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. 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. [49]Image 1 [50]Open in a new tab 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. 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 [[51][1], [52][2], [53][3], [54][4]]. Furthermore, kidney erythropoietin synthesis has been found to regulate bone remodeling under diabetic conditions [[55]5], while the renal UTX-PHGDH-serine axis has been shown to regulate metabolic homeostasis [[56]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 [[57]7,[58]8]. However, under obese and diabetic conditions, KPTCs may shift their metabolic program towards glycolysis [[59][9], [60][10], [61][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 [[62]12]. Recently, we demonstrated that specific nullification of the GLUT2 in KPTCs improved diabetic kidney disease [[63]13], and restored kidney fatty acid oxidation (FAO) under diabetic conditions [[64]12]. Furthermore, non-diabetic KPTC-GLUT2 null mice showed reduced SGLT2 expression and increased glycosuria [[65]13]. Moreover, accumulating evidence has recently supported the regulatory role of GLUT2 in proximal tubule glucose and energy metabolism [[66][13], [67][14], [68][15], [69][16]], which may even extend to systemic effects [[70]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 [[71]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 [[72]18]) and the iL1-sglt2-Cre line [[73]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 O[2] and CO[2] was mathematically compensated. The respiratory exchange rate (RER) was calculated as the ratio between CO[2] produced (VCO[2]) and O[2] consumed (VO[2]) using Equation [74](1): [MATH: RQ=VCO2/VO2 :MATH] (1) Total energy expenditure (TEE) was calculated using VO[2] and RQ as shown in Equation [75](2): [MATH: TEE=VO2×3.815+1.232×RQ :MATH] (2) Fat oxidation (FO) and carbohydrate oxidation (CHO) were calculated using VO[2] and VCO[2], based on Equations [76](3), [77](4), respectively: [MATH: FO=1.69×VO2−1.69×VCO2 :MATH] (3) [MATH: CHO=4.57×VCO2−3.23×VO2 :MATH] (4) 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 [[78]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 [[79]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 [[80]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 [[81]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 [[82]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 [[83]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 [84]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 [[85]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, d[4]-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 [86]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 [[87]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 O[2] 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, [88]www.mmpc.org) using their Energy Expenditure Analysis page ([89]http://www.mmpc.org/shared/regression.aspx) and supported by grants DK076169 and [90]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 [[91]12,[92]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 [[93]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 [[94]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 [[95]13], there were no significant changes in body weight ([96]Figure S1A) and in fed or fasted plasma glucose levels ([97]Figure S1B, C) nor in glucose tolerance and insulin sensitivity ([98]Figure S1D-G). Interestingly, whereas these mice demonstrated normal systemic FAO ([99]Figure S1H and I) and total energy expenditure (TEE; [100]Figure S1J-L), a significant increased whole-body CHO during the day and night periods was noted ([101]Figure 1A,B), probably due to an increase in food intake ([102]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 1. [103]Figure 1 [104]Open in a new tab KPTC-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