All animal experiments adhered to the NIH Guidelines for the Care and Use of Laboratory Animals and received ethical approval from the Jiangnan University Institutional Animal Care and Use Committee (IACUC; Approval No.: JN.NO20220415C0040930[116]). Mice were housed in the Experimental Animal Center of Wuxi School of Medicine under standardized conditions (26°C, 12-h light/dark cycle, ad libitum access to food and water). Only male mice were used in this study. TRPC1-flox/flox, TRPC1-KI/flox, and EC-Cre mice (C57BL/6J background) were acquired from the Jiangsu Institute of Medical Innovation. Endothelial-specific TRPC1 knockout (TRPC1_EC ^−/−) and knockin (TRPC1_EC ^KI/KI) models were generated by crossing TRPC1-flox/flox or TRPC1-KI/flox mice with EC-Cre mice, using littermate TRPC1^fl/fl mice as controls. At 6°weeks of age, all mice received intraperitoneal tamoxifen injections (20 mg/kg; Macklin Biochemical, China) daily for 7 consecutive days to induce tissue-specific gene deletion/overexpression, followed by a 1-week recovery period. To ensure experimental consistency, male mice were used in all experiments, and all groups received Tamoxifen administration (Krüger et al., 2020). Obesity was induced in all mice via 12-week high-fat diet (HFD) feeding (45% kcal from fat; Nantong Trophic, China). At study termination, euthanasia was performed by carbon dioxide asphyxiation followed by cervical dislocation.

Genomic DNA was extracted from mouse tail biopsies using a commercial DNA isolation kit (Yeasen Biotechnology, China). The primer sequences, as listed in Supplementary Table S1, were utilized for the PCR amplification of genomic DNA. The PCR amplification protocol is detailed in Supplementary Tables S2–S4. The PCR products were resolved through agarose gel electrophoresis and visualized using a Tanon-5200 Multi Gel Imaging System (China).

Thoracic aortic frozen sections were fixed in 4% paraformaldehyde (Beyotime, China), rinsed with phosphate-buffered saline (PBS), permeabilized with 0.1% Triton X-100, and subsequently blocked with 5% bovine serum albumin (BSA). The sections were incubated overnight at 4°C with primary antibodies: anti-TRPC1 (1:200, Santa Cruz Biotechnology) and anti-CD31 (1:200, Santa Cruz Biotechnology). Secondary labeling was conducted using Alexa Fluor 568-conjugated goat anti-rabbit (1:200, Invitrogen) and Alexa Fluor 647-conjugated goat anti-mouse (1:200, Invitrogen) antibodies. For nuclear counterstaining, DAPI (1:1,000, Beyotime) was employed. Immunofluorescence imaging was performed using a Zeiss LSM 880 confocal microscope (Germany).

Adipose tissue distribution was analyzed using the IVIS SPECTRUM in vivo micro-CT system (PerkinElmer, United States). Image analysis effectively differentiated between adipose tissue depots, with visceral adipose tissue represented in yellow and subcutaneous adipose tissue depicted in green. Volumetric quantification of the designated regions was subsequently performed using proprietary analysis software.

Respiratory and metabolic parameters were continuously monitored using the Comprehensive Laboratory Animal Monitoring System (CLAMS; Columbus Instruments, United States) at the Jiangnan University Experimental Animal Center. Following a 2-day acclimation period, metabolic phenotyping was conducted over three consecutive days. The recorded parameters included oxygen consumption (VO₂), carbon dioxide production (VCO₂), energy expenditure, respiratory exchange ratio (RER), water and food intake, and locomotor activity.

Glucose tolerance tests (GTT) were conducted after a 12-h fasting period, during which intraperitoneal glucose was administered at a dosage of 1.5 g/kg (Solarbio, China). For insulin tolerance tests (ITT), mice were subjected to a 4-h fasting period prior to receiving an intraperitoneal insulin injection at a dosage of 0.75 U/kg (Beyotime, China). Blood glucose levels were monitored at specified time points using a glucometer (Yuwell Medical, China), with blood samples collected from the tail vein.

Serum levels of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were measured using commercial kits from Nanjing Jiancheng Bioengineering Institute (China), strictly adhering to the manufacturer’s protocols. Additionally, serum metabolomic profiling was conducted by BGI Genomics (China).

Fresh tissue specimens were fixed in 4% paraformaldehyde for 24 h, rinsed with running water for 1 h, and subsequently immersed in PBS for 30 min. The tissues underwent gradient ethanol dehydration (75% ethanol for 4 h, 85% ethanol for 2 h, 90% ethanol for 2 h, and 95% ethanol for 1 h, followed by two changes of absolute ethanol for 30 min each), xylene clearing (three cycles of 20 min each), and paraffin infiltration (three cycles of 1 h each). Paraffin-embedded tissues were sectioned to a thickness of 4 μm and stained using H&E kits (Solarbio, China). Histological images were acquired using the Pannoramic MiDi slide scanner system (3DHISTECH, Hungary). Morphometric analysis of adipocyte size distribution in adipose tissue was conducted using ImageJ software. Adipocytes were stratified into three categories based on equivalent diameter (<50 μm, 50–100 μm, and >100 μm) through automated segmentation of histological sections. Size distribution profiles were generated by quantifying the proportional representation of each cellular cohort (Stenkula and Erlanson-Albertsson, 2018; Wang S. et al., 2020).

Total RNA was isolated from tissues using an RNA extraction kit (Yeasen, China). Complementary DNA (cDNA) synthesis was performed with the QuantiTect Reverse Transcription Kit (Yeasen, China). Quantitative PCR (qPCR) assays were conducted on a LightCycler 480 system (Roche, Switzerland) utilizing Hieff UNICON qPCR SYBR Green Master Mix (Yeasen, China). The primer sequences are detailed in Supplementary Table S5. All reactions were conducted in technical triplicate, with TATA-binding protein (TBP) serving as the reference gene (Ye et al., 2012). Relative gene expression was quantified using the 2^−ΔΔCt method.

Total protein was extracted using RIPA Lysis Buffer (Beyotime Biotechnology, China) supplemented with phenylmethylsulfonyl fluoride (PMSF). Protein samples were resolved via 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and subsequently transferred onto polyvinylidene fluoride (PVDF) membranes (Beyotime Biotechnology, China). Membranes were blocked with 5% bovine serum albumin (BSA) for 2 h at room temperature, followed by overnight incubation at 4°C with primary antibodies: anti-UCP1 (1:1,000, Cell Signaling Technology, CST), anti-PGC1α (1:200, Santa Cruz Biotechnology), and anti-β-tubulin (1:5000, CST). After washing to remove unbound primary antibodies, membranes were incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies (Beyotime Biotechnology, China) for 1 h at room temperature. Protein bands were visualized and quantified using ImageJ software (National Institutes of Health, NIH, USA).

Experimental data are presented as mean ± standard error of the mean (SEM), with n ≥ 3 biological replicates. Statistical analyses were performed using GraphPad Prism 8.0 software (GraphPad Software, United States). Time-course response curves were analyzed using repeated measures two-way analysis of variance (ANOVA), followed by Bonferroni post hoc tests. Comparisons between two groups were conducted using unpaired two-tailed Student’s t-tests. For comparisons involving three or more groups, one-way ANOVA with Tukey’s multiple comparisons test was applied. Statistical significance was defined as p < 0.05.

Building on the critical role of TRPC1 in cardiovascular homeostasis and the pathogenesis of obesity, this study investigates its functional mechanisms in endothelial metabolic regulation. Our previous research has demonstrated that TRPC1 protein expression in endothelial cells is significantly downregulated under obese conditions, and that endothelial-specific TRPC1 deficiency results in impaired vascular contractility and dysregulated blood pressure regulation (Zhu et al., 2025). To elucidate the metabolic regulatory functions of endothelial TRPC1, we generated a tamoxifen-inducible, endothelial cell-specific TRPC1 knockout mouse model (TRPC1_EC ^−/−, Figure 1A). Genomic PCR analysis confirmed the successful Cre-loxP-mediated recombination specifically in the endothelial cells of TRPC1_EC ^−/− mice, as evidenced by the characteristic 600 bp amplification product (Figure 1B). Immunofluorescence staining analysis of thoracic aorta sections further demonstrated the complete ablation of TRPC1 signaling in the endothelial layer of TRPC1_EC ^−/− mice (Figure 1C), thereby validating the efficiency of the endothelial-specific knockout.

To investigate the metabolic regulatory functions of endothelial TRPC1 under both physiological and obese conditions, we employed a high-fat diet (HFD)-induced obesity model. Eight-week-old TRPC1^fl/fl and TRPC1_EC ^−/− mice were subjected to a 12-week isocaloric HFD intervention (Figure 1D). Longitudinal monitoring revealed no significant differences in weight gain trajectory or final body weight at 20 weeks of age between the two groups (Figure 1E; Supplementary Figure S1A). A detailed assessment of adipose tissue distribution through micro-computed tomography analysis demonstrated comparable pathological expansion of both visceral and subcutaneous adipose tissue volumes following HFD feeding, with no significant differences observed between genotypes (Figures 1F,G).

To evaluate the impact of endothelial TRPC1 deficiency on basal metabolic activity, we conducted comprehensive respiratory metabolic monitoring of experimental animals. Under basal metabolic conditions, CTL-TRPC1_EC ^−/− mice exhibited a decreasing trend in the RER compared to CTL-TRPC1^fl/fl controls; however, this difference did not reach statistical significance (Figure 1H). No intergroup differences were observed in parameters such as food intake, locomotor activity, or heat production (Supplementary Figures S1B–I). Under obese conditions, DIO-TRPC1_EC ^−/− mice showed reduced heat production compared to their DIO-TRPC1^fl/fl counterparts, but this effect also failed to achieve statistical significance (Figure 1I). Other metabolic parameters, including RER, food intake, and physical activity, remained stable between the obese genotypes (Supplementary Figures S1J–Q). Collectively, these findings indicate that endothelial TRPC1 deficiency does not alter the development of HFD-induced obesity; however, it may contribute to metabolic regulation through non-significantly reduced energy expenditure.

To further elucidate the role of endothelial TRPC1 deficiency in the pathogenesis of obesity, we systematically evaluated the glucose and lipid metabolic profiles in TRPC1_EC ^−/− and TRPC1^fl/fl mice under both basal and obese conditions. Intraperitoneal glucose tolerance tests revealed that CTL-TRPC1_EC ^−/− mice exhibited significantly impaired glucose clearance compared to CTL-TRPC1^fl/fl controls under basal conditions. However, insulin tolerance tests showed no genotype-specific differences (Figures 2A,B). In contrast, obese DIO-TRPC1_EC ^−/− mice demonstrated more severe glucose intolerance and insulin resistance compared to their DIO-TRPC1^fl/fl counterparts (Figures 2A,B). Lipid metabolic analysis indicated that HFD-induced dyslipidemia was present in TRPC1^fl/fl mice, characterized by elevated serum total TC, LDL-C, and TG, alongside a concurrent reduction in HDL-C (Figures 2C–F). Notably, endothelial TRPC1 deficiency exacerbated these lipid abnormalities under obese conditions: DIO-TRPC1_EC ^−/− mice displayed significantly increased levels of TC, LDL-C, and TG, along with further reductions in HDL-C compared to DIO-TRPC1^fl/fl mice (Figures 2C–F), indicating exacerbated dyslipidemia. In the context of obesity, insulin resistance and dyslipidemia frequently arise from impaired adipose tissue function (Choi et al., 2021). Our histopathological analysis of adipose tissues demonstrated that endothelial TRPC1 deficiency exacerbates high-fat diet-induced epididymal white adipose tissue (eWAT) hypertrophy, resulting in an increased proportion of large adipocytes and a concomitant reduction in small adipocytes within adipose depots, while no significant differences were observed in inguinal white adipose tissue (iWAT) or brown adipose tissue (BAT) (Figures 2G,H; Supplementary Figures S2A,B). These findings suggest that endothelial TRPC1 deficiency drives adipocyte hypertrophy in eWAT, leads to aberrant lipid deposition in serum, disrupts glucose and lipid metabolic homeostasis, and ultimately contributes to systemic insulin resistance.

Adipose tissue plays a pivotal role in regulating energy homeostasis and metabolic balance. However, an imbalance in its inflammatory microenvironment contributes to metabolic disorders, including insulin resistance (Kunz et al., 2021). Through a systematic molecular characterization of distinct adipose depots in endothelial-specific TRPC1 knockout mice, this study elucidates the critical role of endothelial TRPC1 in modulating adipose tissue inflammation and metabolic function. Notably, we observed a significant upregulation of tissue inhibitor of metalloproteinases 1 (TIMP1) in eWAT and mesenteric perivascular adipose tissue (mPVAT), while brown adipose tissue (BAT) and aortic perivascular adipose tissue (aPVAT) exhibited aberrant elevations of interleukin-10 (IL-10) (Figures 3A–D). Chemokine profiling revealed marked increases in serum amyloid A3 (SAA3) levels in mPVAT, BAT, and aPVAT, accompanied by significantly enhanced expression of CC-chemokine ligand 3 (CCL3) and CXC-chemokine ligand 5 (CXCL5) in eWAT and aPVAT. Of particular interest, the concurrent upregulation of IL-1β in BAT and mPVAT suggests differential inflammatory regulatory mechanisms across adipose depots (Figures 3E–H).

At the metabolic functional level, DIO-TRPC1_EC ^−/− mice exhibit systemic thermogenic impairment. The transcriptional and protein expression levels of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) and uncoupling protein 1 (UCP1)—key regulators of thermogenesis—are significantly reduced across all examined adipose depots (Figures 3I–N). PGC1α, a master regulator of mitochondrial biogenesis and oxidative metabolism, directly influences the thermogenic capacity of brown adipose tissue, while UCP1 dysfunction, as the mitochondrial inner membrane thermogenic effector, exacerbates energy metabolic defects (Shen et al., 2021; Rahbani et al., 2024). Notably, endothelial TRPC1 deficiency recapitulates these thermogenic defects and pro-inflammatory gene expression patterns under basal conditions (Supplementary Figure S3), although with greater severity in obese states. Mechanistically, TRPC1-deficient endothelial cells promote chemokine-mediated immune cell infiltration and local inflammatory responses, which in turn suppress adipocyte thermogenic function through paracrine inflammatory signaling. This pathological cascade ultimately contributes to metabolic phenotypes characterized by glucose intolerance and systemic insulin resistance.

Building upon the dyslipidemia phenotype observed in endothelial TRPC1 deficiency, we conducted untargeted serum metabolomic profiling across four experimental groups: CTL-TRPC1_EC ^−/−, CTL-TRPC1^fl/fl, DIO-TRPC1_EC ^−/−, and DIO-TRPC1^fl/fl. Principal Component (PC) analysis revealed distinct metabolic clustering patterns among all groups (Figures 4A,E,I). Under basal conditions, a comparison between CTL-TRPC1_EC ^−/− and CTL-TRPC1^fl/fl indicated significant upregulation of (S)-homostachydrine and gibberellin A12 (GA12), while 1-methylhistidine and (1S, 2R)-1, 2-dihydrodibenzo [b, d]thiophene-1, 2-diol were markedly downregulated (Figures 4B,C). Pathway enrichment analysis suggested that perturbations in histidine metabolism represent a key metabolic signature (Figure 4D), indicating that TRPC1 deficiency may impair basal metabolic functions by disrupting amino acid homeostasis.

In the context of obesity, metabolomic analysis of DIO-TRPC1^fl/fl versus CTL-TRPC1^fl/fl mice revealed 294 significantly altered metabolites (Figure 4F; Supplementary Figure S4), implicating dysregulation across 10 metabolic pathways, including amino acid biosynthesis (Figure 4G). Venn diagram intersection analysis identified a persistent elevation of GA12 in both CTL-TRPC1_EC ^−/− and DIO-TRPC1^fl/fl groups, coupled with a consistent depletion of 1-methylhistidine (Figure 4H). Notably, while the role of GA12 as a phytohormone in mammalian systems remains poorly understood, our study demonstrates its pathological accumulation in TRPC1-deficient mice. This abnormal elevation may drive systemic inflammation (MacMillan et al., 1997; Biagioni et al., 2021). Conversely, 1-methylhistidine—a critical biomarker of muscle protein turnover—showed marked serum reductions in TRPC1-deficient mice (Kochlik et al., 2018). This depletion, which parallels observations in the visceral adipose tissue of metabolic syndrome patients, suggests impaired amino acid sensing and disrupted muscle protein synthesis (Piro et al., 2020). These findings strongly support the potential of 1-methylhistidine as a novel prognostic biomarker for obesity-associated metabolic complications.

Further analysis of endothelial TRPC1-specific deficiency under obese conditions (DIO-TRPC1_EC ^−/− vs. DIO-TRPC1^fl/fl) identified five key downregulated metabolites, including N-acetylvaline, N-methyl-L-proline, indole-3-propionic acid, indole-3-acrylic acid, and beta-D-ethyl glucuronide (Figures 4J,K). Notably, N-acetylvaline exhibited a dual-phase downregulation (Figure 4L), suggesting that TRPC1 deficiency may further compromise metabolic performance through perturbations in amino acid biosynthesis (Holeček, 2020). Metabolic pathway network analysis (Figures 4D,G) revealed that the loss of TRPC1 synergistically suppresses amino acid biosynthesis and histidine metabolism, leading to the depletion of critical metabolites such as 1-methylhistidine and N-acetylvaline. This metabolic dysregulation exacerbates obesity-induced systemic metabolic dysfunction.

The aforementioned findings demonstrate that endothelial TRPC1 deficiency exacerbates obesity-induced metabolic dysfunction. However, it remains unclear whether endothelial TRPC1 overexpression can mitigate this progression. To address this question, we generated a tamoxifen-inducible, endothelial-specific TRPC1-overexpressing mouse model (TRPC1_EC ^KI/KI, Figure 5A), with successful EC-Cre recombination confirmed by genomic PCR analysis (Figure 5B). Immunostaining of thoracic aortas further validated TRPC1 protein overexpression in the endothelial cells of this model (Figure 5C). Evaluation of the metabolic protective effects of TRPC1 overexpression in HFD-induced obesity models revealed that TRPC1_EC ^KI/KI mice exhibited significant attenuation of weight gain following 12 weeks of HFD intervention (Figure 5D). Micro-CT reconstruction demonstrated marked reductions in both visceral and subcutaneous fat deposition compared to control groups (Figures 5E,F). Metabolic chamber monitoring data revealed elevated respiratory exchange ratios in obese TRPC1-overexpressing mice, suggesting improved efficiency in energy substrate utilization (Figure 5G), while basal metabolic parameters, including food intake, activity levels, and energy expenditure, remained unchanged (Supplementary Figure S5A–D). The TRPC1-overexpressing cohort demonstrated enhanced regulation of glucose homeostasis and insulin sensitivity (Figures 5H,I). Serum biochemical analysis revealed a significant improvement in lipid profiles, characterized by reduced pro-atherogenic lipid components and elevated protective lipoprotein levels (Figures 5J–M). Endothelial TRPC1 overexpression attenuates high-fat diet-induced epididymal white adipocyte hypertrophy, thereby decreasing the proportion of large adipocytes and increasing the proportion of small adipocytes within adipose tissue (Figure 5N), in parallel with upregulated expression of thermogenic proteins PGC1α and UCP1 (Figures 5O,P). Collectively, these findings indicate that endothelial TRPC1 overexpression ameliorates obesity-induced metabolic dysfunction.