Metabolic consequences of altered kidney glucose reabsorption under normoglycemic conditions.

Abstract

Objective

Kidney glucose reabsorption, primarily mediated by glucose transporter 2 (GLUT2), is essential for systemic glucose homeostasis. While GLUT2's role has been studied in diabetic conditions, its function in kidney proximal tubule cells (KPTCs) under normo-physiological conditions remains unclear. This study aimed to delineate the metabolic consequences of KPTC-specific GLUT2 deletion on renal and whole-body energy homeostasis.

Methods

We utilized a conditional mouse model with KPTC-specific deletion of GLUT2 to assess the impact of impaired renal glucose reabsorption on systemic metabolism. Comprehensive metabolic and behavioral phenotyping, tissue-specific glucose uptake assays, and multi-omics analyses were performed to evaluate changes in energy balance, organ-specific metabolism, and signaling pathways.

Results

Loss of KPTC-GLUT2 led to increased food intake, enhanced systemic carbohydrate oxidation, and elevated fat and muscle mass. These changes were accompanied by altered glucose utilization across metabolic organs and improvements in whole-body lipid profile. Mechanistically, the phenotype was linked to metabolic reprogramming in the kidney, characterized by increased reabsorption and bioavailability of taurine and creatine, overactivation of mTORC1 signaling, and elevated endocannabinoid tone.

Conclusions

KPTC-GLUT2 plays a previously unrecognized role in regulating renal and systemic energy metabolism. Its deletion induces a systemic energy-conserving phenotype driven by kidney-intrinsic changes, highlighting the kidney's contribution to whole-body metabolic homeostasis beyond glucose filtration.

Untitled section

Keywords: Kidney glucose reabsorption, KPTCs, Energy metabolism, GLUT2, Taurine, Creatine, Endocannabinoid system

Graphical abstract

Energy conserving phenotype - proposed mechanism in KPTC^GLUT2-/- mice. GLUT2 nullification inhibits glucose reabsorption by the kidney, resulting in glucose retention in the KPTCs and enhanced kidney energy metabolism. In turn, mTORC1 activation is enhanced in the KPTCs, accompanied by elevated levels of taurine, creatine, and AEA. These metabolic hubs enhanced kidney and systemic bioavailability results in a pronounced systemic energy-consuming/preservation phenotype. Figure created with BioRender.com. BCAA, branched-chain amino acids; DHAP, dihydroxyacetone phosphate; NATs, N-acyl taurines; NAEs, N-acylethanolamines; FAAH, fatty acid amid hydrolase; FFA, free fatty acid.

Highlights

•KPTC-GLUT2 deletion increases food intake and systemic carbohydrate oxidation.
•Targeted GLUT2 removal raises fat and muscle mass under normal conditions.
•KPTC-GLUT2 loss alters glucose uptake and improves lipid profile across organs.
•KPTC-GLUT2 deletion enhances taurine and creatine bioavailability.
•mTORC1 activation and ECS upregulation observed in GLUT2-deficient kidneys.

Article notes

Untitled section

Received 2025 Apr 16; Revised 2025 Jun 8; Accepted 2025 Jun 15; Collection date 2025 Aug.

Author notes

1.Introduction

Recent studies have challenged the traditional perspective of the kidney as primarily an excretory and homeostatic organ, highlighting its well-established roles in gluconeogenesis and erythropoiesis. Increasing evidence also underscores the kidney’s central role in regulating energy metabolism and inter-organ signaling. These regulatory functions have been primarily studied in the context of acute and chronic kidney pathologies, and have provided insights into the potential therapeutic targets for treating metabolic diseases. For example, targeted inhibition of the kidney sodium glucose cotransporter 2 (SGLT2i) has been shown to improve cardiovascular diseases outcome and protect against fatty liver disease through its ability to lower blood pressure and affecting metabolism, respectively [[1], [2], [3], [4]]. Furthermore, kidney erythropoietin synthesis has been found to regulate bone remodeling under diabetic conditions [5], while the renal UTX-PHGDH-serine axis has been shown to regulate metabolic homeostasis [6]. Despite these advances, the exploration of the kidney’s systemic metabolic effects is still in its early stages, providing further opportunities to uncover novel therapeutic targets for metabolic diseases.

Kidney proximal tubule cells (KPTCs) play a crucial role in metabolism and have significant systemic effects due to their ability to reabsorb extensive amounts of nutrients into the blood stream and perform gluconeogenesis. Despite their high capacity to produce and reabsorb glucose, KPTCs primarily utilize fatty acids (FAs) as their main energy source for their high energetic demands under physiological conditions [7,8]. However, under obese and diabetic conditions, KPTCs may shift their metabolic program towards glycolysis [[9], [10], [11]]. Typically, glucose is transported from the tubular lumen to the intercellular space of KPTCs through an active process mediated by SGLT2 located on the apical brush border membrane. The accumulated glucose is then passively transported along its concentration gradient via glucose transporter 2 (GLUT2) on the basolateral membrane, facilitating its release into the interstitial space and subsequent entry into circulation [12]. Recently, we demonstrated that specific nullification of the GLUT2 in KPTCs improved diabetic kidney disease [13], and restored kidney fatty acid oxidation (FAO) under diabetic conditions [12]. Furthermore, non-diabetic KPTC-GLUT2 null mice showed reduced SGLT2 expression and increased glycosuria [13]. Moreover, accumulating evidence has recently supported the regulatory role of GLUT2 in proximal tubule glucose and energy metabolism [[13], [14], [15], [16]], which may even extend to systemic effects [16]. Together, these findings highlight the critical role of KPTCs and GLUT2 in systemic energy metabolism.

Based on the results obtained from our previous studies and others, we here investigated the metabolic consequences of diminishing glucose reabsorption, at both the local and systemic levels, using KPTC-GLUT2 nullification. Our findings revealed that inhibiting glucose reabsorption in KPTC-GLUT2 KO mice under normo-glycemic conditions significantly altered whole-body glucose metabolism, increased carbohydrate oxidation (CHO), and improved systemic lipid profile. These effects were directly associated with metabolic reprogramming in the kidney, leading to elevated levels of renal and circulating taurine and creatine, both of which are crucial regulators of systemic health. Taken together, these findings offer novel insights into the therapeutic potential of targeting kidney/KPTC metabolism for the treatment of diabetes and obesity.

2.Methods

2.1.Animals

Our study examined male mice because male animals exhibited less variability in phenotype. The experimental protocol used in this study was approved by the Institutional Animal Care and Use Committee of the Hebrew University (AAALAC accreditation #1285) and the ethical approval number was MD-19-15784. Animal studies were conducted in accordance with the ARRIVE guidelines [17]. Mice were fed ad libitum with Teklad irradiated global 18% protein rodent diet (Cat# 2918). To generate mice lacking GLUT2 in KPTCs, we employed a cross-breeding strategy between mice containing two loxP sites flanking the open reading frame of the GLUT2 gene (GLUT2^fl/fl; as described in [18]) and the iL1-sglt2-Cre line [19]. Cre⁻ and Cre⁺ littermates were selected at three weeks of age based on their genotypes, where Cre⁻ or Cre⁺ refers to the presence or deletion of GLUT2, respectively. All animals were homozygous for flox. The mice were monitored weekly until they reached sixteen weeks of age, and a 24-h urine was collected using mouse metabolic cages (CCS2000 Chiller System, Hatteras Instruments, NC, USA) one day before euthanasia. Euthanasia was performed by cervical dislocation under anesthesia. Serum/plasma, kidney, liver and muscle were collected and snap-frozen for farther analysis.

2.2.Multi-parameter metabolic assessment

The metabolic profiles, as well as food and water intake of mice, were assessed using the Promethion High-Definition Behavioral Phenotyping System (Sable Instruments, Inc., Las Vegas, NV, USA). MetaScreen software version 2.2.18.0 was used for data acquisition and instrument control, and ExpeData version 1.8.4 was used to process the obtained raw data utilizing an analysis script that details all aspects of data transformation. The mice, which had free access to food and water, were subjected to a standard 12-h light/12-h dark cycle, which involved a 48-h acclimation period followed by 24-h of sampling. Respiratory gases were measured using the GA-3 gas analyzer (Sable Systems, Inc., Las Vegas, NV, USA) with a pull-mode, negative-pressure system. Airflow was measured and regulated by FR-8 (Sable Systems, Inc., Las Vegas, NV, USA) with a set flow rate of 2000 mL/min. Water vapor was continuously measured, and its dilution effect on O₂ and CO₂ was mathematically compensated. The respiratory exchange rate (RER) was calculated as the ratio between CO₂ produced (VCO₂) and O₂ consumed (VO₂) using Equation (1):

(1)

RQ = {VCO}_{2} / {VO}_{2}

Total energy expenditure (TEE) was calculated using VO₂ and RQ as shown in Equation (2):

(2)

TEE = {VO}_{2} \times (3.815 + 1.232 \times R Q)

Fat oxidation (FO) and carbohydrate oxidation (CHO) were calculated using VO₂ and VCO₂, based on Equations (3), (4), respectively:

(3)

FO = 1.69 \times {VO}_{2} - 1.69 \times {VCO}_{2}

(4)

CHO = 4.57 \times {VCO}_{2} - 3.23 \times {VO}_{2}

2.3.Pair-feeding experiment

To evaluate the contribution of increased food intake to the systemic metabolic changes observed in KPTC^GLUT2–/– mice, a pair-feeding experiment was conducted. Male KPTC^GLUT2–/– mice (16 weeks old) were housed in the Promethion High-Definition Behavioral Phenotyping System (Sable Instruments, Inc., Las Vegas, NV, USA) for four days to assess baseline metabolic and feeding parameters. Following this period, their food intake was restricted to match that of their WT littermates for an additional seven days. Food pellets were provided daily in the afternoon at a consistent hour, placed at the bottom of the cage. To minimize variability due to human presence in the animal facility, average daytime CHO, total activity (all meter), and wheel-running activity (wheel meter) were measured on two consecutive weekend days during both the baseline and pair-feeding periods. At the conclusion of the experiment, mice were euthanized via cervical dislocation under anesthesia. Serum samples were collected before and after the pair-feeding period for biochemical and LC-MS/MS analyses as described below.

2.4.SLC6A6 inhibition in mice

To evaluate the effect of SLC6A6 inhibition on elevated CHO and food intake in KPTC^GLUT2–/– mice, 16-week-old male KPTC^GLUT2–/– mice were housed in the Promethion High-Definition Behavioral Phenotyping System (Sable Instruments, Inc., Las Vegas, NV, USA) for 48 h to establish baseline metabolic parameters. Following this period, the mice received daily administration of 3% β-Alanine (Myprotein, UK) in their drinking water for an additional seven days. At the conclusion of the experiment, euthanasia was performed via cervical dislocation under anesthesia. Serum samples were collected before and after the β-Alanine treatment for biochemical and LC-MS/MS analyses as described below.

2.5.KPTCs-mTORC1 activation in mice

To evaluate the effect of mTORC1 activation on SLC6A6 expression, we analyzed the mRNA and protein expression levels of SLC6A6 in cortical kidney lysates of mice lacking the tuberous sclerosis complex (TSC) specifically in KPTCs (as described in [13]).

2.6.SGLT2 inhibition in mice

To evaluate SGLT2 inhibition effect on SLC6A6 expression, we reanalyzed our published metabolomics data in diabetic mice treated with Dapagliflozin [20]. In brief: two months old, C57Bl/6 male mice, were treated daily with Dapagliflozin (10 mg/kg/day; AstraZeneca, UK; Cat #S1548) in their drinking water, for one week. The mice were euthanized and kidneys were collected for metabolomics analysis.

2.7.Biochemistry

The determination of plasma levels for glucose, cholesterol, triglycerides (TGs), high-density lipoprotein (HDL), low-density lipoprotein (LDL), aspartate transaminase (AST), alkaline phosphatase (ALP), and alanine aminotransferase (ALT) was carried out using the Cobas C-111 chemistry analyzer (Roche, Switzerland). Liver tissues were extracted as per the previously described protocol [21], and their cholesterol and TG contents were assessed using the Cobas C-111 chemistry analyzer (Roche, Switzerland). Urine Na⁺ level was measured at the Hadassah Medical Center laboratories using Atellica® Solution (Siemens Healthineers, Germany). Serum glucagon levels were measured using ELISA kit (Mercodia, Sweden). Creatine kinase activity assay was performed on muscle homogenates, using the Cobas C-111 chemistry analyzer (Roche, Switzerland). Serum FFAs were measured according to the manufacture instructions (#ab65341, Abcam). The relative fluorescent intensity (RFI) was measured using the Multi-Mode Microplate Reader SpectraMax iD3 (Molecular Devices, USA).

2.8.Glucose tolerance test (GTT) and insulin tolerance test (ipITT)

Mice that underwent overnight fasting were administered glucose (1.5 g/kg, ip) and subjected to tail blood collection at 0, 15, 30, 45, 60, 90, and 120 min. Blood glucose levels were determined using the Elite glucometer (Bayer, Pittsburgh, PA). Subsequently, the mice were fasted for 6 h on the next day before receiving insulin (0.75 U/kg, i.p.; Actrapid vials, Novo Nordisk A/S, Bagsværd, Denmark), and blood glucose levels were determined at the same intervals as described above.

2.9.LC-MS kidney metabolomics analysis

Frozen kidney samples weighing approximately 10 mg were transferred into soft tissue homogenizing tubes containing 1.4 mm ceramic beads (CK14, Bertin corp.). The tubes were pre-filled with 400 μL of cold (−20 °C) metabolite extraction solvent (methanol: acetonitrile: water, 5:3:2) and kept on ice. Samples were homogenized using a Precellys 24 tissue homogenizer at 4 °C (3 × 20 s at 6000 rpm, with a 30 s gap between each of the three cycles, Bertin Technologies). The homogenized extracts were centrifuged at 18,000×g for 15 min at 4 °C. The supernatants were collected into microcentrifuge tubes and re-centrifuged at 18,000×g for 10 min at 4 °C. The supernatants were then transferred to glass HPLC vials and stored at 75 °C prior to LC-MS analysis. LC-MS metabolomics analysis was performed as described previously [22]. Briefly, a Dionex Ultimate 3000 high-performance liquid chromatography (UPLC) system coupled to an Orbitrap Q-Exactive Mass Spectrometer (Thermo Fisher Scientific) with a resolution of 35,000 at 200 mass/charge ratio (m/z), electrospray ionization, and polarity switching mode to enable both positive and negative ions across a mass range of 67–1000 m/z, was used. The UPLC setup included a ZIC-pHILIC column (SeQuant; 150 mm × 2.1 mm, 5 μm; Merck) with a ZIC-pHILIC guard column (SeQuant; 20 mm × 2.1 mm). Five μL of the kidney extracts were injected and the compounds were separated with a mobile phase gradient of 15 min, starting at 20% aqueous (20 mM ammonium carbonate adjusted to pH 9.2 with 0.1% of 25% ammonium hydroxide) and 80% organic (acetonitrile) and terminated with 20% acetonitrile. The flow rate and column temperature were maintained at 0.2 mL/min and 45 °C, respectively, for a total run time of 27 min. All metabolites were detected using mass accuracy below 5 ppm. Thermo Xcalibur was used for the data acquisition. Data processing and analysis were conducted using TraceFinder 4.1 (Thermo Fisher Scientific) and Metabolite–Auto Plotter 2.0 [23]. The exact mass of the singly charged ion was identified and confirmed by the known retention time, utilizing an in-house MS library built by running commercial standards for all detected metabolites. Each identified metabolite intensity was normalized to the mass (mg) of kidney tissue. GraphPad Prism 9.0 was employed for PCA and the generation of volcano plot on individual samples, utilizing log(Fold-change) data from KPTC^GLUT2–/– compared to KPTC^GLUT2+/+ mice. MetaboAnalyst 5.0 was utilized to create heatmaps and perform metabolic enrichment analysis using log transformed data, comparing WT and KO mice. The enrichment analysis employed the SMPDB metabolic pathway library, presenting only pathways identifying >6 metabolites.

2.10.LC-MS liver metabolomics analysis

Liver metabolites were extracted, purified, and quantified. The samples were initially weighed, homogenized in a solvent containing methanol, acetonitrile, and water at a ratio of 5:3:2, respectively (Solvent A), and centrifuged. The resulting supernatants were transferred to glass HPLC vials and stored at −80 °C before LC-MS analysis. LC-MS metabolomics analysis was conducted, using a Dionex Ultimate 3000 high-performance liquid chromatography (UPLC) system coupled to an Orbitrap Q-Exactive Plus Mass Spectrometer (Thermo Fisher Scientific) with a resolution of 70,000 at 200 mass/charge ratio (m/z), electrospray ionization in the HESI source, and polarity switching mode to enable both positive and negative ions across a mass range of 70–1000 m/zas described previously [22]. The UPLC setup included a ZIC-pHILIC column (SeQuant; 150 mm × 2.1 mm, 5 μm; Merck) with a Sure-Guard filter (SS frit 0.5 μm). Five μL of the sample extracts were injected, and the compounds were separated with a mobile phase gradient over 15 min, starting at 20% aqueous (20 mM ammonium carbonate adjusted to pH 9.2 with 0.1% of 25% ammonium hydroxide) and 80% organic (acetonitrile) and terminating with 20% acetonitrile. The flow rate and column temperature were maintained at 0.2 mL/min and 45 °C, respectively, for a total run time of 26 min. All metabolites were detected with mass accuracy below 5 ppm. Thermo Xcalibur was utilized for the data acquisition. Data processing and analysis were performed using TraceFinder 5.2 (Thermo Fisher Scientific). The exact mass of the singly charged ion was identified and confirmed by the known retention time using an in-house MS library constructed by running commercial standards for all detected metabolites. Each identified metabolite intensity was normalized to the to the liver weight of each sample.

2.11.Cell culture

Primary mouse KPTCs were isolated from KPTC^GLUT2+/+ and KPTC^GLUT2–/– mice using the following method: The mouse kidney cortices were dissociated into single cells using 0.7 mg/mL collagenase/dispase (Sigma–Aldrich; Cat# 10269638001) in Hanks' Balanced Salt Solution (HBSS) and vortexed in Gentle MACs Dissociator (MACS Miltenyi Biotec) program Multi_E_02. Red blood cells were removed using RBC Lysis solution (Sartorius; Cat #01-888-1B). KPTCs were purified using low speed (100×g) centrifugation and cultured in collagen-coated 6-well plates in REGM BulletKit medium (Lonza; Cat #CC-3191 & #CC-4127).

2.12.SGLT2 inhibition in KPTCs

To evaluate SGLT2 inhibition effect on SLC6A6 expression, primary human KPTCs (Lonza; Cat #CC-2253) were cultured in REGM BulletKit medium for one week, then after cultured in serum free medium with or without Dapagliflozin (Dapa; 5 μM) for 24 h. Cells were collected for protein extraction.

2.13.mTORC1 inhibition in KPTCs

To evaluate mTORC1 inhibition effect on SLC6A6 expression, primary human KPTCs (Lonza; Cat # CC-2253) were cultured in REGM BulletKit medium for one week, then after KPTCs were cultured in complete or SFM with or without mTORC1 inhibitor, rapamycin (100 nM; Cayman Chemical, USA; Cat # 13346), for 24 h. Cells were collected for protein extraction.

2.14.Real-time PCR

Total mRNA from kidney, liver, and muscle tissues was extracted using Bio-Tri RNA lysis buffer (Bio-Lab, Israel), followed by DNase I treatment (Thermo Scientific, IL, USA), and reverse transcribed into cDNA using the Iscript cDNA kit (Bio-Rad, CA). Real-time PCR was conducted with iTaq Universal SYBR Green Supermix (Bio-Rad, CA) on the CFX connect ST system (Bio-Rad, CA). The primers used for detection of mouse genes are provided in Table S1. The expression of mouse genes was normalized to the reference gene Ubc.

2.15.Western blotting

Kidney, liver and muscle tissues were homogenized in a RIPA buffer consisting of 25 mM Tris–HCl pH 7.6, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, and 0.1% SDS. Kidney homogenates were prepared using zirconium oxide beads (Next Advanced, Inc., NY, USA) in a BulletBlender®. Protein concentrations were determined using the Pierce™ BCA Protein Assay Kit (Thermo Scientific, IL, USA). Samples were separated by SDS-PAGE using 4–15% acrylamide gels at 150 V and transferred to PVDF membranes using the Trans-Blot® Turbo™ Transfer System (Bio-Rad, CA). To block unspecific binding, membranes were incubated for 1 h in 5% milk (in 1 × TBS-T). Subsequently, the membranes were incubated overnight at 4 °C with Mouse monoclonal anti 4-HNE (#ab48506, Abcam, 1:1,000), Mouse monoclonal anti-FAAH (#ab54615, Abcam, 1:1,000), Rabbit anti SLC6A6 (#ab236898, Abcam, 1:1,000) or Rabbit anti phospho-S6 (#5364, Cell Signaling, 1:10,000) antibodies. After washing, Anti-Mouse/Rabbit horseradish peroxidase (HRP)-conjugated secondary antibodies (#ab98799/ab97085, Abcam, 1:2,500) were applied for 1 h at room temperature. Detection of the target proteins was carried out by chemiluminescence using Clarity™ Western ECL Blotting Substrate (Bio-Rad, CA) and the ChemiDoc™ Touch Imaging System (Bio-Rad, CA). Densitometry was quantified using Bio-Rad CFX Manager software. The quantification of target proteins was normalized to Mouse anti-β actin antibody (#ab49900, Abcam, 1:30,000) or to Rabbit anti VCP (#ab155146, Abcam, 1:1,000). Phospho-S6 was normalized to Rabbit anti total S6 (2#217, Cell Signaling, 1:500).

2.16.FAAH activity assay

FAAH activity assay was performed according to the manufacture instructions (#ab252895, Abcam) on kidney homogenates. The relative fluorescent intensity (RFI) was measured using the Multi-Mode Microplate Reader SpectraMax iD3 (Molecular Devices, USA).

2.17.Fluorescence immunohistochemistry

Kidney sections were processed by deparaffinization and hydration. Heat-mediated antigen retrieval was conducted using 10 mM citrate buffer pH 6.0 (Thermo Scientific, IL, USA). Nonspecific antigens were blocked by incubating the sections with 2.5% horse serum (#VE-S-2012-50, Vector Laboratories) and 0.25% Triton X for 1 h. The sections were stained with a primary Mouse anti-CPT1A (#ab128568, Abcam, 1:500) antibody and a secondary Goat anti-Mouse-AF488 antibody (#ab150117, Abcam, 1:500). Finally, the sections were mounted with a mounting medium with DAPI (#H-1200, Vector) and imaged using the LSM 700 imaging system (Zeiss). The relative fluorescent intensity (RFI) was quantified using the ImageJ software (NIH, Bethesda, MD).

2.18.Sample preparation and measurements of endocannabinoids, N-arachidonoyl taurine, taurine, and creatine by LC-MS/MS

Endocannabinoids were extracted, purified, and quantified from kidney lysates and serum as reported previously [13]. N-arachidonoyl taurine (NAT) was extracted and purified from kidney lysates the same as endocannabinoids. In brief, kidneys were added with ice-cold Tris Buffer, homogenized using the BulletBlender® and zirconium oxide beads (Next Advanced, Inc., NY, USA); the protein concentration was determined by the BCA assay. Serum samples were supplemented with acetone, vortexed and centrifuged to precipitate proteins, then after the aqueous phase was transferred to new borosilicate tubes. Samples were then supplemented with an ice-cold extraction buffer [1:1 methanol/Tris buffer + an internal standard (IS)] and chloroform/methanol (2:1), vortexed, and centrifuged. The lower organic phase was transferred into borosilicate tubes; this step was repeated three times by adding ice-cold chloroform to the samples and transferring the lower organic phase into the same borosilicate tubes. The samples were dried and kept overnight at −80 °C, then reconstituted with ice-cold chloroform and acetone, kept at −20 °C for 30 min, and then centrifuged to precipitate proteins. Next, the supernatant was dried and reconstituted in an ice-cold LC/MS grade methanol. Taurine and creatine were extracted, purified, and quantified from kidney, plasma, urine and food pellets. The samples were first weighed and homogenized in a solvent containing methanol, acetonitrile, and water at a ratio of 5:3:2, respectively (Solvent A), supplemented with 250 ng/mL IS and centrifuged. For plasma and urine samples, they were diluted 1:10 in Solvent A, containing the IS. The LC-MS/MS analyses of NAT was conducted on an Sciex (Framingham, MA, USA) QTRAP® 6500+ mass spectrometer coupled with a Shimadzu (Kyoto, Japan) UHPLC System. Liquid chromatographic separation was obtained using 5 μL injections of samples onto a Cortecs C18 2.7 μm (100 × 2.1 mm) column from Waters (Ireland). The autosampler was set to 5 °C and the column was maintained at 40 °C during the entire analysis. The Gradient elution mobile phases consisted of 20 mM NH4OAc (phase A) and acetonitrile (phase B). The LC-MS/MS analyses of taurine and creatine were conducted using S-(2-Aminoethyl)-l-cysteine hydrochloride as IS on a Waters (Milford, MA, USA) Xevo TQ-S cronos mass spectrometer. The chromatography was performed using an Arc™ Premier UHPLC System (Waters). Liquid chromatographic separation was obtained using 5 μL injections of samples onto an Intrada Amino Acid column 3 μm (150 × 2 mm) from Imtakt Corp. (Kyoto, Japan). The mobile phase was composed of phase A (100 mM ammonium formate in water) and phase B (0.3% formic acid in acetonitrile/water 95:5). The autosampler was set to 15 °C and the column was maintained at 40 °C during the entire analysis. The gradient elution mobile phases consisted of 100 mM ammonium formate in water (phase A) and 0.1% formic acid in acetonitrile (phase B). NAT, taurine, and creatine were detected in a negative ion mode, using electron spray ionization (ESI) and the multiple reaction monitoring (MRM) mode of acquisition, using, d₄-NAT or S-(2-Aminoethyl)-l-cysteine hydrochloride as IS. The collision energy (CE), declustering potential (DP), and the collision cell exit potential (CXP) for the monitored transitions are presented in Table S2. The levels of NAT, taurine, and creatine in samples were measured against standard curves and normalized to the organ and food pellet weight or plasma and urine volume. The data was acquired using Analyst 1.7.1 and analyzed using Sciex OS Software.

2.19.In vivo micro PET-MRI scanning

The experiments were conducted at the Wohl Institute for Translational Medicine, Hadassah-Hebrew University Medical Center. The PET-MRI images were acquired using a 7T 24 cm bore, cryogen-free MR scanner based on proprietary dry magnet technology (MR Solutions, Guildford, UK) with a 3-ring PET insert that utilizes the latest silicon photomultiplier (SiPM) technology [24]. The PET subsystem comprises 24 detector heads arranged in three octagons, each 116 mm in diameter. A mouse quadrature RF volume coil was used for MRI acquisition. Isoflurane vaporized with O₂ was used for mouse anesthesia. The tracer, 2-[¹⁸F] FDG, was injected into the tail vein (230 ± 30 mCi in 200 mL) to determine its distribution in mice. The mice were subjected to 31 min dynamic PET scans, with the acquired data were binned into 25 image frames (1 × 60, 6 × 10, 8 × 30, 5 × 60, and 4 × 300 s). For anatomical evaluation, T1-and T2-weighted coronal spin echo images were collected. The images were analyzed using VivoQuant pre-clinical image post-processing software (Invicro). The PET-MRI raw data were processed using standard software provided by the manufacturers. The PET data histogrammed by Fourier rebinning and reconstructed using the 3D-OSEM algorithm, with standard corrections for random coincidences, system response, and physical decay applied. The reconstructed PET images from the PET/MR scanner were quantitated using a measured system-specific ¹⁸F calibration factor to convert reconstructed count rates per voxel to activity concentrations (%ID/g). Manual tissue segmentation of kidneys, liver, muscle, inferior vena cava (IVC), and bladder was carried out on co-registered 3D MR images, and the regional ROIs were then used to calculate tissue radiotracer uptake from the reconstructed PET images.

2.20.Statistical power calculations

Prior to data collection, power analyses were carried out in G∗Power 3.1 (two-tailed α = 0.05) using pilot variance estimates and effect sizes deemed physiologically meaningful. For the untargeted metabolomics screen, coefficients of variation (CV) of ∼20 % indicated that a sample size of 6–10 mice per group would provide ≥80% power to detect ≥1.3-fold differences in metabolite abundance, accounting for multiple testing using false discovery rate correction. For dynamic PET–MRI endpoints (e.g., tracer-derived glucose uptake rate constants) pilot data showed lower variability (CV ∼15 %). Accordingly, 8 mice per group were estimated to provide ∼85% power to detect ≥20% between-group differences. Western blot targets exhibited higher variability (CV ∼25 %). Simulations indicated that 5–7 mice per group would yield 80–90% power to detect ≥30% changes in protein expression using one-way ANOVA with Bonferroni correction. These power estimates guided the final cohort sizes used for each experimental modality.

2.21.Statistical analysis

Values are expressed as the mean ± SEM. Unpaired Two-tailed Student’s t-test was used to determine the differences between two groups. Results in multiple groups were compared by One-way ANOVA followed by one-sided Tukey test, using GraphPad Prism v6 for Windows (San Diego, CA). Significance was set at P < 0.05. The EE ANCOVA analysis done for this work was provided by the NIDDK Mouse Metabolic Phenotyping Centers (MMPC, www.mmpc.org) using their Energy Expenditure Analysis page (http://www.mmpc.org/shared/regression.aspx) and supported by grants DK076169 and DK115255.

3.Results

3.1.Impacts of inhibiting glucose reabsorption on glycemic control and systemic metabolism in normal mice

Regulating glucose reabsorption and homeostasis via modulating kidney proximal tubule GLUT2 expression has already been established under pathological conditions [12,13]. Our previous study showed that GLUT2 nullification in KPTCs (KPTC^GLUT2–/–) in non-diabetic mice resulted in reduced kidney injury and fibrotic markers, as well as elevated glycosuria (urine glucose average was 0.0167 ± 0.0019 mg/h and 0.0294 ± 0.0056 mg/h in KPTC^GLUT2+/+ and KPTC^GLUT2–/– mice respectively, P = 0.0437), without changes in blood glucose or insulin levels [13]. This effect was attributed to reduced glucose reabsorption caused by decreased expression of both GLUT2 and SGLT2 on the basolateral and apical membranes of KPTCs, respectively [13]. Therefore, our primary objective here was to evaluate whether this alteration was translated into systemic metabolic effects under normoglycemic conditions. Although these mice exhibited increased urine glucose levels [13], there were no significant changes in body weight (Figure S1A) and in fed or fasted plasma glucose levels (Figure S1B, C) nor in glucose tolerance and insulin sensitivity (Figure S1D-G). Interestingly, whereas these mice demonstrated normal systemic FAO (Figure S1H and I) and total energy expenditure (TEE; Figure S1J-L), a significant increased whole-body CHO during the day and night periods was noted (Figure 1A,B), probably due to an increase in food intake (Figure 1C,D), suggesting that the diminished capacity of glucose reabsorption in KPTC^GLUT2–/– mice may lead to an increase in food intake as a compensatory mechanism to maintain normoglycemia. Paradoxically, this increased food intake did not impact body weight or glucose/insulin homeostasis, likely due to systemic metabolic effects, including enhanced CHO.

Figure 1KPTC-GLUT2 nullification results in systemic metabolic changes. 16-weeks-old KPTC^GLUT2+/+ and KPTC^GLUT2–/– male mice underwent metabolic assessment using metabolic cages. (**A, B**) A significant increase in carbohydrate oxidation (CHO, measured in g/day) in KPTC^GLUT2–/– mice was detected, apparently due to (**C, D**) enhanced food intake in these mice. Lipid profile biochemical analysis revealed a significant reduction in (E) plasma TG, (F) cholesterol and (G) LDL levels, while (H) HDL levels were unchanged and (I) HDL/LDL ratio was elevated. Furthermore, (J) elevated serum FFA were noted. Glucose uptake assessed using PET-MRI, revealed a significant increase (**K, L**) in total fat glucose uptake in KPTC^GLUT2–/– mice. MRI analysis revealed (**M, N**) increased total fat mass. For **A-D**; KPTC^GLUT2+/+n = 6 mice and KPTC^GLUT2–/–n = 7 mice. For **E-I**; KPTC^GLUT2+/+n = 9 mice and KPTC^GLUT2–/–n = 14 mice. For J; KPTC^GLUT2+/+n = 8 mice and KPTC^GLUT2–/–n = 13 mice. For **K, L**; n = 8 mice for each group. For N; KPTC^GLUT2+/+n = 7 mice and KPTC^GLUT2–/–n = 8 mice. Data represent the mean ± SEM and were analyzed by Student’s t-test. ∗P < 0.05, ∗∗P < 0.005, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001 relative to KPTC^GLUT2+/+ mice. CH, carbohydrate; FFA, free fatty acids; AUC, area under the curve; BAT, brown adipose tissue. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Furthermore, alterations in circulating lipid profile were observed in KPTC^GLUT2–/– mice, characterized by lower levels of triglycerides (TG) and cholesterol (Figure 1E,F), reduced low-density lipoprotein (LDL) levels (Figure 1G), unchanged high-density lipoprotein (HDL) levels (Figure 1H), increased HDL-to-LDL ratio (Figure 1I), and elevated levels of free fatty acids (FFA; Figure 1J). These changes in lipid profile were accompanied by increased glucose uptake in white adipose tissue (WAT; Figure 1K,L), which well-correlated with an increase in total fat mass (Figure 1M,N).

Taken together, these findings suggest that inhibiting glucose reabsorption in the kidney significantly affects the systemic metabolic profile in mice. This effect manifests as increased food intake, alteration in CHO, and changes in the circulating lipid profile, ultimately leading to enhanced fat accumulation in adipose tissue.

3.2.Systemic metabolic adaptation in KPTC-GLUT2 KO mice

The liver, a central organ in glucose homeostasis, compensated for the absence of renal glucose reabsorption, leading to a significant increase in hepatic glucose uptake (Figure S2A-C), which correlated with elevated expression of liver Slc2a2 (GLUT2) (Figure S2D). Despite this, liver metabolomics analysis revealed no significant changes in glycolysis- or gluconeogenesis-related metabolites (Figure S2E) or in the expression of the corresponding enzymatic genes (Figure S2F, G). Additionally, the unchanged serum glucagon levels (Figure S2H) suggest that systemic glucose homeostasis remains intact, eliminating the need for increased hepatic glucose production.

Metabolites related to hepatic FAO showed no significant changes (Figure S2I), nor did the transcriptional levels of associated enzymes (Figure S2J). The tricarboxylic acid (TCA) cycle metabolites were also largely unaffected, with the exception of Acetyl-CoA, which was significantly reduced (Figure S2K).

Consistent with the observed alterations in circulating lipids, hepatic TG levels were also reduced (Figure 2A), likely due to decreased levels of glycerol 3-phosphate, a key TG precursor (Figure 2B), and downregulated expression of key biosynthesis TG enzymes (Figure 2C). Hepatic cholesterol levels were also significantly lowered (Figure 2D), potentially attributable to the upregulation of hepatic LDL receptor expression (Figure 2E,F), which negatively regulates HMG-CoA reductase, the rate-limiting enzyme in cholesterol biosynthesis [25]. Additionally, the observed reduction in liver nicotinamide adenine dinucleotide phosphate (NADP⁺, Figure 2G), necessary for HMG-CoA reductase activity, could contribute to this decrease. Lower levels of Acetyl-CoA, its ketogenic amino acid precursors, and Coenzyme A (Figure 2H) suggests these building blocks are redirected towards FA biosynthesis. This is further supported by the elevated transcriptional levels of sterol regulatory element-binding protein 1 (Srebp1), a key transcription factor regulating both fatty acid and cholesterol biosynthesis, as well as the upregulation of enzymes involved in fatty acid synthesis (Figure 2I). Increased levels of polyunsaturated fatty acids (PUFAs; Figure 2J), and elevated expression of the fatty acid exporter ATP-binding cassette sub-family A member 1 (Abca1; Figure 2K) were also observed. Moreover, a significant reduction in 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), an activator of AMP-dependent protein kinase (AMPK), was observed in KPTC^GLUT2–/– mice (Figure S2L). Since AMPK negatively regulate hepatic fatty acid biosynthesis [26], this decrease further supports enhanced hepatic lipid synthesis in these mice. Importantly, no significant changes were observed in serum liver enzyme levels (Figure S2M−O). Collectively, these findings suggest that in KPTC^GLUT2–/– mice, the liver redirects the elevated postprandial glucose availability towards fatty acid biosynthesis and their subsequent release into the circulation (Figure 2L and Figure S2P).

Figure 2Liver and muscle metabolic adaptation in KPTC^GLUT2–/– mice. Lipid profile biochemical analysis revealed (A) a slight reduction in liver TG and (B) a significant reduction in its liver precursor metabolite glycerol 3-phosphate using metabolomics analysis, as well as (C) reduced liver transcriptional expression of TG biosynthesis related genes. The profile biochemical analysis also revealed a significant reduction in (D) liver cholesterol levels as well as (**E, F**) significant elevated liver protein levels of LDL-R using WB and (G) reduced levels of NADP⁺ using metabolomics analysis, which negatively regulates HMG-CoA reductase activity were detected in the liver of KPTC^GLUT2–/– mice. Metabolomics analysis revealed (H) a significant reduction in Acetyl-CoA, its ketogenic amino acids precursors and Coenzyme A, which are building blocks of FA biosynthesis. On the other hand, (I) a significant elevation in liver transcriptional expression of FAs biosynthesis related enzymatic genes, (J) as well as elevated PUFAs using metabolomics analysis, and (K) elevated transcriptional expression of FAs exporter; *Abca1* in the liver of KPTC^GLUT2–/– mice. (L) Illustration of the metabolic changes in hepatic cell of KPTC^GLUT2–/– mice (black-unchanged metabolites, blue-decreased metabolites, red-increased metabolites). Figure created with BioRender.com. PET-MRI analysis revealed reduced (**M, N**) muscle glucose uptake along with decreased (O) muscle transcriptional expression of *Slc2a4* (GLUT4), (P) elevated muscle mass recorded using MRI and increased transcriptional levels of (Q) FAO-related genes, but not (R) glycolytic genes. Additionally, (**S, T**) reduced phosphorylated S6 levels were found using WB as well as (U) elevated transcriptional levels of the FAs transporter CD36 in the muscle of KPTC^GLUT2–/– mice. (V) Illustration of the metabolic changes in muscles of KPTC^GLUT2–/– mice. Figure created with BioRender.com. For **A, D**; n = 9 mice for each group. For **B, F, G, H, J**; n = 6 mice for each group. For C; KPTC^GLUT2+/+n = 6 mice and KPTC^GLUT2–/–n = 10 mice. For I; KPTC^GLUT2+/+n = 6 mice and KPTC^GLUT2–/–n = 10 mice. For K; KPTC^GLUT2+/+n = 6 mice and KPTC^GLUT2–/–n = 10 mice. For **M, N**; n = 8 for each group. For **O, Q, R, U**; KPTC^GLUT2+/+n = 8 mice and KPTC^GLUT2–/–n = 12 mice. For P; KPTC^GLUT2+/+n = 7 mice and KPTC^GLUT2–/–n = 8 mice. For T; n = 5 mice for each group. Data represent the mean ± SEM and were analyzed by Student’s t-test. ∗P < 0.05, ∗∗P < 0.005, ∗∗∗P < 0.001 relative to KPTC^GLUT2+/+ mice. AUC, area under the curve; FAO, fatty acid oxidation; PUFA, polyunsaturated fatty acid. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Interestingly, KPTC^GLUT2–/– mice exhibited decreased glucose uptake in muscle tissue (Figure 2M,N), which corresponded with reduced expression levels of muscle GLUT4 (Slc2a4) (Figure 2O). This decline in glucose uptake was associated an increase in muscle mass (Figure 2P) and upregulation of the FAO transcription factor peroxisome proliferator-activated receptor alpha (PPARα) along with its downstream targets (Figure 2Q). Conversely, the expression of key glycolytic enzymes remained unchanged (Figure 2R). Notably, there was a downregulation in the phosphorylation of ribosomal protein S6 (pS6), a marker for mTORC1 activation, which is linked to muscle aerobic glycolysis [27,28] (Figure 2S,T), as well as increased transcriptional levels of the fatty acid importer, Cd36 (Figure 2U). Altogether, these findings suggest that in KPTC^GLUT2–/– mice, the muscle shifts towards utilization of the abundant circulating FFAs as its main energy source (Figure 2V).

Additionally, increased glucose uptake was observed in the heart (Figure S3A-C) and brain (Figure S3D-F), organs known to utilize glucose for their energy demands [[29], [30], [31], [32], [33], [34]]. Altogether, these results indicate a systemic metabolic adaptation in KPTC^GLUT2–/– mice to cope with the lack of glucose reabsorption by the kidney. This adaptation exhibits a pronounced energy-conserving phenotype.

3.3.Glucose retention in KPTCs leads to enhanced renal energy metabolism

To further understand the systemic adaptation observed in KPTC^GLUT2–/– mice, we next examined the changes occurring within the kidneys of these animals. Surprisingly, no significant alterations in kidney glucose uptake were detected (Figure S4A-C), and there was no compensatory increase in the expression of other GLUT paralogs (Slc2a1, Slc2a4) or SGLT1 (Slc5a2) in the kidney of KPTC^GLUT2–/– mice (Figure S4D). To reconcile the apparent contradiction between unchanged glucose uptake and reduced glucose reabsorption in the kidney, and to explore potential mechanisms underlying the renal and systemic metabolic effects in KPTC^GLUT2–/– mice, we then performed a semi-targeted metabolomics profiling analysis comparing the kidney metabolome of KPTC^GLUT2–/– mice with that of their KPTC^GLUT2+/+ WT counterparts. The results revealed a distinct clustering of kidney metabolites between the two groups (Figure 3A). Further analysis using volcano plot (Figure 3B) and heatmaps (Figure 3C) demonstrated a significant and robust elevation (p ≤ 0.05) in 100 out of the 284 identified metabolites (35.2%) in KPTC^GLUT2–/– mice compared to WT mice. Pathway enrichment analysis revealed an upregulation of pathways related to energy metabolism, including glycolysis, gluconeogenesis, mitochondrial function, and amino and nucleic acid metabolism in the kidneys of KPTC^GLUT2–/– mice (Figure 3D).

Figure 3KPTC-GLUT2 nullification results in a renal metabolomic storm. Kidney metabolomics profiling analysis was conducted by comparing the metabolites of KPTC^GLUT2–/– mice (n = 10) with those of KPTC^GLUT2+/+ counterparts (n = 8). (A) Principal component analysis revealed a distinct clustering of kidney metabolites between KPTC^GLUT2+/+ and KPTC^GLUT2–/– mice. (B) Volcano plot and (C) heatmap demonstrated a significant and robust elevation (p ≤ 0.05) in 100 of the 284 identified metabolites (35.2%) in KPTC^GLUT2–/– mice compared to their wild-type littermates. (D) Pathway enrichment analysis revealed an upregulation of pathways involved in energy metabolism as well as amino and nucleic acid metabolism in KPTC^GLUT2–/– mice. GraphPad prism 9.0 was used to perform the PCA and the volcano plot, using the log(Fold-change) data from KPTC^GLUT2–/– in comparison to KPTC^GLUT2+/+ mice. MetaboAnalyst 5.0 was used to generate the heatmap and to perform a metabolic enrichment analysis using the log transformed data, comparing WT and KO mice. Enrichment analysis was performed using the SMPDB metabolic pathway library, where only pathways identifying >6 metabolites are presented. FDR, false discovery rate.

Notably, KPTC^GLUT2–/– mice exhibited a significant increase in intracellular glucose levels (Figure 4A), implying on glucose retention within proximal tubular cells due to the absence of GLUT2. The simultaneous occurrence of reduced glucose reabsorption and glycosuria, alongside glucose retention in the proximal tubules, may explain the unchanged renal 2-FDG uptake observed in PET-MRI results (Figure S4A-C). Additionally, KPTC^GLUT2–/– mice displayed elevated levels of metabolites involved in glycolysis and gluconeogenesis within the kidneys (Figure 4A). This was accompanied by increased transcriptional levels of key glycolytic enzymes, such as Pkm2, Eno1 and Gapdh (Figure 4B), while the transcriptional levels of gluconeogenic enzymes, Pck1 and Pcx, remained unchanged, and G6p was reduced (Figure 4C). These findings suggest that glucose is increasingly utilized for energy production in the kidney of the null mice.

Figure 4Enhanced kidney energy metabolism in KPTC^GLUT2–/– mice. Kidney metabolomics profiling analysis revealed an increase in metabolites involving (A) glycolysis along with elevated transcriptional levels of (B) glycolytic enzymes but not (C) gluconeogenic ones. Metabolomics profiling also revealed increased levels of (D) FAO related metabolites as well as elevated kidney (E) transcriptional and (**F, G**) protein levels of the FAO rate limiting enzyme CPT1a in KPTC^GLUT2–/– mice compared to KPTC^GLUT2+/+ mice, kidney sections (20 × magnification, scale bar: 50 μm). (H) Elevated levels of TCA related metabolites were also found using metabolomics profiling. Elevated mitochondrial function was assessed by the increase in (I) main co-enzymes involved in the electron transport chain, (J) mitochondrial to nuclear DNA ratio and (**K, L**) oxidative stress marker 4HNE, (M) indicating elevated kidney energy metabolism. Figure created with BioRender.com. For **A, D, H, I**; KPTC^GLUT2+/+n = 8 mice and KPTC^GLUT2–/–n = 10 mice. For **B, C**; KPTC^GLUT2+/+n = 13 mice and KPTC^GLUT2–/–n = 14 mice. For **E, J**; n = 6 mice for each group. For G; n = 5 mice for each group. For L; n = 7 mice for each group. Data represent the mean ± SEM and were analyzed by Student’s t-test. ∗P < 0.05, ∗∗P < 0.005, ∗∗∗P < 0.001 relative to KPTC^GLUT2+/+ mice.

Furthermore, FAO, the primary energy-generating pathway in KPTCs, was also elevated in the kidneys of KPTC^GLUT2–/– mice. This was evidenced by increased levels of carnitine metabolites responsible for transporting long-chain FAs into the mitochondria for FAO (Figure 4D) along with the upregulation of transcription and protein levels of the rate-limiting enzyme, carnitine palmitoyltransferase I (CPT1a; Figure 4E–G). The simultaneous enhancement of glucose utilization and FAO further fueled the TCA cycle (Figure 4H), providing NADH electron donors to the electron transport chain. Correspondingly, we observed elevated levels of NADH and FAD, which are crucial cofactors in the mitochondrial electron transport chain (Figure 4I). Additionally, an increased mitochondrial-to-nuclear DNA ratio (Figure 4J) and elevated levels of 4-Hydroxynonenal (4-HNE), a biomarker of oxidative stress (Figure 4K,L), were found in the kidney of KPTC^GLUT2–/– mice, indicating enhanced oxidative phosphorylation and elevated renal energy metabolism. Collectively, these findings suggest that glucose retention in KPTCs results in the reprogramming of kidney energy metabolism (Figure 4M).

3.4.Elevated energy metabolic hubs in the kidney of KPTC^GLUT2–/– mice

The “metabolomic storm” detected in the kidney of KPTC^GLUT2–/– mice (Figure 3) marked by enhanced production of amino and nucleic acid (Figure S5). Notably, significantly elevations in two key energy metabolic hubs, taurine and creatine (Figure 3, Figure 5B, C) were detected in the kidneys of KPTC^GLUT2–/– mice. These metabolites are primarily obtained through dietary intake or synthesized endogenously, mainly in the liver [35,36] (Figure 5A). Interestingly, the initial step of creatine biosynthesis occurs in the kidney, which aligns with the significant increases in precursor metabolites such as arginine, lysine, and guanidinoacetate (GAA) (Figure 5B). However, metabolites involved in taurine biosynthesis did not show significant changes in the kidney (Figure 5C). Although, the kidney can act as a secondary source for taurine and creatine biosynthesis [37], the expression levels of enzymes associated with their biosynthesis were unchanged (Figure 5D). In contrast, analysis of taurine and creatine synthesis metabolites in the liver of KPTC^GLUT2–/– mice, revealed either unchanged or slightly reduced levels (Figure 5E), with no significant changes in the expression of key liver enzymes involved in these processes (Figure 5F).

Figure 5Kidney and systemic elevated levels of the metabolic hubs; taurine and creatine in KPTC-GLUT2^−/− mice. (A) Schematic representation illustrating the primary sources of taurine and creatine. This figure was generated using BioRender.com. Kidney metabolomics analysis revealed (B) elevated levels of creatine, corresponding with increased levels of its precursor metabolites, and (C) elevated levels of taurine, without changes in its precursor metabolites, which are primarily synthesized in the liver. (D) Transcriptional levels of key enzymes involved in taurine and creatine biosynthesis in the kidney remained unchanged. Liver Metabolomics analysis revealed (E) either unchanged or slightly reduced levels of metabolites involved in taurine and creatine biosynthesis, alongside (F) stable transcriptional levels of key hepatic enzymes in KPTC^GLUT2–/– mice. Systemically, LC-MS/MS analysis showed elevated taurine and creatine levels in (G) serum and (H) urine of KPTC^GLUT2–/– mice. KPTC^GLUT2–/– mice pair-fed for 7 days as their KPTC^GLUT2+/+ littermates, demonstrated (I) a significant reduction in serum taurine and creatine levels in the ratio after and before pair-feeding. WB analysis on kidney lysates from KPTC^GLUT2–/– mice revealed (**J, K**) elevated protein levels of taurine transporter, SLC6A6, accompanied with (L) reduced urinary Na ⁺ levels in KPTC^GLUT2–/– mice. Moreover, WB analysis revealed (**M, N**) enhanced mTORC1 activation, represented by elevated phosphorylated S6 levels (pS6). This activation can be mediated by elevated levels of (O) DHAP and (P) branched-chain amino acids (BCAA) found in the metabolomics analysis. Human primary KPTCs were cultured in complete or serum free medium (SFM) with or without mTORC1 inhibitor, rapamycin (Rap; 100 nM), for 24 h, WB analysis on cell lysates revealed (**Q, R**) a significant reduction in SLC6A6 levels of the SFM and/or rapamycin treated cells. Kidney lysates form mice lacking the TSC specifically in KPTCs revealed elevated SLC6A6 transcriptional (S) and protein (T, U) levels. For **B, C, G, O, P**; KPTC^GLUT2+/+n = 8 mice and KPTC^GLUT2–/–n = 10 mice. For D; n = 15 for each group. For E; n = 6 for each group. For F; KPTC^GLUT2+/+n = 7 mice and KPTC^GLUT2–/–n = 10 mice. For H; n = 16 for each group. For I; KPTC^GLUT2+/+n = 3 mice and KPTC^GLUT2–/–n = 6 mice. For **K, N**; n = 5 mice for each group. For L; KPTC^GLUT2+/+ n = 13 mice and KPTC^GLUT2–/–n = 16 mice. For R; n = 4 for each group. For S; n = 8 mice for each group. For U; KPTC^TSC+/+ n = 5 mice and KPTC^TSC−/−n = 4 mice. Data represent the mean ± SEM and were analyzed by Student’s t-test, R was analyzed by one-way ANOVA followed by Tukey’s multiple comparison test. ∗P < 0.05, ∗∗P < 0.005, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001 relative to KPTC^GLUT2+/+ or KPTC^TSC+/+ mice. DHAP, dihydroxyacetone phosphate; BCAA, branched-chain amino acids; SFM, serum free medium; Rap, rapamycin; TSC, tuberous sclerosis complex.

Thus, the elevated levels of taurine and creatine in KPTC^GLUT2–/– mice are likely attributed to the increased food intake (Figure 1C,D), which typically contains taurine and creatine at concentrations of 4.64 ± 1.004 ng/mg and 101.03 ± 6.302 pg/mg, respectively. Indeed, systemic increases in these two metabolic hubs were also observed in the circulation (Figure 5G) and urine (Figure 5H) of the KO mice. A pair-feeding experiment, in which KPTC^GLUT2–/– mice’s food intake was restricted to match that of their WT littermates for seven days, led to a significant reduction in serum taurine and creatine levels (Figure 5I). These findings indicate that the elevated systemic levels of taurine and creatine in KPTC^GLUT2–/– mice are primarily attributed to their increased food intake.

3.5.Nullification of GLUT2 in KPTCs affects renal taurine reabsorption via an endocannabinoid-mTORC1 signaling pathway

Given that GLUT2 nullification reduces SGLT2 expression [13] and increases cellular glucose retention in KPTCs (Figure 4A), we hypothesized that taurine reabsorption in these cells could influence Na⁺ reabsorption. Indeed, the expression levels of the Na⁺/Cl⁻-dependent taurine transporter (TauT/SLC6A6) were upregulated in the kidneys of KPTC^GLUT2–/– mice (Figure 5J,K), which may contribute to the observed reduction in urinary Na⁺ concentrations (Figure 5L).

To explore the mechanism by which GLUT2 nullification in KPTCs enhances SLC6A6 expression and alters taurine bioavailability, we next assessed the role of kidney mTORC1 signaling, as mTORC1 is known to regulate amino acid transport in KPTCs [38], and its inhibition in primary trophoblast cells has been shown to decrease the activity and transcriptional expression of SLC6A6 [39]. Indeed, in KPTC^GLUT2–/– mice, we found an upregulation of pS6 (Figure 5M,N). This activation is likely driven by elevated levels of mTORC1 activators such as dihydroxyacetone phosphate (DHAP; Figure 5O), branched-chain amino acids (BCAAs; Figure 5P), and enhanced arginine metabolism (Figure 3D and Figure S5A), all of which modulate mTORC1 activation [[40], [41], [42]]. Accumulating evidence supports a direct connection between taurine transport and mTORC1 signaling, with several studies highlighting the ability of enhanced taurine uptake to activate mTORC1 [[43], [44], [45], [46], [47]]. To assess the potential regulatory link between mTORC1 and SLC6A6 expression in KPTCs, we treated human primary KPTCs with the mTORC1 inhibitor rapamycin under serum-free and serum-containing conditions. Serum deprivation (SFM), with or without rapamycin, significantly reduced SLC6A6 expression (Figure 5Q,R). Complementary in vivo evidence was obtained using a mouse model with constitutive mTORC1 activation, achieved by deletion of the tuberous sclerosis complex (TSC) specifically in KPTCs. In these mice, both Slc6a6 mRNA and protein levels were significantly elevated (Figure 5S-U), further supporting a functional link between mTORC1 signaling and SLC6A6 expression. Together, these findings suggest that mTORC1 activation may mediate enhanced renal taurine reabsorption in the context of GLUT2 deficiency.

Activation of the of the endocannabinoid system (ECS), particularly the cannabinoid-1 receptor (CB₁R) may stimulate mTORC1 signaling in KPTCs [13], thereby increasing glycolysis and regulating mitochondrial biogenesis and function [[48], [49], [50]], consistent with our findings (Figure 4). To further investigate whether the ECS is also involved in this pathway, we next evaluated the levels of key endocannabinoids and their degrading and metabolizing enzymes. While 2-arachidonoylglycerol (2-AG) and its enzymatic machinery remained largely unchanged (Figure S6A-D), there were significant elevations in renal levels of the second major endocannabinoid N-acylethanolamine [anandamide (AEA)] and the endocannabinoid-like molecules N-palmitoylethanolamine (PEA) and N-oleoylethanolamine (OEA), which share a common catabolic pathway with AEA [51] (Figure S6E-G). These changes were indeed associated with a significant reduction in the transcriptional expression of AEA/OEA/PEA-degrading enzyme fatty acid amid hydrolase (Faah; Figure S6H) in the kidney of KPTC^GLUT2–/– mice, leading to reduced FAAH activity (Figure S6I). FAAH plays a critical role in both ECS and taurine metabolism by degrading two major lipid metabolite classes: N-acylethanolamines (NAEs) and N-acyl taurines (NATs), both serving as signaling metabolic molecules [[52], [53], [54], [55]]. The observed positive correlation between AEA and N-arachidonoyl taurine (NAT) levels (Figure S6J) further supports FAAH inhibition in the kidneys of KPTC^GLUT2–/– mice. Additionally, significant elevations in circulating AEA levels were found in KPTC^GLUT2–/– mice (Figure S6K).

Taken together, the significant elevations of the three metabolic hubs-taurine, creatine, and AEA in the kidneys of KPTC^GLUT2–/– mice also enhanced their systemic bioavailability in the circulation and urine (Figure 5G,H and Figure S6K), suggesting systemic effects mediated by these factors.

3.6.Taurine and creatine mediate systemic changes in KPTC^GLUT2–/– mice

The increased systemic bioavailability of taurine and creatine has the potential to modulate overall energy metabolism [35,36]. In KPTC^GLUT2–/– mice, the observed increase in muscle mass and enhanced FAO (Figure 2P-U) may be attributed to the elevated availability of taurine in the muscles [[56], [57], [58], [59]], as indicated by the upregulation of the taurine transporter SLC6A6 in muscle tissue (Figure 6A,B). Additionally, the enhanced availability of creatine to the muscles can replenish phosphocreatine (PCr) stores, providing an immediate and accessible energy source [35], thereby reducing the reliance on glucose for energy. Consistently, there was an increase in the expression of the muscle creatine transporter (SLC6A8; Figure 6C,D), alongside a decrease in creatine-kinase (CK) activity (Figure 6E) in the muscle of KPTC^GLUT2–/– mice.

Figure 6Taurine and creatine mediates systemic changes in KPTC^GLUT2–/– mice. (**A, B**) Elevated muscle protein levels of taurine transporter, SLC6A6, and (**C, D**) creatine transporter, SLC6A8, were found using WB in muscle lysates of KPTC^GLUT2–/– mice. Additionally, (E) reduced muscle CK activity was found using biochemical analysis. Elevated (**F, G**) liver protein levels of taurine transporter, SLC6A6, were found using WB and (H) enhanced liver transcriptional expression of bile acid synthesis rate-limiting enzyme *Cyp7a1*. To inhibit SLC6A6, 16-week-old male KPTC^GLUT2–/– mice were treated with 3% β-Alanine in their drinking water for 7 days, resulting in (**I, J**) reduced CHO and (**K, L**) food intake compared to baseline levels. (M) β-Alanine did not change LDL levels; however, it reduced (N) HDL and (O) HDL/LDL ratio. Food consumption was restricted in 16-week-old male KPTC^GLUT2–/– mice to match that of their WT littermates for a period of 7 days. This pair-feeding regime resulted in (P) CHO reduction compared to baseline levels, (**Q, R**) with no alterations in activity profile. Moreover, (S) pair-feeding did not change LDL levels, but reduced (N) HDL and (U) HDL/LDL ratio. For **B, D, G**; n = 5 mice for each group. For E; KPTC^GLUT2+/+n = 14 mice and KPTC^GLUT2–/–n = 12 mice. For H; KPTC^GLUT2+/+n = 6 mice and KPTC^GLUT2–/–n = 10 mice. For **I–O**; n = 6 mice for each group. For **P-Q**; n = 3 mice for each group. For **S–U**; n = 15 mice for each group. Data represent the mean ± SEM and were analyzed by Student’s t-test. ∗P < 0.05, ∗∗P < 0.005, ∗∗∗∗P < 0.0001 relative to KPTC^GLUT2+/+ mice.

Furthermore, the observed reduction in hepatic cholesterol levels (Figure 2D) may be attributed to increased taurine availability in the liver [60], as evidenced by the upregulation of hepatic SLC6A6 (Figure 6F, G) and the increased expression of hepatic cholesterol 7α-hydroxylase (Cyp7a1; Figure 6H), the rate-limiting enzyme for bile acid synthesis, which utilizes both taurine and cholesterol. Collectively, these findings suggest that targeted nullification of GLUT2 in KPTCs leads to alterations in muscle and liver metabolism, as well as changes in the systemic lipid profile.

To further elucidate the relationship between elevated taurine levels and the systemic metabolic effects observed in KPTC^GLUT2–/– mice, we next assessed whether inhibition of SLC6A6 via β-Alanine supplementation (3% in drinking water for 7 days) would modulate the observed increased in whole-body CHO and food intake. Indeed, β-Alanine treatment led to a reduction in both parameters in KPTC^GLUT2–/– mice (Figure 6I-L), indicating that these metabolic alterations are mediated by taurine. Moreover, while SLC6A6 inhibition did not affect LDL levels, it resulted in a reduction in HDL levels and the HDL-to-LDL ratio in KPTC^GLUT2–/– mice (Figure 6M−O), suggesting that the taurine-mediated systemic metabolic effects extend to lipid homeostasis. Furthermore, pair-feeding KPTC^GLUT2–/– mice to match the food intake of their WT littermates similarly reduced CHO (Figure 6P) without altering physical activity or LDL levels (Figure 6Q–S) but led to a decrease in HDL levels and the HDL-to-LDL ratio (Figure 6T-U), mirroring the effects observed with β-Alanine treatment. These findings further support the role of dietary taurine and creatine in mediating the observed metabolic effects.

In summary, KPTC^GLUT2–/– mice exhibit a pronounced systemic energy-conserving phenotype. The impaired glucose reabsorption in KPTC^GLUT2–/– mice triggers a significant metabolic adaptation within the kidney, characterized by increased energy metabolism and elevated taurine and creatine levels. Importantly, the upregulation of KPTC-SLC6A6 is mTORC1-dependent, with significant mTORC1 activation observed in the kidneys of KPTC^GLUT2–/– mice. This activation is likely driven by various metabolites, including elevated AEA levels. Consequently, the elevated renal and circulating taurine, creatine, and AEA levels may contribute to the systemic energy-conserving phenotype (Graphical Abstract).

4.Discussion

Energy metabolism is a crucial process that underlines normal kidney function, and disruptions in energy metabolism have been linked to both chronic [61,62] and acute [63] kidney diseases. These renal pathologies may also affect other tissues and organs as well as modulate systemic energy metabolism. Therefore, understanding the mechanisms and key players involved in kidney energy metabolism is of paramount importance. In this study, we demonstrated that KPTC-GLUT2, responsible for renal glucose reabsorption and homeostasis, plays a major role in regulating local and systemic energy metabolism. Specifically, deletion of KPTC-GLUT2 leads to increased kidney FAO and whole-body metabolic changes in liver, fat, muscle, heart, and brain. These metabolic effects were associated with increased food intake, CHO, increased fat and muscle masses, as well as improved liver and plasma lipid profile resembling a systemic energy-conserving phenotype. Additionally, KPTC^GLUT2–/– mice exhibited increased kidney energy metabolism as indicated by metabolomics analysis, revealing elevated levels of glycolysis, TCA cycle, and FAO metabolites, as well as enhanced nutrient production including amino and nucleic acids. These findings suggest that KPTC-GLUT2 is a key player in the regulation of kidney energy metabolism and provide insights into potential therapeutic targets for the treatment of kidney and metabolic diseases.

Our recent studies have shown that nullification of KPTC-GLUT2 protects diabetic mice from developing diabetic kidney disease [13] and restores kidney energy metabolism in diabetic conditions by enhancing FAO [12]. Additionally, whole-kidney knockout of GLUT2 was found to reverse hyperglycemia and normalized body weight in diabetic mice [5]. These findings in diabetic mice along with the findings of enhanced glycosuria and decreased SGLT2 expression in non-diabetic KPTC^GLUT2–/– mice [13] led us to hypothesize that the absence of GLUT2 in the proximal tubules may affect kidney and systemic energy metabolism. Indeed, we found a robust metabolic shift in the kidney of KPTC-GLUT2 null mice, increased kidney and urine glucose levels without any effect on plasma glucose level or homeostasis. These findings imply on glucose retention in the tubules, which lack the ability to transport it back to the interstitium and circulation due to the nullification of GLUT2. The contrasting processes, with reduced glucose reabsorption and glycosuria on one hand, and glucose retention in the proximal tubules on the other hand, may explain the unchanged renal 2-FDG uptake observed in the PET-MRI results. A previous study in whole-body GLUT2-null mice [64] demonstrated a complete absence of kidney glucose reabsorption using 4-FDG, a substrate for SGLTs. However, the use of 2-FDG, a substrate for GLUTs, resulted in increased kidney uptake, potentially due to the activity of other GLUTs. In our KPTC-specific GLUT2 KO model, no compensatory expression of other GLUTs was observed in the kidney, which explains the lack of change in renal 2-FDG uptake. In KPTC^GLUT2–/– mice, glucose retention within the tubules forces KPTCs to reprogram their metabolism, leading to an upregulation of various renal metabolic pathways that utilize glucose and FAs, as well as parallel pathways involved in amino and nucleic acid production. In KPTC^GLUT2–/– mice, impaired renal glucose reabsorption may lead to increased food intake in order to maintain glucose demands, resulting in enhanced carbohydrate utilization. Despite this, these mice do not experience weight gain, but do exhibit higher fat mass composition and enhanced glucose uptake into adipose tissue, with no significant changes in TEE or fat oxidation.

Our study further identified a significant elevation in circulating, urinary, and renal levels of taurine, a key energy metabolic hub [36], in KPTC^GLUT2–/– mice. This elevation may underlie the observed increase in systemic CHO in these mice. Notably, intervention by inhibiting the taurine Na⁺/Cl⁻-dependent transporter, SLC6A6, using β-Alanine, a well-established SLC6A6 inhibitor [65,66], normalized CHO and abolished the improvements in systemic lipid profile. Similar findings were also found by a pair-feeding experiment in KPTC^GLUT2–/– mice. Taurine is primarily obtained from the diet, with meat products being a notable source. Additionally, it is synthesized in the liver. In KPTC^GLUT2–/– mice, liver taurine metabolism remains relatively unaltered, and therefore the observed elevation in taurine levels can be attributed to increased food consumption seen in these mice. Similar to KPTC^GLUT2–/– mice, the association between inhibited/reduced SGLT2 expression and elevated taurine levels were also found clinically in patients with primary renal glycosuria due to defect in the SGLT2 gene [67] as well as in patients with type 2 diabetes treated with Dapagliflozin [68]. Interestingly, reanalyzing our published metabolomics data in diabetic mice treated with Dapagliflozin [20] revealed increased renal and liver taurine levels following SGLT2 inhibition (Figure S7). Taurine may potentially play a role in osmoregulation during Na⁺ absorption; thus, downregulating SGLT2 expression due to KPTC-GLUT2 nullification enhances glycosuria, leading to reduced active Na⁺ reabsorption in these cells. However, compensatory mechanisms, such as increased taurine intake through the diet and elevated kidney expression levels of SLC6A6 help maintain active Na⁺ reabsorption, as evidenced by lower levels of urinary Na⁺ in KPTC^GLUT2–/– mice. This compensatory mechanism is likely mediated by mTORC1, which was found to be highly activated in the kidneys of KPTC^GLUT2–/– mice. However, additional studies measuring other key sodium transporters are needed to fully elucidate the mechanisms underlying this effect.

Taurine is an amino acid involved in various aspects of energy metabolism in different organs, including muscle, heart, liver (reviewed in [36]), adipose tissue [69,70], and brain [71]. Its decline with aging is associated with age-related diseases [72]. In mice deficient in taurine due to knockout of the taurine transporter SLC6A6 (TauT-KO), a reduction in body weight, skeletal muscle mass, and exercise capacity has been reported [[73], [74], [75]], accompanied by decreased FAO and increased glycolysis [75]. On the other hand, taurine supplementation has been reported to increase FAO in trained cyclists [58], increases lipolysis and FAO during exercise, and delay the decrease in blood glucose concentration [59]. In line with these reports, we found reduced glucose uptake in the skeletal muscle of KPTC^GLUT2–/– mice due to a metabolic rewiring from glycolysis to FAO, coupled by increased muscle taurine availability as seen by increased SLC6A6 expression. Taurine has also been shown to stimulate bile acid synthesis from cholesterol [60,76,77] and increase hepatic FAO [78,79], leading to reduced hepatic cholesterol and TG levels [80,81], circulating LDL levels [82], and increased HDL-to-LDL ratio; findings that were also found here in KPTC^GLUT2–/– mice. In the heart, taurine modulates Ca²⁺ homeostasis, acts as an antioxidant (reviewed in [83]), and promotes FAO [65,84], which is the preferred energy source for this organ [85]. Interestingly, the heart may shift to oxidize other substrates such as glucose or ketone bodies in order to adapt to environmental changes, such as substrate supply, and energy metabolism [30]. Furthermore, taurine has been shown to increase cardiac glucose levels [86]. These findings go hand in hand with the increased glucose uptake in the heart of KPTC^GLUT2–/– mice found here. Taurine also plays a role in brain function, acting as an osmoregulator and neuromodulator that can protect against mitochondrial dysfunction and inhibit neuronal apoptosis and inflammation (reviewed in [87,88]) as well as modulates metabolic neuronal homeostasis [71], and reducing age-related anxiety and memory loss [72]. In accordance with these reports, we also observed a link between high circulating taurine levels and elevated glucose uptake in the brain of KPTC^GLUT2–/– mice.

Other significantly elevated kidney metabolites may also contribute to the observed improvements in systemic energy metabolism in KPTC^GLUT2–/– mice. Notably, creatine plays a crucial role in energy metabolism and buffering across various organs, including skeletal and cardiac muscle, liver, kidney, adipose tissue, brain, immune cells, spermatozoa, and photoreceptors (reviewed in [35,89,90]). The beneficial effects of creatine supplementation, such as increased anaerobic energy capacity, reduced protein breakdown, and subsequent increases in muscle mass and physical performance, are well-documented in athletic populations [91]. Creatine also holds potential as a clinical and therapeutic supplement; for instance, creatine supplementation has been shown to reduce fat accumulation in models of fatty liver disease [[92], [93], [94]]. These positive effects were observed in both the muscle and liver of KPTC^GLUT2–/– mice. In the brain, creatine can be synthesized by neurons and oligodendrocytes [95] or taken up via the blood–brain barrier. Creatine supplementation has been found to improve cognitive function in cases of brain creatine deficiency and has shown benefits for conditions such as brain injury, concussion, and depression (reviewed in [96,97]). Furthermore, brain glucose uptake has been positively correlated with brain creatine levels under insulin clamp conditions in humans [98], which may explain the elevated brain glucose uptake in KPTC^GLUT2–/– mice.

Our findings suggest the potential for translating these results into therapeutic strategies for managing metabolic disorders by pharmacologically targeting GLUT2. However, GLUT2 plays a vital physiological role in various organs, including the intestine, pancreas, brain, and liver, and its inactivating mutations in humans results in Fanconi–Bickel syndrome, characterized by hepatomegaly, growth retardation, and renal syndrome [99]. Therefore, targeting KPTC-GLUT2 specifically may present significant challenges, given the essential function of GLUT2 in multiple organs. Firstly, targeting should be confined to the kidney. Secondly, while targeting proteins on the luminal or apical side of KPTCs may seem theoretically straightforward by utilizing exclusive targets such as megalin and SGLT2 [100], the basolateral side of KPTCs lacks distinctive molecules, posing a challenge for therapeutic targeting. Nonetheless, megalin-mediated endocytosis could facilitate the use of small, targeted molecules to inhibit the cytosolic portion of GLUT2 within KPTCs. Another concern should be the chronic activation of KPTC-mTORC1 as a result of glucose retention in the proximal tubules, as overactivation of mTORC1 has been related to the development of chronic kidney disease (CKD; reviewed in [101]), and has been shown by us to exacerbate kidney dysfunction and morphology disruptions in non-diabetic mice [13]. Moreover, high circulating taurine metabolites levels (e.g., taurine, hypotaurine, and NATs) were associated with the development of CKD in a cohort of 11,966 subjects of the EPIC-Norfolk study [72]. High renal levels of taurine were also found in a diabetic kidney disease mouse model [102]. Although this association does not establish causation, it may very well be that the taurine absorption machinery in the kidney, which involves mTORC1 signaling, is overactivated in CKD. Furthermore, the renal syndrome resulting from loss-of-function mutations in GLUT2, as seen in Fanconi–Bickel syndrome, is marked by glycosuria, aminoaciduria, hyperphosphaturia, hyperuricemia, and proteinuria [99], underscoring the potential risks associated with GLUT2 inhibition. In our model, the specific nullification of GLUT2 in KPTCs did not result in any morphological or functional alterations at 16 weeks of age, apart from a slight but significant elevation in proteinuria [13] and enhanced oxidative stress, which may indicate age-related deterioration. Therefore, while the inhibition of kidney-specific GLUT2 and taurine supplementation holds potential for treating metabolic disorders, it must be approached with caution.

mTORC1 serves as a central hub orchestrating the energy-conserving phenotype by integrating signals from growth factors, nutrients, and energy to regulate cellular functions and respond to metabolic stress [9]. The ECS is similarly associated with the ‘thrifty phenotype’ and energy preservation [[103], [104], [105]]. In our previous work, we demonstrated that mTORC1 activation in KPTCs can be facilitated through the activation of the CB₁R [13]. In this study, we observed elevated levels of AEA, an endogenous CB₁R agonist, in the kidneys of KPTC^GLUT2–/– mice, which was associated with reduced enzymatic activity of FAAH. Elevated AEA levels were also detected in the circulation, suggesting a potential role in contributing to the systemic energy-conserving phenotype observed in these mice.

CB₁R activation is known to stimulate adipogenesis [106,107], while its inhibition can prevent fat accumulation [108]. Indeed, high circulating AEA levels have been associated with increased body fat mass in mice during lactation [109], whereas decreased AEA levels in diabetic patients following caloric restriction correlate with reduced lipid accumulation in adipose tissue [110]. These adipogenic properties of AEA/CB₁R may contribute to the increased total fat mass in KPTC^GLUT2–/– mice. Elevated circulating AEA levels can also influence food intake, energy expenditure, and glucose uptake into adipocytes [[111], [112], [113], [114], [115]]. While the precise origin of the elevated circulating levels of taurine and AEA remains unclear, it is plausible to speculate, at this juncture, that they play a role in the systemic whole-body adaptation observed in the absence of GLUT2 in KPTCs.

In summary, our research offers the first and comprehensive insight into the effects of manipulating KPTC-GLUT2 in non-pathological conditions. The reduced glucose reabsorption and accumulation in the kidney lead to substantial changes in kidney and systemic energy metabolism. An increase in taurine levels via enhanced food intake and its increased reabsorption mediated by an mTORC1-dependent SLC6A6 upregulation process that occurs as a compensatory response to kidney Na⁺ absorption alongside elevated creatine and AEA levels may be the underlying mechanism that explains the energy-conserving phenotype observed in KPTC^GLUT2–/– mice. This response may result from adaptive changes to the broader metabolic shift and could underlie favorable systemic energy-metabolic outcomes, such as enhanced glucose uptake in highly metabolic organs, increased utilization of fat as an energy source in the muscle, and a decrease in harmful lipid levels in the liver and circulation.

CRediT authorship contribution statement

Majdoleen Ahmad: Methodology, Investigation, Formal analysis, Data curation. Anna Permyakova: Methodology, Investigation, Data curation. Saja Baraghithy: Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation. Nilanjan Sahu: Software, Methodology. Ifat Abramovich: Methodology, Formal analysis, Data curation. Bella Agranovich: Methodology, Formal analysis, Data curation. Ori Shalev: Methodology, Formal analysis, Data curation. Aviram Kogot-Levin: Writing – review & editing, Methodology, Formal analysis. Alina Nemirovski: Methodology, Formal analysis. Eyal Gottlieb: Methodology. Rinat Abramovitch: Methodology, Formal analysis, Data curation. Gil Leibowitz: Writing – review & editing, Methodology, Formal analysis. Liad Hinden: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Joseph Tam: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Financial support statement

This work was supported by the Israel Science Foundation (#158/18, #1266/24) and JDRF (1-INO-2022-1128-A-N) grants to J.T.

Declaration of competing interest

All authors declare no conflicts of interest related to the work reported in this paper.

Acknowledgments

We thank Asaf Kleiner for his technical support with the animal models.

Footnotes

Footnote Group

Contributor Information

Liad Hinden, Email: liad.hinden@mail.huji.ac.il.

Joseph Tam, Email: yossi.tam@mail.huji.ac.il.

Appendix A.Supplementary data

The following are the Supplementary data to this article:

Data availability

Data will be made available on request.

References

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Associated Data

Supplementary Materials

Data Availability Statement

Data will be made available on request.

Studies

Conditions

Cannabinoids and active compounds

Related research

Abstract

Objective

Methods

Results

Conclusions

Untitled section

Graphical abstract

Highlights

Article notes

Untitled section

Author notes

1.Introduction

2.Methods

2.1.Animals

2.2.Multi-parameter metabolic assessment

2.3.Pair-feeding experiment

2.4.SLC6A6 inhibition in mice

2.5.KPTCs-mTORC1 activation in mice

2.6.SGLT2 inhibition in mice

2.7.Biochemistry

2.8.Glucose tolerance test (GTT) and insulin tolerance test (ipITT)

2.9.LC-MS kidney metabolomics analysis

2.10.LC-MS liver metabolomics analysis

2.11.Cell culture

2.12.SGLT2 inhibition in KPTCs

2.13.mTORC1 inhibition in KPTCs

2.14.Real-time PCR

2.15.Western blotting

2.16.FAAH activity assay

2.17.Fluorescence immunohistochemistry

2.18.Sample preparation and measurements of endocannabinoids, N-arachidonoyl taurine, taurine, and creatine by LC-MS/MS

2.19.In vivo micro PET-MRI scanning

2.20.Statistical power calculations

2.21.Statistical analysis

3.Results

3.1.Impacts of inhibiting glucose reabsorption on glycemic control and systemic metabolism in normal mice

3.2.Systemic metabolic adaptation in KPTC-GLUT2 KO mice

3.3.Glucose retention in KPTCs leads to enhanced renal energy metabolism

3.4.Elevated energy metabolic hubs in the kidney of KPTCGLUT2–/– mice

3.5.Nullification of GLUT2 in KPTCs affects renal taurine reabsorption via an endocannabinoid-mTORC1 signaling pathway

3.6.Taurine and creatine mediate systemic changes in KPTCGLUT2–/– mice

4.Discussion

CRediT authorship contribution statement

Financial support statement

Declaration of competing interest

Acknowledgments

Footnotes

Footnote Group

Contributor Information

Appendix A.Supplementary data

Data availability

References

Untitled section

References

Associated Data

Supplementary Materials

Data Availability Statement

Additional materials

3.4.Elevated energy metabolic hubs in the kidney of KPTC^GLUT2–/– mice

3.6.Taurine and creatine mediate systemic changes in KPTC^GLUT2–/– mice