Abstract Glyphosate (Gly) is a widely used herbicide for weed control in agriculture, but it can also adversely affect crops by impairing growth, reducing yield, and disrupting nutrient uptake, while inducing toxicity. Therefore, adopting integrated eco-friendly approaches and understanding the mechanisms of glyphosate tolerance in plants is crucial, as these areas remain underexplored. This study provides proteome insights into Si-mediated improvement of Gly-toxicity tolerance in Brassica napus. The proteome analysis identified a total of 4,407 proteins, of which 594 were differentially abundant, including 208 up-regulated and 386 down-regulated proteins. These proteins are associated with diverse biological processes in B. napus, including energy metabolism, antioxidant activity, signal transduction, photosynthesis, sulfur assimilation, cell wall functions, herbicide tolerance, and plant development. Protein-protein interactome analyses confirmed the involvement of six key proteins, including L-ascorbate peroxidase, superoxide dismutase, glutaredoxin-C2, peroxidase, glutathione peroxidase (GPX) 2, and peptide methionine sulfoxide reductase A3 which involved in antioxidant activity, sulfur assimilation, and herbicide tolerance, contributing to the resilience of B. napus against Gly toxicity. The proteomics insights into Si-mediated Gly-toxicity mitigation is an eco-friendly approach, and alteration of key molecular processes opens a new perspective of multi-omics-assisted B. napus breeding for enhancing herbicide resistant oilseed crop production. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-87024-5. Keywords: Key antioxidant proteins, Eco-friendly approach, Herbicide toxicity, Herbicide tolerance, Label-free proteomics Subject terms: Plant sciences, Environmental sciences Introduction In modern agriculture, glyphosate (N-(phosphonomethyl) glycine) is a systemic non-selective herbicide valued for its broad-spectrum effectiveness against a diverse range of weeds. Since its introduction in the 1970s, Gly become an essential component of worldwide agricultural operations, especially with the rise of genetically engineered crops that are resistant to its effect^[44]1. This compatibility led to more effective weed control, reduced labor costs, and increased agricultural productivity and overall farming efficiency. Despite its widespread use and effectiveness, the indiscriminate application of Gly has raised concerns about its environmental and ecological impacts, particularly on non-target plant species^[45]2. Scientific research has linked the widespread use of Gly to potential negative impacts, including biodiversity loss, the emergence of Gly-resistant weed species, and disturbance to microbial communities in soil ecosystems^[46]3. Understanding the molecular mechanisms underpinning Gly tolerance in plants is critical in developing environmentally suitable approaches to reduce glyphosate-induced toxicity. Silicon (Si) has emerged as a promising agent for enhancing plant resistance against various abiotic and biotic stresses, counteracting the negative impacts of Gly on non-target plants^[47]4,[48]5. Recent studies have revealed the significance of Si in modulating plant physiological responses, including those related to stress tolerance mechanisms through restoring redox homeostasis^[49]6. However, the molecular basis of Si-mediated mitigation of Gly toxicity, particularly in B. napus L., remain largely unexplored. Brassica napus L., also commonly known as rapeseed or canola, is an economically significant oilseed crop that substantially contributes to the edible oil sector. It contains high levels of essential fatty acids, carbohydrates, proteins, vitamins, and minerals and plays an important role in the human diet by providing a variety of nutritional advantages^[50]7,[51]8. It also provides a sustainable source for biodiesel and biolubricant production. However, it has been observed to exhibit lower yield and modified physiological processes when exposed to Gly, highlighting the need for sustainable farming approaches that minimize these harmful effects^[52]9. Due to the distinct genetic makeup and the biochemical compositions, this plant is an ideal model for advanced study on the resilience mechanisms, especially when it comes to environmental stresses such as glyphosate-induced toxicity^[53]10,[54]11. Hence, this work utilizes the resilient features of B. napus to uncover the underlying proteomic responses and adaptive mechanisms used by this plant to counteract the Gly-induced stress, integrating the physiological observations with state-of-the-art proteomic techniques. The advent of proteomics has provided insights into the complex molecular dynamics of plant responses to various environmental stressors^[55]12. Label-free quantification is a widely used proteomic technique that enables comprehensive and unbiased assessment of protein expression changes without requiring complex labeling processes^[56]13. This contrasts with traditional gel-based approaches, which, while effective, are sometimes constrained by their lower throughput and sensitivity. Researchers may now unravel the intricate networks of protein interactions as well as modifications that help plants sustain herbicide-induced stress by exploiting the capabilities of label-free proteomics^[57]14. Thus, our study aims to elucidate the protective implications of Si in B. napus exposed to Gly, using a label-free proteomic approach to map the protein expression landscape. We sought to understand the molecular mechanisms behind silicon’s mitigating effects by studying the differential expression of proteins involved in critical biological functions such as energy metabolism, photosynthesis, signal transduction, and antioxidant defense. Our findings reveal a considerable alteration in the proteome of B. napus leaves, as evidenced by the differential expression of key proteins involved in antioxidant responses, sulfur absorption, and herbicide tolerance. These insights not only improve our understanding of the molecular responses of B. napus to Gly treatment but also open the path towards developing targeted breeding and management techniques to enhance Gly tolerance in crops (Fig. [58]1). Fig. 1. [59]Fig. 1 [60]Open in a new tab Graphical abstract of Si-mediated Gly toxicity tolerance in Brassica napus. Glyphosate application inhibits the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPs), triggering mitochondrial dysfunction, the overproduction of reactive oxygen species (ROS), and consequent cellular damage manifested as chlorosis, necrosis and impaired growth. In contrast, Si application under Gly stress boosts photosynthesis, biomass accumulation, growth, and nutrient uptake while alleviating chlorosis and necrosis. Proteomic analysis reveals that Si treatment activates some diverse protective mechanisms, including energy and metabolism, photosynthesis, signal transduction, antioxidant defense, cell wall and cytoskeleton, herbicide tolerance and sulfur assimilation, and plant developmental processes. Among these mechanisms, several key proteins related to antioxidant activity, sulfur assimilation, and herbicide tolerance contribute to glyphosate tolerance as confirmed by interactome analysis in the main text. The proteomic alterations enhance Gly-tolerance in Brassica napus under Si supplementation. Abbreviation, EPSPs, 5-enolpyruvylshikimate-3-phosphate synthase; ROS, reactive oxygen species; Si; silicon; Gly, glyphosate. Materials and methods Plant culture and treatments The healthy seeds of Brassica napus were obtained from the National Institute of Crop Research (NICR), Rural Development Administration (RDA), Muan, South Korea as a gift. The B. napus seeds were subjected to surface sterilization using a 1% sodium hypochlorite solution for 20 min, followed by thorough washing with sterile purified water three times. Subsequently, the seeds were transferred to the germination tray and placed in a controlled environment for five days, with a photoperiod of 14 h of light and 10 h of darkness, at a temperature of 25 °C. A growth chamber was used to maintain a relative humidity of 65%, and 14 h light with a light density of 150 molm^− 2s^− 1, 10 h darkness, with 25 °C temperature. After germination, healthy seedlings were transplanted into plastic boxes containing nutrient solutions. The seedlings were hydroponically cultivated by using the Hoagland nutrient solution^[61]15. The solution was changed every 2 days to prevent potential precipitation of nutrients, Gly and Si. The air was supplied continuously through the electric air pump in the nutrient solution for sufficient oxygen. After 21 days of cultivation, the seedlings underwent exposure to different nutrient solutions, either with or without Gly and Si: Control; Gly (40 µM); Gly (40 µM) + Si (0.5 mM), Si (0.5 mM). The experiments included three biological replicates and five technical replicates for each treatment. The plants were harvested after seven days of the treatment application. The samples were immediately frozen in liquid nitrogen and stored at -80 °C until they were ready for molecular and biochemical analyses. Measurement of morphological features The shoot and root heights of the plants were measured (cm), and their fresh weights were measured with electronic balance immediately (EPG214C, Pine Brook, USA). The samples were dried and dry weights were then recorded. Analysis of chlorophyll contents The photosynthetic pigments concentration was determined by following a slightly modified method^[62]16. In brief, 0.04 g of plant material was homogenized with dimethyl sulfoxide (DMSO). The homogenate was incubated at 65 °C for 4 h, then centrifuged at 10,000 rpm for 10 min. The supernatant’s absorbance was measured at 452, 644 and 663 nm. The photosynthetic pigments concentrations were calculated using the following equations^[63]17: graphic file with name M1.gif graphic file with name M2.gif graphic file with name M3.gif graphic file with name M4.gif Measurement of ROS levels (H2O2 and O2•−) The concentration of hydrogen peroxide (H[2]O[2]) was determined according to previously described method^[64]18. Superoxide (O[2]^•−) levels were determined using the previously described extinction coefficient method^[65]19. Analysis of antioxidant enzymes (SOD, CAT, APX and GST) Leaf tissue was homogenized individually using a mortar and pestle with 100 mM potassium phosphate buffer (pH 7.0). The homogenate was centrifuged at 8000 rpm for 10 min, and the supernatant was collected for enzyme activity analysis. SOD activity was measured by adding 100 µL of plant extract to a mixture containing 50 mM NaHCO[3] (pH 9.8), 0.1 mM EDTA, and 0.6 mM epinephrine, following the previously described protocol^[66]20. After four min, the formation of adrenochrome was recorded at 475 nm. To determine CAT activity, a mixture of 100 µL of plant extract and 6% H[2]O[2], 100 mM potassium phosphate buffer (pH 7.0) was used. The absorption of the solution was measured at 240 nm at 30-second intervals, using an extinction coefficient of 0.036 mM⁻¹cm⁻¹. APX activity was assessed by mixing 0.1 mL of plant extract with 0.1 mM EDTA, 0.1 mM H[2]O[2], 50 mM potassium phosphate buffer (pH 7.0), and 0.5 mM ascorbic acid with, according to the previously described method^[67]21. The absorbance of the mixture was measured at 290 nm, with APX activity calculated using an extinction coefficient of 2.8 mM⁻¹cm⁻¹. GST activity was determined by adding 100 µL of the sample extract in 1.5 mM GSH, 1 mM 1-chloro-2,4-dinitrobenzene (CDNB) and 100 mM Tris-HCl buffer (pH 6.5), following the previously described method^[68]22. The absorbance of the mixture was measured at 340 nm. Extraction and measurement of proteins Protein extraction from the tissue was conducted using a TCA/acetone-based previously described method^[69]23. Leaf samples were ground with liquid nitrogen using a mortar and pestle. A 0.5 g sample was homogenized in a solution of 10% TCA, 0.07% (v/v) 2-mercaptoethanol and ice-cold acetone. The mixture was sonicated for 10 min, incubated at -20 °C for 1 h., and centrifuged at 9000 g for 20 min at 4 °C. The protein pellet was washed with cold acetone, dried and reconstituted in a buffer. After 1 h at room temperature, the mixture was centrifuged at 20,000 g for 20 min at 25 °C, and the protein concentration was measured using the Bradford assay^[70]24. Purification and digestion The leaf proteins of B. napus were purified using the methanol-chloroform method^[71]25. Initially, 450 µL of water with 150 µL of chloroform were added, vortexed and centrifuged at 20,000 g for 10 min. After removing the aqueous phase, the organic phase was mixed with 450 µL of methanol. After another centrifugation under the same conditions, the supernatant was discarded. The resulting pellet was air-dried for 10 min and re-dissolved in 50 mM NH[4]CO[3]. Each sample was reduced by incubating with 50 mM DTT at 56 °C for 30 min. IAA was then added, and the samples were kept at 37 °C temperature for 30 min. Trypsin was added to the sample and incubated for 16 h, following previously described method^[72]26. To prepare the trypsin solution, 200 µL of Trypsin Resuspension Buffer (PROMEGA) was added to a vial containing 20 µg of sequencing-grade modified trypsin (porcine). The samples were purified using previously described method^[73]23, transferred to new tubes and prepared for MS analysis. LC MS analysis The extracted peptides were analyzed using a mass spectrometer (Thermo Fisher LTQ Orbitrap, Germany) combined with an Agilent 1100 nano-flow HPLC system with a standard ion source. The setup involved two columns. A three-way tee connector was used to connect the pre-column, waste line, and analytic column (C18 AQ, 3 m, 100 m x 15 cm, Nano LC, USA). A 10 µL volume of peptide solution was loaded onto the trap column (75 μm x 2 cm, nano Viper C18, 3 μm, Thermo Fisher Scientific). Two distinct solvent phases, A and B, were utilized, consisting of 0.1% formic acid (FA) in water (solvent A) and 0.1% FA in 100% ACN (solvent B). The peptides were desalted and concentrated on the trap column for 10 min using solvent (A) A fixed linear gradient over 150 min was used to elute the peptides with solvent B at a flow rate of 300 nL/min. To ensure cleanliness, the column was washed with at least ten column volumes of 100% solvent (B) Peak validity was confirmed using a standard peak shape method, considering only those peaks with well-defined symmetrical shapes as valid^[74]27. In full MS scans, the top five peaks were fragmented using data-dependent acquisition with 35% normalized collision energy. Peptide ions were introduced at 2.2 kV capillary voltage. The MS settings included a 0.5 Da mass exclusion width, 180 s dynamic exclusion, and spectra were recorded from 50 to 2000 m/z. Validation of peptide The MS/MS spectra were analyzed using Mascot Daemon, against the GPR database ([75]http://www.uniprot.org.). Search parameters included a ± 1.5 Da precursor mass tolerance, ± 0.8 Da fragment mass tolerance, up to two missed trypsin cleavages, and carbamidomethyl cysteine modification. Mascot’s ion score threshold was set at 0.05, and peptide identification was validated with a 1% FDR (false discovery rate) threshold. The peptide score, calculated as -10 Log, this peptide needed a homology score with P < 0.01. Label-free quantification followed the previously described protocol^[76]28, excluding reverse decoy matches and impurities. Proteins required identification with at least two distinct peptides and quantification in at least two technical replicates across four biological replicates, with average intensities calculated for each group. Statistical analysis Statistical analysis used a two-sided t-test, with FDR (false discovery rate) correction for multiple comparisons, conducted in Perseus statistical software with default settings. Data were normalized by linear regression and transferred to excel for detailed analysis. Peptides matching common impurities were filtered out and at least three biological replicates were used for relative quantification and protein identification. Analysis of bioinformatics Gene-encoded proteins were analyzed for their cellular components, molecular functions, and biological processes using the DAVID Bioinformatics ([77]https://david.ncifcrf.gov/). This DAVID tool provides a comprehensive platform for the analysis of gene lists and functional annotation, integrating various genomic resources to elucidate gene functions and their biological significance. The abundance pattern of proteins were visualized with a heatmap generated by ClustVis ([78]https://biit.cs.ut.ee/clustvis/). Fold change in protein levels between the control and the treatments was calculated by comparing the average normalized values, with p-value analysis determining significance. Upregulation and downregulation patterns were analyzed using the previously described methodology^[79]29, with a significance threshold of ≤ 0.05. Furthermore, the KEGG ([80]http://www.genome.jp/kegg/pathway.html) was used to confirm the involvement of these proteins in plant molecular processes^[81]30. Interactome analyses Protein-protein interactions were examined with STRING database ([82]https://string-db.org/), which classified the interactions according to the primary functions of the candidate proteins. The resulting network was visualized by Cytoscape ([83]https://cytoscape.org/)^31. The 3D structures of key proteins related to sulfur assimilation, antioxidant activity, and Gly tolerance were modeled using the SWISS-MODEL ([84]https://swissmodel.expasy.org/) web tool. Models were chosen based on the Global Model Quality Estimation (GMQE) score, which ranges from 0 to 1, with higher scores indicating greater confidence and accuracy in the protein models. Data analyses Data analysis was conducted using ANOVA, and the results are displayed as the mean of three biological replicates with standard error (SE). Comparisons between treatments were performed using Student’s t-test, considering a p-value of ≤ 0.05 as statistically significant. Graphical presentations were generated using GraphPad Prism software (Version 9.0). Results Morphological features Gly toxicity significantly inhibited the growth of B. napus, causing notable reductions in root and shoot lengths, as well as a substantial decrease in overall plant biomass. However, the addition of Si restored these characteristics (Fig. [85]2). Specifically, Gly toxicity reduced shoot length by 28.27% and root length by 53.13% compared to control plants. Similarly, shoot fresh weight, root fresh weight, shoot dry weight, and root dry weight decreased by 53.63%, 41.29%, 27.21%, and 50.76%, respectively (Fig. [86]2). Fig. 2. [87]Fig. 2 [88]Open in a new tab Effect of exogenous Gly and Si on shoot length (A), Root length (B), shoot fresh weight (C), root fresh weight (D), shoot dry weight (E) and root dry weight (F) in Brassica napus seedlings with 40 µM Gly and 0.5 mM Si. Abbreviation, Gly, glyphosate, Si, silicon. Each value represents the mean of three replicates ± SE. Different letters indicate significant differences at p < 0.05 among treatments by Tukey’s test. Chlorophyll contents Due to Gly toxicity, photosynthetic pigments, including chlorophyll a, chlorophyll b, total chlorophyll and carotenoids were drastically reduced by 62.30%, 73.56%, 65.47% and 88.50% respectively compared to seedlings under control treatments (Fig. [89]3A-D). Alternatively, the addition of Si to Gly (40 µM) treatment significantly restored these pigments in B. napus. Specifically, Chlorophyll a, Chlorophyll b, total Chlorophyll and carotenoids increased by 90.68%, 73.54%, 86.97% and 191.76%, respectively, compared to Gly-treated seedlings (Fig. [90]3A-D). Fig. 3. [91]Fig. 3 [92]Open in a new tab Effect of exogenous Gly and Si on chlorophyll a (A), chlorophyll b (B), total chlorophyll a + b (C), carotenoids (D), H[2]O[2] content (E), O[2]•^− content (F) in Brassica napus leaves. The normal growth condition (absence of Gly and Si; control), Gly (40µM), Gly + Si (40µM Gly + 0.5 mM Si), and Si (0.5 mM Si). Abbreviation, Gly, glyphosate; Si, silicon. Each value represents the mean of three replicates ± SE. Different letters indicate significant differences at p < 0.05 among treatments by Tukey’s test. Changes of H2O2 and O2•- Under Gly stress, the H[2]O[2] content in B. napus increased by 63.82% compared to control plants (Fig. [93]3E). Exogenous supplementation of Si significantly reduced H[2]O[2] and O[2]^•-. Additionally, the concentration of O[2]^•- raised by 45.67% under Gly-treated plants compared to the plants under control treatments (Fig. [94]3F). However, the addition of Si considerably decreased O[2]•^-, indicating that Si effectively mitigates the overproduction of O[2]•^- under Gly stress. No significant difference was detected between the control plants and those treated exclusively with Si. These findings suggest that Si was active in response to Gly-toxicity that significantly mitigated oxidative stress in B. napus. Changes in antioxidant enzyme activity Compared to the control plants, Gly treatment resulted in a prominent elevation in SOD activity (Fig. [95]4A). Si supplementation remarkably reduced this SOD activity, whether or not Gly was present (Fig. [96]4A). Under Gly treatment, CAT and APX activities significantly increased compared to control plants (Fig. [97]4B, C). However, these activities decreased following Si supplementation, both with and without Gly treatment (Fig. [98]4B, C). Additionally, GST activity consistently increased under Gly treatment compared to the control (Fig. [99]4D). Notably, the addition of Si to Gly treatment further enhanced GST activity, whereas Si treatment alone resulted in a reduction in GST activity (Fig. [100]4D). Fig. 4. [101]Fig. 4 [102]Open in a new tab Effect of exogenous Gly and Si on enzyme activities SOD (A), CAT (B), APX (C), GST (D) in Brassica napus leaves. Each value represents the mean of three replicates ± SE. Different letters indicate significant differences at p < 0.05 among treatments by Tukey’s test. Gly-induced alterations of B. napus proteome In B. napus, Gly-toxicity substantially altered the responses of the global leaf proteome. A proteomic approach was used to identify a total of 4407 proteins, from which many key functional proteins were screened. A proteomic approach identified a total of 4,407 proteins, among which several key functional proteins were screened. Across all treatment groups, 594 differentially abundant proteins (DAPs) were identified (Fig. [103]5A, Suppli. Table S3). Comparison between the control plants and the Gly-treated plants (C vs. Gly), we identified 208 DAPs, with 75 proteins showing increased abundance and 133 showing decreased abundance. In the C vs. Gly + Si comparison, 106 and 192 proteins were differentially abundant, respectively, while in the C vs. Si comparison, 27 and 61 proteins were differentially abundant (Fig. [104]5A). Fig. 5. [105]Fig. 5 [106]Open in a new tab Identification and statistics analysis of identified proteins under different treatment groups. (A) number of up or downregulated proteins between the control group and different treatments, (B) venn diagram analysis for common proteins (CP), and (C) venn diagram analysis for upregulated and downregulated proteins. Abbreviation, C, control; Gly, glyphosate; Si, silicon. We identified a total of 2004 differentially abundant common proteins across the control, Gly, Gly + Si, and Si groups (Fig. [107]5B). A Venn diagram was used to display the protein abundance patterns, highlighting the upregulated and downregulated DAPs for thorough understanding (Fig. [108]5C, Suppli. Table S3). Particularly, the commonly identified proteins were 16 DAPs among C vs. Gly, C vs. Gly + Si, and C vs. Si treatment groups. Gly stress induced a total of 75 proteins, while Gly + Si altered 106 DAPs in B. napus. The quantified protein profile differences were visually displayed using a heatmap. These proteins were classified according to their functions within cellular components, molecular functions, and biological processes (Fig. [109]6). Fig. 6. [110]Fig. 6 [111]Open in a new tab Heatmap of differentially abundant candidate proteins. The zero (0) indicates the neutral or no significant changes, while 2 value indicate the highest significant upregulation, -2 value indicates the lowest significant downregulation of candidate proteins. Abbreviation, Gly, glyphosate; Si, silicon. GO analysis of commonly identified proteins (CIPs) Biological processes, molecular functions and cellular components of frequently discovered proteins were displayed by Gene Ontology (GO) findings (Fig. [112]7A-C). In the category of biological process, proteins were associated with some functions, including translation (34%), protein folding (11%), proteasomal protein catabolic process (10%), Photosynthesis (8%), response to oxidative stress (8%), protein refolding (7%), photorespiration (6%), chaperone mediated protein folding requiring cofactor (6%), protein peptidyl-prolyl isomerization 5%) and ATP synthesis coupled proton transport (5%) (Fig. [113]7A, Suppli. Table S4). Likewise, in cellular component analyses category, the proteins showed the significant association, including cytoplasm (29%), chloroplast (16%), cytosol (12%), nucleosome (10%), mitochondrion (8%), cytosolic large ribosomal subunit (6%), cytosolic small ribosomal subunit (5%), chloroplast thylakoid membrane (5%), ribosome (5%) and proteasome core complex (4%) (Fig. [114]7B, Suppli. Table S4). In molecular function category, the identified proteins were associated with some functions, including structural constituent of ribosome (22%), RNA binding (15%), protein heterodimerization activity (15%), oxidoreductase activity (9%), ATPase activity (8%), mRNA binding (8%), peptidyl-prolyl cis-trans isomerase activity (6%), hydrolase activity, acting on ester bonds (6%), pyridoxal phosphate binding (6%), and serine-type endopeptidase activity (5%) (Fig. [115]7C, Suppli. Table S4). Fig. 7. [116]Fig. 7 [117]Open in a new tab Gene ontology (GO) function analyses in Brassica napus leaf samples. (A) biological process, (B) cellular component, and (C) molecular function of the common identified proteins (CIPs) in Brassica napus seedlings in response to Si-mediated Gly stress using DAVID bioinformatics platform. The result of GO analysis showed the commonly identified differentially abundant proteins were significantly affected by Gly stress. According to the DAVID Bioinformatics analysis, a total of 2004 proteins exhibited alterations with 43 KEGG pathways correspondence (Suppli. Table S2). These proteins were associated with various metabolic pathways, including general metabolic pathways (bna01100) involving 817 proteins, carbon metabolism (bna01200) involving 214 proteins, amino acid biosynthesis (bna01230) involving 142 proteins, ribosome function (bna03010) involving 279 proteins, and secondary metabolite biosynthesis (bna01110) involving 419 proteins (Suppli. Table S2). GO analysis of differentially abundant proteins (DAPs) The relation of DAPs to various biological process were revealed through GO analysis (Suppli. Table S1). In the category of biological process, the DAPs were associated with some processes, including translation (40 DAPs), protein folding (13 DAPs), proteasomal protein catabolic process (12 DAPs), photosynthesis (10 DAPs), response to oxidative stress (9 DAPs), protein refolding (8 DAPs), and photorespiration (7 DAPs). (Fig. [118]8, Suppli. Table S5). In cellular component category, cytoplasm (82 DAPs), chloroplast (44 DAPs), cytosol (33 DAPs), nucleosome (29 DAPs), mitochondrion (21 DAPs), cytosolic large ribosomal subunit (16 DAPs), cytosolic small ribosomal subunit (15 DAPs), chloroplast thylakoid membrane (13 DAPs) and ribosome (13 DAPs) displayed the leading categories (Fig. [119]8, Suppli. Table S5). In the category of molecular functions, GO terms of DAPs displayed important enrichment, including structural constituent of ribosome (41 DAPs), RNA binding (28 DAPs), protein heterodimerization activity (27 DAPs), oxidoreductase activity (16 DAPs), ATPase activity (14 DAPs), mRNA binding (14 DAPs), peptidyl-prolyl cis-trans isomerase activity (12 DAPs), hydrolase activity, acting on aster bonds (12 DAPs), and pyridoxal phosphate binding (12 DAPs) (Fig. [120]8, Suppli. Table S5). Fig. 8. [121]Fig. 8 [122]Open in a new tab The GO functions of differentially abundant proteins (DAPs) involved in different physiological process in Brassica napus leaves in response to Gly and Si. Abbreviation, BP, biological process; CC, cellular component; and MF, molecular function. The bar chart was constructed through the DAVID bioinformatics platform. KEGG pathways of CIPs and DAPs The impact of Gly stress on leaf metabolism in B. napus seedlings was examined by constructing a potential metabolic pathway using the KEGG database ([123]http://www.kegg.jp/; accessed on January 24, 2024). DAPs and CIPs were the key components for developing this pathway. The dot plot visualized the KEGG pathways with the highest enrichment (Fig. [124]9A, B). Fig. 9. [125]Fig. 9 [126]Open in a new tab Dot plot of the KEGG pathway enrichment analysis for (A) common identified proteins (CIPs) and (B) differentially abundant proteins (DAPs) in Brassica napus seedlings in response to Si-mediated Gly stress. The horizontal axis represents the enrichment rate of the input proteins in the pathway, while the vertical axis represents the name of pathways. The color scale indicates different thresholds of the p-value, and the size of the dot indicates the number of proteins corresponding to each term. The bubble map was constructed through the Science and Research Plot platform ([127]https://tinyurl.com/pve3dtnw). In all treatment groups of CIPs, the KEGG pathways that showed the highest enrichment were identified as follows: metabolic pathways (bna01100) with 817 proteins, biosynthesis of secondary metabolites (bna01110) with 419 proteins, ribosome (bna03010) with 279 proteins, carbon metabolism (bna01200) with 214 proteins, biosynthesis of amino acids (bna01230) with 142 proteins, photosynthesis (bna00195) with 96 proteins, carbon fixation in photosynthetic organisms (bna00710) with 90 proteins, biosynthesis of cofactors (bna01240) with 87 proteins, oxidative phosphorylation (bna00190) with 85 proteins, glycolysis/gluconeogenesis (bna00010) with 84 proteins, glyoxylate and dicarboxylate metabolism (bna00630) with 80 proteins, cysteine and methionine metabolism (bna00270) with 67 proteins, and pyruvate metabolism (bna00620) with 62 proteins. (Suppli. Table S2). In all DAPs treatment groups, the pathways that showed the highest enrichment were identified as follows: metabolic pathways (bna01100) with 69 proteins, biosynthesis of secondary metabolites (bna01110) with 41 proteins, ribosome (bna03010) with 23 proteins, carbon metabolism (bna01200) with 17 proteins, glyoxylate and dicarboxylate metabolism (bna00630) with 11 proteins, biosynthesis of amino acids (bna01230) with 11 proteins, proteasome (bna03050) with 8 proteins, cysteine and methionine metabolism (bna00270) with 8 proteins, alanine, aspartate and glutamate metabolism (bna00250) with 6 proteins, fatty acid metabolism (bna01212) with 6 proteins, glycine, serine and threonine metabolism (bna00260) with 6 proteins, peroxisome (bna04146) with 6 proteins, and arginine biosynthesis (bna00220) with 5 proteins (Suppli. Table S6). Protein network Interactions between proteins offer crucial biological insights into the processes occurring within B. napus. The analysis of these interactions was facilitated by the tool STRING, which categorized the proteins based on their functions. Within the category of energy-metabolism-related proteins (Table [128]1), the protein ATP synthase subunit O (BnaC09g43620D, A0A078F9W7) was found to interact within a network that A0A078DNQ5, A0A078FXT7, A0A078FR19, A0A078GFM5, A0A078H5Q9 and A0A078FQR6 (Fig. [129]10A). The photosynthesis category (Table [130]1) exhibited that photosystem I reaction center subunit II (BnaA09g01080D, A0A078G9Q8) sharing the protein network with A0A078J8I6, A0A078G7F6, A0A078I263, A0A078GY42 and A0A078GLT1 (Fig. [131]10B). The category of signal transduction (Table [132]1) displayed a significant interactions, where the protein (BnaA04g15900D, A0A078H195) exhibited a protein network sharing with A0A078FWF3, A0A078IT30, A0A078HEE7, A0A078HCR8, A0A078F7P2, A0A078FXI3, A0A078IMT1, A0A078F1F5, A0A078FJL5, A0A078GTV5, A0A078F3D0 and D1L8S1 (Fig. [133]10C). In protein categories (Table [134]1) antioxidant, sulfur assimilation and herbicide tolerance, the L-ascorbate peroxidase (BnaAnng04450D, A0A078HFK7) protein showed a share network with GPX 2 (BnaCnng27540D, A0A078IXA9), superoxide dismutase (BnaC03g16120D, A0A078H5C3), and probable phospholipid hydroperoxide GPX 6 (BnaA02g21680D, A0A078GL08) (Fig. [135]10D). Interactome of six candidate proteins related with sulfur assimilation and herbicide tolerance, and antioxidant, including L-ascorbate peroxidase (A0A078HFK7, BnaAnng04450D), superoxide dismutase (A0A078H5C3, BnaC03g16120D), glutaredoxin-C2 (A0A078HHH4, BnaC04g32420D), peroxidase (A0A078IWR4, BnaAnng12900D), GPX 2 (A0A078IXA9, BnaCnng27540D) and peptide methionine sulfoxide reductase A3 (A0A078JHR9, BnaC09g47890D) were shared protein networks by being mapped and analyzed within different protein interaction networks. This approach facilitated the identification of key interactions and functional roles across multiple biological contexts (Fig. [136]11A-F). Table 1. List of differentially abundant proteins (DAPs) identified in Brassica napus leaves in response to gly and Si using LC MS/MS mass spectrometry. Uniprot accession Protein name Gene accession Coverage (%) Protein score Fold change T1/CK T2/CK T3/CK Energy and metabolism-related proteins A0A078F9W7 ATP synthase subunit O BnaC09g43620D 27.9 112 0.641914 0.308654 0.515482 A0A078DNQ5 ATP synthase subunit d BnaA04g05550D 39.9 221 0.610627 0.07293 0.532053 A0A078HBM9 Sucrose-phosphate synthase BnaC09g37470D 5.2 51 1.160603 1.054256 0.368837 A0A078JFK9 Glucose-6-phosphate isomerase BnaA09g16190D 21.1 137 1.110806 0.859891 0.398182 A0A078FQR6 Pyruvate dehydrogenase E1 component subunit alpha BnaC05g00810D 30.1 389 0.278459 0.369308 0.501324 A0A078FHB3 NADP-dependent D-sorbitol-6-phosphate dehydrogenase BnaA09g43270D 10.7 38 0.560104 0.477702 0.576195 A0A078G5J5 Acetyl-CoA acetyltransferase, cytosolic 1 BnaA09g02880D 8.7 88 1.560391 1.027869 1.465700 A0A078FR19 2-hydroxyacyl-CoA lyase BnaC09g40570D 12.3 115 1.543537 1.151831 0.941912 A0A078I1T6 3‘(2’),5’-bisphosphate nucleotidase BnaA06g23120D 16.6 195 1.551473 1.401666 1.308774 A0A078FXT7 Isocitrate dehydrogenase [NAD] regulatory subunit 1, mitochondrial-like BnaC03g65310D 11 113 1.644654 1.450731 1.134525 A0A078J7I1 Probable NAD(P)H dehydrogenase (quinone) FQR1-like 2 BnaAnng18230D 4.2 51 2.130197 1.023216 1.279924 A0A078HTX7 Ferredoxin-thioredoxin reductase, variable chain-like BnaC02g41630D 20.3 207 1.147394 0.556879 1.243849 A0A078FU33 Acetyl-coenzyme A synthetase, chloroplastic/glyoxysomal BnaA04g12330D 4.7 66 0.940429 0.552378 0.889766 A0A078JN33 Glucose-1-phosphate adenylyltransferase BnaC09g54280D 20 161 0.677495 0.652565 0.898576 A0A078GX98 Ferredoxin BnaA01g18870D 36.1 346 0.675095 0.260915 0.741719 A0A078H0E1 ATP-dependent Clp protease proteolytic subunit-related protein 3 BnaCnng06590D 8.6 142 0.417604 0.808942 0.739474 A0A078I6S3 Ferredoxin, leaf L-A-like BnaCnng11890D 60.8 493 0.576922 1.184970 1.457765 A0A078FLD4 ATP-dependent Clp protease proteolytic subunit BnaC05g01290D 23.9 243 0.627616 0.844326 0.937172 A0A078GA43 Alternative NAD(P)H-ubiquinone oxidoreductase C1 BnaC09g47290D 11 81 0.535182 0.587395 1.150194 A0A078FUD9 NAD(P)H-quinone oxidoreductase subunit U BnaC09g36720D 6.5 54 0.417060 0.634000 1.045862 A0A078ICZ4 1,4-dihydroxy-2-naphthoyl-CoA synthase BnaC09g14630D 14.5 122 0.650433 0.614697 0.762897 A0A078JJZ9 Glucose-6-phosphate 1-dehydrogenase BnaCnng48180D 12 175 0.532154 0.641487 0.965326 A0A078F3 × 9 Acetyl-CoA carboxytransferase BnaA03g17570D 23.9 595 0.508116 0.555084 0.801322 A0A078IZH1 Phosphoglucomutase (alpha-D-glucose-1,6-bisphosphate-dependent) BnaC02g44120D 16.3 141 0.648889 0.656212 0.801299 A0A078GTL5 NADPH-protochlorophyllide oxidoreductase BnaA03g48610D 28.3 1331 0.510446 0.606909 1.297102 A0A078J698 Ribulose bisphosphate carboxylase/oxygenase activase BnaC06g43890D 18.8 148 0.598431 0.549122 0.814076 A0A078H5Q9 ATP-citrate synthase beta chain protein 2 BnaA02g30820D 27.1 420 0.563960 0.590482 0.666005 A0A078FEZ7 Phosphoglucomutase (alpha-D-glucose-1,6-bisphosphate-dependent) BnaC06g31970D 11.5 128 0.336701 0.301114 0.707119 A0A078IUF6 4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase (ferredoxin) BnaC09g54000D 40.1 757 0.646842 0.677358 0.745123 A0A078IKT4 NAD(P)H-quinone oxidoreductase subunit M BnaC03g61160D 20.9 74 0.572738 1.050565 0.787579 A0A078GAK7 Probable NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 12 BnaC04g49930D 12.6 56 1.516589 1.662329 1.532316 A0A078JE46 3-hydroxyisobutyryl-CoA hydrolase BnaCnng45560D 19.2 228 1.409853 1.666521 1.150921 A0A078GEI0 3-ketoacyl-CoA thiolase 2, peroxisomal-like BnaC04g43560D 18.4 251 1.576170 1.540472 1.301873 A0A078GFM5 Citrate synthase BnaC04g49560D 29.3 431 1.718077 2.309301 0.757696 A0A078HMR7 Ferredoxin–NADP reductase, chloroplastic BnaC09g21770D 6.6 76 2.784496 3.937910 2.047532 Photosynthesis-related proteins A0A078GDB8 Pyruvate dehydrogenase E1 component subunit alpha-1 BnaA01g22040D 21.9 279 1.503392413 1.095588 0.979475 A0A078H395 Acetyltransferase component of pyruvate dehydrogenase complex BnaC06g07040D 4.9 163 1.529129 1.144697 0.987798 A0A078G9Q8 Photosystem I reaction center subunit II BnaA09g01080D 60 731 0.779631 0.524350 1.207470 A0A078JQI2 Ribulose bisphosphate carboxylase small subunit BnaCnng55860D 60.8 2977 0.687302 0.59090 0.935430 A0A078FCT5 Cytochrome b5 BnaC04g12100D 21.8 32 0.582401 1.026269 1.014617 A0A078GHQ4 Light-harvesting complex-like protein 3 isotype 2 BnaC09g20020D 12.9 65 0.630690 0.849381 1.319439 A0A078G7F6 Chlorophyll a-b binding protein BnaC04g05260D 44.6 643 0.612507 0.803099 1.146516 A0A078F191 RuBisCO large subunit-binding protein subunit beta BnaA05g13740D 56.8 1586 0.654017 0.754457 0.875406 A0A078JWT1 Carboxypeptidase BnaCnng66490D 4.5 91 0.560883 0.615016 1.027021 A0A078IQK6 psbP domain-containing protein 2 BnaA04g16500D 9.3 56 0.413269 0.453155 0.789982 A0A078GUT8 Protochlorophyllide reductase B BnaC01g19630D 58.7 2075 0.466504 0.471211 1.074177 A0A078J638 Photosystem II stability/assembly factor HCF136 BnaC07g49760D 38.7 609 0.651477 0.648676 0.762717 A0A078IBE5 Cytochrome c oxidase subunit 6b-1 BnaA07g10470D 28.1 197 1.141994 1.215388 1.806969 A0A078J8I6 Chlorophyll a-b binding protein CP26 BnaC02g46810D 52 1277 0.618674 1.027023 1.591433 A0A078GY42 Photosystem I reaction center subunit VI-1 BnaC05g37250D 47.6 356 0.935938 1.026269 1.997100 A0A078GLT1 Chlorophyll a-b binding protein 1 BnaA09g26570D 67.4 1663 0.845850 0.967379 1.529286 A0A078I263 Chlorophyll a-b binding protein 1 BnaA07g07560D 67.4 1535 0.845850 0.967379 1.529286 A0A078F5S2 Cytochrome b-c1 complex subunit Rieske BnaC09g43660D 14.8 78 2.858618 3.551948 5.188301 Signal transduction A0A078H195 Ribosomal protein BnaA04g15900D 17.9 357 0.936630 0.301479 0.542141 A0A078G6 × 0 30 S ribosomal protein S3 BnaA01g34120D 58.6 272 0.413802 0.300090 0.465979 A0A078GH13 40 S ribosomal protein S3-2-like BnaC03g17580D 45.4 541 0.420976 0.633565 0.500272 A0A078G4M4 50 S ribosomal protein L9 BnaC01g24010D 42.3 345 0.363187 0.106646 0.505546 A0A078IQV6 Peptidylprolyl isomerase BnaA03g57740D 19 160 0.754682 0.878080 0.593926 A0A078CAM5 40 S ribosomal protein S5-1 BnaC03g73560D 29 259 0.811626 0.423112 0.523401 A0A078G7Z8 Peptidylprolyl isomerase BnaA02g09180D 38.5 583 0.428816 0.415404 0.613298 A0A078FTA7 Peptidyl-prolyl cis-trans isomerase NIMA-interacting 4 BnaA09g28980D 25.9 118 0.611649 0.672394 0.451239 A0A078G3Y5 30 S ribosomal protein S20 BnaA01g28980D 17.1 154 0.727015 0.289791 0.966337 D1L8R1 Ribosomal protein L20 rpl20 29.1 155 0.878813 0.385762 0.793634 A0A078GTV5 50 S ribosomal protein L22 BnaA06g19340D 28.8 343 0.958983 0.624092 0.973985 A0A078F9 × 4 50 S ribosomal protein L10 BnaC09g43570D 21.6 307 0.463351 0.612582 0.865896 A0A078FXI3 60 S ribosomal protein L7-3 BnaC04g03350D 31.8 250 0.651839 0.287923 0.693873 A0A078J2Z4 Aquaporin PIP2-1 BnaCnng31040D 11.5 143 0.705092 0.641418 0.804387 A0A078FGQ0 50 S ribosomal protein L15 BnaA06g33230D 39.5 679 0.591781 0.649133 0.957670 D1L8S1 Ribosomal protein S11 rps11 34.1 240 0.409063 0.615914 1.131517 A0A078F3D0 50 S ribosomal protein L17 BnaC06g15120D 20.6 92 0.276407 0.408465 1.137502 A0A078FJL5 50 S ribosomal protein L13 BnaC02g25080D 38.3 685 0.771884 0.539970 0.945665 A0A078JCZ3 30 S ribosomal protein S9 BnaAnng19390D 32.1 287 0.674137 0.438083 1.063720 A0A078F1F5 60 S ribosomal protein L13a-4 BnaA02g30400D 26.7 488 0.940910 0.542686 0.947710 A0A078GAJ5 GTP-binding protein SAR1A BnaA09g00560D 22.3 114 0.653454 0.716521 1.066103 A0A078GNF2 Peptidyl-prolyl cis-trans isomerase-like BnaC09g09060D 69 1005 0.630977 0.771292 0.958601 A0A078IHA7 40 S ribosomal protein S16-3-like BnaA05g33140D 52.1 138 0.751221 0.582845 0.814145 A0A078IMT1 40 S ribosomal protein S16-3 BnaA03g07060D 52.1 179 0.751221 0.582845 0.814145 A0A078IUM5 50 S ribosomal protein L1 BnaAnng12530D 40.4 740 0.856801 0.648034 1.004073 A0A078IT30 40 S ribosomal protein S7 BnaC01g41990D 41.9 638 0.853907 0.650349 1.402254 A0A078HCR8 60 S ribosomal protein L18a-2-like BnaC03g59540D 26.4 82 1.609555 0.843797 1.047634 A0A078GP33 Chaperone protein ClpB3 BnaC09g42450D 4.8 85 1.7074686 1.046612 0.655224 A0A078FY34 Co-chaperone protein p23 BnaC03g30910D 4.6 37 1.374372 1.500503 1.286792 A0A078FDD6 Peptidyl-prolyl cis-trans isomerase CYP28 BnaC08g08050D 18.6 115 1.183340 2.637557 1.474462 A0A078JIQ0 Peptidyl-prolyl cis-trans isomerase FKBP18 BnaCnng50370D 5.7 41 1.742753 1.594670 2.467164 A0A078HTZ3 Peptidylprolyl isomerase BnaA01g05720D 13.5 92 1.530424 1.612151 1.240177 A0A078DMP0 Peptidyl-prolyl cis-trans isomerase CYP18-3 BnaC03g60160D 54.7 545 1.412029 1.775994 0.604640 A0A078F7P2 60 S ribosomal protein L27 BnaC08g09980D 26.6 99 1.329520 0.871083 1.792157 A0A078J6H5 Peptidyl-prolyl cis-trans isomerase BnaA04g27460D 26 429 1.272562 1.207818 1.607132 A0A078HEE7 40 S ribosomal protein S8 BnaC09g37460D 38.4 882 1.158817 1.364160 1.613969 A0A078FWF3 40 S ribosomal protein S3a BnaC03g65890D 32.7 210 0.935013 1.209417 1.601761 A0A078GVL1 14-3-3-like protein GF14 nu BnaCnng05840D 23.4 103 1.457646 1.713257 2.099661 A0A078GJ98 Nucleoside diphosphate kinase III BnaA02g21890D 23.8 194 1.475067 1.916405 1.866466 A0A078GVF8 Peptidylprolyl isomerase BnaA06g14640D 6.5 83 2.027866 1.425783 1.857198 Antioxidant-related proteins A0A078HFK7 L-ascorbate peroxidase BnaAnng04450D 21.4 221 0.811401 0.240271 0.715595 A0A078H5C3 Superoxide dismutase BnaC03g16120D 7.7 79 0.575918 0.283087 0.481150 A0A078F5 × 4 Formate dehydrogenase BnaC09g42760D 30.5 212 2.212749 2.407629 1.158634 A0A078IIB3 Heat shock 70 kDa protein 9 BnaC03g61170D 19.4 519 1.546281 1.366098 0.797890 A0A078GSE1 2Fe-2 S ferredoxin-like BnaC05g44490D 7.6 43 0.935938 2.318608 1.754885 A0A078FU93 Glutaredoxin-C4 BnaC09g37340D 14.4 106 0.933258 1.579110 1.629717 A0A078HHH4 Glutaredoxin-C2 BnaC04g32420D 44.1 261 1.483304 1.613732 1.002576 A0A078IWR4 Peroxidase BnaAnng12900D 17.1 233 1.006332 0.651766 0.771208 A0A078H2Z1 Catalase-1 BnaC07g15270D 19.1 239 1.290740 1.639032 1.052930 Cell wall-related proteins A0A078GI07 Eukaryotic translation initiation factor 3 subunit F BnaC03g22380D 14.3 127 1.234423 1.811705 1.281683 A0A078F7G0 Endo-1,3; 1,4-beta-D-glucanase-like BnaC01g30540D 27.6 70 1.256936 1.513637 0.818176 A0A078GZR9 Glucan endo-1,3-beta-glucosidase BnaC04g24330D 28.8 266 0.998580 1.264229 1.730090 A0A078FEH1 Germin-like protein BnaA09g39580D 13.2 88 0.933341 1.519650 1.572200 A0A078I1B1 Glucan endo-1,3-beta-glucosidase 6 BnaC09g33610D 4.6 34 1.312819 1.629957 2.011610 A0A078BXJ1 Probable glucan endo-1,3-beta-glucosidase BG3 BnaCnng07500D 8.5 113 2.334582 2.821929 2.367895 A0A078JUQ1 Xyloglucan endotransglucosylase/hydrolase BnaCnng62600D 21 144 0.661825 0.496963 1.248429 A0A078GSK1 Xyloglucan endotransglucosylase/hydrolase protein 24-like BnaA01g06750D 9.6 54 1.121947 0.650191 1.083272 Herbicide tolerance and sulfur assimilation A0A078IXA9 Glutathione peroxidase 2 BnaCnng27540D 12.4 57 0.399320 0.980806 0.745672 A0A078IY55 Protein disulfide isomerase-like 1–3 BnaA09g55010D 2.1 53 0.645412 0.562957 1.105768 A0A078FY06 Thiocyanate methyltransferase 1 BnaC04g03180D 40.3 253 0.769093 0.843758 0.584605 A0A078H0T9 Cysteine synthase, chloroplastic/chromoplastic-like BnaA04g25390D 50.9 1629 0.936927 0.750959 0.626689 A0A078FXM1 Cysteine synthase, chloroplastic/chromoplastic BnaC04g03050D 51.3 1127 1.034496 0.616173 0.644198 A0A078GL08 Probable phospholipid hydroperoxide glutathione peroxidase 6 BnaA02g21680D 14.4 87 0.791784 1.669100 1.070403 A0A078JMZ9 Glutamine synthetase cytosolic isozyme 1–3 BnaCnng57900D 19.2 311 0.927470 1.618427 0.919078 A0A078FXL6 Cysteine proteinase RD21A BnaC06g00260D 12.7 107 1.347847 2.516433 1.463737 A0A078IFI4 Bifunctional D-cysteine desulfhydrase/1-aminocyclopropane-1-carboxylate deaminase BnaC06g01990D 11.4 142 1.267775 1.516280 0.571718 A0A078JHR9 Peptide methionine sulfoxide reductase A3 BnaC09g47890D 5.4 58 0.935938 2.309105 1.287020 A0A078GQ38 Peptide methionine sulfoxide reductase B9 BnaC03g64610D 12.5 53 0.659267 1.332218 1.342620 A0A078GC86 Peptide methionine sulfoxide reductase B1 BnaA06g00780D 4.9 38 0.657927 0.721426 0.904724 A0A078FC13 Cystine lyase CORI3 BnaC01g15060D 29 302 2.188200 3.346658 0.936847 Plant development-related proteins A0A078FG80 Early nodulin-like protein 1 BnaA03g51730D 13.5 72 0.655443 1.029282 1.237389 A0A078H4R1 Elongation factor G BnaC09g13110D 41.3 1648 0.625852 0.582129 0.965449 A0A078ITJ0 Eukaryotic translation initiation factor 3 subunit G BnaCnng24840D 14.3 99 1.620657 0.959656 1.024812 A0A078HEL5 Elongation factor Ts, mitochondrial BnaA01g07830D 44.7 1786 0.499439 0.499206 0.742859 A0A078HFL8 Nodulin-related protein 1 BnaC02g35030D 22.1 95 0.473006 1.215405 1.256836 A0A078G1A8 Early nodulin-like protein 2 BnaC01g20120D 15.1 71 2.193042 1.836736 1.521730 A0A078HAL9 Early nodulin-like protein 1 BnaA09g41080D 11.2 37 0.974623 0.643809 1.882587 Unknown A0A078GYM2 Uncharacterized protein At5g39570-like BnaC04g31650D 18.2 275 1.364852 1.500183 1.270977 A0A078FG18 Uncharacterized BNAC06G13920D BnaC06g13920D 29.1 91 0.681077 0.412087 0.807609 A0A078HEC4 Uncharacterized LOC106361260 BnaA08g04600D 9.6 70 0.653270 0.716320 1.279594 A0A078FEM7 Uncharacterized LOC106429057 BnaC03g70960D 11.2 74 0.858384 0.185963 0.538548 A0A078GY92 Uncharacterized BNAA03G49580D BnaA03g49580D 9.7 115 0.596141 1.232989 0.597545 A0A078J322 Uncharacterized LOC106433592 BnaC05g49260D 13.8 369 0.221306 0.206383 0.541906 A0A078HEZ5 Uncharacterized LOC106452857 BnaA05g29710D 24.7 271 0.615216 0.525478 0.437132 [137]Open in a new tab Fig. 10. [138]Fig. 10 [139]Open in a new tab Protein interactome analysis of differentially abundant proteins (A) energy and metabolism, (B) photosynthesis, (C) signal transduction and (D) antioxidant, sulfur assimilation and herbicide tolerance related proteins identified in leaves of Brassica napus seedlings exposed to Si-mediated Gly stress. Fig. 11. [140]Fig. 11 [141]Open in a new tab Protein-protein interaction of candidate proteins involving antioxidant, sulfur assimilation and herbicide tolerance processes in Brassica napus. (A) L-ascorbate peroxidase (A0A078HFK7, BnaAnng04450D), (B) Superoxide dismutase (A0A078H5C3, BnaC03g16120D), (C) glutaredoxin-C2 (A0A078HHH4, BnaC04g32420D), (D) peroxidase (A0A078IWR4, BnaAnng12900D), (E) glutathione peroxidase 2 (A0A078IXA9, BnaCnng27540D) and (F) peptide methionine sulfoxide reductase A3 (A0A078JHR9, BnaC09g47890D). Discussion The study offers proteome insights into the mechanisms underlying Si-mediated protection against Gly toxicity in B. napus. We observed Gly-induced toxicity leads to the generation of excess ROS consequently increasing the oxidative stress, and negatively affecting the morphological and physiological characteristics of the B. napus seedlings. However, addition of Si restored the oxidative stress. In our study, Si restored the pigments of photosynthesis as well as increased GST activity. A relationship exists between the pigments of light-harvest and efficiency of photosynthesis, which in turn enhances growth and development in B. napus^[142]32. Therefore, Si is crucial in restoring the pigments of photosynthesis in B. napus under Gly-toxicity. Additionally, the minimization of Gly-induced oxidative stress indicators (O[2]^•−, H[2]O[2]) in response to Si supplementation indicates that Si actively reduces oxidative stress in plants under Gly stress. This reduction in oxidative stress is achieved through the ability of Si to enhance antioxidant activity, thereby improving plant tolerance to abiotic stress^[143]33. GO and KEGG analysis are vital for proteomic studies as they provide comprehensive insights into the functional roles and pathways associated with identified proteins. The analysis of functional categories for 130 DAPs suggests their involvement in diverse biological processes, including energy and metabolism, photosynthesis, signal transduction, antioxidant, cell wall functions, herbicide tolerance and sulfur assimilation, and plant development. In the subsequent categories, we explored all mechanisms and interpretations, highlighting results that either align or differ from those observed in other plant species when compared to B. napus. Energy and metabolism-related proteins Plants produce carbohydrates through photosynthetic CO[2] fixation, which serve as substrates for various functions, including energy metabolism, secondary metabolism, growth, development, and stress responses. Proper regulation of photosynthesis and carbohydrate metabolism is crucial for plant growth, development, and stress adaptation, especially in a changing environment^[144]34. Energy production from carbohydrates is vital for supporting metabolic processes and the growth of plants. Studies have demonstrated a connection between elevated glucose storage and improved resilience to metal stress in several plant species^[145]35. In this research, we identified 35 DAPs engaged in citric acid cycle and the metabolism of carbohydrate. Plants have developed intricate regulatory mechanisms to regulate glycolysis pathways and the TCA cycle, ensuring efficient energy production and metabolic adaptation during environmental stress. These pathways are fine-tuned to optimize resource utilization and maintain cellular homeostasis under abiotic stresses^[146]36. The increase in proteins associated with glycolysis suggests the B. napus seedlings can maintain critical respiration processes and produce more ATP through enhanced glycolytic activity under Gly stress. Si application enhances the ability of plants to mitigate toxic effects on cellular components through cellular homeostasis. Proteins such as NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 12, NAD(P)H-quinone oxidoreductase subunit U, and pyruvate dehydrogenase E1 component subunit, which are engaged in the citric acid cycle, help maintain cellular energy production and metabolic balance under Gly stress. These results align with findings from a proteomic study on the roots of Oenothera glazioviana under the stress of Cu^[147]37. Collectively, these proteins engaged in the citric acid cycle, along with the beneficial effects of Si supplementation on antioxidant activity, metabolic pathways, and plant physiology, contribute to Gly stress tolerance in B. napus. Photosynthesis-related proteins Plants regulate their photosynthetic capacity in response to environmental conditions, optimizing yield and overall growth and development^[148]34. Gly-toxicity markedly inhibits photosynthesis and plant growth by immobilizing essential micronutrients required for chlorophyll formation and photosynthesis and disrupting physiological processes and cell metabolism^[149]38,[150]39. In our study, we observed unique response patterns of differentially abundant proteins (DAPs) associated with photosynthesis, particularly those involved in the Calvin cycle and the electron transport chain, under Gly stress. The detrimental effects of Gly on photosynthesis have also been documented in willow plants^[151]38. The reduced abundance of leaf proteins, such as ribulose bisphosphate, indicates that energy metabolism and carbon fixation processes are significantly impaired in B. napus Gly toxicity, likely due to diminished gas exchange capacity^[152]40. These findings indicate that Gly toxicity impairs photosynthetic machinery. Additionally, our study suggests that Gly or Gly + Si induced proteomic regulations did not show similar abundance patterns. However, physiological analysis confirmed that Si restored the content of photosynthetic pigments. Thus, the proteomic alterations induced by Gly + Si suggest that Si actively responds even under Gly stress. The findings suggest that increased energy generation is necessary for B. napus under Gly stress in order to activate carbon fixation. The higher abundance of these potential proteins under Gly stress indicates that they may have a role in supporting B. napus plants by encouraging better growth and development. Signal transduction Signaling pathway is crucial for mobilizing defense mechanisms against toxic substances in the plants^[153]41. This proteomic study examines Gly-associated signal alterations and the metabolism of differentially abundant proteins. We discovered that the peptidyl-prolyl cis-trans isomerase CYP28 is upregulated, while CYP18-3 is downregulated. Both of these enzymes play a crucial role in speeding up the cis-trans isomerization of proline imidic peptide bonds in oligopeptides, aiding in protein folding. Stress signals triggered by protein kinases lead to changes in gene expression, resulting in the upregulation of CYP28 and downregulation of CYP18-3, contributing to Gly stress tolerance in B. napus. Additionally, we identified an upregulated GTP-binding protein SAR1A. The upregulation of SAR1A by Gly treatment suggests it functions as a molecular switch in signal transduction cascades, contributing to Si-mediated Gly stress tolerance in B. napus. Comparable results were found in a proteomic study of glyphosate-induced oxidative stress in rice leaves^[154]42. Antioxidant-related proteins Several stress-related and defensive proteins, along with vital antioxidant enzymes, play crucial roles in defending plant mechanisms, and enhancing stress tolerance^[155]43. In this current study, nine DAPs were identified under the stress of Gly. Among these, one SOD, one CAT, and one APX showed notable upregulation in response to Gly and Si exposure. SOD and APX are key players in ROS detoxification in plant cells. SOD, the first enzyme in the detoxification process, converts superoxide anion (O[2]^•−) to H[2]O[2], while APX reduces H[2]O[2] to water using ascorbic acid as an electron donor^[156]44. Comparable results were found in a proteomic study of glyphosate-induced oxidative stress in rice leaves^[157]42. Two possible ways that Si reduces abiotic stress are by controlling ROS levels and enhancing antioxidant metabolism^[158]45. Our results revealed that Gly induced ROS were successfully regulated by enhanced activities of DAPs and key antioxidants (SOD, APX, CAT). This indicates that the antioxidant defense system was completely operational under Gly stress, further enhancing Gly tolerance in B. napus through exogenous Si supplementation. Cell wall-related proteins Cell wall and cytoskeleton related proteins cause rapid changes due to Gly exposure. The cell wall acts as the primary mechanism against abiotic stressors such as Gly toxicity, acting as a barrier and undergoing modifications when under stress. We identified eight differentially abundant proteins (DAPs) under Gly stress. Among these proteins, the xyloglucan endotransglucosylase/hydrolase protein family, which cleaves and reconnects xyloglucan molecules, plays a crucial role in cell wall synthesis, reconstruction, and stress resistance. This supports findings in poplar plants that show tolerance to abiotic stress, such as salt stress^[159]46. Our results indicate that Si-mediated tolerance to Gly stress involves the processing of proteins associated with the cell wall. Herbicide tolerance and sulfur assimilation Sulfur (S) is crucial for regulating plant tolerance to glyphosate^[160]47. In our B. napus proteome research, we identified thirteen key proteins involved in herbicide tolerance and sulfur assimilation processes, which enhance development and growth of B. napus under Gly toxicity. We noted increased levels of proteins associated with sulfur assimilation, which aid in incorporating sulfur into compounds such as methionine and GSH, thereby enhancing Gly tolerance in B. napus. The role of Si in mitigating Gly toxicity has also been observed in tomato plants, highlighting its protective effects against Gly-induced stress^[161]5. Among these proteins, three peptide methionine sulfoxide reductase proteins, which catalyze the reduction of methionine sulfoxide to methionine, play a protective role against oxidative stress^[162]48. In this current study, the minimization of H[2]O[2] and O[2]^•− in response to Si supplementation suggests that involvement of Si in Gly tolerance is linked to its availability in B. napus. Additionally, the significant upregulation of these three DAPs indicate the role of Si in facilitating sulfur-mediated Gly tolerance in B. napus. Plant development-related proteins We identified seven DAPs associated with plant growth and development. Notably, early nodulin-like protein 1 was significantly upregulated, which plays a critical role in regulating translation processes within plants. This protein plays the crucial role under stress responses, as validated by a combined transcriptome and proteome approach in pigeon pea^[163]49. In our investigation, this heightened synthesis of protein, activated by silicon, enhances the cellular defensing ability against Gly toxicity and promotes overall growth of the plants. Unknown proteins Several unknown proteins, such as uncharacterized protein At5g39570-like, uncharacterized BNAA03G49580D, and uncharacterized LOC106361260, showed increased responses, while uncharacterized LOC106429057, uncharacterized BNAC06G13920D, uncharacterized LOC106452857, and uncharacterized LOC106433592 exhibited decreased responses under Gly stress. The precise biological functions of these proteins are currently unknown. However, our research observed their responses to Gly and/or Si supplementation. Further investigation is necessary to uncover their specific biological functions related to Gly-stress tolerance. Protein interactome analysis The activity of a protein is often significantly influenced by its interactions with other proteins and regulatory modifications^[164]50. Protein-protein interactions are crucial for various biological processes, such as cell-to-cell communication and the regulation of metabolic processes^[165]51. The functions of the target protein can be predicted by examining its co-expression patterns and interactome analysis. Typically, the desired phenotypic traits are often produced by a series of molecular alterations caused by the interaction of genes and proteins^[166]52. Gaining insight into the protein interactome helps to understand the biochemical interactions, cellular signaling and signal transduction among B. napus leave’s diverse protein composition. Within the energy and metabolism category, some proteins, including pyruvate dehydrogenase E1 component subunit, acetyl-CoA carboxytransferase, NAD(P)H-quinone oxidoreductase subunit U, and NAD(P)H-quinone oxidoreductase subunit M are interconnected, contributing to the overall energy balance and metabolic activities within plant cells during the stress conditions. This method highlights their important contribution to plant’s metabolic processes and energy^[167]53. The proteins related to photosynthesis, such as chlorophyll a-b binding protein, chlorophyll a-b binding protein 1, chlorophyll a-b binding protein CP26, photosystem I reaction center subunit II and subunit VI-1, photosystem II stability/assembly factor HCF136, and RuBisCo small subunit, are directly related with photosynthesis process and CO[2] assimilation through the mutual interactions of that proteins. Some proteins such as 60 S ribosomal protein L7-3, L13a-4, L18a-2-like, and 40 S ribosomal protein S3-2-like, S5-1, S16-3-like, and S7 are engaged with the process of metabolism and signal transduction. Additionally, the interactome analysis of antioxidant, sulfur assimilation, and herbicide tolerance proteins, counting L-ascorbate peroxidase, GPX 2, superoxide dismutase, and phospholipid hydroperoxide GPX 6, facilitated functional protein interactions associated with stress defense, translation, and sulfur assimilation processes in Brassica juncea^[168]54. Determining how interrelated protein networks react to Gly toxicity reveals their possible functions and connections in plants facing Gly stress. This investigation reveals shared networks among candidate proteins involved in mitigating Gly stress in B. napus. The widespread use of herbicides causes oxidative stress in plants despite their weed control benefits. However, they also have negative side effects on main crops. Interactome analysis of key antioxidant defense and herbicide (Gly) tolerance proteins in B. napus showed that L-ascorbate peroxidase and superoxide dismutase interact with proteins involved in ascorbate and Si metabolism, enhancing the plant’s antioxidant capacity and mitigating Gly-induced oxidative stress. These enzymes play a crucial role in scavenging ROS^[169]43. Peroxidase degrades H[2]O[2] to alleviate oxidative stress, while GPX utilizes peroxidase as electron acceptors to reduce oxidative damage^[170]55. Glutaredoxins are oxidoreductases with electrostatic properties relevant for protein-protein interactions required for oxidoreductase activity^[171]56. These enzymes catalyze oxidation-reduction reactions by facilitating electron transfer between donor and acceptor molecules, participating in metabolic processes such as cellular respiration, photosynthesis, and detoxification. GRX plays a critical role in maintaining thiol-redox homeostasis and mediating redox signal transduction. Disruptions in the Grx system have been linked to the development and progression of various oxidative stress-related diseases, highlighting its importance in cellular redox balance and signaling pathways^[172]57. Peptide methionine sulfoxide reductase interacts with proteins that protect against oxidative stress by inactivating methionine oxidation^[173]48. In this current study, we found that these proteins are essential for reducing oxidative stress caused by Gly and improving Gly tolerance in B. napus by exogenous addition of Si. Conclusion The research impact explores the proteomic insights of Si-mediated Gly-toxicity mitigation in B. napus. This study further highlights the urgent need for environmentally sustainable strategies to address Gly toxicity. In this study, the Si supplementation as a potential method to mitigate Gly toxicity in B. napus leaves provided promising results, revealing substantial alterations in protein expression profiles. Particularly the identification of key target proteins connected to antioxidant defense, herbicide tolerance and sulfur assimilation processes through interactome analyses. These findings enhance our understanding of the molecular mechanisms underlying plant responses to Gly stress and offer valuable insights into tolerance pathways. Collectively, these results lay the groundwork for further in-depth field studies to elucidate the molecular basis of Gly stress responses and explore the potential of Si in mitigating Gly toxicity in B. napus. Statistical analyses Statistical analysis used a two-sided t-test, with FDR (false discovery rate) correction for multiple comparisons, conducted in Perseus statistical software with default settings. Data were normalized by linear regression and transferred to Excel for detailed analysis. Peptides matching common impurities were filtered out, and at least three biological replicates were used for relative quantification and protein identification. Electronic supplementary material Below is the link to the electronic supplementary material. [174]Supplementary Material 1^ (33.1KB, xlsx) [175]Supplementary information^ (20.6KB, docx) [176]Supplementary Material 1^ (48.5KB, xlsx) [177]Supplementary Material 1^ (242.7KB, xlsx) [178]Supplementary information^ (33.6KB, docx) [179]Supplementary information^ (17.3KB, docx) Acknowledgements