Systematic qualitative proteome-wide analysis of lysine malonylation profiling in 
Protein modification plays an essential role in biological organisms. It changes protein composition and structure through methylation, glycosylation, hydroxylation, glyoxylation, etc. (Lin and Caroll ) to regulate corresponding biosynthetic processes. So far, more than 450 kinds of protein post-translational modifications (PTMs) have been found (Zhou et al. ). Unlike animals and bacteria, the protein PTM process in plants is more focused on resisting external invasion or adapting to environmental changes (Taguchi et al. ). Malonylation is active in flavonoid and isoflavone biosynthesis, and there are clear traces of malonylation in soybeans (Ahmad et al. , ), corn (Xu et al. ), rice (Mujahid et al. ) and tobacco (Manjasetty et al. ). If some small molecules are to undergo enzymatic acylation reaction, they need some external assistance, that is, high-energy acyl donors (Yu et al. ), such as acetyl coenzyme A thioester and 1-O-acyl glucoside. Moreover, 30-45% of malonylation reactions occur in chloroplasts (Berghold et al. ; Xu et al. ) for plant photosynthesis. Lysine malonylation is a reversible reaction, adding malonyl to lysine residues (Figure S1). It was found earlier in microorganisms and mammals, such as Toxoplasma gondii , Escherichia coli (Nie et al. ), and humans (Nahomi et al. ), and its evolution is conserved. Malonylation can affect many biochemical processes, including various cell functions and disease processes. Existing data show that proteins modified by malonylation are enriched in the energy metabolism and fatty acid synthesis pathways (Qian et al. ; Zhang et al. ), in cells with damaged mitochondrial function, and the process of fatty acid oxidation (Wang et al. ), which shows that malonylation is related to energy metabolism. Only a few studies studying malonylation in plants have been conducted, although studies have shown that lysine malonylation can play a role in the biological metabolism process under drought stress(Wang et al. ). However, there are no relevant reports on the important medicinal plant P. grandiflorus . The research literature in plants suggests that malonylation is also closely related to energy metabolism, similar to microorganisms and mammals. Although malonylation can affect various biochemical processes, due to the dynamic characteristics and low abundance of malonylation (Chen et al. ; Liu et al. ), malonylation sites on proteins in plants cannot be analyzed thoroughly. The matching cell annotation, that is, the recognition of modification sites, is the most crucial step in clarifying the relevant mechanism (Wang et al. ), which limits the functional study of malonylation. Although malonylation site prediction tools, such as Long Short-Term Memory (LSTM) (Al-Barakati et al. ), Malonylation Prediction (Mal-Prec) (Liu et al. ) and LSTM-based Ensemble Malonylation Predictor (LEMP) (Chen et al. ) have been developed by scientists in recent years, conventional mass-based proteomic approaches are a more reliable method for malonylation site identification. In addition to malonylation, there is another lysine modification (Nahomi et al. ). Malonylation and succinylation have similar modification structures (Taherzadeh et al. ), therefore, malonylation may be reversible, dynamic, conservative, and able to influence the physiology and pathology of animals, photosynthesis and tricarboxylic acid cycle (TCA cycle) in plants, cell cycle and growth in the process of life such as succinylation (Dong et al. ; Sreedhar et al. ; Wang et al. ). Malonylation and succinylation are short-chain acylation modifications and can change the charge state of amino acids (Colak et al. ). This acidic modification differs from widely studied modifications such as acetylation (Colak et al. ; Qian et al. ). P. grandiflorus is the only plant in the genus Platycodon in the family Campanulaceae. Nowadays, the main production areas of P. grandiflorus are located in Shandong, Anhui, and Inner Mongolia in China, and the seed resources are relatively rich (WANG Zhi-fen et al. ). So far, more than 100 types of secondary metabolites have been isolated from P. grandiflorus , including triterpenoids, saponins, flavonoids, polysaccharides, etc. (Jia et al. ), and more than 70 kinds of major active ingredients have been identified (Huang et al. ), among which triterpenoid saponins are the effective compounds, including platycodin D, platycodin A, platycodonic acid, etc. (Su et al. ). These organics are used as the chemical basis for the clinical treatment of cancer (Deng et al. ), bronchitis (Deng et al. ), and other diseases. In addition, P. grandiflorus can also be a material for gardening and food (Jia et al. ). Therefore, its potential economic value is very high. Nevertheless, the study of its metabolic pathway and protein modification is still limited. Nevertheless, there is no study analyzing lysine malonylation modifications in P. grandiflorus . Those achievements will likely serve as the foundation of follow-up research and accelerate the development of potential malonylation applications in plant physiology and biology. In this research study, we aim to identify the role of lysine malonylation modifications in environmental stress responses and explore potential methods for promoting the generation of secondary metabolites in P. grandiflorus .   Plant materials The plant materials used in this study are the whole P. grandiflorus plant, which come from Hefei, Anhui in China grwogin on loess soil type. It was collected in autumn when the plant was blooming. Before detection, sample of P. grandiflorus , include root, stem and leaves, must be washed with distilled water and alcohol and stored in liquid nitrogen. In addition, these plants are the same as the materials described by Su et al. (Su et al. , ). Protein extraction Proteins were extracted according to the procedures in our previous study (Palomba et al. ; Shi et al. ) by minor modifications. Three replicates of the appropriate samples amount (2.4 g) (-80℃) were ground into powder using a mortar and pestle precooled with liquid nitrogen. Each sample group were subjected to ultrasonicate after adding buffer [10 mM DL-Dithiothreitol (DTT), 1% protease inhibiter cocktail, 3 µM Trichostatin A (TSA), 50 mM Nicotinamide (NAM)] which was four times the sample volume. The same volume of Tris-saturated phenol was added before centrifugation (4℃, 10 min, 5500 g). Supernatants were precipitated and pellets were washed with ammonium acetate/methanol, and protein was quantified using BCA protein assay kit (Beyotime) after re-dissolving it in 8 M urea. Western blot analysis Extracted proteins (10 µg) from P. grandiflorus were separated using a 15.0% SDS-PAGE gel and then electro-transferred to a polyvinylidene fluoride (PVDF) membrane (Millipore) for Western blot analysis. Malonylated proteins were tested using the primary anti-malonyllysine antibody (PTM-902, Lot: 23056103M119, PTM Biolabs, Hangzhou, China) at a 1: 2000 (v/v) dilution. The secondary antibody goat anti-mouse IgG [Thermo, Pierce, (H + L), Peroxidase Conjugated, 31430] was diluted at a 1: 10,000 (v/v) dilution. Protein trypsin digestion Every equal-volume sample was enzymatically broken by trypsin (Promega), and their volume was adjusted to be equal using a lysis solution. They were precipitated after adding TCA (20%) to the sample and mixing (4℃, 2 h). The pellet was washed with precooked acetone and left air dried. The dried pellet was dissolved with 200 mM TEAB (defined the composition) and mixed using an ultrasonic, then hydrolyzed by trypsin (protease/protein: 1/50). DTT was added to a final concentration of 2 mM (30 min) and 11mM IAA (15 min). Modification enrichment The supernatant, attained when putting the peptide in immunoprecipitation (IP) buffer (100 mM NaCl, 1 mM EDTA, 50 mM Tris-HCl, 0.5% NP-40, pH 8.0) was moved into malonyl resin (Article Number: PTM-904). It was incubated on a rotary shaker overnight (4℃) and with IP buffer (4 times), deionized water (2 times), and 0.1% TFA (3 times). Then, it was freeze dried. After desalting according to instructions included with C18 ZipTips, it was dried again. Finally, it was sent for LC-MS/MS analysis. LC-MS/MS analysis The tryptic peptides were dissolved in solvent A (0.1% formic acid, 2% acetonitrile/in water) and loaded directly onto a home made reversed-phase analytical column (25 cm length, 75/100 µm i.d.). Peptides were separated using a gradient from 6 to 24% solvent B (0.1% formic acid in acetonitrile) over 70 min, 24–35% in 14 min, and climbing to 80% in 3 min, then holding at 80% for the last 3 min, all at a constant flow rate of 450 nL/min on a nanoElute UHPLC system (Bruker Daltonics). The peptides were subjected to a capillary source followed by timsTOF Pro (Bruker Daltonics) mass spectrometry. The electrospray voltage applied was 1.60 kV. Precursors and fragments were analyzed at the TOF detector, with a MS/MS scan range from 100 to 1700 m/z. The timsTOF Pro was operated in parallel accumulation serial fragmentation (PASEF) mode. Precursors with charge states 0–5 were selected for fragmentation, and 10 PASEF-MS/MS scans were acquired per cycle. The dynamic exclusion was set to 30s. Data analyzes showed that most of the first-order mass error in the spectra were under 4ppm, entirely base on the precision standard of Orbitrap MS. Consequently, the subsequent qualitative and quantitative analyses were not influenced by quality error. In addition, since the score of the matching peptide in the spectrogram (representing the reliability of peptide identification) is negatively correlated with the quality deviation distribution, the higher the score, the smaller the quality deviation. Database search We used Maxquant (v1.6.15.0) (Palomba et al. ) to retrieve the original data file and searched tandem mass spectrometry data according to the P. grandiflorus protein database, which was uploaded by authors. This database comprises reverse bait and contamination databases, which could eliminate the influence of contaminated proteins. The enzyme digestion mode was set to Trypsin/P. The number of missing bits was set to four; the minimum peptide length was set to seven amino acid residues; the maximum number of modified peptides was set to five; the mass error tolerance for primary parent ions in the first and main searches were set to 20 ppm and 20 ppm, respectively, and the mass error tolerance for secondary fragment ions was set to 20 ppm. Cysteine alkylation Carbamidomethyl was set as a fixed modification, and the variable modifications were methionine oxidation, protein N-terminal acetylation, and lysine malonylation. False discovery rate (FDR) for protein identification was set to 1%. Protein functional enrichment and protein annotation method The protein annotation and functional enrichment were analyzed using a comprehensive approach, for example, gene ontology (GO), protein domain, KEGG pathway, COG/KOG functional classification and subcellular localization. GO analysis is a bioinformatics analysis method that can combine every kind of information on genes and gene products together (Sun et al. ). It integrates information based on the eggnog database to provide statistical information. It includes cell components, molecular functions and biological processes. It can produce information on genes and proteins, classify them based on the analysis content, and function as a database for the information that the authors attained. Protein domain is a structural element with molecular functions so that it can function independently and is conserved on the order of the protein. We prepared an annotation of protein domains found based on the Pfam database and PfamScan. KEGG can integrate known protein interaction network information, such as pathways and related complexes, genes and gene products, biological complexes, and related reactions. The annotated contents in this study are protein pathways, such as metabolism, genetic information processing, cellular processes, and environmental information processing. The highest score in the blast comparison of modified proteins was selected to annotate the results. In addition, we also used the KOG database to construct a phylogenetic tree and annotated the functions of homologous gene clusters. Moreover, because the proteins in eukaryotic tissue cells can be localized to various elements in cells, Wolf Psort software can be used to annotate the submitted proteins for subcellular localization. Protein interaction network analysis After comparing the identified protein sequence or modified protein database number with the STRING protein interaction network database, we attained the protein interaction relationship according to the confidence score > 0.7 (high confidence) and used the R package “network D3” tool to display it visually.   The plant materials used in this study are the whole P. grandiflorus plant, which come from Hefei, Anhui in China grwogin on loess soil type. It was collected in autumn when the plant was blooming. Before detection, sample of P. grandiflorus , include root, stem and leaves, must be washed with distilled water and alcohol and stored in liquid nitrogen. In addition, these plants are the same as the materials described by Su et al. (Su et al. , ).   Proteins were extracted according to the procedures in our previous study (Palomba et al. ; Shi et al. ) by minor modifications. Three replicates of the appropriate samples amount (2.4 g) (-80℃) were ground into powder using a mortar and pestle precooled with liquid nitrogen. Each sample group were subjected to ultrasonicate after adding buffer [10 mM DL-Dithiothreitol (DTT), 1% protease inhibiter cocktail, 3 µM Trichostatin A (TSA), 50 mM Nicotinamide (NAM)] which was four times the sample volume. The same volume of Tris-saturated phenol was added before centrifugation (4℃, 10 min, 5500 g). Supernatants were precipitated and pellets were washed with ammonium acetate/methanol, and protein was quantified using BCA protein assay kit (Beyotime) after re-dissolving it in 8 M urea.   Extracted proteins (10 µg) from P. grandiflorus were separated using a 15.0% SDS-PAGE gel and then electro-transferred to a polyvinylidene fluoride (PVDF) membrane (Millipore) for Western blot analysis. Malonylated proteins were tested using the primary anti-malonyllysine antibody (PTM-902, Lot: 23056103M119, PTM Biolabs, Hangzhou, China) at a 1: 2000 (v/v) dilution. The secondary antibody goat anti-mouse IgG [Thermo, Pierce, (H + L), Peroxidase Conjugated, 31430] was diluted at a 1: 10,000 (v/v) dilution.   Every equal-volume sample was enzymatically broken by trypsin (Promega), and their volume was adjusted to be equal using a lysis solution. They were precipitated after adding TCA (20%) to the sample and mixing (4℃, 2 h). The pellet was washed with precooked acetone and left air dried. The dried pellet was dissolved with 200 mM TEAB (defined the composition) and mixed using an ultrasonic, then hydrolyzed by trypsin (protease/protein: 1/50). DTT was added to a final concentration of 2 mM (30 min) and 11mM IAA (15 min).   The supernatant, attained when putting the peptide in immunoprecipitation (IP) buffer (100 mM NaCl, 1 mM EDTA, 50 mM Tris-HCl, 0.5% NP-40, pH 8.0) was moved into malonyl resin (Article Number: PTM-904). It was incubated on a rotary shaker overnight (4℃) and with IP buffer (4 times), deionized water (2 times), and 0.1% TFA (3 times). Then, it was freeze dried. After desalting according to instructions included with C18 ZipTips, it was dried again. Finally, it was sent for LC-MS/MS analysis.   The tryptic peptides were dissolved in solvent A (0.1% formic acid, 2% acetonitrile/in water) and loaded directly onto a home made reversed-phase analytical column (25 cm length, 75/100 µm i.d.). Peptides were separated using a gradient from 6 to 24% solvent B (0.1% formic acid in acetonitrile) over 70 min, 24–35% in 14 min, and climbing to 80% in 3 min, then holding at 80% for the last 3 min, all at a constant flow rate of 450 nL/min on a nanoElute UHPLC system (Bruker Daltonics). The peptides were subjected to a capillary source followed by timsTOF Pro (Bruker Daltonics) mass spectrometry. The electrospray voltage applied was 1.60 kV. Precursors and fragments were analyzed at the TOF detector, with a MS/MS scan range from 100 to 1700 m/z. The timsTOF Pro was operated in parallel accumulation serial fragmentation (PASEF) mode. Precursors with charge states 0–5 were selected for fragmentation, and 10 PASEF-MS/MS scans were acquired per cycle. The dynamic exclusion was set to 30s. Data analyzes showed that most of the first-order mass error in the spectra were under 4ppm, entirely base on the precision standard of Orbitrap MS. Consequently, the subsequent qualitative and quantitative analyses were not influenced by quality error. In addition, since the score of the matching peptide in the spectrogram (representing the reliability of peptide identification) is negatively correlated with the quality deviation distribution, the higher the score, the smaller the quality deviation.   We used Maxquant (v1.6.15.0) (Palomba et al. ) to retrieve the original data file and searched tandem mass spectrometry data according to the P. grandiflorus protein database, which was uploaded by authors. This database comprises reverse bait and contamination databases, which could eliminate the influence of contaminated proteins. The enzyme digestion mode was set to Trypsin/P. The number of missing bits was set to four; the minimum peptide length was set to seven amino acid residues; the maximum number of modified peptides was set to five; the mass error tolerance for primary parent ions in the first and main searches were set to 20 ppm and 20 ppm, respectively, and the mass error tolerance for secondary fragment ions was set to 20 ppm. Cysteine alkylation Carbamidomethyl was set as a fixed modification, and the variable modifications were methionine oxidation, protein N-terminal acetylation, and lysine malonylation. False discovery rate (FDR) for protein identification was set to 1%.   The protein annotation and functional enrichment were analyzed using a comprehensive approach, for example, gene ontology (GO), protein domain, KEGG pathway, COG/KOG functional classification and subcellular localization. GO analysis is a bioinformatics analysis method that can combine every kind of information on genes and gene products together (Sun et al. ). It integrates information based on the eggnog database to provide statistical information. It includes cell components, molecular functions and biological processes. It can produce information on genes and proteins, classify them based on the analysis content, and function as a database for the information that the authors attained. Protein domain is a structural element with molecular functions so that it can function independently and is conserved on the order of the protein. We prepared an annotation of protein domains found based on the Pfam database and PfamScan. KEGG can integrate known protein interaction network information, such as pathways and related complexes, genes and gene products, biological complexes, and related reactions. The annotated contents in this study are protein pathways, such as metabolism, genetic information processing, cellular processes, and environmental information processing. The highest score in the blast comparison of modified proteins was selected to annotate the results. In addition, we also used the KOG database to construct a phylogenetic tree and annotated the functions of homologous gene clusters. Moreover, because the proteins in eukaryotic tissue cells can be localized to various elements in cells, Wolf Psort software can be used to annotate the submitted proteins for subcellular localization.   After comparing the identified protein sequence or modified protein database number with the STRING protein interaction network database, we attained the protein interaction relationship according to the confidence score > 0.7 (high confidence) and used the R package “network D3” tool to display it visually.   Identification of lysine malonylation-modified proteins in P. Grandiflorus In order to ensure that these protein modification data used meet standards, proteome scale analysis was carried out on these existing data (Fig. ). The existence of lysine malonylation in P. grandiflorus was confirmed using a Western blot with an antimalonyl lysine antibody (Fig. A). The overall quality error is less than 5 ppm (Fig. B), which indicates that these MS data used in this study are reliable. Moreover, most peptide segments were only modified once (Fig. C). After checking the distribution of all peptides, it was found that most of these peptides were in the 7–20 amino acids ranges (Fig. D), which aligned with the general law based on enzymatic hydrolysis and mass spectrometry fragmentation, indicating that the length distribution of peptides identified by this mass spectrometer met the quality control requirements. Through statistics, 1755 lysine malonylation modification sites in 888 proteins were identified in this study (Supplementary Table S1). A representative MS/MS diagram is available in Fig. E. Although lysine malonylation modifications have been reported in some other plant species (Nahomi et al. ; Nie et al. ), similar to pathogens (Shi et al. ), there is no relevant record in P. grandiflorus . These results are the first report of lysine malonylation in P. grandiflorus . Functional annotation and subcellular localization of lysine malonylation modified proteins in P. Grandiflorus In order to further understand the functional role of lysine malonylation modification in P. grandiflorus , the identified modified proteins were classified based on the GO annotation according to biological process, cellular components, and molecular function (Supplementary Table S2). From the Fig. A, the proteins related to cellular processes (24%), metabolic processes (20%), and stimulation reactions (17%) have been modified by malonylation. It was consistent with the observation made in recent years that lysine malonylation modification affects biological and metabolic processes (Liu et al. ). Data on cell composition (Fig. A) show that Most of the modified proteins were located within the cell., and only a few are located in protein-containing complexes (11%). Based on the molecular function analysis, it is evident that malonylation modification is closely related to the activities of catalysis (45%) and binding (37%) (Fig. A), which are similar to results obtained in wheat (Liu et al. ). The above data show that malonylation modification can affect various biological metabolic processes in P. grandiflorus , and play an indispensable role in plant life activities. After further subcellular localization (Fig. B, Supplementary Table S2) of the modification sites, it was found that most of the modification sites existed in chloroplasts (38%) and cytoplasm (34%), but there are few in mitochondria (6%). This includes proteases such as phosphoribulokinase (PRK), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and aconite hydratase (Supplementary Table S1), which may suggest that the metabolic processes of photosynthesis and ATP conversion are influenced by malonylation modifications. In addition, these modification sites also exist in the nucleus (11%) and extracellularly (3%). The above results may provide some reference for the study of malonylation modification of P. grandiflorus . Then, the functional classification of these modified proteins is performed (Fig. C, Supplementary Table S2). Based on the analysis of homologous clusters (COGs) in the COG database, it was found that the number of modified proteins related to PTMs, protein turnover, and chaperones ranks first at 132 each, followed by translation, ribosomal structure, and biogenesis (92). This may imply that malonylation modification will affect the gene expression process. At the same time, a large number of modified proteins are predicted to be related to carbohydrate transport, metabolism (73), and energy production and conversion (67). Functional enrichment analysis of lysine malonylation-modified proteins To further explore the properties of these modified proteins, GO and KEGG enrichment analyses were carried out (Supplementary Table S3). GO enrichment plots (Fig. A) indicated many modified proteins related to the biological processes of molecular functions, including cellular processes, stimulus responses, transcription translation, etc. In which catalysis, and binding accounts for the vast majority of these modified proteins (Fig. A). Combined with its high expression levels inside the cell and chloroplast (Fig. B), it may suggest that malonylation can have a certain impact on photosynthesis. Enrichment analysis of KEGG pathways was performed to verify the reliability of these resulting data. The results showed that malonylated proteins were greatly enriched in carbon fixation, the TCA cycle, and glucose metabolism pathways. This illustrated that these modified proteins were closely related to them, sufficient to confirm the above points. Domain enrichment plots (Fig. C, Supplementary Table S3) suggest that proteins with structures similar to transferases, dehydrogenases, and pyruvate kinase are more likely to be modified, resulting in the corresponding malonylated proteins. Lysine malonylation site pattern analysis To understand whether specific amino acid motifs were present in the vicinity of modified lysine residues (Supplementary Table S4), they were analyzed for frequency, from − 10 to + 10. As can be seen in the heat map (Fig. A), A, C, G, and V residues have relatively high frequencies. A distribution is more diffuse, occurring at -1, + 1, and + 10, while C, G, and V residues are relatively concentrated between − 4 and + 4. These suggest that the surrounding sequence of lysine residues may influence whether malonylation occurs. Six of these motifs were more frequent and are represented after their columns in a graphic (Fig. B), including C…Kma, C…Kma, Kma…C, C…Kma and KmaA, suggesting that malonylation is more likely to occur when these motifs are present near lysine. In order to further understand the role of malonylated proteins in P. grandiflorus , the secondary structures of malonylated proteins were analyzed. As shown in Fig. C, malonylation occurs preferentially in coils (67.8%), followed by α-helices (26.0%), and only about 6.17% of the sites appeared as β-strand in the spiral. Moreover, the probability of their appearance on the protective surface is small, and the relative surface accessibility can reach 98.2%, so malonylation modification may neither change nor affect protein surface properties. Thus, lysine malonylation modifications may be directional rather than random. Protein interaction network of lysine malonylation modified proteins in P. Grandiflorus All the identified associated proteins were characterized using a database network (Fig. ), and after the protein interaction network was constructed, it was able to make a clear observation of the relationship between a target protein and other proteins. Based on this interaction network, three high-score enriched pathways were picked along with their corresponding action networks (Fig. , Supplementary Table S5), including glucose metabolism pathways (Fig. A), TCA cycle (Fig. B), and carbon fixation (Fig. C), according to the Cytoscape algorithm and enrichment analysis of KEGG pathways. These data suggest that multiple pathways may be regulated by lysine malonylation in P. grandiflorus , however the current study did not investigate this and lacks corresponding biological information, which should be studied more closely and perhaps uncover new key enzymes in known biological metabolic pathways or unprecedented special mechanisms. Lysine malonylation involved in pathway analysis of carbon fixation, TCA cycle, and glucose metabolism The Calvin and TCA cycles belong to chloroplasts and mitochondria, respectively. Both play important roles in P. grandiflorus . Studies have shown that lysine malonylation is closely related to the Calvin cycle (Liu et al. ) and the TCA cycle (Qian et al. ). According to KEGG pathway enrichment analysis (Fig. B), carbon fixation, TCA cycle and sugar metabolism pathways show the highest malonylation enrichment. Subcellular localization results (Fig. C) also showed that malonylated proteins were distributed in chloroplasts and mitochondria. With further research, it can be seen (Fig. ) (Table S6) that most enzymes in carbon fixation, TCA cycle and sugar metabolism pathway have more or less malonylation modifications, and these three are interconnected by phosphoenolpyruvate, oxaloacetate and acetyl CoA as bridges. Although the presence of modified proteins in mitochondria in subcellular localization is not in the forefront, it has a high level of enrichment in the TCA cycle, which may indicate that malonylation selectively acts on this cycle in mitochondria without affecting other parts or having a small impact. The above results indicate that lysine malonylation may regulate the energy conversion process in P. grandiflorus , including energy collection, production, fixation, and application. Malonylated proteins involved in stress and defense responses When plants are exposed to unfavorable conditions for survival, their stress response is denoted as the environmental stress response. Environmental stress can be divided into biological and abiotic stresses, among which abiotic stress includes heavy metals, ultraviolet light, strong light, drought, salinity, extreme temperature, ozone, etc. (Saijo and Loo ). Stress is likely to cause plants to produce reactive oxygen species (ROS) (Waszczak et al. ), causing damage to plant organism, resulting in slower growth and a decline in yield. Moreover, in the natural environment, plants generally face various different environmental stresses (Suzuki et al. ). Correspondingly, when plants respond to external stress, they regulate gene expression and produce a variety of special proteins or secondary metabolites to ensure their survival (Ramakrishna and Ravishankar ). There is no special report on P. grandiflorus in response to environmental stress. In this study, we found many malonylated proteins responding to environmental stress in this plant. Based on the GO analysis, P. grandiflorus has noticeable biological reactions to cadmium ions and cytokinins and has a variety of molecular functions to deal with metal ions and antioxidants (Fig. ). A large number of heat shock proteins (1.58%) and antioxidant-related proteins (2.58%) can be found malonylated in P. grandiflorus , including HSP22, HSP70, HSP90, APX1, APX3, and APX6. HSP22, HSP70, and HSP90 are common plant heat shock proteins (Berka et al. ; Li et al. ; Lund et al. ), while APX1, APX3 and APX6 are related proteins that protect against ROS in plants (Chen et al. ; Maruta et al. ; Wang et al. ). HSP22 has been proved to be a member of the small heat shock protein superfamily, and it is highly expressed in maize (Lund et al. ), pea (Avelange-Macherel et al. ), tomato (Banzet et al. ) and other plants. In order to ensure the smooth progress of photosynthesis, the active oxygen in chloroplasts needs to be rapidly removed, and the key component involved is ascorbic acid. However, monodehydroascorbate reductase (Maynard et al. ), the key enzyme for ascorbic acid regeneration in P. grandiflorus , was not significantly enriched, indicating that malonylation may not have an apparent scavenging effect on active oxygen in chloroplasts. Interestingly, 2.23% of the proteins are elongation factor proteins, which belong to the molecular functions involved in metal ion binding. Perhaps elongation factor proteins have some correlation with the heavy metal ion stress response in plants. Inaddition, APX1 is related to the lead stress response (Jiang et al. ), maybe the heavy metal ion stress response intersects with other stress responses. The results show that although many proteins in P. grandiflorus are closely related to environmental stress, the specific mechanism and main target types of environmental stress response have not been clearly explained. In addition, P. grandiflorus is used as food and medicine, so the direction of biological stress promoting certain secondary metabolites in P. grandiflorus should be a future research direction. Comparative analysis of lysine malonylation in P. Grandiflorus and other plants As a type of PTM, malonylation, similar to succinylation, acetylation, and other modifications, is not unique to P. grandiflorus . Although there are a wealth of experimental data for malonylation modification studies in microbes and mammals, studies in plants in this context are still in their infancy. The advent of technologies such as LEMP (Chen et al. ), MalPrec (Liu et al. ), and LETM (Al-Barakati et al. ) have facilitated malonylation modification studies in plants as diverse as Oryza sativa (Mujahid et al. ), Triticum aestivum (Liu et al. ) and Zea mays (Xu et al. ). However, no P. grandiflorus literature on this aspect has been reported in available studies. As can be seen in the table (Table ), according to related data, 1755 malonylation modification sites (the most) among 888 modified proteins were found in P. grandiflorus . Maize, which is similar to P. grandiflorus , had 1722 modification sites found among 810 modified proteins, and the least similar is wheat, with only 342 modification sites. Whereas there was a strong malonylation enrichment in photosynthesis in either plant, suggesting that the site and function of malonylation in different plants may be conserved. Regardless, these obtained data for malonylation modifications, in general, are relatively sparse relative to common PTMs such as acetylation and phosphorylation, suggesting that this class of modifications still holds great research value and potential.   P. Grandiflorus In order to ensure that these protein modification data used meet standards, proteome scale analysis was carried out on these existing data (Fig. ). The existence of lysine malonylation in P. grandiflorus was confirmed using a Western blot with an antimalonyl lysine antibody (Fig. A). The overall quality error is less than 5 ppm (Fig. B), which indicates that these MS data used in this study are reliable. Moreover, most peptide segments were only modified once (Fig. C). After checking the distribution of all peptides, it was found that most of these peptides were in the 7–20 amino acids ranges (Fig. D), which aligned with the general law based on enzymatic hydrolysis and mass spectrometry fragmentation, indicating that the length distribution of peptides identified by this mass spectrometer met the quality control requirements. Through statistics, 1755 lysine malonylation modification sites in 888 proteins were identified in this study (Supplementary Table S1). A representative MS/MS diagram is available in Fig. E. Although lysine malonylation modifications have been reported in some other plant species (Nahomi et al. ; Nie et al. ), similar to pathogens (Shi et al. ), there is no relevant record in P. grandiflorus . These results are the first report of lysine malonylation in P. grandiflorus .   P. Grandiflorus In order to further understand the functional role of lysine malonylation modification in P. grandiflorus , the identified modified proteins were classified based on the GO annotation according to biological process, cellular components, and molecular function (Supplementary Table S2). From the Fig. A, the proteins related to cellular processes (24%), metabolic processes (20%), and stimulation reactions (17%) have been modified by malonylation. It was consistent with the observation made in recent years that lysine malonylation modification affects biological and metabolic processes (Liu et al. ). Data on cell composition (Fig. A) show that Most of the modified proteins were located within the cell., and only a few are located in protein-containing complexes (11%). Based on the molecular function analysis, it is evident that malonylation modification is closely related to the activities of catalysis (45%) and binding (37%) (Fig. A), which are similar to results obtained in wheat (Liu et al. ). The above data show that malonylation modification can affect various biological metabolic processes in P. grandiflorus , and play an indispensable role in plant life activities. After further subcellular localization (Fig. B, Supplementary Table S2) of the modification sites, it was found that most of the modification sites existed in chloroplasts (38%) and cytoplasm (34%), but there are few in mitochondria (6%). This includes proteases such as phosphoribulokinase (PRK), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and aconite hydratase (Supplementary Table S1), which may suggest that the metabolic processes of photosynthesis and ATP conversion are influenced by malonylation modifications. In addition, these modification sites also exist in the nucleus (11%) and extracellularly (3%). The above results may provide some reference for the study of malonylation modification of P. grandiflorus . Then, the functional classification of these modified proteins is performed (Fig. C, Supplementary Table S2). Based on the analysis of homologous clusters (COGs) in the COG database, it was found that the number of modified proteins related to PTMs, protein turnover, and chaperones ranks first at 132 each, followed by translation, ribosomal structure, and biogenesis (92). This may imply that malonylation modification will affect the gene expression process. At the same time, a large number of modified proteins are predicted to be related to carbohydrate transport, metabolism (73), and energy production and conversion (67).   To further explore the properties of these modified proteins, GO and KEGG enrichment analyses were carried out (Supplementary Table S3). GO enrichment plots (Fig. A) indicated many modified proteins related to the biological processes of molecular functions, including cellular processes, stimulus responses, transcription translation, etc. In which catalysis, and binding accounts for the vast majority of these modified proteins (Fig. A). Combined with its high expression levels inside the cell and chloroplast (Fig. B), it may suggest that malonylation can have a certain impact on photosynthesis. Enrichment analysis of KEGG pathways was performed to verify the reliability of these resulting data. The results showed that malonylated proteins were greatly enriched in carbon fixation, the TCA cycle, and glucose metabolism pathways. This illustrated that these modified proteins were closely related to them, sufficient to confirm the above points. Domain enrichment plots (Fig. C, Supplementary Table S3) suggest that proteins with structures similar to transferases, dehydrogenases, and pyruvate kinase are more likely to be modified, resulting in the corresponding malonylated proteins.   To understand whether specific amino acid motifs were present in the vicinity of modified lysine residues (Supplementary Table S4), they were analyzed for frequency, from − 10 to + 10. As can be seen in the heat map (Fig. A), A, C, G, and V residues have relatively high frequencies. A distribution is more diffuse, occurring at -1, + 1, and + 10, while C, G, and V residues are relatively concentrated between − 4 and + 4. These suggest that the surrounding sequence of lysine residues may influence whether malonylation occurs. Six of these motifs were more frequent and are represented after their columns in a graphic (Fig. B), including C…Kma, C…Kma, Kma…C, C…Kma and KmaA, suggesting that malonylation is more likely to occur when these motifs are present near lysine. In order to further understand the role of malonylated proteins in P. grandiflorus , the secondary structures of malonylated proteins were analyzed. As shown in Fig. C, malonylation occurs preferentially in coils (67.8%), followed by α-helices (26.0%), and only about 6.17% of the sites appeared as β-strand in the spiral. Moreover, the probability of their appearance on the protective surface is small, and the relative surface accessibility can reach 98.2%, so malonylation modification may neither change nor affect protein surface properties. Thus, lysine malonylation modifications may be directional rather than random.   P. Grandiflorus All the identified associated proteins were characterized using a database network (Fig. ), and after the protein interaction network was constructed, it was able to make a clear observation of the relationship between a target protein and other proteins. Based on this interaction network, three high-score enriched pathways were picked along with their corresponding action networks (Fig. , Supplementary Table S5), including glucose metabolism pathways (Fig. A), TCA cycle (Fig. B), and carbon fixation (Fig. C), according to the Cytoscape algorithm and enrichment analysis of KEGG pathways. These data suggest that multiple pathways may be regulated by lysine malonylation in P. grandiflorus , however the current study did not investigate this and lacks corresponding biological information, which should be studied more closely and perhaps uncover new key enzymes in known biological metabolic pathways or unprecedented special mechanisms.   The Calvin and TCA cycles belong to chloroplasts and mitochondria, respectively. Both play important roles in P. grandiflorus . Studies have shown that lysine malonylation is closely related to the Calvin cycle (Liu et al. ) and the TCA cycle (Qian et al. ). According to KEGG pathway enrichment analysis (Fig. B), carbon fixation, TCA cycle and sugar metabolism pathways show the highest malonylation enrichment. Subcellular localization results (Fig. C) also showed that malonylated proteins were distributed in chloroplasts and mitochondria. With further research, it can be seen (Fig. ) (Table S6) that most enzymes in carbon fixation, TCA cycle and sugar metabolism pathway have more or less malonylation modifications, and these three are interconnected by phosphoenolpyruvate, oxaloacetate and acetyl CoA as bridges. Although the presence of modified proteins in mitochondria in subcellular localization is not in the forefront, it has a high level of enrichment in the TCA cycle, which may indicate that malonylation selectively acts on this cycle in mitochondria without affecting other parts or having a small impact. The above results indicate that lysine malonylation may regulate the energy conversion process in P. grandiflorus , including energy collection, production, fixation, and application.   When plants are exposed to unfavorable conditions for survival, their stress response is denoted as the environmental stress response. Environmental stress can be divided into biological and abiotic stresses, among which abiotic stress includes heavy metals, ultraviolet light, strong light, drought, salinity, extreme temperature, ozone, etc. (Saijo and Loo ). Stress is likely to cause plants to produce reactive oxygen species (ROS) (Waszczak et al. ), causing damage to plant organism, resulting in slower growth and a decline in yield. Moreover, in the natural environment, plants generally face various different environmental stresses (Suzuki et al. ). Correspondingly, when plants respond to external stress, they regulate gene expression and produce a variety of special proteins or secondary metabolites to ensure their survival (Ramakrishna and Ravishankar ). There is no special report on P. grandiflorus in response to environmental stress. In this study, we found many malonylated proteins responding to environmental stress in this plant. Based on the GO analysis, P. grandiflorus has noticeable biological reactions to cadmium ions and cytokinins and has a variety of molecular functions to deal with metal ions and antioxidants (Fig. ). A large number of heat shock proteins (1.58%) and antioxidant-related proteins (2.58%) can be found malonylated in P. grandiflorus , including HSP22, HSP70, HSP90, APX1, APX3, and APX6. HSP22, HSP70, and HSP90 are common plant heat shock proteins (Berka et al. ; Li et al. ; Lund et al. ), while APX1, APX3 and APX6 are related proteins that protect against ROS in plants (Chen et al. ; Maruta et al. ; Wang et al. ). HSP22 has been proved to be a member of the small heat shock protein superfamily, and it is highly expressed in maize (Lund et al. ), pea (Avelange-Macherel et al. ), tomato (Banzet et al. ) and other plants. In order to ensure the smooth progress of photosynthesis, the active oxygen in chloroplasts needs to be rapidly removed, and the key component involved is ascorbic acid. However, monodehydroascorbate reductase (Maynard et al. ), the key enzyme for ascorbic acid regeneration in P. grandiflorus , was not significantly enriched, indicating that malonylation may not have an apparent scavenging effect on active oxygen in chloroplasts. Interestingly, 2.23% of the proteins are elongation factor proteins, which belong to the molecular functions involved in metal ion binding. Perhaps elongation factor proteins have some correlation with the heavy metal ion stress response in plants. Inaddition, APX1 is related to the lead stress response (Jiang et al. ), maybe the heavy metal ion stress response intersects with other stress responses. The results show that although many proteins in P. grandiflorus are closely related to environmental stress, the specific mechanism and main target types of environmental stress response have not been clearly explained. In addition, P. grandiflorus is used as food and medicine, so the direction of biological stress promoting certain secondary metabolites in P. grandiflorus should be a future research direction.   P. Grandiflorus and other plants As a type of PTM, malonylation, similar to succinylation, acetylation, and other modifications, is not unique to P. grandiflorus . Although there are a wealth of experimental data for malonylation modification studies in microbes and mammals, studies in plants in this context are still in their infancy. The advent of technologies such as LEMP (Chen et al. ), MalPrec (Liu et al. ), and LETM (Al-Barakati et al. ) have facilitated malonylation modification studies in plants as diverse as Oryza sativa (Mujahid et al. ), Triticum aestivum (Liu et al. ) and Zea mays (Xu et al. ). However, no P. grandiflorus literature on this aspect has been reported in available studies. As can be seen in the table (Table ), according to related data, 1755 malonylation modification sites (the most) among 888 modified proteins were found in P. grandiflorus . Maize, which is similar to P. grandiflorus , had 1722 modification sites found among 810 modified proteins, and the least similar is wheat, with only 342 modification sites. Whereas there was a strong malonylation enrichment in photosynthesis in either plant, suggesting that the site and function of malonylation in different plants may be conserved. Regardless, these obtained data for malonylation modifications, in general, are relatively sparse relative to common PTMs such as acetylation and phosphorylation, suggesting that this class of modifications still holds great research value and potential.   In the present study, the processing analysis of whole tissues of P. grandiflorus led to the identification of a total of 888 lysine malonylation proteins, which harbor 1755 unique modification sites, indicating that lysine malonylation modification is widely present in P. grandiflorus. Lysine malonylation mainly occurs in chloroplasts (38%) and cytoplasm (34%), similar to the results of GO enrichment analysis. G, A, C, and V residues are usually enriched near the modification site when a malonylation reaction occurs. The impacted protein network is related to energy metabolism reactions such as glucose metabolism, the TCA cycle, and carbon fixation. A large number of modified proteins, such as HSP22, are associated with heat shock and antioxidant activity. Malonylation is significantly enriched in photosynthesis in different plants.   Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6 Supplementary Material 7   