leaf proteins in response to Bacillus inoculation as shown in Fig. 7 and Supplementary sheet 1 (Table 3). In the Bacillus -HT1 vs Control (Fig. 7 A) comparison, negatively enriched categories dominated, including cellular process, cellular metabolic process, and biosynthetic process, along with translation-related terms such as translation, peptide biosynthetic process, and peptide metabolic process. The suppression of these biosynthetic and metabolic pathways suggests that HT1 primarily attenuated host protein synthesis relative to the control. In contrast, the Bacillus- HT2 vs Control (Fig. 7 B) comparison displayed a distinct enrichment profile characterized by positive enrichment of several metabolic categories, including small molecule metabolic process, carboxylic acid metabolic process, oxoacid metabolic process, and organic acid metabolic process. Pathways such as small molecule biosynthetic process and organic acid biosynthetic process were also significantly upregulated, whereas macromolecular biosynthesis (e.g., macromolecule biosynthetic process, peptide biosynthetic process) exhibited negative enrichment. These results indicate that HT2 preferentially enhanced primary and small-molecule metabolism while suppressing large-scale biosynthetic processes. By contrast, Bacillus- HT3 vs. Control exhibited the broadest enrichment pattern, with strong positive enrichment of photosynthesis- and chloroplast-related categories alongside metabolic pathways such as organic acid biosynthetic process and small molecule biosynthetic process. The presence of several highly significant terms with large enrichment scores suggests that HT3 treatment promoted a coordinated upregulation of both metabolic and structural functions, consistent with its observed effect on leaf expansion and biomass accumulation. Gene Ontology (GO) enrichment based on post hoc analysis (Table 1 ) revealed that proteins involved in cellular component organization and microtubule organization were produced at significantly higher levels in plants from seeds treated with Bacillus -HT2 and HT3 supporting their roles in cytoskeletal and organelle organization. In contrast, proteins associated with intracellular organelle components were significantly enriched in Bacillus -HT1 and HT2-treated plants suggesting that these treatments influenced intracellular compartmentalization. Notably, Bacillus -HT3 treatment induced significantly higher abundance of proteins involved in various metabolic pathways, including amino acid metabolism and biosynthetic processes, compared to the control confirming the broad metabolic stimulation inferred from the enrichment analysis. Table 1 Post Hoc comparison of protein abundance in soybean leaves of plants treated with Bacillus species Proteins ID -log ANOVA P-value GOBP Slim Significant Pairs A0A0R0ER52; C6SZE7; C6SXS0; I1LWT2 5.741931 cellular component organization; cellular component organization or biogenesis; cellular process; cytoskeleton organization; microtubule cytoskeleton organization; microtubule-based process; organelle organization Control_ Bacillus -HT3; Bacillus -HT2_ Bacillus -HT3; Bacillus -HT1_ Bacillus -HT3 I1J8Y8;C6SV99 6.28034692458043 cellular anatomical entity; intracellular membrane-bounded organelle; intracellular organelle; membrane; nucleus; organelle Bacillus -HT2_ Bacillus -HT3; Bacillus -HT1_ Bacillus -HT3; Control_ Bacillus -HT3 C6TMD6; C6TG97 ;C6T4I5;I1K1X5 4.78750116803613 cellular anatomical entity; cytoplasm; intracellular membrane-bounded organelle; intracellular organelle; nucleus; organelle; protein-containing complex Bacillus -HT2_ Bacillus -HT3; Bacillus -HT1_ Bacillus -HT3; Control_ Bacillus -HT3 I1NF54;I1NF5; A0A0R0EVG9;A0A0R0F675;K7MPL4 4.6640872956235 metabolic process; amino acid metabolic process; biosynthetic process; cellular aromatic compound metabolic process; cellular nitrogen compound metabolic process; cellular process; heterocycle metabolic process; metabolic process; nitrogen compound metabolic process; organic acid metabolic process; primary metabolic process; small molecule metabolic process Bacillus -HT2_Control; Bacillus -HT3_Control; Bacillus -HT2_ Bacillus -HT1; Bacillus -HT3_ Bacillus -HT1 4. Discussion The endophytic microbiome of the soybean plant is of great interest because of the specialized signals released by the soybean roots that attract the beneficial microbes from the surrounding community [ 9 ]). Many studies have been conducted on endophytes of plants, but questions remain regarding how they enter the seed, what they do inside, and whether they are stable populations or just passersby. Despite this scarcity of knowledge, endophytes have opened new possibilities for applying microbes for sustainable crop production. Soybean plant endophytes have the potential to inhibit the growth of pathogens, enhance yield and plant growth, and improve the growth regulatory mechanism of plants. They exert lasting influence on both the endosphere and rhizosphere microbiomes, ultimately impacting overall plant productivity—a phenomenon referred to as the “priority effect” in microbial ecology [ 22 ]). Collectively, these effects of the microbiome can improve overall plant growth which can be leveraged for sustainable crop protection. In a previous study, we isolated the bacterial strains used here from soybean plant roots and tested them for their potential antagonism against the pathogen Fusarium oxysporum. Using a dual confrontation assay we showed that the Bacillus -HT1 and HT2 inhibit the growth of F. oxysporum isolated from a soybean plant and identified putative antifungal metabolites produced by these microorganisms [ 21 ]. In the present study, we showed that Bacillus -HT1 and Bacillus- HT2 have pronounced effects on soybean seed germination, whereas Bacillus -HT3 did not enhance germination at any of the concentrations tested. Seed germination, together with seed vigour, represents a key factor in determining crop yield and affects the initial rate of plant growth. Seed germination is a very important stage in the life cycle of a plant and one that is very sensitive to both the intrinsic and extrinsic factors. The present study found that Bacillus -HT1 and Bacillus -HT2 improve the germination rate compared to the unprimed control. Shah et al. [ 23 ]noted that in germination assays, nearly all seeds typically germinate by the final assessment point, regardless of treatment, except in cases where germination is inhibited, such as with the high bacterial concentration observed in the present study. However, maximum seed germination was often attained much earlier for treated seeds than for untreated seeds, depending on the efficacy of the biostimulants or the technique used. In this study, the enhancement in the final seed germination rate in plants treated with Bacillus -HT1 and Bacillus -HT2 was statistically significant compared to the control. Bacillus- HT2 significantly improved the seed germination rate at early time points and seeds attained the final seed germination level much before the untreated seeds, whereas Bacillus -HT3 lack the potential to initiate early seed germination and improved final germination. These findings are aligned with Sari et al [ 24 ] who showed that the rhizobacterial treatment on the germination process had a significantly increased effect on maximum growth potential, germination, vigour index and growth simultaneity on chilli seeds. Pérez-García et al [ 25 ] found similar results biopriming of rhizobacteria with Bacillus cereus, Acinetobacter radioresistens, Pseudomonas paralactis and Sinorhizobium meliloti on some parameters, such as the percentage of germination and vigor and the germination index in the seeds of Cucumis sativus L. These findings suggest that the two bacterial strains Bacillus -HT1 and HT2 have the potential to be potential biostimulants that act by inducing early and highly efficient seed germination, whereas Bacillus -HT3 does not. This leads us to conclude that while all three strains are endophytes, their effects differ and they either induce seed germination or improve growth at the vegetative stage followed by overall changes in the physiology of soybean plants. In the present study, the optimal working concentration was 10 7 CFU for all three bacterial strains. When applied on the plants, Bacillus -HT3 did not show a pronounced effect at the initial seed germination stage, but it proved to have the most pronounced beneficial effects on plant growth at the late vegetative as expressed, for example, by increased the leaf surface area. This effect has been observed for other plant growth-promoting bacteria (PGPR) where it is mediated by dissolving phosphorus and fixed nitrogen, that the plant leverages for enhanced leaf growth [ 26 ][ 27 ]. Our observations are aligned with the findings of Elbagory et al [ 28 ] that PGPR, Azospirillum lipoferum and Pseudomonas koreneesis , along with vermicompost, improve biomass and leaf area of lettuce plant. The application of plant growth-promoting Bacillus strains resulted in distinct physiological and molecular responses, with Bacillus -HT3 showing the most pronounced effects on vegetative growth. Specifically, Bacillus -HT3 treatment significantly increased leaf area, suggesting enhanced photosynthetic capacity and overall plant vigour. Our proteomic analysis demonstrates that Bacillus inoculation triggers distinct and strain-specific reprogramming of the soybean leaf proteome, which can be directly linked to the phenotypic outcomes observed. Proteomic analysis further supported this observation, as Bacillus -HT3-treated plants exhibited a distinct production profile characterized by the elevated abundance of proteins involved in amino acid metabolism, biosynthetic processes, and other metabolic pathways associated with growth and development. The unique clustering pattern of HT3-treated samples in the PCA and post hoc profile plots underscore the differential regulatory effects of this strain at the molecular level. Interestingly, the PCA biplot also suggests that the degree of variability among the replicates of the control was comparable to that observed among the Bacillus -treated samples. While such variability is statistically acceptable and supports the assumptions of ANOVA, it raises a biologically meaningful consideration. The proteomic divergence among control replicates may reflect slight differences in endogenous microbial populations, even in the absence of exogenous inoculation. Consequently, the observed proteomic responses may not be solely attributable to the introduced Bacillus strains but may also arise from their interactions with resident microbial communities. These interactions could influence host proteomic responses in complex, context-dependent ways. Kaya [ 29 ] reported that the convergence of microbial activity within the rhizosphere and endosphere represents a critical interface where modulation of hormone signaling and proteomic dynamics occurs. This interpretation is supported by the distinct spatial separation of Bacillus -treated samples in the PCA, indicating that the microbial additions induced shifts away from the average (centred) proteomic profile observed in control plants. The Bacillus -HT1 treatment was characterized by negative enrichment of biosynthetic and translational categories (e.g., translation, peptide biosynthetic process), suggesting reduced leaf protein synthesis. Despite this suppression, HT1 significantly enhanced seed germination, indicating that metabolic resources may be redirected from sustained leaf protein production toward early developmental processes. This observation is consistent with the known ability of PGPR to promote germination by modulating energy mobilization and stress signaling [ 30 ][ 31 ]. Furthermore, our earlier work demonstrated that HT1 exhibits biocontrol activity [ 21 ], and the suppression of biosynthetic pathways alongside enrichment of defense-related processes (e.g., cellular component organization, intracellular organelle functions) may reflect its role in priming host immunity while supporting germination. Similarly, Bacillus -HT2 promoted metabolic flexibility, with positive enrichment of small molecule metabolic and organic acid biosynthetic pathways and significant upregulation of proteins linked to cellular and organelle organization. These changes align with the strain's dual activity in enhancing seed germination and vigor while providing biocontrol capacity, as previously reported. The ability of HT2 to activate metabolic priming alongside immune-related processes highlights its potential as a versatile PGPR strain capable of balancing early growth promotion with host defense support. Seed treatment with PGPR induces structural reinforcement of the cell wall and triggers physiological and biochemical changes that stimulate the synthesis of defense-related proteins, peptides, and metabolites [ 32 ]. By contrast, Bacillus -HT3 triggered pronounced responses in terms of protein enrichment, with strong positive regulation of photosynthesis, chloroplast organization, amino acid biosynthesis, and microtubule organization. These changes are consistent with observed effects on leaf expansion and biomass accumulation, indicating that HT3 functions predominantly as a growth-promoting strain. Unlike HT1 and HT2, however, HT3 did not demonstrate biocontrol properties in our previous study, suggesting that its functional contribution is directed more towards enhancing vegetative growth rather than defense. For instance, the present study found that anthranilate synthase (I1NF54) is more abundant in Bacillus -HT2 and Bacillus -HT3 treated plants. Anthranilate and its derivatives are precursors for important secondary metabolites, including indole-3-acetic acid (IAA), a major plant hormone in the auxin class, which is crucial for cell elongation and differentiation [ 33 ][ 34 ]. Therefore, elevated abundance of anthranilate synthase can be associated with enhanced auxin biosynthesis and overall plant growth promotion. The broader metabolic reprogramming triggered by Bacillus -HT3, beyond tryptophan metabolism, may explain its stronger effect on leaf area expansion compared to Bacillus -HT2. In contrast, Bacillus -HT1 and HT2 treatments were particularly effective in promoting early-stage growth, as evidenced by their significant enhancement of seed germination rates which may linked to enrichment of proteins involved in cellular component organization, microtubule organization, and intracellular organelle function. Such proteins play essential roles in cell division, cytoskeleton dynamics, and organelle integrity, which are critical during the early stages of seedling establishment [ 35 ][ 36 ]. For instance, the proteasome subunit alpha type (I1K1X5), upregulated in HT1 and HT2-treated plants, is part of the ubiquitin–proteasome system that regulates seed germination by mobilizing storage reserves and modulating growth repressors [ 36 ][ 38 ][ 39 ][ 40 ]). Together, these findings reveal that different Bacillus strains exert distinct growth-promoting effects depending on the developmental stage of the plant. While Bacillus -HT1 and HT2 contribute significantly to seed germination and early cellular organization, Bacillus -HT3 has a broader influence on vegetative growth through the activation of metabolic and biosynthetic pathways. While the observed increased abundance of proteins such as proteasome subunit alpha type suggests mechanistic insights into potential plant growth-promoting effects of Bacillus treatments, these interpretations warrant further validation. Future studies could be conceived to be based on inhibit these pathways (e.g., anthranilate synthase or proteasome activity) to directly test their roles in Bacillus -mediated growth promotion. Notably, the current study focused on the proteomic profiling of soybean leaves at a later developmental stage and did not include proteomic analysis of seedlings or germinating seeds. As a result, the molecular basis underlying the enhanced seed germination observed in Bacillus -HT1 and HT2 treatments remains indirect and inferred from later-stage protein production. Given that seed germination is a highly regulated and temporally distinct process involving unique signaling cascades and proteolytic mechanisms, it is crucial to examine the proteomic landscape of seedlings during early developmental windows to directly link bacterial treatment with molecular changes driving plant germination. Future studies should include temporal proteomics of germinating seeds and early seedlings to determine whether Bacillus -induced activation of the ubiquitin-proteasome pathway and tryptophan-derived auxin biosynthesis occurs at the onset of development. This would help clarify whether the observed increase in seed germination is directly mediated by early protein-level changes or whether it is the cumulative outcome of downstream physiological modulation. This duality highlights the potential for strategic use of specific PGPR strains to target different stages of plant development, contributing to optimized and sustainable crop production systems. 5. Conclusion Seed germination is a tightly regulated and temporally distinct developmental phase, orchestrated by specific signaling pathways and proteolytic mechanisms. In this study, enrichement analysis revealed strain specific effects of Bacillus treatment on soybean development. Bacillus -HT1 and HT-2 were associated with enrichment of categories linked to cellular component organization, microtubule dynamics, and intracellular organelle function, which may underlie their strong effects on seed germination and early establishment whereas Bacillus -HT3 induced broader enrichment of photosynthesis, chloroplast organization, and biosynthetic pathways, consistent with its pronounced impact on leaf expansion and biomass accumulation. Moreover, functional inhibition of these enriched pathways—such as cytoskeleton organization, proteasome-mediated turnover, or auxin biosynthesis—will be critical to confirm their causal role in Bacillus -mediated growth promotion. However, since our analysis focused on mature leaf tissue, the molecular basis of enhanced seed germination required further investigation. Our findings underscore the importance of investigating the early proteomic landscape during seed germination to directly link bacterial treatment with the molecular events that drive developmental transitions. Future studies incorporating temporal proteomics of germinating seeds and seedlings are essential to determine whether Bacillus -induced activation of key regulatory pathways occurs at the onset of development. Such insights would clarify whether improved germination outcomes arise from early protein-level reprogramming or are the result of downstream physiological changes. Overall, this dual perspective highlights the potential for strategic application of specific PGPR strains to modulate distinct stages of plant development, offering a promising avenue toward more sustainable and targeted crop management practices. Declarations 6. Author contributions: H.T. performed the experiments and wrote the manuscript. P.D. assisted with statistical analysis and provided comprehensive guidelines and edited the manuscript. J.G.-M guided proteomic analysis and participated in manuscript review and revision. D.S. and A.G. supervised the planning and execution of the project, provided funding and edited the manuscript. All authors have read and agreed to the published version of the manuscript. 7. Acknowledgements : The authors extend special thanks to Dr. Denis Faubert’s group at Institute de recherches cliniques de Montréal (IRCM) for providing label-free LC-MS/MS metabolomics services. The authors gratefully acknowledge Jason McAlister for his valuable guidance and support in data analysis. 8. Funding: This research was funded Biomass Canada Cluster. The Biomass Canada Cluster is managed by BioFuelNet Canada and is funded by the Government of Canada under the Sustainable Canadian Agricultural Partnership and industrial partners. 10. Data availability statement The RAW and affiliated files deposited into the publicly available PRIDE partner database for the ProteomeXchange consortium with accession number PXD065756 11. Ethics, Consent to Participate, and Consent to Publish declarations: Not applicable. References Fitzpatrick, C. R., Copeland, J., Wang, P. W., Guttman, D. S., Kotanen, P. M., & Johnson, M. T. (2018). Assembly and ecological function of the root microbiome across angiosperm plant species. Proceedings of the National Academy of Sciences , 115 (6), E1157-E1165. Gupta, A., Mishra, R., Rai, S., Bano, A., Pathak, N., Fujita, M., ... & Hasanuzzaman, M. (2022). Mechanistic insights of plant growth promoting bacteria mediated drought and salt stress tolerance in plants for sustainable agriculture. International Journal of Molecular Sciences , 23 (7), 3741. Sharma, M. M. M., Sharma, P., Kapoor, D., Beniwal, P., & Mehta, S. (2021). Phytomicrobiome community: an agrarian perspective towards resilient agriculture. Plant performance under environmental stress: hormones, biostimulants and sustainable plant growth management , 493-534. Ali, S., Tyagi, A., Park, S., Mir, R. A., Mushtaq, M., Bhat, B., ... & Bae, H. (2022). Deciphering the plant microbiome to improve drought tolerance: mechanisms and perspectives. Environmental and Experimental Botany , 201 , 104933. Uroz, S., Courty, P. E., & Oger, P. (2019). Plant symbionts are engineers of the plant-associated microbiome. Trends in plant science , 24 (10), 905-916. Lyu, D., Zajonc, J., Pagé, A., Tanney, C. A., Shah, A., Monjezi, N., ... & Smith, D. L. (2021). Plant holobiont theory: the phytomicrobiome plays a central role in evolution and success. Microorganisms , 9 (4), 675. Astapati, A. D., & Nath, S. (2023). The complex interplay between plant-microbe and virus interactions in sustainable agriculture: Harnessing phytomicrobiomes for enhanced soil health, designer plants, resource use efficiency, and food security. Crop Design , 2 (1), 100028. Longley, R., Noel, Z. A., Benucci, G. M. N., Chilvers, M. I., Trail, F., & Bonito, G. (2020). Crop management impacts the soybean (Glycine max) microbiome. Frontiers in microbiology , 11 , 1116. Ayilara, M. S., Adeleke, B. S., & Babalola, O. O. (2023). Bioprospecting and challenges of plant microbiome research for sustainable agriculture, a review on soybean endophytic bacteria. Microbial ecology , 85 (3), 1113-1135. Agyekum, D. V., Kobayashi, T., Dastogeer, K. M., Yasuda, M., Sarkodee-Addo, E., Ratu, S. T., ... & Okazaki, S. (2023). Diversity and function of soybean rhizosphere microbiome under nature farming. Frontiers in Microbiology , 14 , 1130969. Anguraj Vadivel, A. K., Sukumaran, A., Li, X., & Dhaubhadel, S. (2016). Soybean isoflavonoids: role of GmMYB176 interactome and 14-3-3 proteins. Phytochemistry Reviews , 15 , 391-403. Sugiyama, A., & Yazaki, K. (2014). Flavonoids in plant rhizospheres: secretion, fate and their effects on biological communication. Plant Biotechnology , 31 (5), 431-443. Dong, W., & Song, Y. (2020). The significance of flavonoids in the process of biological nitrogen fixation. International journal of molecular sciences , 21 (16), 5926. Srinivasa, C., Mellappa, G., Patil, S. M., Ramu, R., Shreevatsa, B., Dharmashekar, C., ... & Shivamallu, C. (2022). Plants and endophytes–a partnership for the coumarin production through the microbial systems. Mycology , 13 (4), 243-256. Wen, Y., Liao, Y., Tang, Y., Zhang, H., Zhang, J., & Liao, Z. (2023). Metabolic effects of elicitors on the biosynthesis of tropane alkaloids in medicinal plants. Plants , 12 (17), 3050. Sardans, J., Gargallo‐Garriga, A., Urban, O., Klem, K., Holub, P., Janssens, I. A., ... & Peñuelas, J. (2021). Ecometabolomics of plant–herbivore and plant–fungi interactions: a synthesis study. Ecosphere , 12 (9), e03736. Dudeja, S. S., Suneja‐Madan, P., Paul, M., Maheswari, R., & Kothe, E. (2021). Bacterial endophytes: molecular interactions with their hosts. Journal of basic microbiology , 61 (6), 475-505. Zhao, L., Xu, Y., & Lai, X. (2018). Antagonistic endophytic bacteria associated with nodules of soybean (Glycine max L.) and plant growth-promoting properties. Brazilian Journal of Microbiology , 49 (2), 269-278. Zulfiqar, U., Haider, F. U., Maqsood, M. F., Mohy-Ud-Din, W., Shabaan, M., Ahmad, M., ... & Shahzad, B. (2023). Recent advances in microbial-assisted remediation of cadmium-contaminated soil. Plants , 12 (17), 3147. Kim, J., Ahn, S. H., Yang, J. S., Choi, S., Jung, H. W., & Jeon, J. (2023). Plant protective and growth-promoting effects of seed endophytes in soybean plants. The Plant Pathology Journal , 39 (5), 513. Tariq, H., Viau, C., Subramanian,S., Geitmann, A. & Donald L Smith (2025).Exo-metabolome profiling of soybean endophytes: A road map of antagonism against Fusarium oxysporum . Msystems.In press Dubey, A., Saiyam, D., Kumar, A., Hashem, A., Abd_Allah, E. F., & Khan, M. L. (2021). Bacterial root endophytes: Characterization of their competence and plant growth promotion in soybean (Glycine max (L.) Merr.) under drought stress. International Journal of Environmental Research and Public Health , 18 (3), 931. Shah, A., Subramanian, S., & Smith, D. L. (2022). Seed priming with Devosia sp. cell-free supernatant (CFS) and citrus bioflavonoids enhance canola and soybean seed germination. Molecules , 27 (11), 3410. Sari, R. N., Hafsah, S., & Hidayat, T. (2024, February). The effect of seed treatment using plant growth promoter rhizobacteria (PGPR) on the germination process of chili (Capsicum annum L.). In IOP Conference Series: Earth and Environmental Science (Vol. 1297, No. 1, p. 012010). IOP Publishing. Pérez-García, L. A., Sáenz-Mata, J., Fortis-Hernández, M., Navarro-Muñoz, C. E., Palacio-Rodríguez, R., & Preciado-Rangel, P. (2023). Plant-growth-promoting rhizobacteria improve germination and bioactive compounds in cucumber seedlings. Agronomy , 13 (2), 315. Johnson, N. C. (2010). Resource stoichiometry elucidates the structure and function of arbuscular mycorrhizas across scales. New Phytologist , 185 (3), 631-647. Hasan, A., Tabassum, B., Hashim, M., & Khan, N. (2024). Role of Plant Growth Promoting Rhizobacteria (PGPR) as a Plant Growth Enhancer for Sustainable Agriculture: A Review. Bacteria 2024, 3, 59–75. Interaction between Plants and PGPR for Sustainable Development , 1. Elbagory, M., Farrag, D. K., & Doha, N. M. (2024). Effects of PGPR inoculation and Vermicompost on the growth, physiological traits, microbial activity, and yield of lettuce (Lactuca sativa L.) plants. Environment, Biodiversity and Soil Security , 8 (2024), 83-95. Kaya, C. (2024). Microbial modulation of hormone signaling, proteomic dynamics, and metabolomics in plant drought adaptation. Food and Energy Security , 13 (1), e513. Jalmi, S. K., & Sinha, A. K. (2022). Ambiguities of PGPR-induced plant signaling and stress management. Frontiers in microbiology , 13 , 899563. Tripathi, A., Pandey, V. K., Jain, D., Singh, G., Brar, N. S., Taufeeq, A., ... & Rustagi, S. (2024). An updated review on significance of PGPR-induced plant signalling and stress management in advancing sustainable agriculture. Journal of Agriculture and Food Research , 16 , 101169 Meena, M., Swapnil, P., Divyanshu, K., Kumar, S., Harish, Tripathi, Y. N., ... & Upadhyay, R. S. (2020). PGPR‐mediated induction of systemic resistance and physiochemical alterations in plants against the pathogens: Current perspectives. Journal of Basic Microbiology , 60 (10), 828-861 Fattorini, L., Veloccia, A., Della Rovere, F., D’angeli, S., Falasca, G., & Altamura, M. M. (2017). Indole-3-butyric acid promotes adventitious rooting in Arabidopsis thaliana thin cell layers by conversion into indole-3-acetic acid and stimulation of anthranilate synthase activity. BMC plant biology , 17 , 1-14. Ali, J., Mukarram, M., Ojo, J., Dawam, N., Riyazuddin, R., Ghramh, H. A., ... & Bayram, A. (2024). Harnessing phytohormones: Advancing plant growth and defence strategies for sustainable agriculture. Physiologia Plantarum , 176 (3), e14307. Yan, H., Chaumont, N., Gilles, J. F., Bolte, S., Hamant, O., & Bailly, C. (2020). Microtubule self-organisation during seed germination in Arabidopsis. BMC biology , 18 , 1-15. Kumar, S., Jeevaraj, T., Yunus, M. H., Chakraborty, S., & Chakraborty, N. (2023). The plant cytoskeleton takes center stage in abiotic stress responses and resilience. Plant, cell & environment , 46 (1), 5-22. Han, C., He, D., Li, M., & Yang, P. (2014). In-depth proteomic analysis of rice embryo reveals its important roles in seed germination. Plant and Cell Physiology , 55 (10), 1826-1847. Xu, F. Q., & Xue, H. W. (2019). The ubiquitin‐proteasome system in plant responses to environments. Plant, cell & environment , 42 (10), 2931-2944. Blanco-Touriñán, N., Serrano-Mislata, A., & Alabadí, D. (2020). Regulation of DELLA proteins by post-translational modifications. Plant and Cell Physiology , 61 (11), 1891-1901. Srivastava, A. K., Suresh Kumar, J., & Suprasanna, P. (2021). Seed ‘primeomics’: plants memorize their germination under stress. Biological Reviews , 96 (5), 1723-1743. Additional Declarations No competing interests reported. Supplementary Files Supplementarysheet1.xlsx Graphicalabstract.jpg Cite Share Download PDF Status: Published Journal Publication published 27 Dec, 2025 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 14 Nov, 2025 Reviews received at journal 26 Oct, 2025 Reviews received at journal 23 Oct, 2025 Reviewers agreed at journal 22 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers invited by journal 25 Sep, 2025 Editor assigned by journal 19 Sep, 2025 Editor invited by journal 17 Sep, 2025 Submission checks completed at journal 17 Sep, 2025 First submitted to journal 17 Sep, 2025 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. 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11:16:37","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140941,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/bb3f5136651d8b64c8832279.html"},{"id":92940423,"identity":"9d356bac-ec12-433a-9815-7e91430bdc38","added_by":"auto","created_at":"2025-10-07 11:16:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":419769,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSeed Germination assay\u003c/strong\u003e. Effect of different cell concentrations of \u003cem\u003eBacillus sp. \u003c/em\u003eon seed germination of soybean after 48h. Seeds were treated in the petri plates with 5 mL of 10 mM MgSO₄ (Control, A) or 5 mL of cell suspension of \u003cem\u003eBacillus\u003c/em\u003e-HT1 (B), \u003cem\u003eBacillus-\u003c/em\u003eHT2 (C),\u003cem\u003e \u003c/em\u003eor\u003cem\u003e Bacillus-\u003c/em\u003eHT3 (D) at CFU of 10⁶ or 10⁷, or 10⁸ in 10 mM MgSO₄.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/885895377546c05ac9dec0fe.jpg"},{"id":92941228,"identity":"3e7f5c29-b4f1-450c-9ae0-24aeb79c71fa","added_by":"auto","created_at":"2025-10-07 11:24:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":193106,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGermination rate\u003c/strong\u003e. Effect of different cell concentrations of \u003cem\u003eBacillus sp. \u003c/em\u003eon seed germination of soybean. Seeds were treated in the petri plates with 5 mL of 10 mM MgSO₄ (Control) or 5 mL of cell suspension of \u003cem\u003eBacillus\u003c/em\u003e-HT1 (B), \u003cem\u003eBacillus-\u003c/em\u003eHT2 (C),\u003cem\u003e \u003c/em\u003eor\u003cem\u003e Bacillus-\u003c/em\u003eHT3 (D) at CFU of 10⁶ or 10⁷, or 10⁸ in 10 mM MgSO₄. Values represent Mean ± SE (n = 20) and asterisk on the bar showed significant change among treatments and control (a = 0.05).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/2a418fb4123de56cb680d019.jpg"},{"id":92941229,"identity":"c69e6e25-5e0d-4f3c-9f85-cad75050ec14","added_by":"auto","created_at":"2025-10-07 11:24:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":191252,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhysiological parameters and biomass analysis\u003c/strong\u003e: (A) Fresh biomass, (B) Dry biomass, (C) Plant height, (D) Leaf area, (E) Chlorophyll content of leaves. Soybean seeds were treated with 5 mL of 10 mM MgSO₄ (Control) or 5 mL of cell suspension of \u003cem\u003eBacillus\u003c/em\u003e-HT1, \u003cem\u003eBacillus-\u003c/em\u003eHT2,\u003cem\u003e \u003c/em\u003eor\u003cem\u003e Bacillus-\u003c/em\u003eHT3 \u0026nbsp;at CFU 10⁷ in 10 mM MgSO₄. Values represent Mean ± SE (n = 9) and no letters on the bar showed no significant change among treatments (a = 0.05).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/6b4f3e75c6cb9a3ae8213daf.jpg"},{"id":92940426,"identity":"4fe2c800-1f09-4bca-8bf9-8e1e22c2b7f0","added_by":"auto","created_at":"2025-10-07 11:16:37","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":62776,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRoot analysis\u003c/strong\u003e: (A) Root length, (B) Root surface area, (C) Root dry weight (D) Root projection area. Soybean seeds were treated with 5 mL of 10 mM MgSO₄ (Control) or 5 mL of cell suspension of \u003cem\u003eBacillus\u003c/em\u003e-HT1, \u003cem\u003eBacillus-\u003c/em\u003eHT2,\u003cem\u003e \u003c/em\u003eor\u003cem\u003eBacillus-\u003c/em\u003eHT3 at CFU 10⁷ in 10 mM MgSO₄. Values represent Mean ± SE (n = 9) and no letters on the bar showed no significant change among treatments (a = 0.05).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/3e70a70c376f7b772636df8d.jpg"},{"id":92941398,"identity":"8a2bc404-fd55-4c7e-9367-989c7e3f2d5e","added_by":"auto","created_at":"2025-10-07 11:32:37","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":156814,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrincipal Component Analysis (PCA) and profile plot of proteomic data\u003c/strong\u003e. (A) PCA score plot illustrating the clustering of biological replicatesof control, \u003cem\u003eBacillus\u003c/em\u003e-HT1, HT2, and HT3 treatments, based on LFQ intensities. Distinct clustering indicates treatment-specific proteomic profiles. (B) Profile plot showing the abundance patterns of significantly altered proteins (identified via post hoc test, p ≤ 0.05) across treatments. \u003cem\u003eBacillus\u003c/em\u003e-HT3 exhibits a proteomic profile distinct from HT1, HT2, and the control group.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/eed86fe90765246459341be8.jpg"},{"id":92940447,"identity":"c4b659b7-aff1-4901-81e4-0e0302d5332e","added_by":"auto","created_at":"2025-10-07 11:16:37","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":133076,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolcano plots. \u003c/strong\u003eVolcano plot illustrating the distribution of differentially quantified proteins of soybean leaves as -log10 (p-values) plotted against log₂ (fold change)\u003cstrong\u003e.\u003c/strong\u003e (A) Differentially abundant protein in leaves of \u003cem\u003eBacillus\u003c/em\u003e-HT1-treated plants vs. Control. D) Differentially abundant protein in \u003cem\u003eBacillus-\u003c/em\u003eHT2-treated plants vs. Control. (E) Differentially abundant proteins in \u003cem\u003eBacillus-\u003c/em\u003eHT3-treated plants vs. Control\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/e61c1073f0030a2c6e788652.jpg"},{"id":92941232,"identity":"80393c1c-2385-4501-b041-d1b166af948e","added_by":"auto","created_at":"2025-10-07 11:24:37","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":174057,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional enrichment of differentially abundant proteins in soybean leaves in response to \u003cem\u003eBacillus\u003c/em\u003etreatments. Enrichment was assessed using 1D annotation in Perseus with Student’s \u003cem\u003et\u003c/em\u003e-test (FDR ≤ 0.001). Bubble plots display enriched Gene Ontology (GO) terms for (A) \u003cem\u003eBacillus\u003c/em\u003e-HT1 vs Control, (B) \u003cem\u003eBacillus\u003c/em\u003e-HT2 vs Control, and (C) \u003cem\u003eBacillus\u003c/em\u003e-HT3 vs Control. The Y-axis lists enriched GO terms grouped by Biological Process, Cellular Component, and Molecular Function. The X-axis shows the enrichment score (positive = more abundant in treatment; negative = more abundant in control). Bubble size indicates significance (−log₁₀ FDR), and bubble color reflects the enrichment score.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/eeb34ca54a9e74ddae74c8b1.jpg"},{"id":99172328,"identity":"5a573a2d-0573-4d25-aa7c-cffde2b2ce66","added_by":"auto","created_at":"2025-12-29 16:07:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2384097,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/69ddd314-8183-4e83-ab46-ba5a67b266bb.pdf"},{"id":92940432,"identity":"2264ef95-a3d6-4d4d-a845-67a77089d79b","added_by":"auto","created_at":"2025-10-07 11:16:37","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1134662,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarysheet1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/e126084373a26ed7bac850bc.xlsx"},{"id":92940425,"identity":"9513cf32-5469-4e18-8e9d-09d08abf73e8","added_by":"auto","created_at":"2025-10-07 11:16:37","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":79716,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602726/v1/5afc5d680ab7442cc24d9405.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Plant Growth-Promoting Bacillus Strains Modulate Early Soybean Development via Proteome Remodelling","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDue to their sessile nature, plants cannot avoid exposure to numerous stressors that threaten their survival [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]). Plants use adaptation tactics to deal with environmental stress on a cellular, molecular, and biochemical level. One such approach is the use of microbial species associated with the plant known as the plant microbiome or phytomicrobiome, which is often referred to as the second genome, and which plays an important role in the health of the plant [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The presence of microbes in every part of the plant plays an important role in the development and reproduction of the plant. As a result of these interactions, plants develop, grow, and become adapted to a stressful environment, establishing the basis for the Holobiont theory, which considers plants and their microorganisms to be one evolutionary unit rather than separate entities[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Microbiomes can be greatly influenced by a variety of host-based factors, such as plant species, genotype, developmental stage, canopy type, and metabolite production.\u003c/p\u003e\u003cp\u003eSoybean is an important agricultural crop due to its high protein and oil content. As a model plant, it is also useful for exploring the associated phytomicrobiome since the plant produces secondary metabolites that are released into the soil-root environment to attract beneficial bacteria [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]For instance, isoflavonoids are biologically active specialized metabolites synthesized by legumes through the phenylpropanoid pathway, and soybean roots produce large amounts of these compounds that influence the rhizosphere microflora with spatiotemporal variations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Root exudates from legume species contain a combination of flavonoids that serve as selective agents for compatible symbiotic organisms. Flavonoids, such as medicarpin, are produced by \u003cem\u003eTrifolium\u003c/em\u003e and \u003cem\u003eMedicago\u003c/em\u003e species and inhibit the growth of bacterial strains that are incompatible with these species [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The antimicrobial activity of plant-derived coumarins is limited to pathogenic bacteria and does not affect endophytic bacteria [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, rhizobacteria have developed resistance to the toxic structural mimic of arginine (cotinine) produced by legumes, allowing them to thrive in the rhizosphere [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Plant metabolites, such as polyamine amino acids, organic acids, or sugars, can also be used by symbionts to identify their host plants [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, plants selectively recruit beneficial endophytes from complex microbial communities by secreting specific signals, including nutrients, antimicrobial compounds, and secondary metabolites. These metabolic signals likely play a key role in shaping symbiotic associations between host plants and endophytes, ultimately, facilitating the colonization of plant tissues by beneficial bacteria. Upon colonizing the host tissues, endophytic bacteria establish an intimate relationship with plants. For instance, some bacteria affect the growth of plants by producing phytohormones, aminocyclopropane-1-carboxylase-deaminase, and antibiotic compounds, as well as by fixing nitrogen, solubilizing phosphate, or suppressing pathogens through the competence of invasion sites [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e][\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e][\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] found that the endophytic bacteria in soybean plants can produce siderophore, indole acetic acid, promote nitrogen fixation, and inhibit the specific to pathogenic fungi. These metabolites mediate the growth-promoting effects of endophytic bacteria on soybean seedlings. Soybean seed endophytes protect seeds from seed-borne pathogens, promote plant growth, and suppress diseases, all of which support their use in crop protection and growth [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs described in the literature above, root endophytes of soybean plants form a selectively beneficial and diverse community that needs to be studied further to determine their direct effects on the plant. This study explores the beneficial effects of members of the soybean endophyte community on the soybean phenotype. Soybean-associated \u003cem\u003eBacillus\u003c/em\u003e endophytes influence host development by reprogramming leaf proteomes at the mid-vegetative stage. Through modulation of signaling, metabolic, and structural pathways, these endophytes differentially enhance seed germination, vegetative growth, or defense responses, thereby shaping soybean phenotypes under both optimal and controlled conditions. In our previous study [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], we used an LC-MS/MS-based untargeted metabolomics workflow to profile secondary metabolites produced by \u003cem\u003eBacillus\u003c/em\u003e strains HT1, HT2 and HT3 used in the present study. MS\u0026sup2;-guided annotation indicated that HT1 and HT2 secrete multiple putative antifungal compounds that attribute to their anti-fungal activity against \u003cem\u003eFusarium oxysporum\u003c/em\u003e, whereas HT3 lacks these features. Motivated by these findings, we tested the direct effects of these plant growth-promoting bacteria on soybean and sought to elucidate their mechanisms of action. In this study, we analyzed the soybean leaf proteome to signalling pathways associated with elucidating the mechanisms of plant growth that are modulated by inoculation with \u003cem\u003eBacillus\u003c/em\u003e species. This approach provides a comprehensive understanding of the molecular interactions between soybean endophytes and their host, offering new insights into plant-microbe symbiosis.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Bacteria Culture Propagation and Inoculation\u003c/h2\u003e\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e-HT1 (Accession No. PV534845), \u003cem\u003eBacillus-\u003c/em\u003eHT2 (Accession No. PV534846), and \u003cem\u003eBacillus\u003c/em\u003e-HT3 (Accession No. PV534847) were preselected from the microbiome of soybean roots grown in Sainte-Anne-de-Bellevue, Quebec, Canada, previously by the author [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The cultures of these three bacteria were grown from glycerol stock in TSB (Tryptic Soy broth) medium for 48 h incubated at 25\u0026deg;C and 150 rpm. The cultures were harvested by centrifugation at 5,000xg for 10 min at room temperature (AwelTM MF 48-R, NuAire, United States) and the supernatant was discarded. The pellet was resuspended in 10 mM MgSO\u003csub\u003e4\u003c/sub\u003e, and three different cell concentrations were prepared. The optical density of the cultures was adjusted to three different concentrations i.e., 10\u003csup\u003e6,\u003c/sup\u003e 10\u003csup\u003e7\u003c/sup\u003e and 10\u003csup\u003e8\u003c/sup\u003e colony forming unit (CFU) using a spectrophotometer (Ultraspec 4300 pro UV/Visible Spectrophotometer, Biochrom) at absorbance A\u003csub\u003e600nm\u003c/sub\u003e. The three different concentrations of \u003cem\u003eBacillus-\u003c/em\u003eHT1, HT2 and HT3 strains were prepared in 10 mM MgSO\u003csub\u003e4\u003c/sub\u003e to screen the best concentration for germination.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Screening for Optimal Bacterial Concentration\u003c/h2\u003e\u003cp\u003eA screening test was performed to select optimal concentrations for in-planta application. Three different concentrations (10\u003csup\u003e6\u003c/sup\u003e, 10\u003csup\u003e7\u003c/sup\u003e and 10\u003csup\u003e8\u003c/sup\u003e CFU) of \u003cem\u003eBacillus\u003c/em\u003e-HT1, HT2 and HT3 strains were prepared in 10 mM MgSO\u003csub\u003e4\u003c/sub\u003e. The soybean germination experiments were carried out in a phytorium located at the Macdonald Campus of McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada. Seeds of soybean (\u003cem\u003eGlycine max\u003c/em\u003e L. var B088Y1) were used for the study. Per sample, ten soybean seeds were surface sterilized using 2% sodium hypochlorite for 2 mins, rinsed with sterilized distilled water five times, and placed in Petri dishes (Cat. no. 431760, sterile 100 \u0026times; 15 mm polystyrene Petri dish, Fisher Scientific Co., Whitby, Ontario, Canada), lined with filter paper (09-795D, QualitativeP8, porosity coarse, Fisher Scientific Co., Pittsburgh, PA, United States). \u003cem\u003eBacillus\u003c/em\u003e suspension (5 mL) was added to each Petri dish for a total of 9 treatments (3 bacterial strains administered at 3 different concentrations each). Control seeds were treated with 10 mM MgSO\u003csub\u003e4\u003c/sub\u003e. Each Petri plate contained 10 seeds, and each treatment was replicated 10 times, and the experiment was repeated two times. The Petri plates were sealed with parafilm and incubated in a phytorium set at 25\u0026deg;C with a relative humidity of 70% and 24h darkness. Seeds were considered germinated when their radicle was about 2 mm long; data were collected at 24, 30, 36 and 48h.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003cp\u003eSeed germination percentages were first calculated for each replicate of each treatment. These percentage data were then submitted to the arcsine-square-root transformation and analyzed by one-way analysis of variance (ANOVA) with PROC GLM (SAS Version 9.4). In particular, differences between the treatments and control were assessed using Dunnett's test after the treatment main effects had been found significant with the ANOVA \u003cem\u003eF\u003c/em\u003e-test. Differences with a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Soybean growth condition and sample collection\u003c/h2\u003e\u003cp\u003eBased on their optimal effects on soybean germination, a concentration of 10\u003csup\u003e7\u003c/sup\u003e CFU was used for all bacterial strains for the investigation of their effects on soybean vegetative growth. There were three bacterial treatments (10⁷ CFU of each strain) and one control (10 mM MgSO₄). Pots (15.25 cm diameter) filled with vermiculite (Perlite Canada Inc., Laval, QC, Canada) were supplied with 300 mL of water. After two hours, 5 seeds were placed in each pot. Each seed in a pot was treated with 500 \u0026micro;L of bacterial suspension and covered with vermiculite. The pots were placed under greenhouse conditions at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 50% relative humidity. After seedling emergence, the plants were thinned to one seedling per pot. The plants were irrigated with 300 mL water twice a week (every 3\u0026ndash;4 days) and sampled on the 28th day after planting. Above-ground plant growth variables, including plant height, leaf area, shoot fresh weight and dry weight were measured. Intact roots were harvested, placed on a 30 \u0026times; 40 cm plastic plate, and submerged in deionized water. The roots were scanned (Modified Epson Expression 10000XL, Regent Instruments Inc., Qu\u0026eacute;bec, QC, Canada) and the output images were analyzed using WinRhizo software (Regent Instruments Inc.). Several root parameters were measured, including root length, root projection area, root surface area, and dry root weight. The experiment was repeated three times with three treatments and six replicates per treatment each time. Three replicates were allocated for measuring growth variables and three replicates were allocated for protein extraction.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003cp\u003eGrowth data were analyzed in SAS Version 9.4. One-way ANOVA and Dunnett's test were used to determine differences between each treatment and the control. The level of significance was set at 0.05.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Label free proteomics analysis\u003c/h2\u003e\u003cp\u003eShotgun proteomics analysis was performed on soybean plants grown from seeds coated with \u003cem\u003eBacillus\u003c/em\u003e strains HT1, HT2, and HT3 at a concentration of 10⁷ CFU per seed prior to germination. Trifoliate leaves harvested after 28 days of planting were flash frozen in liquid nitrogen. A biological replicate was constructed by pooling the three technical replicates from each experiment. The collected leaf samples were dried in a lyophilizer and the total protein was extracted using a plant total protein extraction kit (Sigma-Aldrich, St. Louis, MO, USA). Approximately 100 mg of the fine powder was placed in sterile Eppendorf tubes and 1 mL of ice-cold methanol-protease cocktail inhibitor (Cat. No. 15468-7, Sigma-Aldrich Co., St. Louis, MO, USA) was added; the resulting mix was vortexed, incubated at -20\u0026deg;C for 2 h and centrifuged for 10 mins at 4\u0026deg;C (Micro12, Fisher Scientific, Denver Instrument Co., USA). Following the removal of the supernatant, ice-cold methanol was added and incubated overnight at -20\u0026deg;C, followed by centrifugation at 13,000 rpm for 10 mins, followed by incubation in ice-cold methanol again for 1 h and centrifugation at the same speed. A similar incubation in acetone was performed to remove phenolics and secondary metabolites that might interfere with the LC-MS/MS (liquid chromatography tandem mass spectrometry) analysis. Following the removal of acetone from the samples, wash buffer solution (RW4) was added, vortexed for 30 s, and incubated for 30 mins at room temperature (22\u0026deg;C). The samples were centrifuged at 13,000 rpm for 10 minutes, and the supernatants were carefully collected in sterile tubes, which constituted the total proteins from leaves. Proteins were quantified using the Lowry method [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and a sample of 10 \u0026micro;g of proteins in 20 \u0026micro;L of 1M urea were analyzed for untargeted proteomics at the \u003cem\u003eInstitute de Recherches Cliniques de Montr\u0026eacute;al (IRCM)\u003c/em\u003e for label-free shotgun proteomics.\u003c/p\u003e\u003cp\u003eTotal extracted proteins from trifoliate leaves were tryptic digested before analyses by LC-MS/MS on a Velos Orbitrap instrument (Thermo Fisher Scientific, Waltham, MA, USA). Proteins were solubilized in 20 \u0026micro;L of 8 M urea buffer. Reduction was performed by adding 10 \u0026micro;L of 45 mM dithiothreitol (DTT) in 100 mM ammonium bicarbonate, followed by incubation for 30 min at 37\u0026deg;C. Alkylation was carried out with 10 \u0026micro;L of 100 mM iodoacetamide in 100 mM ammonium bicarbonate, and samples were incubated for 30 min at 24\u0026deg;C in the dark. To remove nucleic acids, 50 units of benzonase were added in the presence of 2 mM MgCl₂ and incubated for 1 h at 37\u0026deg;C.\u003c/p\u003e\u003cp\u003eProtein Aggregation Capture (PAC) digestion was then performed using hydroxyl-functionalized magnetic beads (ReSyn Biosciences). Ten \u0026micro;L of pre-washed beads were added to each sample, and proteins were precipitated by adjusting the acetonitrile concentration to 50%. Samples were incubated for 20 min at room temperature with agitation (1,000 RPM), placed on a magnetic rack for 2 min, and the supernatant was discarded. Beads were washed three times with 70% ethanol.\u003c/p\u003e\u003cp\u003eFor digestion, beads were resuspended in 100 \u0026micro;L of trypsin solution (0.0005 \u0026micro;g/\u0026micro;L Promega trypsin in 50 mM ammonium bicarbonate), sonicated in a water bath for 1 min, and incubated overnight at 37\u0026deg;C with shaking (700 RPM). Following digestion, peptides were recovered by placing samples on a magnetic rack, transferring the supernatant to Eppendorf LoBind tubes, and rinsing beads with 25 \u0026micro;L of 50 mM ammonium bicarbonate. The rinses were pooled with the corresponding digests. Samples were dried in a SpeedVac and stored at \u0026minus;\u0026thinsp;20\u0026deg;C until analysis.\u003c/p\u003e\u003cp\u003eBefore LC-MS/MS, peptides were reconstituted in 11 \u0026micro;L of 2% acetonitrile / 1% formic acid with agitation for 15 min. Separation was performed on a 75 \u0026micro;m i.d. \u0026times; 150 mm self-packed C18 column using an Easy-nLC II system (Proxeon Biosystems) with a binary buffer system: buffer A (0.2% formic acid in water) and buffer B (90% acetonitrile, 0.2% formic acid). Peptides were eluted at 250 nL/min with a three-step gradient: 2\u0026ndash;34% B over 120 min, 34\u0026ndash;42% B over 14 min, and 42\u0026ndash;80% B over 5 min.\u003c/p\u003e\u003cp\u003eThe LC system was coupled to an LTQ Orbitrap Velos mass spectrometer (Thermo Scientific) via a Nanospray Flex Ion Source. Data-dependent acquisition employed a 17-scan cycle: one full MS scan in the Orbitrap (resolution 60,000 at m/z 400) followed by MS/MS of the 16 most intense ions in the linear ion trap. MS scans were acquired over m/z 360\u0026ndash;1600 with a target value of 1 \u0026times; 10⁶ charges. MS/MS scans were collected from one-third of the parent ion m/z up to m/z 2000 with a target value of 10,000 charges. Maximum ion fill times were 100 ms, with one microscan per spectrum. Dynamic exclusion was set to 8 s.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Mass spectrometry data analysis and protein quantification\u003c/h2\u003e\u003cp\u003eRaw mass spectrometry (MS) data were processed using MaxQuant software (version v2.6.7.0). The spectra were searched against the \u003cem\u003eGlycine max\u003c/em\u003e (85,130 sequences; accessed on June 2025\u003cb\u003e)\u003c/b\u003e database from UniProtKB (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"http://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). An initial precursor mass tolerance of 15 ppm was applied. Trypsin was specified as the digestion enzyme, allowing up to two missed cleavages and a fragment ion mass tolerance of 20 ppm. Carbamidomethylation of cysteine was set as a fixed modification, while N-terminal acetylation and methionine oxidation were treated as variable modifications. A global false discovery rate (FDR) threshold of \u0026lt;\u0026thinsp;1% was applied for both peptide-spectrum matches (PSMs) and protein identifications. Only proteins identified by at least two unique peptides and consistently detected in at least two of three replicates per sample were considered confidently identified and selected for downstream analysis. Protein quantification was carried out using LFQ based on peptide intensities. Match-between-runs functionality was enabled to align quantification data across replicates.\u003c/p\u003e\u003cp\u003eSubsequent analysis of the MaxQuant-processed output (specifically the \u0026ldquo;proteinGroups.txt\u0026rdquo; file) was conducted in Perseus (v2.1.4.0). Reverse database hits, potential contaminants, and proteins identified solely by modified peptides were excluded from the dataset. Label-free quantification (LFQ) intensities were log-transformed, and proteins detected in all three replicates within at least one experimental group were retained for further analysis (valid-value filter\u0026thinsp;=\u0026thinsp;3 in at least one group). Missing values were imputed using a normal distribution, applying a downshift of 1.8 and a width of 0.3 standard deviation to simulate low abundance. Significant differences were evaluated with Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test (significance level\u0026thinsp;=\u0026thinsp;0.05) with the multiple-hypothesis testing correction of Benjamini-Hochberg FDR\u0026thinsp;=\u0026thinsp;0.05 with \u003cem\u003eS\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1) and the post hoc test used to identify pairwise group differences. The variability and associations in the data table were summarized into a small number of principal components (PC) using the multivariate statistical method of principal-component analysis (PCA). Proteins with a fold change greater than 1.5 and a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were identified as differentially abundant proteins (DAPs) compared to the control.SRplot (SRplot - Science and Research online plot) was used for visual representation of the data and results (e.g., PCA biplots). For pairwise comparisons, Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-tests were performed in Perseus. Volcano plots were generated using a permutation-based FDR of 0.05 with an S₀ parameter of 1 to balance statistical significance with effect size. Annotation enrichment analysis was performed in Perseus using the 1D annotation enrichment function. The Benjamini\u0026ndash;Hochberg procedure was applied to control the FDR, and a stringent significance threshold of FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.001 was used to identify significantly enriched annotations. Enrichment plots were generated in RStudio (R Core Team, version 4.5.1) using the \u003cem\u003eggplot2\u003c/em\u003e package.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Determining the optimal concentration of bacterial cultures based on their effect on seed germination\u003c/h2\u003e\u003cp\u003eThree \u003cem\u003eBacillus\u003c/em\u003e strains were tested for their potential to positively affect the seed germination of soybean. To this end, seeds were inoculated with three concentrations of \u003cem\u003eBacillus\u003c/em\u003e-HT1, \u003cem\u003eBacillus\u003c/em\u003e-HT2 and \u003cem\u003eBacillus\u003c/em\u003e-HT3 and seed germination was scored (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-D). In addition, seed germination rates were determined revealing that the administration of \u003cem\u003eBacillus\u003c/em\u003e-HT1 at 10\u003csup\u003e7\u003c/sup\u003e CFU increased the seed germination rate of soybean in statistically significant manner compared to the uninoculated control and. However, this effect was not detectable until 48h after administration of the treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). \u003cem\u003eBacillus\u003c/em\u003e-HT2, 10\u003csup\u003e7\u003c/sup\u003e CFU increased seed germination significantly at all tested time points compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). However, none of the concentrations of \u003cem\u003eBacillus\u003c/em\u003e-HT3 tested showed any statistically significant effect on soybean seed germination (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Based on these results, 10\u003csup\u003e7\u003c/sup\u003e CFU was chosen as the working concentration for \u003cem\u003eBacillus\u003c/em\u003e-HT1 and \u003cem\u003eBacillus-\u003c/em\u003eHT2 for subsequent experiments to assay for plant growth promotion at the vegetative stage. While not generating any positive effect on seed generation, we nevertheless decided to test \u003cem\u003eBacillus\u003c/em\u003e-HT3 at 10\u003csup\u003e7\u003c/sup\u003e CFU for potential growth stimulating effects at the vegetative stage.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Effects of \u003cem\u003eBacillus\u003c/em\u003e strains on soybean plant growth at the vegetative stage\u003c/h2\u003e\u003cp\u003eBased on the screening test results described above, 10\u003csup\u003e7\u003c/sup\u003e CFU was chosen as a suitable concentration for testing the effect of \u003cem\u003eBacillus\u003c/em\u003e-HT1, \u003cem\u003eBacillus\u003c/em\u003e-HT2 and \u003cem\u003eBacillus\u003c/em\u003e-HT3 on soybean at the vegetative stage. At the age of 28 days, plants produced from the soybean seeds coated with \u003cem\u003eBacillus\u003c/em\u003e-HT1, HT2 and HT3 were tested for change in fresh and dry biomass, plant height, chlorophyll content, and leaf area (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-E). The results showed that only \u003cem\u003eBacillus\u003c/em\u003e-HT3 showed a pronounced effect on leaf area whereas \u003cem\u003eBacillus\u003c/em\u003e-HT1 and \u003cem\u003eBacillus\u003c/em\u003e-HT2 did not lead to any changes in plant traits at the concentrations tested (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Plant roots were analyzed for changes in root length, root surface area, root weight, and root projection area. None of the bacterial strains led to any changes in root parameters (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Protein profiling\u003c/h2\u003e\u003cp\u003eComparative analysis of total proteins extracted from leaves from plants treated with \u003cem\u003eBacillus\u003c/em\u003e-HT1, HT2, and HT3 revealed distinct changes in protein abundance patterns. Label-Free Quantification (LFQ) intensities and corresponding spectral annotations are provided in Supplementary sheet-Table\u0026nbsp;1.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1. Multivariate analysis\u003c/h2\u003e\u003cp\u003eOn a global scale, the PCA demonstrates clear clustering patterns among the treatments and the control, indicating treatment-specific proteomic shifts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) revealed that the three replicates in each treatment group, including the control, were similarly dispersed, suggesting comparable degrees of variability within groups. Notably, the replicates of the control clustered near the center of the biplot, indicating a proteomic profile that represents the dataset\u0026rsquo;s centroid. In contrast, replicates of \u003cem\u003eBacillus\u003c/em\u003e-treated samples were positioned farther from the center, consistent with treatment-specific proteomic shifts. The profile plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) derived from the post hoc test highlights a unique protein production pattern in \u003cem\u003eBacillus\u003c/em\u003e-HT3-treated plants, distinct from both \u003cem\u003eBacillus\u003c/em\u003e-HT1, HT2, and the control group. This indicates that \u003cem\u003eBacillus\u003c/em\u003e-HT3 induces a unique proteomic response, likely linked to enhanced metabolic and stress-related processes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2. Univariate analysis\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the number of significantly higher and lower abundance proteins across all three treatments compared to the control. In the present study, no proteins with significantly differential abundance were identified in the leaves of plants treated with \u003cem\u003eBacillus\u003c/em\u003e-HT1 or HT2 compared to the control. In the case of \u003cem\u003eBacillus\u003c/em\u003e-HT3 treatment, the abundance of 10 proteins was lower than in the control, while a group of 10 different proteins was significantly more abundant.\u003c/p\u003e\u003cp\u003eSupplementary sheet 1 (Table\u0026nbsp;2) provides detailed information on the 20 differentially abundant proteins, ranked by their abundance difference. The abundant proteins in the leaves of \u003cem\u003eBacillus\u003c/em\u003e-HT3-treated plants included important proteins like glucan endo-1,3-beta-D-glucosidase, methionine adenosyl transferase and 20 kDa chloroplastic chaperonin. Proteins with increased abundance in \u003cem\u003eBacillus\u003c/em\u003e-HT3-treated plants were primarily associated with ion transmembrane transport, ATPase activity, protein folding, signal transduction, and biosynthetic and catabolic processes. These proteins are localized to diverse subcellular structures, including the cytoplasm, nucleus, ribosome, proteasome, and membrane complexes. In contrast, proteins more abundant in \u003cem\u003eBacillus\u003c/em\u003e-HT3-treated plants were enriched in peptidase activity, cytoskeleton organization, and regulatory functions such as enzyme inhibition and protein modification. This contrast suggests that \u003cem\u003eBacillus\u003c/em\u003e-HT3 treatment reprograms key cellular processes toward energy metabolism, protein synthesis, and signalling, while untreated plants maintain higher levels of structural and regulatory proteins. These findings suggest that \u003cem\u003eBacillus\u003c/em\u003e-HT3 induces distinct proteomic changes in the host plant, potentially reflecting a stronger or more specific interaction compared to \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3. Enrichment analysis\u003c/h2\u003e\u003cp\u003eFunctional enrichment analysis revealed treatment-specific reprogramming of soybean leaf proteins in response to \u003cem\u003eBacillus\u003c/em\u003e inoculation as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Supplementary sheet 1 (Table\u0026nbsp;3). In the \u003cem\u003eBacillus\u003c/em\u003e-HT1 vs Control (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA) comparison, negatively enriched categories dominated, including cellular process, cellular metabolic process, and biosynthetic process, along with translation-related terms such as translation, peptide biosynthetic process, and peptide metabolic process. The suppression of these biosynthetic and metabolic pathways suggests that HT1 primarily attenuated host protein synthesis relative to the control. In contrast, the \u003cem\u003eBacillus-\u003c/em\u003eHT2 vs Control (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) comparison displayed a distinct enrichment profile characterized by positive enrichment of several metabolic categories, including small molecule metabolic process, carboxylic acid metabolic process, oxoacid metabolic process, and organic acid metabolic process. Pathways such as small molecule biosynthetic process and organic acid biosynthetic process were also significantly upregulated, whereas macromolecular biosynthesis (e.g., macromolecule biosynthetic process, peptide biosynthetic process) exhibited negative enrichment. These results indicate that HT2 preferentially enhanced primary and small-molecule metabolism while suppressing large-scale biosynthetic processes. By contrast, \u003cem\u003eBacillus-\u003c/em\u003eHT3 vs. Control exhibited the broadest enrichment pattern, with strong positive enrichment of photosynthesis- and chloroplast-related categories alongside metabolic pathways such as organic acid biosynthetic process and small molecule biosynthetic process. The presence of several highly significant terms with large enrichment scores suggests that HT3 treatment promoted a coordinated upregulation of both metabolic and structural functions, consistent with its observed effect on leaf expansion and biomass accumulation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGene Ontology (GO) enrichment based on post hoc analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed that proteins involved in cellular component organization and microtubule organization were produced at significantly higher levels in plants from seeds treated with \u003cem\u003eBacillus\u003c/em\u003e-HT2 and HT3 supporting their roles in cytoskeletal and organelle organization. In contrast, proteins associated with intracellular organelle components were significantly enriched in \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2-treated plants suggesting that these treatments influenced intracellular compartmentalization. Notably, \u003cem\u003eBacillus\u003c/em\u003e-HT3 treatment induced significantly higher abundance of proteins involved in various metabolic pathways, including amino acid metabolism and biosynthetic processes, compared to the control confirming the broad metabolic stimulation inferred from the enrichment analysis.\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\u003ePost Hoc comparison of protein abundance in soybean leaves of plants treated with \u003cem\u003eBacillus\u003c/em\u003e species\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\u003eProteins ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-log ANOVA P-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGOBP Slim\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSignificant Pairs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA0A0R0ER52; C6SZE7;\u003c/p\u003e\u003cp\u003eC6SXS0; I1LWT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.741931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecellular component organization; cellular component organization or biogenesis; cellular process; cytoskeleton organization; microtubule cytoskeleton organization; microtubule-based process; organelle organization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl_\u003cem\u003eBacillus\u003c/em\u003e-HT3; \u003cem\u003eBacillus\u003c/em\u003e-HT2_\u003cem\u003eBacillus\u003c/em\u003e-HT3; \u003cem\u003eBacillus\u003c/em\u003e-HT1_\u003cem\u003eBacillus\u003c/em\u003e-HT3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI1J8Y8;C6SV99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.28034692458043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecellular anatomical entity; intracellular membrane-bounded organelle; intracellular organelle; membrane; nucleus; organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e-HT2_\u003cem\u003eBacillus\u003c/em\u003e-HT3; \u003cem\u003eBacillus\u003c/em\u003e-HT1_\u003cem\u003eBacillus\u003c/em\u003e-HT3; Control_\u003cem\u003eBacillus\u003c/em\u003e-HT3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC6TMD6; C6TG97\u003c/p\u003e\u003cp\u003e;C6T4I5;I1K1X5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.78750116803613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecellular anatomical entity; cytoplasm; intracellular membrane-bounded organelle; intracellular organelle; nucleus; organelle; protein-containing complex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e-HT2_\u003cem\u003eBacillus\u003c/em\u003e-HT3; \u003cem\u003eBacillus\u003c/em\u003e-HT1_\u003cem\u003eBacillus\u003c/em\u003e-HT3; Control_\u003cem\u003eBacillus\u003c/em\u003e-HT3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI1NF54;I1NF5;\u003c/p\u003e\u003cp\u003eA0A0R0EVG9;A0A0R0F675;K7MPL4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.6640872956235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emetabolic process; amino acid metabolic process; biosynthetic process; cellular aromatic compound metabolic process; cellular nitrogen compound metabolic process; cellular process; heterocycle metabolic process; metabolic process; nitrogen compound metabolic process; organic acid metabolic process; primary metabolic process; small molecule metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e-HT2_Control; \u003cem\u003eBacillus\u003c/em\u003e-HT3_Control; \u003cem\u003eBacillus\u003c/em\u003e-HT2_\u003cem\u003eBacillus\u003c/em\u003e-HT1;\u003cem\u003eBacillus\u003c/em\u003e-HT3_\u003cem\u003eBacillus\u003c/em\u003e-HT1\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\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe endophytic microbiome of the soybean plant is of great interest because of the specialized signals released by the soybean roots that attract the beneficial microbes from the surrounding community [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]). Many studies have been conducted on endophytes of plants, but questions remain regarding how they enter the seed, what they do inside, and whether they are stable populations or just passersby. Despite this scarcity of knowledge, endophytes have opened new possibilities for applying microbes for sustainable crop production. Soybean plant endophytes have the potential to inhibit the growth of pathogens, enhance yield and plant growth, and improve the growth regulatory mechanism of plants. They exert lasting influence on both the endosphere and rhizosphere microbiomes, ultimately impacting overall plant productivity\u0026mdash;a phenomenon referred to as the \u0026ldquo;priority effect\u0026rdquo; in microbial ecology [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]). Collectively, these effects of the microbiome can improve overall plant growth which can be leveraged for sustainable crop protection.\u003c/p\u003e\u003cp\u003eIn a previous study, we isolated the bacterial strains used here from soybean plant roots and tested them for their potential antagonism against the pathogen \u003cem\u003eFusarium oxysporum.\u003c/em\u003e Using a dual confrontation assay we showed that the \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2 inhibit the growth of \u003cem\u003eF. oxysporum\u003c/em\u003e isolated from a soybean plant and identified putative antifungal metabolites produced by these microorganisms [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the present study, we showed that \u003cem\u003eBacillus\u003c/em\u003e-HT1 and \u003cem\u003eBacillus-\u003c/em\u003eHT2 have pronounced effects on soybean seed germination, whereas \u003cem\u003eBacillus\u003c/em\u003e-HT3 did not enhance germination at any of the concentrations tested. Seed germination, together with seed vigour, represents a key factor in determining crop yield and affects the initial rate of plant growth. Seed germination is a very important stage in the life cycle of a plant and one that is very sensitive to both the intrinsic and extrinsic factors. The present study found that \u003cem\u003eBacillus\u003c/em\u003e-HT1 and \u003cem\u003eBacillus\u003c/em\u003e-HT2 improve the germination rate compared to the unprimed control. Shah et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]noted that in germination assays, nearly all seeds typically germinate by the final assessment point, regardless of treatment, except in cases where germination is inhibited, such as with the high bacterial concentration observed in the present study. However, maximum seed germination was often attained much earlier for treated seeds than for untreated seeds, depending on the efficacy of the biostimulants or the technique used. In this study, the enhancement in the final seed germination rate in plants treated with \u003cem\u003eBacillus\u003c/em\u003e-HT1 and \u003cem\u003eBacillus\u003c/em\u003e-HT2 was statistically significant compared to the control. \u003cem\u003eBacillus-\u003c/em\u003eHT2 significantly improved the seed germination rate at early time points and seeds attained the final seed germination level much before the untreated seeds, whereas \u003cem\u003eBacillus\u003c/em\u003e-HT3 lack the potential to initiate early seed germination and improved final germination. These findings are aligned with Sari et al [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] who showed that the rhizobacterial treatment on the germination process had a significantly increased effect on maximum growth potential, germination, vigour index and growth simultaneity on chilli seeds. P\u0026eacute;rez-Garc\u0026iacute;a et al [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found similar results biopriming of rhizobacteria with \u003cem\u003eBacillus cereus, Acinetobacter radioresistens, Pseudomonas paralactis\u003c/em\u003e and \u003cem\u003eSinorhizobium meliloti\u003c/em\u003e on some parameters, such as the percentage of germination and vigor and the germination index in the seeds of \u003cem\u003eCucumis sativus\u003c/em\u003e L. These findings suggest that the two bacterial strains \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2 have the potential to be potential biostimulants that act by inducing early and highly efficient seed germination, whereas \u003cem\u003eBacillus\u003c/em\u003e-HT3 does not. This leads us to conclude that while all three strains are endophytes, their effects differ and they either induce seed germination or improve growth at the vegetative stage followed by overall changes in the physiology of soybean plants. In the present study, the optimal working concentration was 10\u003csup\u003e7\u003c/sup\u003e CFU for all three bacterial strains. When applied on the plants, \u003cem\u003eBacillus\u003c/em\u003e-HT3 did not show a pronounced effect at the initial seed germination stage, but it proved to have the most pronounced beneficial effects on plant growth at the late vegetative as expressed, for example, by increased the leaf surface area. This effect has been observed for other plant growth-promoting bacteria (PGPR) where it is mediated by dissolving phosphorus and fixed nitrogen, that the plant leverages for enhanced leaf growth [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Our observations are aligned with the findings of Elbagory et al [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] that PGPR, \u003cem\u003eAzospirillum lipoferum and Pseudomonas koreneesis\u003c/em\u003e, along with vermicompost, improve biomass and leaf area of lettuce plant.\u003c/p\u003e\u003cp\u003eThe application of plant growth-promoting \u003cem\u003eBacillus\u003c/em\u003e strains resulted in distinct physiological and molecular responses, with \u003cem\u003eBacillus\u003c/em\u003e-HT3 showing the most pronounced effects on vegetative growth. Specifically, \u003cem\u003eBacillus\u003c/em\u003e-HT3 treatment significantly increased leaf area, suggesting enhanced photosynthetic capacity and overall plant vigour. Our proteomic analysis demonstrates that \u003cem\u003eBacillus\u003c/em\u003e inoculation triggers distinct and strain-specific reprogramming of the soybean leaf proteome, which can be directly linked to the phenotypic outcomes observed. Proteomic analysis further supported this observation, as \u003cem\u003eBacillus\u003c/em\u003e-HT3-treated plants exhibited a distinct production profile characterized by the elevated abundance of proteins involved in amino acid metabolism, biosynthetic processes, and other metabolic pathways associated with growth and development. The unique clustering pattern of HT3-treated samples in the PCA and post hoc profile plots underscore the differential regulatory effects of this strain at the molecular level. Interestingly, the PCA biplot also suggests that the degree of variability among the replicates of the control was comparable to that observed among the \u003cem\u003eBacillus\u003c/em\u003e-treated samples. While such variability is statistically acceptable and supports the assumptions of ANOVA, it raises a biologically meaningful consideration. The proteomic divergence among control replicates may reflect slight differences in endogenous microbial populations, even in the absence of exogenous inoculation. Consequently, the observed proteomic responses may not be solely attributable to the introduced \u003cem\u003eBacillus\u003c/em\u003e strains but may also arise from their interactions with resident microbial communities. These interactions could influence host proteomic responses in complex, context-dependent ways. Kaya [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] reported that the convergence of microbial activity within the rhizosphere and endosphere represents a critical interface where modulation of hormone signaling and proteomic dynamics occurs. This interpretation is supported by the distinct spatial separation of \u003cem\u003eBacillus\u003c/em\u003e-treated samples in the PCA, indicating that the microbial additions induced shifts away from the average (centred) proteomic profile observed in control plants.\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eBacillus\u003c/em\u003e-HT1 treatment was characterized by negative enrichment of biosynthetic and translational categories (e.g., translation, peptide biosynthetic process), suggesting reduced leaf protein synthesis. Despite this suppression, HT1 significantly enhanced seed germination, indicating that metabolic resources may be redirected from sustained leaf protein production toward early developmental processes. This observation is consistent with the known ability of PGPR to promote germination by modulating energy mobilization and stress signaling [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e][\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Furthermore, our earlier work demonstrated that HT1 exhibits biocontrol activity [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and the suppression of biosynthetic pathways alongside enrichment of defense-related processes (e.g., cellular component organization, intracellular organelle functions) may reflect its role in priming host immunity while supporting germination. Similarly, \u003cem\u003eBacillus\u003c/em\u003e-HT2 promoted metabolic flexibility, with positive enrichment of small molecule metabolic and organic acid biosynthetic pathways and significant upregulation of proteins linked to cellular and organelle organization. These changes align with the strain's dual activity in enhancing seed germination and vigor while providing biocontrol capacity, as previously reported. The ability of HT2 to activate metabolic priming alongside immune-related processes highlights its potential as a versatile PGPR strain capable of balancing early growth promotion with host defense support. Seed treatment with PGPR induces structural reinforcement of the cell wall and triggers physiological and biochemical changes that stimulate the synthesis of defense-related proteins, peptides, and metabolites [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. By contrast, \u003cem\u003eBacillus\u003c/em\u003e-HT3 triggered pronounced responses in terms of protein enrichment, with strong positive regulation of photosynthesis, chloroplast organization, amino acid biosynthesis, and microtubule organization. These changes are consistent with observed effects on leaf expansion and biomass accumulation, indicating that HT3 functions predominantly as a growth-promoting strain. Unlike HT1 and HT2, however, HT3 did not demonstrate biocontrol properties in our previous study, suggesting that its functional contribution is directed more towards enhancing vegetative growth rather than defense.\u003c/p\u003e\u003cp\u003eFor instance, the present study found that anthranilate synthase (I1NF54) is more abundant in \u003cem\u003eBacillus\u003c/em\u003e-HT2 and \u003cem\u003eBacillus\u003c/em\u003e-HT3 treated plants. Anthranilate and its derivatives are precursors for important secondary metabolites, including indole-3-acetic acid (IAA), a major plant hormone in the auxin class, which is crucial for cell elongation and differentiation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, elevated abundance of anthranilate synthase can be associated with enhanced auxin biosynthesis and overall plant growth promotion. The broader metabolic reprogramming triggered by \u003cem\u003eBacillus\u003c/em\u003e-HT3, beyond tryptophan metabolism, may explain its stronger effect on leaf area expansion compared to \u003cem\u003eBacillus\u003c/em\u003e-HT2.\u003c/p\u003e\u003cp\u003eIn contrast, \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2 treatments were particularly effective in promoting early-stage growth, as evidenced by their significant enhancement of seed germination rates which may linked to enrichment of proteins involved in cellular component organization, microtubule organization, and intracellular organelle function. Such proteins play essential roles in cell division, cytoskeleton dynamics, and organelle integrity, which are critical during the early stages of seedling establishment [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e][\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. For instance, the proteasome subunit alpha type (I1K1X5), upregulated in HT1 and HT2-treated plants, is part of the ubiquitin\u0026ndash;proteasome system that regulates seed germination by mobilizing storage reserves and modulating growth repressors [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e][\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e][\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e][\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]). Together, these findings reveal that different \u003cem\u003eBacillus\u003c/em\u003e strains exert distinct growth-promoting effects depending on the developmental stage of the plant. While \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2 contribute significantly to seed germination and early cellular organization, \u003cem\u003eBacillus\u003c/em\u003e-HT3 has a broader influence on vegetative growth through the activation of metabolic and biosynthetic pathways. While the observed increased abundance of proteins such as proteasome subunit alpha type suggests mechanistic insights into potential plant growth-promoting effects of \u003cem\u003eBacillus\u003c/em\u003e treatments, these interpretations warrant further validation. Future studies could be conceived to be based on inhibit these pathways (e.g., anthranilate synthase or proteasome activity) to directly test their roles in \u003cem\u003eBacillus\u003c/em\u003e-mediated growth promotion. Notably, the current study focused on the proteomic profiling of soybean leaves at a later developmental stage and did not include proteomic analysis of seedlings or germinating seeds. As a result, the molecular basis underlying the enhanced seed germination observed in \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT2 treatments remains indirect and inferred from later-stage protein production.\u003c/p\u003e\u003cp\u003eGiven that seed germination is a highly regulated and temporally distinct process involving unique signaling cascades and proteolytic mechanisms, it is crucial to examine the proteomic landscape of seedlings during early developmental windows to directly link bacterial treatment with molecular changes driving plant germination. Future studies should include temporal proteomics of germinating seeds and early seedlings to determine whether \u003cem\u003eBacillus\u003c/em\u003e-induced activation of the ubiquitin-proteasome pathway and tryptophan-derived auxin biosynthesis occurs at the onset of development. This would help clarify whether the observed increase in seed germination is directly mediated by early protein-level changes or whether it is the cumulative outcome of downstream physiological modulation. This duality highlights the potential for strategic use of specific PGPR strains to target different stages of plant development, contributing to optimized and sustainable crop production systems.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eSeed germination is a tightly regulated and temporally distinct developmental phase, orchestrated by specific signaling pathways and proteolytic mechanisms. In this study, enrichement analysis revealed strain specific effects of \u003cem\u003eBacillus\u003c/em\u003e treatment on soybean development. \u003cem\u003eBacillus\u003c/em\u003e-HT1 and HT-2 were associated with enrichment of categories linked to cellular component organization, microtubule dynamics, and intracellular organelle function, which may underlie their strong effects on seed germination and early establishment whereas \u003cem\u003eBacillus\u003c/em\u003e-HT3 induced broader enrichment of photosynthesis, chloroplast organization, and biosynthetic pathways, consistent with its pronounced impact on leaf expansion and biomass accumulation. Moreover, functional inhibition of these enriched pathways\u0026mdash;such as cytoskeleton organization, proteasome-mediated turnover, or auxin biosynthesis\u0026mdash;will be critical to confirm their causal role in \u003cem\u003eBacillus\u003c/em\u003e-mediated growth promotion. However, since our analysis focused on mature leaf tissue, the molecular basis of enhanced seed germination required further investigation. Our findings underscore the importance of investigating the early proteomic landscape during seed germination to directly link bacterial treatment with the molecular events that drive developmental transitions. Future studies incorporating temporal proteomics of germinating seeds and seedlings are essential to determine whether \u003cem\u003eBacillus\u003c/em\u003e-induced activation of key regulatory pathways occurs at the onset of development. Such insights would clarify whether improved germination outcomes arise from early protein-level reprogramming or are the result of downstream physiological changes. Overall, this dual perspective highlights the potential for strategic application of specific PGPR strains to modulate distinct stages of plant development, offering a promising avenue toward more sustainable and targeted crop management practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e6. Author contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.T. performed the experiments and wrote the manuscript. P.D. assisted with statistical analysis and provided comprehensive guidelines and edited the manuscript. J.G.-M guided proteomic analysis and participated in manuscript review and revision. D.S. and A.G. supervised the planning and execution of the project, provided funding and edited the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Acknowledgements\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend special thanks to Dr. Denis Faubert\u0026rsquo;s group at \u003cem\u003eInstitute de recherches cliniques de Montr\u0026eacute;al (IRCM)\u003c/em\u003e for providing label-free LC-MS/MS metabolomics services. The authors gratefully acknowledge Jason McAlister for his valuable guidance and support in data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8. Funding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded Biomass Canada Cluster. The Biomass Canada Cluster is managed by BioFuelNet Canada and is funded by the Government of Canada under the Sustainable Canadian Agricultural Partnership and industrial partners.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e10. Data availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RAW and affiliated files deposited into the publicly available PRIDE partner database for the ProteomeXchange consortium with accession number PXD065756\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e11. Ethics, Consent to Participate, and Consent to Publish declarations:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFitzpatrick, C. R., Copeland, J., Wang, P. W., Guttman, D. S., Kotanen, P. M., \u0026amp; Johnson, M. T. (2018). Assembly and ecological function of the root microbiome across angiosperm plant species. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e, \u003cem\u003e115\u003c/em\u003e(6), E1157-E1165.\u003c/li\u003e\n\u003cli\u003eGupta, A., Mishra, R., Rai, S., Bano, A., Pathak, N., Fujita, M., ... \u0026amp; Hasanuzzaman, M. (2022). Mechanistic insights of plant growth promoting bacteria mediated drought and salt stress tolerance in plants for sustainable agriculture. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(7), 3741.\u003c/li\u003e\n\u003cli\u003eSharma, M. M. M., Sharma, P., Kapoor, D., Beniwal, P., \u0026amp; Mehta, S. (2021). Phytomicrobiome community: an agrarian perspective towards resilient agriculture. \u003cem\u003ePlant performance under environmental stress: hormones, biostimulants and sustainable plant growth management\u003c/em\u003e, 493-534.\u003c/li\u003e\n\u003cli\u003eAli, S., Tyagi, A., Park, S., Mir, R. A., Mushtaq, M., Bhat, B., ... \u0026amp; Bae, H. (2022). Deciphering the plant microbiome to improve drought tolerance: mechanisms and perspectives. \u003cem\u003eEnvironmental and Experimental Botany\u003c/em\u003e, \u003cem\u003e201\u003c/em\u003e, 104933.\u003c/li\u003e\n\u003cli\u003eUroz, S., Courty, P. E., \u0026amp; Oger, P. (2019). Plant symbionts are engineers of the plant-associated microbiome. \u003cem\u003eTrends in plant science\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(10), 905-916.\u003c/li\u003e\n\u003cli\u003eLyu, D., Zajonc, J., Pag\u0026eacute;, A., Tanney, C. A., Shah, A., Monjezi, N., ... \u0026amp; Smith, D. L. (2021). Plant holobiont theory: the phytomicrobiome plays a central role in evolution and success. \u003cem\u003eMicroorganisms\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(4), 675.\u003c/li\u003e\n\u003cli\u003eAstapati, A. D., \u0026amp; Nath, S. (2023). The complex interplay between plant-microbe and virus interactions in sustainable agriculture: Harnessing phytomicrobiomes for enhanced soil health, designer plants, resource use efficiency, and food security. \u003cem\u003eCrop Design\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(1), 100028.\u003c/li\u003e\n\u003cli\u003eLongley, R., Noel, Z. A., Benucci, G. M. N., Chilvers, M. I., Trail, F., \u0026amp; Bonito, G. (2020). Crop management impacts the soybean (Glycine max) microbiome. \u003cem\u003eFrontiers in microbiology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 1116.\u003c/li\u003e\n\u003cli\u003eAyilara, M. S., Adeleke, B. S., \u0026amp; Babalola, O. O. (2023). Bioprospecting and challenges of plant microbiome research for sustainable agriculture, a review on soybean endophytic bacteria. \u003cem\u003eMicrobial ecology\u003c/em\u003e, \u003cem\u003e85\u003c/em\u003e(3), 1113-1135.\u003c/li\u003e\n\u003cli\u003eAgyekum, D. V., Kobayashi, T., Dastogeer, K. M., Yasuda, M., Sarkodee-Addo, E., Ratu, S. T., ... \u0026amp; Okazaki, S. (2023). Diversity and function of soybean rhizosphere microbiome under nature farming. \u003cem\u003eFrontiers in Microbiology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 1130969.\u003c/li\u003e\n\u003cli\u003eAnguraj Vadivel, A. K., Sukumaran, A., Li, X., \u0026amp; Dhaubhadel, S. (2016). Soybean isoflavonoids: role of GmMYB176 interactome and 14-3-3 proteins. \u003cem\u003ePhytochemistry Reviews\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, 391-403.\u003c/li\u003e\n\u003cli\u003eSugiyama, A., \u0026amp; Yazaki, K. (2014). Flavonoids in plant rhizospheres: secretion, fate and their effects on biological communication. \u003cem\u003ePlant Biotechnology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(5), 431-443.\u003c/li\u003e\n\u003cli\u003eDong, W., \u0026amp; Song, Y. (2020). The significance of flavonoids in the process of biological nitrogen fixation. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(16), 5926.\u003c/li\u003e\n\u003cli\u003eSrinivasa, C., Mellappa, G., Patil, S. M., Ramu, R., Shreevatsa, B., Dharmashekar, C., ... \u0026amp; Shivamallu, C. (2022). Plants and endophytes\u0026ndash;a partnership for the coumarin production through the microbial systems. \u003cem\u003eMycology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(4), 243-256.\u003c/li\u003e\n\u003cli\u003eWen, Y., Liao, Y., Tang, Y., Zhang, H., Zhang, J., \u0026amp; Liao, Z. (2023). Metabolic effects of elicitors on the biosynthesis of tropane alkaloids in medicinal plants. \u003cem\u003ePlants\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(17), 3050.\u003c/li\u003e\n\u003cli\u003eSardans, J., Gargallo‐Garriga, A., Urban, O., Klem, K., Holub, P., Janssens, I. A., ... \u0026amp; Pe\u0026ntilde;uelas, J. (2021). Ecometabolomics of plant\u0026ndash;herbivore and plant\u0026ndash;fungi interactions: a synthesis study. \u003cem\u003eEcosphere\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(9), e03736.\u003c/li\u003e\n\u003cli\u003eDudeja, S. S., Suneja‐Madan, P., Paul, M., Maheswari, R., \u0026amp; Kothe, E. (2021). Bacterial endophytes: molecular interactions with their hosts. \u003cem\u003eJournal of basic microbiology\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(6), 475-505.\u003c/li\u003e\n\u003cli\u003eZhao, L., Xu, Y., \u0026amp; Lai, X. (2018). Antagonistic endophytic bacteria associated with nodules of soybean (Glycine max L.) and plant growth-promoting properties. \u003cem\u003eBrazilian Journal of Microbiology\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e(2), 269-278.\u003c/li\u003e\n\u003cli\u003eZulfiqar, U., Haider, F. U., Maqsood, M. F., Mohy-Ud-Din, W., Shabaan, M., Ahmad, M., ... \u0026amp; Shahzad, B. (2023). Recent advances in microbial-assisted remediation of cadmium-contaminated soil. \u003cem\u003ePlants\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(17), 3147.\u003c/li\u003e\n\u003cli\u003eKim, J., Ahn, S. H., Yang, J. S., Choi, S., Jung, H. W., \u0026amp; Jeon, J. (2023). Plant protective and growth-promoting effects of seed endophytes in soybean plants. \u003cem\u003eThe Plant Pathology Journal\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(5), 513.\u003c/li\u003e\n\u003cli\u003eTariq, H., Viau, C., Subramanian,S., Geitmann, A. \u0026amp; Donald L Smith (2025).Exo-metabolome profiling of soybean endophytes: A road map of antagonism against \u003cem\u003eFusarium oxysporum\u003c/em\u003e.\u003cem\u003eMsystems.In press\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eDubey, A., Saiyam, D., Kumar, A., Hashem, A., Abd_Allah, E. F., \u0026amp; Khan, M. L. (2021). Bacterial root endophytes: Characterization of their competence and plant growth promotion in soybean (Glycine max (L.) Merr.) under drought stress. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(3), 931.\u003c/li\u003e\n\u003cli\u003eShah, A., Subramanian, S., \u0026amp; Smith, D. L. (2022). Seed priming with Devosia sp. cell-free supernatant (CFS) and citrus bioflavonoids enhance canola and soybean seed germination. \u003cem\u003eMolecules\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(11), 3410.\u003c/li\u003e\n\u003cli\u003eSari, R. N., Hafsah, S., \u0026amp; Hidayat, T. (2024, February). The effect of seed treatment using plant growth promoter rhizobacteria (PGPR) on the germination process of chili (Capsicum annum L.). In \u003cem\u003eIOP Conference Series: Earth and Environmental Science\u003c/em\u003e (Vol. 1297, No. 1, p. 012010). IOP Publishing.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Garc\u0026iacute;a, L. A., S\u0026aacute;enz-Mata, J., Fortis-Hern\u0026aacute;ndez, M., Navarro-Mu\u0026ntilde;oz, C. E., Palacio-Rodr\u0026iacute;guez, R., \u0026amp; Preciado-Rangel, P. (2023). Plant-growth-promoting rhizobacteria improve germination and bioactive compounds in cucumber seedlings. \u003cem\u003eAgronomy\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(2), 315.\u003c/li\u003e\n\u003cli\u003eJohnson, N. C. (2010). Resource stoichiometry elucidates the structure and function of arbuscular mycorrhizas across scales. \u003cem\u003eNew Phytologist\u003c/em\u003e, \u003cem\u003e185\u003c/em\u003e(3), 631-647.\u003c/li\u003e\n\u003cli\u003eHasan, A., Tabassum, B., Hashim, M., \u0026amp; Khan, N. (2024). Role of Plant Growth Promoting Rhizobacteria (PGPR) as a Plant Growth Enhancer for Sustainable Agriculture: A Review. Bacteria 2024, 3, 59\u0026ndash;75. \u003cem\u003eInteraction between Plants and PGPR for Sustainable Development\u003c/em\u003e, 1.\u003c/li\u003e\n\u003cli\u003eElbagory, M., Farrag, D. K., \u0026amp; Doha, N. M. (2024). Effects of PGPR inoculation and Vermicompost on the growth, physiological traits, microbial activity, and yield of lettuce (Lactuca sativa L.) plants. \u003cem\u003eEnvironment, Biodiversity and Soil Security\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(2024), 83-95.\u003c/li\u003e\n\u003cli\u003eKaya, C. (2024). Microbial modulation of hormone signaling, proteomic dynamics, and metabolomics in plant drought adaptation. \u003cem\u003eFood and Energy Security\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), e513.\u003c/li\u003e\n\u003cli\u003eJalmi, S. K., \u0026amp; Sinha, A. K. (2022). Ambiguities of PGPR-induced plant signaling and stress management. \u003cem\u003eFrontiers in microbiology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 899563.\u003c/li\u003e\n\u003cli\u003eTripathi, A., Pandey, V. K., Jain, D., Singh, G., Brar, N. S., Taufeeq, A., ... \u0026amp; Rustagi, S. (2024). An updated review on significance of PGPR-induced plant signalling and stress management in advancing sustainable agriculture. \u003cem\u003eJournal of Agriculture and Food Research\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e, 101169\u003c/li\u003e\n\u003cli\u003eMeena, M., Swapnil, P., Divyanshu, K., Kumar, S., Harish, Tripathi, Y. N., ... \u0026amp; Upadhyay, R. S. (2020). PGPR‐mediated induction of systemic resistance and physiochemical alterations in plants against the pathogens: Current perspectives. \u003cem\u003eJournal of Basic Microbiology\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e(10), 828-861\u003c/li\u003e\n\u003cli\u003eFattorini, L., Veloccia, A., Della Rovere, F., D\u0026rsquo;angeli, S., Falasca, G., \u0026amp; Altamura, M. M. (2017). Indole-3-butyric acid promotes adventitious rooting in Arabidopsis thaliana thin cell layers by conversion into indole-3-acetic acid and stimulation of anthranilate synthase activity. \u003cem\u003eBMC plant biology\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e, 1-14.\u003c/li\u003e\n\u003cli\u003eAli, J., Mukarram, M., Ojo, J., Dawam, N., Riyazuddin, R., Ghramh, H. A., ... \u0026amp; Bayram, A. (2024). Harnessing phytohormones: Advancing plant growth and defence strategies for sustainable agriculture. \u003cem\u003ePhysiologia Plantarum\u003c/em\u003e, \u003cem\u003e176\u003c/em\u003e(3), e14307.\u003c/li\u003e\n\u003cli\u003eYan, H., Chaumont, N., Gilles, J. F., Bolte, S., Hamant, O., \u0026amp; Bailly, C. (2020). Microtubule self-organisation during seed germination in Arabidopsis. \u003cem\u003eBMC biology\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e, 1-15.\u003c/li\u003e\n\u003cli\u003eKumar, S., Jeevaraj, T., Yunus, M. H., Chakraborty, S., \u0026amp; Chakraborty, N. (2023). The plant cytoskeleton takes center stage in abiotic stress responses and resilience. \u003cem\u003ePlant, cell \u0026amp; environment\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(1), 5-22.\u003c/li\u003e\n\u003cli\u003eHan, C., He, D., Li, M., \u0026amp; Yang, P. (2014). In-depth proteomic analysis of rice embryo reveals its important roles in seed germination. \u003cem\u003ePlant and Cell Physiology\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(10), 1826-1847.\u003c/li\u003e\n\u003cli\u003eXu, F. Q., \u0026amp; Xue, H. W. (2019). The ubiquitin‐proteasome system in plant responses to environments. \u003cem\u003ePlant, cell \u0026amp; environment\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(10), 2931-2944.\u003c/li\u003e\n\u003cli\u003eBlanco-Touri\u0026ntilde;\u0026aacute;n, N., Serrano-Mislata, A., \u0026amp; Alabad\u0026iacute;, D. (2020). Regulation of DELLA proteins by post-translational modifications. \u003cem\u003ePlant and Cell Physiology\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(11), 1891-1901.\u003c/li\u003e\n\u003cli\u003eSrivastava, A. K., Suresh Kumar, J., \u0026amp; Suprasanna, P. (2021). Seed \u0026lsquo;primeomics\u0026rsquo;: plants memorize their germination under stress. \u003cem\u003eBiological Reviews\u003c/em\u003e, \u003cem\u003e96\u003c/em\u003e(5), 1723-1743.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Soybean microbiome, Label-free proteomics, Endophyte-host interaction, Bacillus strains, Proteomic reprogramming","lastPublishedDoi":"10.21203/rs.3.rs-7602726/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7602726/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Plant adaptation to environmental stress involves tightly regulated cellular, molecular, and biochemical responses. Among these, microbe-assisted strategies have gained attention, particularly the role of the plant microbiome (phytomicrobiome) in promoting growth and stress resilience. Soybean (), a major agricultural crop, actively recruits beneficial microbes through root-secreted secondary metabolites, fostering symbiotic interactions with endophytic bacteria. However, the direct and indirect impacts of root-associated endophytes on plant development remain incompletely understood. In this study, we investigated three strains (HT1, HT2, and HT3) isolated previously from the soybean root microbiome for their potential plant growth-promoting and biocontrol activities. -HT1 and HT2 significantly enhanced soybean seed germination, while -HT3 promoted leaf area expansion significantly compared to the control, indicating strain-specific developmental effects. To elucidate the molecular basis of these effects, we conducted shotgun proteomic profiling of soybean leaves. Enrichment analysis revealed distinct functional signatures, with HT1 and HT2 associated with pathways linked to cellular component organization, microtubule dynamics, and organelle function, and -HT3 inducing broader enrichment of photosynthesis, chloroplast organization, and biosynthetic processes. These findings suggest that HT1 and HT2 promote early developmental transitions, while HT3 enhances vegetative growth through large-scale metabolic reprogramming. Notably, proteins such as anthranilate synthase and proteasome subunit alpha type were differentially abundant, pointing to the potential involvement of auxin biosynthesis and ubiquitin\u0026ndash;proteasome\u0026ndash;mediated regulation but, the actual roles of these pathways remain to be validated. These findings provide mechanistic insights into how specific strains modulate soybean development at the molecular level and highlight their potential for use as bio-inoculants to enhance crop productivity and resilience under stress conditions.","manuscriptTitle":"Plant Growth-Promoting Bacillus Strains Modulate Early Soybean Development via Proteome Remodelling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-07 11:16:32","doi":"10.21203/rs.3.rs-7602726/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-14T05:08:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-26T09:03:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T22:44:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186057265570571945029682540638731036516","date":"2025-10-22T04:49:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172399346276238829227073210193521156988","date":"2025-10-17T03:18:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66708741157301642739105940950343860126","date":"2025-09-25T06:19:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75795460057536794479707020435579298442","date":"2025-09-25T04:39:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-25T04:11:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-19T08:10:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-18T03:39:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T14:17:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-09-17T14:13:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"278e6804-8c9d-404a-af8b-ab85d6e6e8c6","owner":[],"postedDate":"October 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:01:28+00:00","versionOfRecord":{"articleIdentity":"rs-7602726","link":"https://doi.org/10.1186/s12870-025-07972-y","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2025-12-27 15:57:55","publishedOnDateReadable":"December 27th, 2025"},"versionCreatedAt":"2025-10-07 11:16:32","video":"","vorDoi":"10.1186/s12870-025-07972-y","vorDoiUrl":"https://doi.org/10.1186/s12870-025-07972-y","workflowStages":[]},"version":"v1","identity":"rs-7602726","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7602726","identity":"rs-7602726","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}