All animal experiments were carried out according to the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, and the ARRIVE guidelines 2.0. C57BL/6J mice were purchased from the Experimental Animal Center of the Daping Hospital. The experimental protocol was approved by the Third Military Medical University Animal Use and Care Committee (AMUWEC20247120).

MI was induced in 8-week-old male mice through permanent ligation of the proximal left anterior descending (LAD) coronary artery, as previously described (10). Briefly, mice were maintained under anesthesia with 2% isoflurane inhalation delivered in 100% oxygen flow, followed by an incision made between the third and fourth intercostal spaces. After exposing the heart, the LAD was ligated with a 7-0 silk suture, positioned 2–3 mm distal to the left atrial appendage. The thoracic cavity was closed with 6-0 silk sutures, and the mice were then extubated. Sham-operated mice, which underwent the same procedure as the MI group except for the ligation of the LAD, served as the control group. After 3 days of MI induction, the hearts were collected for analysis.

The heart tissue samples were taken from −80 °C and placed into a mortar pre-chilled with liquid nitrogen. Liquid nitrogen was added, and the samples were finely ground into a powder. Each group of samples was then mixed with four times the volume of lysis buffer (50 µM PR-619 (Cat. #HY-13814, MedChemExpress), 1% Triton X-100 (Sangon Biotech), 50 mM Nicotinamide (Cat. #HY-B0150, MedChemExpress), 10 mM dithiothreitol (Sigma-Aldrich), 1% protease inhibitor cocktail (Merck Millipore), 3 µM Trichostatin A (Cat. #HY-15144, MedChemExpress) and 2 mM EDTA(Sigma-Aldrich)) (11), followed by sonication for cell lysis. After centrifugation at 12,000 g for 10 min at 4 °C, the supernatant was transferred to a new centrifuge tube, and protein concentration was measured by an enhanced BCA protein assay kit (Cat. #P0010, Beyotime). Equal amounts of protein from each group were taken, and Trichloroacetic acid (Sigma-Aldrich) was slowly added to reach the final concentration of 20%, followed by vortex mixing. After 2 h of precipitation at 4 °C, the samples were centrifuged at 4,500 g for 5 min. The pellet was washed three times with acetone and air-dried. Then, 200 mM Tetraethylammonium bromide (Sigma-Aldrich) was added, and the mixture was sonicated. Trypsin [0.1 μg/μl; trypsin: protein = 1:50 (m/m)] was added for overnight digestion. Dithiothreitol (Sigma-Aldrich) was then added to a final concentration of 5 mM, and the mixture was reduced at 56 °C for 30 min. Subsequently, iodoacetamide (Sigma-Aldrich) was added to a final concentration of 11 mM, and the samples were incubated in the dark at room temperature for 15 min.

The peptides were dissolved in immunoprecipitation (IP) buffer (100 mM NaCl, 1 mM EDTA, 50 mM Tris-HCl, 0.5% NP-40, pH = 8.0) and the supernatant was transferred to pre-washed resin (Cat. #PTM1404, PTM Bio) (12). The mixture was gently shaken for overnight incubation on a rotating shaker at 4 °C. After incubation, the resin was washed four times with IP buffer and twice with deionized water. Finally, the peptides bound to the resin were eluted with 0.1% trifluoroacetic acid elution buffer. For liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, the resulting peptides were desalted with C18 ZipTips (Millipore) according to the manufacturer's instructions.

The peptides were dissolved in mobile phase A of the liquid chromatography and then separated using the NanoElute ultra-high-performance liquid chromatography (UHPLC) system (Bruker Daltonics). The mobile phase consisted of solvent A (0.1% formic acid, 2% acetonitrile in water) and solvent B (0.1% formic acid in acetonitrile). The liquid chromatography gradient settings were as follows: 0–18 min, 6%–22% B; 18–22 min, 22%–30% B; 22–26 min, 30%–80% B; 26–30 min, 80% B, with a flow rate maintained at 500 nl/min. After separation by the UHPLC system, the peptides were subjected into the Capillary Electrospray Source for ionization and then analyzed by the timsTOF Pro mass spectrometer for data acquisition (13). The electrospray source voltage was set to 1.6 kV, and both the peptide precursors and their secondary fragments were detected and analyzed using time-of-flight (TOF). The data acquisition mode used was data-independent parallel accumulation serial fragmentation (dia-PASEF). The range for the primary mass spectrum scan was set from 100–1,700 m/z. After acquiring one primary mass spectrum, 8PASEF mode acquisitions were performed. The secondary mass spectrum scan range was set from 425–1,025 m/z, with a window of 25 m/z for each scan.

Raw mass spectrometry data were searched against a Swissprot protein sequence database (Mus_musculus_10090_SP_20230103.fasta) by Spectronaut (v17). A maximum of four missing cleavages was allowed for trypsin/P digestion. Cysteine alkylation was considered a fixed modification. Variable modifications were methionine oxidation, N-terminal acetylation and lysine lactylation. For further data filtering, the identification result filtering criteria were set as follows: Precursor and protein false discovery rate (FDR) were set to 1%; identified proteins must contain at least one unique peptide.

GO enrichment analysis and KEGG pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). GSEA was performed with GSEA v4.3.3 software. The motif characteristics of the modification sites were analyzed by MoMo analysis tool (http://meme-suite.org/tools/momo) based on the motif-x algorithm. The protein interaction relationships were obtained by comparing with the STRING protein interaction network database (https://string-db.org/; v12.0), and then visualized using the Cytoscape v3.7.2 tool. The subcellular localization of proteins was annotated using the WolF PSORT software (http://www.genscript.com/psort/wolf_psort.html).

Heart tissue lactate levels were quantified using a Lactate Assay Kit (Cat. #A019-2, Jiancheng Bio, Nanjing, China) following the manufacturer's instructions. Briefly, tissues were homogenized in four volumes of lactate assay buffer and centrifuged to obtain the soluble supernatant for analysis. The assay procedure was performed as follows: the sample, enzyme working solution, and chromogenic agent were sequentially added to the reaction mixture. After vortex mixing, the reaction was incubated at 37 °C for 10 min and then terminated by adding stop solution. Absorbance was measured at 530 nm using a cuvette with a 1 cm light path.

Paraffin sections were deparaffinized, and then were put in sodium citrate antigen repair buffer (Cat. #P0083, Beyotime) for high-temperature antigen repair for 30 min. The sections were blocked with blocking solution (Cat. #P0260, Beyotime) for 60 min at room temperature and then treated with antibodies against pan-Kla (Cat. #PTM-1401RM, PTM Bio) and Cardiac Troponin T (cTNT, Cat. #MA5-12960, Invitrogen) overnight at 4 °C. The sections were then washed with PBS thrice and incubated with Alexa Fluor 488 and 555 secondary antibodies (Invitrogen) for 60 min in the dark at 37 °C.

Mouse heart tissues were homogenized in lysis buffer [Protease inhibitor cocktail III (Cat. #535140, Merck Millipore, 1:200), Protease inhibitor Cocktail IV (Cat. #524633, Merck Millipore, 1:200), Protease inhibitor Cocktail V (Cat. #539137, Merck Millipore, 1:60), 50 μM PR-619 (Cat. #HY-13814, MedChemExpress), 50 mM nicotinamide (Cat. #HY-B0150, MedChemExpress) and 3 μM Trichostatin A (Cat. #HY-15144, MedChemExpress)]. For WB, the proteins samples were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to a Nitrocellulose Membrane (Cat. #66485, Pall Corporation). After 1 h of incubation in 5% nonfat milk (Cat. #P0216, Beyotime), the membranes were incubated with specific primary antibodies at 4 °C overnight and appropriate secondary antibodies (Li-Cor, IRDye 800 CW, 1:10000) for 1 h at room temperature next day. For IP, the hearts were homogenized in above-mentioned prepared lysis buffer. The lysates were centrifuged at 12,000 g for 15 min at 4 °C. The supernatant was collected and the extracted protein was determined with BCA Protein Assay kit (Beyotime). The pre-washed 50ug Protein A/G magnetic beads (Cat. #HY-K0202, MedChemExpress) were mixed with 5 μg anti-Pan Kla antibody (Cat. #PTM-1401RM, PTM Bio, RRID: AB_2942013) at room temperature for 1 h. Then, 1 mg of protein lysate and the antibody-conjugated beads complex were incubated 4 °C overnight on an orbital shaker. The supernatant was collected next day, and the magnetic beads bound with protein were washed three times with PBST (PBS containing 0.1% Tween-20). Then the magnetic beads were separated, and 50 μl 1 × SDS-PAGE Loading Buffer was added to the magnetic beads and heated at 95 °C for 5 min. For IP negative controls, only 1/40 of each sample was used. Finally, the protein was detected using immunoblotting. The following antibodies were used for WB and IP: rabbit anti-Pan Kla (Cat. #PTM-1401RM, PTM Bio, 1:1,000 for WB, 5 μg for IP), rabbit anti-CS (Cat. #ab96600, Abcam, RRID: AB_10678258, 1:1,000), mouse anti-PFKL (Cat. #68385-1-Ig, Proteintech, RRID: AB_3085103, 1:1,000), mouse anti-MYH6 (Cat. #sc-32732, Santa cruz, RRID: AB_670118, 1:200), rabbit anti-CSRP1 (Cat. #sc-390418, Santa cruz, 1:100), rabbit anti-PDLIM1 (Cat. #11674-1-AP, Proteintech, RRID: AB_2161631, 1:1,000), rabbit anti-DDX5 (Cat. #F1128, Selleck, 1:1,000), rabbit anti-SARNP (Cat. #15798-1-AP, Proteintech, RRID: AB_1959356, 1:1,000), mouse anti-GAPDH (Cat. #60004-1-Ig, Proteintech, RRID: AB_2107436, 1:10,000).

Statistical analyses were performed using GraphPad Prism (version 9.5.1) or R (version 4.3.3). The procedure for quantification of proteomic data was referenced from a previous study (14). Briefly, protein/peptide intensities were normalized across all samples to generate normalized intensity values. Subsequently, a centering transformation was applied to these normalized intensities to obtain relative quantification values. The relative quantification value of each modification site was divided by the relative quantification value of its corresponding protein to eliminate the effect of protein expression on the observed modification levels. The fold change (FC) between two comparison groups was then defined as the ratio of the mean quantification values for each protein or peptide. Prior to statistical analysis, all relative quantification values were log2-transformed to ensure the data approximated a normal distribution. Then the normality of data distribution was assessed using the Shapiro–Wilk test, and the homogeneity of variances was assessed using Levene's test. For comparisons that met both the assumptions of normality and equal variance, Student's t-test was applied; otherwise, the Welch's t-test was used. Additionally, for the proteomics data, FDR correction was applied to p-values via the Benjamini-Hochberg procedure, and the resulting q-values were calculated and presented. All quantification graphs in this study are presented as the mean ± S.D. A p-value < 0.05 was considered statistically significant.

To elucidate the pathophysiological processes underlying MI in mouse hearts, we performed comprehensive proteomic profiling to compare global protein expression patterns between sham-operated controls and infarcted hearts (Figure 1A). We totally identified 28,543 peptides and 4,366 proteins, in which 4,330 proteins were comparable (Figure 1B, Supplementary Material S1). By setting FC > 1.5 or FC < 1/1.5, with a p-value < 0.05, 490 proteins were upregulated and 182 proteins were downregulated 3 days post-MI (Figure 1C, Supplementary Material S2). We then performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of all the differentially expressed proteins. The results of GO enrichment analysis suggested that some biological processes were influenced in post-MI hearts, such as immune system process, kinds of metabolic processes, RNA processing, angiogenesis and acute-phase response (Figure 1D). KEGG pathway analysis showed that the most significant change was relation to metabolic pathways in post-MI hearts (Figure 1E). Subsequently, we asked the status of metabolic pathways through Gene Set Enrichment Analysis (GSEA), then found that fatty acid metabolism and oxidative phosphorylation were significantly inhibited (Figures 1F,G), whereas hypoxia-related pathway and glycolysis tended to be activated instead (Figures 1H,I). Collectively, these results defined metabolic remodeling as a central pathophysiological feature of post-MI hearts, featuring coordinated downregulation of fatty acid metabolism and oxidative phosphorylation, concomitant with induction of glycolysis.

Previous studies have revealed that MI can increase circulating lactate levels (3, 4). As glycolysis increases in infarcted heart, we directly measured the total protein lactylation status together with the lactate levels of heart tissues. We observed that the abundance of lysine lactylation and lactate both increased slightly in infarcted hearts one day post-MI, peaked at three days post-MI, and then declined (Figures 2A,B). Immunofluorescence staining of cardiac tissues also confirmed an overall increase in protein lactylation modifications three days post-MI (Figure 2C). Therefore, in the subsequent study, we identified Kla sites in both the control group and MI group, aiming to explore the pattern of this modification under physiological conditions and disease states.

Figure 1A illustrates the workflow of our Kla omics analysis. Eight-week-old mice were subjected to control or MI treatment. Proteins from left ventricular tissues were harvested and Kla proteins were purified by IP targeting lactylated lysines and detected through LC-MS/MS. Based on proteomics and Kla omics analyses, Kla levels at each site were detected by normalizing Kla peptide abundance with protein abundance. The principal component analysis (PCA), which was performed to validate the quality of the MS data, showed that the two groups, control and MI groups, were separated into two distant quadrants (Figure 3A).

Although lactate levels increase after MI, it can also be produced in the healthy heart, and lactylation occurs under normal conditions, as confirmed in our previous experiments. The lactylation of cardiac proteins under physiological conditions and its potential regulatory functions have not been described. Therefore, we first attempted to identify all the Kla sites in the healthy heart. A total of 1,674 Kla sites were identified from 477 proteins in mouse hearts (Figure 3B, Supplementary Material S3). To investigate the Kla motifs, we compared the amino acids surrounding Kla sites against the mouse proteome and found that a overrepresentation of positively charged lysine (K) at many positions (−10, −9, −8, −7, −6, −5, −4, −3, +6, +7, +8, +9 and +10), also a notable overrepresentation of nonpolar alanine (A) at many positions (−10, −9, −8, −7, −6, −5, −4, −3, −2, −1, +1, +2, +3 and +4), while negatively charged glutamic acid (E) and nonpolar glycine (G) were largely overrepresented at the +3 position or −2, −1, 1, +1, +2, +3 and +5 positions, respectively (Figure 3C). Nearly half of the proteins (44.03%) had only one Kla site and a small proportion of proteins (1.26%) had more than 20 Kla sites (Figure 3D). Myosin-6 and titin, two important cytoskeletal proteins, have 83 and 77 Kla sites separately, which are far more than other identified proteins (Supplementary Material S4). We performed cellular compartment analysis of all lysine-lactylated proteins identified from mouse heart tissue by using a predictive tool (Wolf PSORT), and found that these proteins were widely distributed in the nucleus, mitochondria, cytoplasm, plasma membrane, and extracellular space, suggesting that lactylation modification might regulate biological functions not limited to a specific cellular sublocation, but potentially involved in various cellular compartments (Figure 3E). Thus, to understand the biological functions of lysine-lactylated substrates, we performed enrichment analysis with the GO annotation database. Our data showed that lysine-lactylated proteins were significantly enriched in cellular metabolic process with specific enrichment in proton motive force-driven mitochondrial ATP synthesis (adjusted P = 1.13 × 10⁻³⁹), fatty acid metabolic process (adjusted P = 1.83 × 10⁻²⁴), aerobic respiration (adjusted P = 7.01 × 10⁻²³), and tricarboxylic acid (TCA) cycle (adjusted P = 6.31 × 10⁻²¹). Analysis of the PFAM domain database showed that Lys-lactylated proteins were enriched for acyl-CoA dehydrogenase, PDZ domain-containing protein, and biotin-requiring enzyme (Figure 3F). To understand the cellular pathways involving lysine lactylation, we performed enrichment analysis of KEGG pathways. Lysine-lactylated proteins were largely associated with metabolic pathways (adjusted P = 4.41 × 10⁻⁴²), diabetic cardiomyopathy (adjusted P = 1.24 × 10⁻⁴¹), carbon metabolism (adjusted P = 4.20 × 10⁻³⁸) and oxidative phosphorylation (adjusted P = 3.91 × 10⁻³⁷) (Figure 3G). We constructed and visualized the protein-protein interaction (PPI) networks of lysine-lactylated proteins using the STRING v12.0 database (15). Our data set revealed an extensive, highly interconnected network with clusters of nodes forming distinct protein complex patterns (Figure 4A). Using the MCODE tool (16), we identified a number of highly connected subnetworks among lysine-lactylated proteins, including aerobic respiration (cluster 1, score = 37.579), translation (cluster 2, score = 16.750), glycolysis, fatty acid beta-oxidation and sarcomere organization (cluster 3, score = 11.120), TCA cycle (cluster 4, score = 9.444), and mRNA processing (cluster 5, score = 9.000) (Figures 4A–F).

We next compared the changes in Kla levels between control and MI groups. Compared to the control group, an average Kla levels above 1.5 or below 0.67, together with P value < 0.05, was considered as a significant change (Supplementary Material S5). In total, 61 sites across 53 proteins exhibited a remarkable increase in Kla levels, and 30 sites across 27 proteins exhibited a remarkable decrease in Kla levels (Figures 5A,B). The venn diagram showed that 79% of the 53 proteins exhibiting increased Kla sites and 74% of the 27 proteins exhibiting decreased Kla sites, did not have changes in protein contents (Figure 5C). The above results indicated that Kla modification might play roles post-MI independent of protein-level changes. To identify the pathophysiological processes involved in these proteins that undergo Kla-modified alteration, we performed GO and KEGG analyses. As shown in Figure 5D, proteins exhibiting Kla changes were largely associated with succinate metabolic process, TCA cycle, mRNA processing, regulation of the force of heart contraction, mitochondrial ATP synthesis coupled protein transport and RNA splicing. The cellular components in which these proteins were involved included mitochondrion, cytoplasm, ribonucleoprotein complex and Z disc (Figure 5D). Consistently, KEGG analyses also showed that proteins exhibiting Kla changes were largely associated with carbon metabolism, TCA cycle and cardiac muscle contraction (Figure 5E). Totally, lactylation may affect energy metabolism, RNA synthesis, and cytoskeleton after MI in mouse heart.

Cell compartment analysis was performed to probe the subcellular localization of proteins containing differentially lactylated lysine residues (Figure 5F). According to the prediction by Wolf PSORT, the upregulated lactylated proteins were found to be more represented in the nucleus in the ischemic hearts, hinting that the distribution of lactate and Kla modifications suggestive of a healthy or ischemic heart might have different propensity for subcellular localization. We then performed PPI analysis and observed that complicated interactions existed between most of the lactylated proteins, suggesting that Kla modifications exert a broad regulatory role by affecting a group of proteins with specific functions (Figure 5G).

Many metabolic enzymes exhibited extensive Kla changes following MI and were associated mostly with TCA cycle, fatty acid metabolism, glucose metabolism and respiratory electron (Figure 6A). Two heatmaps separately displayed all the altered Kla sites of these metabolic enzymes and their protein levels between control and MI groups (Figure 6B). As mentioned earlier, Kla changes and protein-level changes might not be consistently altered. For example, CS, SUCLG1, SUCLG2, SDHA and SDHB, five important enzymes that participant in TCA cycle, showed upregulated Kla sites respectively, whereas their protein levels decreased after MI (Figure 6B). To better visualize the changed Kla sites of metabolic enzymes, and metabolic processes that were influenced, we drew a summary diagram showing overview of metabolism pathways based on proteome and lactylome (Figure 6C). Kla changed of CS and PFKL, representing proteins involved in TCA cycle and glucose metabolism, was validated using IP and WB (Figures 6D,E).

Cytoskeletal proteins, which include myofilaments, microtubules, and intermediate filaments, are essential for maintaining cell shape and structural integrity, regulating rhythmic myocardial contractility, driving cell division and participating in cell signaling transduction (17). Following MI, cytoskeletal proteins showed extensively altered Kla, particularly myofilament proteins (Figure 7A). We also drew two heatmaps separately to display all the altered Kla sites and protein-level changes of these cytoskeletal proteins between control and MI groups (Figure 7B). Among proteins of thick filament, MYH6 exhibited most altered Kla sites, perhaps as it's the main structure protein of cardiomyocytes (Figure 7B). Moreover, seven microtubule proteins, including TPPP, TPPP3, RCC2, TBCB, MAPRE1, ARL3 and RAN exhibited a consistent increase in Kla modifications (Figure 7B). An overview of Kla-level changes of cytoskeletal proteins based on proteome and lactylome was shown in Figure 7C. Kla of a selected subset (MYH6, CSRP1 and PDLIM1) was validated using IP and WB (Figures 7D–F).

Based on Kla omics analyses, we noticed that a series of proteins which participate in RNA metabolism exhibited significant changes of Kla levels. RNA metabolism contains any events in the life cycle of RNA molecules, including synthesis, processing, transport, translation and degradation (18). Our results demonstrated that proteins exhibiting extensive Kla alteration were associated with RNA translation, splicing, 3′end procession, nuclear-to-cytoplasmic transport and translation (Figure 8A). It's worth noting that all proteins that play roles in the events that happens in nucleus, including transcription, splicing and 3′end processing, showed increases in their Kla levels (Figures 8B,C). Our previous cell compartment analysis results indicated that the increased lactylated proteins were found to be more represented in the nucleus in the ischemic hearts. The above facts suggest that lactylation modifications of the infarcted heart occurred more often in the nucleus. We selected DDX5 and SARNP as representative proteins to verify their Kla changes using IP and WB (Figures 8D,E).