The Gut Metabolite Phenylacetylglutamine Inhibits the Angiogenic Potential of Human Umbilical Vein Endothelial Cells Via the β-Adrenergic Receptor-LDHA Axis
Yin Zhang, Wenlong Yang, Jinyan Zhang, Jixiang A, Jinye Shen, Zhiyong Qi, Juying Qian, Aijun Sun, Junbo Ge, Shuning Zhang
TL;DR
A gut metabolite called PAGln reduces blood vessel growth in human cells by affecting a specific receptor and enzyme pathway.
Contribution
This study reveals a novel mechanism by which the gut metabolite PAGln inhibits angiogenesis through the β-adrenergic receptor-LDHA axis in endothelial cells.
Findings
PAGln impairs HUVEC proliferation, migration, and tube formation.
PAGln suppresses glycolytic pathways and lactate production via downregulation of LDHA.
LDHA overexpression rescues PAGln-induced angiogenic impairment.
Abstract
Phenylacetylglutamine (PAGln), a gut microbiota-derived metabolite, is associated with enhanced thrombosis. However, its impact on endothelial function and angiogenesis remains unclear. A murine hindlimb ischemia model was used to assess perfusion recovery. Human umbilical vein endothelial cell (HUVEC) proliferation, migration, and tube formation were evaluated in vitro. Gene set enrichment analysis (GSEA) was performed for pathway enrichment analyses. Furthermore, glycolytic flux and enzyme expression were measured. Lentiviral lactate dehydrogenase A (LDHA) overexpression was performed both in vitro and in vivo. Elevated PAGln impaired blood flow recovery and inhibited HUVEC proliferation, migration and tube formation. β-receptor blocker zenidolol was able to reverse the adverse effects. PAGln downregulated glycolytic pathways, reduced proton efflux, and suppressed LDHA expression and…
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Figure 7- —the National Natural Science Foundation of China
- —Shanghai Sailing Program
- —Natural Science Foundation of Shanghai
- —Shanghai Top Priority center construction project
- —Shanghai Clinical Research Center for Interventional Medicine
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TopicsGut microbiota and health · Cancer, Hypoxia, and Metabolism · Cancer Research and Treatments
Introduction
Phenylacetylglutamine (PAGln) is a metabolite derived from phenylacetic acid by gut microbiota. Factors, such as disruption of the gut microbiome, reduced kidney clearance, altered amino acid metabolism, and dietary intake of phenylalanine-rich foods, significantly raise PAGln concentrations [1]. PAGln is associated with the development of cardiovascular disease and an increased risk of major adverse cardiovascular events (MACE) in patients with diabetes, and the adverse effects are independent of glycaemic control [2–4]. In terms of mechanism, PAGln enhances platelet reactivity and thrombosis potential, thereby contributing to the increased incidence of MACE[5]. Given that cardiovascular diseases remain the leading cause of mortality worldwide[6–9], identifying comprehensive risk factors is crucial. Beyond arterial thrombosis [2], endothelial dysfunction is also recognised as an independent predictor of adverse cardiovascular outcomes, including MACE [5, 10]. Damage and dysfunction of endothelial cells can result in impaired synthesis and secretion of vascular endothelial growth factor (VEGF), which not only adversely affects cardiovascular prognosis but also suppresses angiogenesis. Notably, patients with diabetes exhibit significantly reduced angiogenic capacity and VEGF levels even when blood glucose levels are well controlled [11–14]. Hence, whether PAGln, independent of blood glucose, directly impairs endothelial function and angiogenesis remains to be investigated [15, 16].
Mechanistic studies have revealed that PAGln interacts with G protein-coupled receptors (GPCRs), specifically the α- and β-adrenergic receptors [17]. Among them, the β_2_ receptor is widely recognised to be associated with endothelial cell growth and VEGF/fibroblast growth factor 2 (FGF2) mediated angiogenesis [18, 19]. However, it is unclear whether PAGln exerts anti-angiogenesis and whether this is mediated by β_2_-adrenergic receptors.
Therefore, we hypothesised that PAGln might serve as an independent risk factor for impaired angiogenesis, unrelated to blood glucose, mediated by adrenal receptors. This study aimed to investigate the impacts of the gut metabolite PAGln on angiogenesis in vivo and in vitro, and to elucidate the underlying role of β-adrenergic receptors in modulating this process. Furthermore, the beneficial effects of β-receptor blockers on angiogenesis were evaluated.
Materials and Methods
Cell Cultures
HUVEC were obtained from iCell (Shanghai, China) and cultured in endothelial cell medium (ECM; ScienCell, USA) supplemented with 5% foetal bovine serum (FBS; ScienCell), 1% endothelial cell growth supplement (ScienCell), and 1% penicillin/streptomycin (ScienCell). The cells were maintained in a humidified incubator at 37 °C with 5% CO2.
Transwell Assay
Migration assays were performed with a Transwell cell culture insert (8 µm, Corning, NY, USA). HUVECs (1 × 10^4^ cells) were placed in the upper chamber in serum-free medium, and 500 μm ECM containing PAGln or an equal ECM with 10% FBS was placed below the cell-permeable membrane. Following an incubation period (24 h), the cells that had migrated through the membrane were stained with crystal violet (Beyotime Biotechnology) for 15 min and counted.
EdU Staining
EdU experiments were performed with a BeyoClick™ EdU Cell Proliferation Kit with Alexa Fluor 555 (Beyotime Biotechnology, C0075S). Briefly, HUVECs were seeded in a 6-well plate at a density of 2 × 10^6^ cells per well. Cultured cells were labelled with EdU, fixed, washed, and permeabilised. A click reaction solution (Click Reaction Buffer, CuSO4, Azide 555, and Click Additive Solution) was used for the EdU reaction and detection. Hoechst 33342 staining was used to stain the nuclei. Fluorescence was observed using an inverted fluorescence microscope. The number of positive nuclei/total nuclei was counted using the ImageJ software.
Endothelial Tube Formation Assay
The tube formation assay was performed according to the manufacturer’s instructions. Briefly, HUVECs from different groups were seeded onto 10 μL Matrigel Matrix (Corning, NJ) in µ-Slide 15 Well 3D (Ibidi, USA) for 3 h. Endothelial networks were counted using an inverted microscope.
Cell-Counting Kit (CCK-8) Assay
The CCK-8 assay was performed using a CCK-8 (Beyotime, C0037, China). HUVEC cells were distributed in a 96-well plate, with 100 μL of medium containing 2,000 cells per well, and were allowed to adhere overnight. The cells were changed to fresh medium containing various concentrations of PAGln (0, 10, 100, 200, and 500 μM) dissolved in PBS and incubated for 48 h [20]. Subsequently, 10 μL of CCK8 solution was added to each well, and the plate was incubated in a cell culture incubator for 1 h. The absorbance values at 450 nm were measured at 0, 6, 12, and 24 h.
Western Blotting
Western blotting was performed as previously described [21]. Total protein from the cell lines was extracted using RIPA lysis buffer (Beyotime, Shanghai, China) containing protease, phosphatase, and PMSF triple package (Wellbi, China), and the protein concentration was measured using a BCA kit (Beyotime) according to the manufacturer’s instructions. The same amount of protein was added to the sodium dodecyl sulphate–polyacrylamide gel, then subjected to electrophoresis and the proteins were transferred onto PVDF membranes. The membranes were blocked and incubated with the primary antibody at 4 °C overnight. The next day, an IgG-hydrogen peroxide (HRP) secondary antibody was added, and the membrane was washed, visualised with enhanced chemiluminescence, and quantified by densitometry. All reagents used are listed in Supplementary Table S1.
RNA Extraction and Reverse Transcription-Real-Time Polymerase Chain Reaction (RT-PCR)
The total RNA from HUVECs was extracted using the RNA isolation kit V2 (Vazyme, China) and quantified, and 1 μg of total RNA was reverse transcribed. The PrimeScript RT Reagent Kit (Takara, Japan) was used to synthesise cDNA according to the manufacturer’s instructions. Quantitative PCR (qPCR) was performed using SYBR Green (Takara Bio, Shiga, Japan) [22]. The primer sequences are presented in Supplementary Table S2. The 2 − ΔΔCt method was used to quantify the relative expression levels. β-actin was used as an internal control.
Glycolytic Activity
The glycolytic proton efflux rate (GlycoPER), which is the rate of proton efflux into the extracellular solution during glycolysis, was measured using a Seahorse XF Glycolysis Rate Test Kit (Agilent Technologies, Palo Alto, CA). HUVECs were seeded into the 96-well cell culture plates in medium with 10% FBS and incubated at 37 °C overnight, and then the cells were used for the measurement of glycoPER. Cells were treated with 500 μm PAGln or an equal volume of PBS overnight before adding the XF glycolysis rate measuring compounds. After measuring the baseline concentration, Rot/AA and 2-DG were sequentially added to each well to measure the glycoPER. Seahorse XF-96 Wave software was used to analyse the data. Basal glycolysis refers to the rate of cellular glycolysis before the addition of the mitochondrial inhibitor Rot/AA. Compensatory glycolysis is the rate of cellular glycolysis after the addition of the mitochondrial inhibitor Rot/AA, which effectively inhibits oxidative phosphorylation and drives compensatory changes in cells [23, 24]. GlycoPER was measured as an indicator of glycolytic activity and represents the rate at which protons are released into the extracellular solution during glycolysis. Assay parameters and kinetic profile are shown in Fig S1b.
Extracellular Lactate Content Detection
Extracellular lactate content was measured using the L-lactic acid colorimetric assay kit (Elabscience, E-BC-K043-S, China). HUVECs were seeded in 96-well plates at a density of 2,000 cells in 100 μL of medium and incubated for 24 h. The cells were then treated with 500 μM PAGln, 10 μM zenidolol, or PBS for 48 h. After treatment, the cells were centrifuged at 10,000 × g for 10 min at 4ºC to collect the supernatant, which was kept on ice for subsequent analysis. To prepare the samples, 0.02 mL of lactic acid standard, supernatant, or double-distilled water was added to 5 mL Eppendorf tubes. Next, 1,000 μL of enzyme working solution and 200 μL of chromogenic agent were added in sequence to each sample. The reaction mixture was incubated at 37 °C for 10 min. Finally, 2,000 μL of stop solution was added, and the optical density of each sample was measured at 530 nm.
RNA Sequencing and Data Analysis
HUVECs were treated with 500 μM PAGln or PBS for 48 h. Total RNA was extracted and used for RNA-Seq analysis. cDNA library construction and sequencing were performed by Biotech Company (Shanghai, China). Gene expression levels were normalised to Fragments Per Kilobase of Exon Model per million mapped reads (FPKM). Genes with a false discovery rate (FDR) < 0.05 and |log_2_FC|≥ 0.5 were considered as DEGs. Subsequently, a more stringent threshold of |log2FC|> 1 was applied to identify top candidate genes, aiming to select targets with more robust biological alterations. Pathway enrichment analysis was performed using the Cluster Profiler package in R.
Gene Set Enrichment Analysis (GSEA)
Glycolysis-related genes were selected from the GSEA database. For biological process and pathway enrichment analyses, GSEA was performed using GSEA software (version 4.1.0). To rigorously control for multiple testing, the Benjamini–Hochberg method was applied to control the FDR. Reported p-values for Gene Ontology and GSEA results are adjusted p-values (FDR), ensuring statistical rigour.
Experimental Animals and Study Protocols
Male C57BL/6 healthy mice (10 weeks old, weighing 25–35 g) were purchased from the Shanghai Animal Management Center (Shanghai, China). The mice were housed in a temperature-controlled environment with a 12 h/12 h light/dark cycle. Mice were randomly divided into four groups (n = 25): the control group (n = 6) received intraperitoneal injections of PBS; the PAGln group (n = 7) received intraperitoneal injections of 4 mg/kg body weight PAGln; the control + zenidolol group (n = 6) received intraperitoneal injections of 1 mg/kg body weight zenidolol; the PAGln + zenidolol group (n = 6) received intraperitoneal injections of 4 mg/kg body weight PAGln combined with 1 mg/kg body weight zenidolol. The Experimental Animal Ethics Committee of Fudan University approved the animal research protocol. All animal procedures were performed in accordance with the Guiding Principles for the Use and Care of Animals (NIH Publication No. 85–23, revised in 1996). At least six mice per group were used for blood flow recovery and pathological evaluation. All reagents used are listed in Supplementary Table S1.
Mouse Model of Hindlimb Ischemia
Chronic ischemia was induced in compliance with well-established unilateral hind limb surgery protocols [25]. A hind limb ischemia model was established as previously described. Briefly, the mice were anesthetised intraperitoneally with 10% chloral hydrate (0.1 mL/10 g). The femoral artery was separated from the femoral nerve and vein, ligated using 6–0 silk sutures, and excised. Vertical longitudinal incisions were also made in the contralateral hindlimbs. On the first day after surgery, PAGln and zenidolol were individually or concurrently suspended in 50 mL PBS or an equal amounts of PBS and administered via intraperitoneal injection. Blood flow perfusion in the lower limbs was evaluated using laser Doppler perfusion imaging on days 0,1, 7, and 14. The perfusion ratio of the ischemic limb to the non-ischemic hindlimb was quantified by averaging the relative units of flux from the knee to the toe using PIMSoft Software (Perimed, Sweden).
Lentivirus Transfection
The control adenovirus and lentiviral lactate dehydrogenase A (LDHA) adenovirus were constructed by the Obio Technology Company (Shanghai, China). The LDHA-lentivirus vector used was pcSLenti-CMV-MCS-3Xflag-pgk-Puro-WPRE3. When the cells were 70–80% confluent, they were transfected for 72 h with lentiviral vectors (MOI: 10) [26] in 6-well plates according to the manufacturer's instructions. The supernatant containing the lentivirus was replaced with ECM after 12 h. The infected HUVEC cells were selected by a 1-week puromycin (1 μg/mL) treatment, and puromycin-resistant colonies were picked, expanded, and analysed. Gene transfection efficiency was verified using a Western blot 72 h later.
The mice were randomly divided into two groups, with 12 mice per group: the empty lentivirus group and the LDHA-lentivirus group. Each mouse received a tail vein injection of 200 µL of suspension (4 × 10^8^ TU LDHA lentivirus per mL) [27]. One week after infection, unilateral hind limb ischemia surgery was performed. Following surgery, each group was further divided into two subgroups (n = 6), which received intraperitoneal injections of either 4 mg/kg body weight PAGln or PBS.
Immunofluorescence
Paraffin-embedded serial Sects. (6 μm) obtained from the gastrocnemius and thigh adductor muscles of the ischemic hind limb models were used for IF staining. Sections were heated in citric acid buffer (pH 6.0, 100 °C, 10 min) for antigen retrieval and subsequently blocked with 5% bovine serum albumin in PBS containing Tween (PBST) for 1 h at room temperature prior to an overnight incubation at 4 °C with the primary antibodies diluted in PBST. The sections were then incubated with secondary antibodies at room temperature. To define small arteries and capillaries on day 14 after surgery, a primary antibody against α-smooth muscle actin (SMA; Abcam, Shanghai, China) and a primary antibody against CD31 (Abcam, Shanghai, China) were used to detect smooth muscle cells and endothelial cells, respectively. Tissues were mounted with DAPI nuclear counterstain. Images were obtained at 100 × magnification using an inverted fluorescence microscope and captured using ImageJ software (NIH, version 1.8.0).
Statistical Analysis
At least three biological replicates were performed per experiment using different cell samples each time, and at least three technical replicates were performed per sample. Continuous variables are presented as mean ± SEM. The normal distribution of these variables was assessed using the Kolmogorov–Smirnov test. For comparisons between two groups, parametric data were analysed using a two-tailed Student’s t-test, whereas nonparametric data were analysed using the Mann–Whitney U test. When the experiment involved multiple groups and only one factor varied, one-way analysis of variance (ANOVA) was used. In experiments where two factors were varied, a two-way ANOVA test was used. Data were analysed using ANOVA, followed by Bonferroni’s correction (α = 0.05). Additionally, one- or two-way ANOVA with Tukey's multiple comparisons test was applied for comparisons between multiple groups. Statistical significance was determined using GraphPad Prism Software Version 5.9 (San Diego, CA, USA). P-values < 0.05 were deemed statistically significant.
Results
PAGln Inhibited Angiogenesis in the Hindlimb Ischemia Mouse Model and in Human Umbilical Vein Endothelial Cells (HUVECs)
To investigate the association between angiogenesis in vivo and PAGln concentration, we developed a hindlimb ischemia mouse model by femoral artery ligation. Laser Doppler imaging revealed that PAGln significantly inhibited blood flow to the ischemic hindlimb in a time-dependent manner. On day 7, a significant difference was noted in hindlimb perfusion between the two groups (control vs. PAGln: 46.78% vs. 29.50%, p < 0.05) (Fig. 1a and 1c). On day 14, the intergroup difference was most pronounced (control vs. PAGln, 69.80% vs. 42.97%, p < 0.05). Moreover, the immunofluorescence staining for HUVEC in vitro consistently demonstrated that the expression of CD31 and SMA, the validated biomarkers of angiogenesis, was significantly decreased after PAGln treatment (Fig. 1b and 1 d).Fig. 1PAGln inhibits angiogenesis in vitro and in vivo a. The ratio of blood perfusion was investigated by laser Doppler perfusion imaging analysis in the ischemic limbs of normal mice injected with DMSO or PAGln at 0, 1, 7, and 14 days post-operation. Representative pictures are shown. n = 6 per group, per time point.b. Immunofluorescence staining results, n = 6. c. The blood perfusion index was significant higher in DMSO group than PAGln group. Left hindlimb (HLI surgery) perfusion was normalized to right hindlimb perfusion for each mouse. n = 6 per group per time point. d. quantitative analysis of immunofluorescence(n = 6). e. HUVEC were treated with different concentrations of PAGln in a humidified incubator at 37 °C with 5% CO2 for 48 h. Cell viability was determined using the EDU assay. f. Cell viability was determined using EdU/DAPI. g,h. HUVEC were treated with different concentrations of PAGln for 24 h and the cell migration capacity was determined using a transwell assay. i,j.HUVEC were treated with various concentrations of PAGln or PBS for 6 h. Angiogenesis was assessed using a tube formation assay. k. HUVEC were treated with different concentrations of PAGln, and cell viability was determined using a CCK8 assay. Results are expressed as mean ± SEM. Each experiment was independently repeated at least three times. (*p < 0.05; **p < 0.01; ***p < 0.001, ****p < 0.0001)
PAGln Inhibited Cell Proliferation, Migration, and Tube Formation of HUVEC in Vitro
Endothelial function and angiogenesis capability were evaluated using 5-ethynyl-2′-deoxyuridine (EdU), CCK-8, and Transwell tube formation assays. EdU and CCK8 assays showed that PAGln markedly suppressed the proliferation of HUVEC cells (Fig. 1e, 1f, and 1k). Meanwhile, PAGln significantly decreased the migration ability of HUVEC in the Transwell assay (Fig. 1g and 1 h). In the tube formation assay, PAGln showed worse performance with shorter tube lengths and branch points compared with the control (Fig. 1i and 1j). In all the assays, the inhibitory effect increased gradually with rising concentrations of PAGIn from 0 to 500 μM. At the concentration of 500 μM, PAGln showed a 27.4% decrease in HUVEC proliferation, 72.6% decrease in migration, 76.7% decrease in branch points, and 55.4% decrease in tube length (all p < 0.01, compared with the control group).
Beta Receptor-Blocker Alleviated the Adverse Effects of PAGln on Endothelial Function and Angiogenesis in Vivo and in Vitro
HUVEC were treated with 500 μM PAGln and/or 10 μM zenidolol, a selective β_2_-receptor inhibitor. HUVEC cotreated with zenidolol showed significant improvement in cell proliferation capacity, migration capacity, and tube formation than those receiving PAGln alone. Specifically, the CCK8 and EdU assay consistently revealed that zenidolol increased cell proliferation compared with PAGln at 24 h (Fig. 2a, 2b, and 2 g). Moreover, the transwell invasion assay showed that the β-blocker zenidolol alleviated the adverse effect of PAGln on the inhibition of HUVEC migration capacity (Fig. 2c and 2 d). The tube formation assay demonstrated a pronounced improvement in endothelial progenitor cell meshes, nodes, and branches in the zenidolol-treated group (Fig. 2e and 2f).Fig. 2. Beta-blockers can alleviate PAGln effects in vitro and in vivo a,b. Beta-blockers improved the proliferation of HUVECs, as demonstrated by the EdU assays at 48 h. c,d. The migration of HUVECs was enhanced as determined by the transwell assay at 24 h, and the difference was statistically significant (p < 0.05). e,f. The angiogenesis ability was determined by a tube formation assay. g. Beta-blockers alleviated the proliferation inhibition of HUVECs, as demonstrated by the Cell Counting Kit-8 (CCK-8). h. The ratio of blood perfusion was investigated by laser Doppler perfusion imaging analysis in the ischemic limbs of normal mice injected with PBS, PAGln or beta-blocker at 0, 14, 28 days post-operation,n = 6 per group, per time point. i. At 28 days after lower limb ischemia surgery, the PAGln group showed significantly decreased blood flow recovery compared to the control group. However, after the addition of β-blockers, the inhibitory effect was alleviated, compared to the PAGln group(n = 6). j,k. Immunofluorescence staining results and quantitative analysis at 28d. There are differences between the control group and PAGln group, as well as between the PAGln group and the PAGln + β-blocker groups, with P < 0.05. Results are expressed as mean ± SEM. Each experiment was independently repeated at least three times. Scar bar: 100 μm. (*p < 0.05; **p < 0.01; ***p < 0.001, ****p < 0.0001)
Compared with PAGln alone, the additional zenidolol treatment enhanced post-ischemic angiogenesis and blood perfusion, as indicated by an increase in mean ratios of blood perfusion by 82.7% in vivo (PAGln + zenidolol vs. PAGln: 17.44% vs. 9.547%, p < 0.05) (Fig. 2h and 2i). Immunofluorescence staining further confirmed that zenidolol also significantly increased the expression levels of CD31 and SMA of HUVEC in vitro compared with PAGln (Fig. 2j and 2k).
Identification of PAGln-Associated Differentially Expressed Genes (DEGs) and Functional Annotation
We analysed the gene expression profiles of HUVEC treated with PAGln or phosphate-buffered saline (PBS) for 48 h. The 17 genes most correlated with PAGln were shown, most of which were highly related to the cell cycle, including MYBL2 and EXO1 (Fig. 3a). Gene ontology analysis revealed that differences were enriched in homotypic cell–cell adhesion in biological processes (Fig. 3b). Although we identified 28 DEGs with a q-value < 0.05 and |log2fc|> 1, it was still difficult to explain the correlation between DEGs and the phenotype described above.Fig. 3. The bioinformatics analysis results revealed differences in gene expression between the control group and the PAGln group a. RNA heatmap showing significantly altered RNA in response to PAGln treatment.b. Gene Ontology (GO) analysis enriched the functions of differentially expressed genes, dividing cell functions into three categories: biological process, cellular component, and molecular function. To visualize this, we have selected the top ten enriched pathways and represented them graphically. c. In the GSEA analysis, we observed a significant enrichment of gene sets related to glycolysis inhibition in the PAGln-treated samples compared to the control group. d. Differential expression of glycolysis related genes between the control group and the PAGln treatment group
GSEA revealed that PAGln had a suppressive role in glycolysis (NES = −1.93, p < 0.01, FDR: 0.012; Fig. 3c), as indicated by a decrease in the expression of key enzymes involved in glycolysis, including hexokinase (HK2), 6-phosphofructokinase-1 (PFKM), pyruvate kinase (PKM), and LDHA (Fig. 3d).
PAGln Inhibited Glycolysis and Regulated the Expression of LDHA
PAGln significantly inhibited the rate of glycolysis, as evidenced by the reduced glycoPER under basal glycolysis and reduced glycoPER during compensatory glycolysis (Fig. 4a). The key rate-limiting enzymes in glycolysis include HK2, PFKM, PKM, and LDHA. In the heat map analysis (Fig. 3d), the RNA expression levels of these key enzymes were downregulated after PAGln treatment. Then, western blot and PCR analyses were conducted; RNA and protein levels of these key enzymes were consistently suppressed in response to PAGln treatment. Notably, among all the downregulated key glycolytic enzymes, HK2, PKM, PFKM, and LDHA were significantly downregulated at the RNA and protein expression level after PAGln treatment. However, only the degree of LDHA downregulation showed statistical significance (Fig. 4b, 4c, and 4 d). Full-length blots are available in Supplementary Fig. S3. Lactate content analysis also confirmed that treatment with PAGln significantly reduced extracellular lactate levels (Fig. 4e).Fig. 4PAGln inhibited glycolysis. a. PAGln suppressed the glycolysis rate The glycoPER was measured in the presence of the mitochondrial complex III inhibitor antimycin A (Rote/AA) and the glycolytic inhibitor 2-DG at indicated time points. The bar graph shows the quantified data. b. Quantitative analysis of the RNA level. c,d. The protein level was determined by western blot. e. Lactate content test confirmed that treatment with PAGln significantly reduced extracellular lactate level. Results are expressed as mean ± SEM. Each experiment was independently repeated at least three times. (*p < 0.05; **p < 0.01; ***p < 0.001, ****p < 0.0001). GlycoPER: Glycolytic Proton Efflux Rate; PER: Proton Efflux Rate
Glycolysis serves as the primary energy source for endothelial cell angiogenesis, with VEGF and FGF being key regulators of this process. However, quantitative experiments showed that PAGln treatment did not alter the protein or RNA expression of VEGF and FGF (Fig S2).
Beta-Blockers Alleviated the Inhibitive Effect of PAGln on Glycolysis
Β_2_-blockers mitigated the glycolytic inhibition caused by PAGln, as was evident from the enhanced GlycoPER underbasal glycolysis and compensatory glycolysis in the PAGln + zenidolol group compared with the PAGln group (Fig. 5a). Simultaneously, the expression of key enzymes (HK2, PKM, PFKM, and LDHA) increased both at the RNA and protein levels. Notably, at the RNA level, the expression of key enzymes in the PAGln + zenidolol group was significantly increased, compared with the PAGln group (Fig. 5b). However, at the protein level, only the changes in LDHA were statistically significant (Fig. 5c and 5 d). Full-length blots are available in Supplementary Fig. S3. Furthermore, the reduction in extracellular lactate content caused by PAGln was also reversed in the presence of zenidolol (Fig. 5e).Fig. 5. Beta-blockers can alleviate the inhibition of glycolysis by PAGln a. Beta-blockers improved glycolysis. The bar graph shows the quantified data.** b**. Quantitative analysis of the RNA level. c,d. The protein level was determined by western blot. e. Lactate content test confirmed that the reduction in extracellular lactate content caused by PAGln was also reversed in the presence of zenidolol. Results are expressed as mean ± SEM. Each experiment was independently repeated at least three times. (*p < 0.05; **p < 0.01; ***p < 0.001, ****p < 0.0001)
Overexpression of LDHA Improved the Angiogenesis Inhibition Caused by PAGln
To investigate the role of LDHA in PAGln-induced angiogenesis inhibition, HUVEC were transduced with a lentiviral vector carrying LDHA DNA for 72 h. The findings showed that LDHA-Flag was expressed in HUVEC transduced with lentivirus LDHA (Fig S1a). The PAGln + LDHA-lentivirus group consistently showed a marked increase in cell proliferation compared with the PAGln group (Fig. 6a, 6 d, and 6e). In addition, the addition of lentivirus LDHA increased cell migration and invasion (Fig. 6b and 6f). Furthermore, LDHA overexpression improved angiogenesis inhibition caused by PAGln by increasing the number of meshes, nodes, and branches (Fig. 6c, 6 g, and 6 h).Fig. 6. Overexpression of LDHA improves angiogenesis inhibition caused by PAGln a,d. overexpression of LDHA improved the proliferation of HUVECs, as demonstrated by the EdU assays at 48 h. b,f. the migration of HUVECs was enhanced as determined by the transwell assay at 24 h. c,g,h. The angiogenesis ability was determined by a tube formation assay and was quantified by the numbers of meshes, nodes and branches. e. Overexpression of LDHA alleviated the proliferation inhibition of HUVECs, as demonstrated by the Cell Counting Kit-8 (CCK-8). i, Blood perfusion was assessed using laser Doppler perfusion imaging in the ischemic limbs of mice injected with lentivirus, followed by PBS or PAGln treatment. n = 6 per mouse strain per time point. Representative pictures are shown. j. PAGln + LDHA-lentivirus group showed a significant increase in the mean blood perfusion ratio at 28 d compared to PAGln group. k,l. Immunofluorescence staining and quantitative analysis results (n = 6). Results are expressed as mean ± SEM. Each experiment was independently repeated at least three times. Scale bar: 100 μm. (*p < 0.05; **p < 0.01; ***p < 0.001, ****p < 0.0001)
In vivo experiments showed that LDHA overexpression enhanced post-ischemic angiogenesis and blood perfusion, as evidenced by a significant increase in the mean blood perfusion ratio at day 28 (PAGln vs. PAGln + LDHA-lentivirus: 9.88% vs. 28.86%, p < 0.05) (Fig. 6i and 6j). Immunofluorescence staining further confirmed that LDHA overexpression significantly upregulated the expression of CD31 and SMA, established biomarkers of angiogenesis (Fig. 6k and 6 l).
Discussion
In this study, we found that PAGln inhibited endothelial proliferation, migration, and angiogenesis under conditions of ischemia in vivo and in vitro. Mechanically, PAGln mainly suppressed the activity of β receptor-LDHA enzyme, subsequently inhibiting the process of glycolysis. The antiangiogenic effect induced by PAGln could be reversed by LDHA overexpression. Moreover, the β receptor blocker zenidolol significantly weakened the unfavourable effect of PAGln on inhibiting angiogenesis. Thus, these findings demonstrated that PAGln suppressed angiogenesis following ischemia by modulating the function of β receptors and the expression of their downstream protein LDHA.
Under ischemic conditions, compensatory growth of blood vessels is an important response to tissue ischemia injury. The consequence following this compensation is angiogenesis or neogenesis, which is entirely regulated by proangiogenic and antiangiogenic factors [28]. Well-known angiogenic stimulators include VEGF and FGF, whereas angiogenic inhibitors include pixel epithelial-derived factor, kallistatin, and thrombospondin-1 [14, 28]. Previous studies have found that metabolites from the gut microbiota also participate in vascular regulation, such as trimethylamine N-oxide, which promoted the migration and angiogenesis of vascular endothelial cells [29]. The role of microbiome-derived secondary metabolites in regulating tumour angiogenesis has also been widely confirmed. PAGln, as one of the intestinal metabolites with the most significant difference between diabetic and non-diabetic patients, is associated with MACE and does not significantly correlate with glycemia. The effect of PAGln on the growth of metastatic lung tumour cells has been confirmed [30], but its impact on endothelial functions, including angiogenesis, remains unclear. The present research confirmed that PAGln was able to inhibit endothelial cell proliferation, migration, and angiogenesis, leading to impaired angiogenesis capacity. Further, after PAGln treatment, the blood flow recovery ability of the lower limb ischemia model decreased, and the expression of CD31 and SMA in blood vessels decreased. Overall, PAGln exerted antiangiogenic effects by impairing endothelial cell function.
Previous studies have confirmed that PAGln interacts with GPCRs, specifically the α- and β-adrenergic receptors [17]. However, the role of the α-adrenergic system in angiogenesis remains controversial. In most cases, the α1-adrenergic receptor exhibits antiangiogenic effects, and treatment with α-adrenergic receptor blockers facilitates the induction of capillary growth in human skeletal muscles [31] and angiogenesis in ischemic hindlimbs [32]. Conversely, some studies have suggested that overexpression of α1A-adrenergic receptors stimulates endothelial angiogenesis [13]. When discussing beta-adrenergic receptors, previous studies have confirmed the involvement of the β-adrenergic system in endothelial-dependent angiogenesis. Specifically, β2-AR is a key mediator of endothelial growth in ischemia-induced angiogenic response, whereas β1 and β3 receptors are associated with VEGF production in adipose tissue [33]. β2-AR knockout transgenic mice exhibited impaired angiogenesis, which was restored by gene therapy with adenovirus-β2-AR [33]. Zenidolol treatment impedes HUVEC angiogenesis [18]. However, this study found that the proliferative, migratory, and angiogenesis-inhibitory effects of PAGln on blood vessels were reversed by β2 receptor blockers. On the basis of PAGln treatment, the β2 receptor blocker group exhibited better recovery of lower limb blood flow and a higher ratio of CD31 and SMA expression compared with the PAGIn-only group. This apparent discrepancy highlights the context-dependent nature of adrenergic signalling. Under normal physiological conditions, basal β₂-AR activation supports endothelial survival. However, we hypothesise that elevated PAGln levels induce pathological over-activation or aberrant downstream signalling of the β₂-adrenergic pathway, which may impair endothelial metabolic flexibility. In the high-PAGln microenvironment, β-blockers do not inhibit essential angiogenic signals but rather normalise aberrant receptor activity, thereby restoring endothelial function. In conclusion, PAGln exerts vascular inhibitory effects via β₂-AR signalling.
When pro-angiogenesis factors prevail in vivo, glycolysis allows endothelial cells to increase energy supply and provides approximately 80% of the energy for endothelial cell proliferation, migration, and sprouting. The high levels of glycolysis in ECs are maintained through control of several rate-limiting steps such as HK2, PFKM and LDHA [34]. Previous studies have found that these key enzymes are involved in angiogenesis and endothelial function maintenance, especially LDHA [35, 36]. LDHA catalyses the conversion of pyruvate to lactate and constructs an acidic microenvironment to maintain endothelial growth, metastasis, and pathological angiogenesis [37, 38]. In this study, GSEA and glycolytic flux assays demonstrated that PAGln treatment inhibited glycolysis. Heat map and quantification analyses confirmed that this effect was primarily a result of reduced LDHA expression, which consequently impacted glycolytic activity. In endothelial cells, LDHA is essential for enhancing VEGF production, maintaining the phenotype of tip cells, and facilitating the conversion of non-tip cells into tip cells. Inhibition of LDHA reduces sprout numbers, thus affecting angiogenesis [39]. This study used an adenovirus carrying LDHA to transfect endothelial cells and mice, and found that, on the basis of PAGln treatment, additional LDHA lentivirus increased GlycoPER as well as endothelial cell proliferation, migration, and angiogenic capacity. Moreover, decreased limb blood flow recovery and CD31 and SMA expression were significantly improved compared with those in the PAGln group. A previous study found that the β2-AR signaling increases cyclic adenosine monophosphate production, which in turn induces stimulation of glycolysis [40]. However, some literature has also found that β2-AR signalling degrades glycolysis and increases oxidative phosphorylation and fatty acid oxidation in myeloid-derived suppressor cells [38]. In this study, after using β2 receptor blockers, the glycolysis rate was restored, the expression of key enzymes was upregulated, and extracellular lactate content was increased compared with PAGIn treatment alone. Mechanistically, our findings highlight the critical role of metabolic reprogramming in maintaining endothelial health. PAGln act as a metabolic disruptor, modulating LDHA expression via the β₂-adrenergic pathway and thereby impairing the metabolic machinery necessary for vessel sprouting. By demonstrating that β-blockers can restore this metabolic flux, we establish a novel mechanistic link between gut microbiota-derived metabolites and vascular metabolic plasticity. These results extend beyond traditional cardiovascular risk factors, providing insight into how targeted metabolic intervention may serve as a precise strategy to rescue endothelial funct Our findings suggest that β-blockers ion. Additionally, research has demonstrated that β2-AR can activate the PKA/CREB1 pathway, with phosphorylated CREB1 influencing the transcription of glycolytic key enzymes [41]. Further experiments are needed to confirm whether the β2AR/PKA/CREB1 pathway mediates the effect of PAGln on LDHA. Overall, PAGln acts on β-AR and further exerts vascular inhibitory effects by affecting LDHA.
In clinical practice, angiogenesis is involved in coronary collateral circulation, diabetic lower limb artery disease, and foot ulcer wound repair. Patients with diabetes have an increased risk of poor coronary collateral circulation, lower limb artery occlusion, and decreased ischemic injury healing capacity. It is currently assumed that boththe generation of high glucose-induced ROS and the secretion of inflammatory factors produced by high glucose or advanced glycosylation end products impair angiogenesis in diabetic patients. However, despite intensive glycaemic control, serum VEGF levels in patients with diabetes still exhibit a significant decrease [14]. Therefore, in addition to blood glucose control, patients with diabetes should pay attention to other independent risk factors, for example, PAGln. Our findings suggest that β-blockers may counteract PAGln-induced impairments in angiogenesis. However, the use of beta-blockers and their angiogenic effects in population studies remains controversial. Previous research has found that for patients with severe lower limb ischemia, the use of β2 receptor blockers may lead to predominant peripheral alpha-1 effect, which can cause vasoconstriction and aggravate limb ischemia. However, no significant detrimental effects were observed in patients with intermittent claudication. Although other studies have found that the use of β2 receptor blockers has no significant effect on the perfusion of the calf muscles [42]. Another study found that first- and second-generation beta-blockers could reduce coronary collateral blood flow [42]. This study found that the use of β2 receptor blockers can reverse the action of PAGln, ultimately promoting endothelial function recovery and angiogenesis. Our data provide strong evidence that the PAGln–adrenergic axis plays a critical role in angiogenesis and may serve as a promising therapeutic target. These findings highlight potential avenues for targeted interventions aimed at modulating this pathway. Future clinical trials will be essential to determine whether selective modulation of this axis can enhance angiogenesis in patients with elevated PAGln while minimising potential systemic hemodynamic side effects.
We acknowledge that this study has limitations. Angiogenesis is a long-term process, and cell and mouse assays primarily simulate short-term changes. Therefore, the use of high concentrations of PAGln over a short duration in this experiment may not fully reflect the long-term pathophysiological effects observed in humans.
In conclusion, PAGln inhibits key glycolytic enzymes, especially LDHA, through beta receptors, thereby inhibiting endothelial cell proliferation, migration, and angiogenesis. Further human trials are required to validate these findings.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 9392 KB)