Programmable Artificial Glucose-sensing Receptor for Autonomous Single-Cell Closed-loop Glycemic Control

Programmable Artificial Glucose-sensing Receptor for Autonomous Single-Cell Closed-loop Glycemic Control | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Programmable Artificial Glucose-sensing Receptor for Autonomous Single-Cell Closed-loop Glycemic Control zhou nie, Fang He, Meixia Wang, Yiyu Wang, Yuping Cai, Zheng-jiang Zhu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7115886/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Synthetic receptors enable programmable cellular functions, but their metabolism-regulating applications remain underexplored. Current synthetic cell strategies for glycemic control mimic pancreatic β-cell glucose-responsive insulin output to mediate peripheral glucose-uptake effector cells via multicellular closed-loop coordination, yet incurring delayed responses and limited efficacy under insulin resistance. Herein, we present a de novo-designed artificial glucose-sensing receptor (AGSR) enabling glucose-uptake effector cells (hepatocytes/myocytes) to sense glucose directly and achieve autonomous single-cell closed-loop glycemic regulation. AGSR is formed through equipping a cell-wearable glucose-regulating DNA nanodevice (CWGN) onto endogenous c-Met receptors, integrating glucose sensing, threshold-based decision-making, and c-Met-mediated metabolism-modulating actuation within a CWGN-built-in DNA molecular circuit. AGSR exhibits precise hyperglycemia-specific responsiveness, minute-level activation of glucose uptake, and sustained efficacy in insulin-resistant settings due to its insulin receptor-independence. In type 1 and type 2 diabetic mice/dog models, AGSR significantly improves glucose tolerance without hypoglycemia risk, highlighting the potential of DNA nanotechnology-based precision treatment of metabolic disorders. Physical sciences/Nanoscience and technology/DNA nanotechnology Biological sciences/Chemical biology/DNA Biological sciences/Cell biology/Cell signalling Biological sciences/Chemical biology/Synthetic biology Physical sciences/Engineering/Biomedical engineering Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Main Engineering cellular sensing capabilities to enable biomarker-driven diagnostic and therapeutic outputs holds significant potential for precision medicine [1, 2, 3] . An important strategy to achieve this goal is synthetic receptor engineering, which endows cells with customizable input recognition and programmable signaling responses [4, 5, 6] , exemplified clinically by chimeric antigen receptor (CAR) T cells [7] . While synthetic receptors have greatly advanced applications in cancer immunotherapy and autoimmune disorder treatments [7, 8] , their development for metabolic regulation remains nascent. This underscores an urgent need to develop novel synthetic receptor platforms capable of restoring or maintaining metabolic homeostasis. Glucose metabolism plays a central role in human metabolic networks, with systemic homeostasis maintained through multi-organ closed-loop regulation [9, 10] . Pancreatic β-cells act as glucose-sensing hubs, detecting glycemia and secreting insulin to direct peripheral effector cells (hepatocytes/myocytes) to promote glucose uptake and storage [11] . Dysfunction in this axis leads to diabetes mellitus (DM), either through β-cell destruction (type 1 diabetes, T1D) [12] or insulin resistance in effector tissues (type 2 diabetes, T2D) [13] . Current glucose-responsive synthetic β-cell strategies mimic β-cells’ metabolism-dependent pathway by coupling glucose metabolism to insulin transgene expression [14, 15] . However, these systems are constrained by delayed response kinetics (hour-scale transcriptional activation) and the inability to address insulin resistance [16, 17, 18] . While translational-level switches enable faster insulin release, these synthetic cell designs lack glucose responsiveness for closed-loop glycemic regulation [19, 20] . Notably, emerging evidence reveals glucose-sensing receptors (GSR) [21] , e.g. T1R2/T1R3 receptors [22] and ADGRL1 receptors [23] , involved in metabolism-independent rapid glycemia detection. However, their limited understanding and intrinsic constraints, including promiscuous ligand selectivity, undefined glucose-binding kinetics, and incomplete mapping of downstream signaling, hinder their application in synthetic closed-loop glucose regulation. Herein, we report a de novo -designed artificial glucose-sensing receptor (AGSR) to directly transform effector cells (hepatocytes/myocytes) into self-contained closed-loop glycemic regulators. Unlike natural GSRs, AGSR adopts a semi-synthetic DNA-protein biohybrid architecture featuring a molecularly defined cell-wearable glucose-regulating DNA nanodevice (CWGN) capable of selectively attaching to endogenous cell-surface receptors to reprogram their function for glucose-responsive signaling. CWGN enables plug-and-play receptor functionalization via reversible integration, allowing in situ on-demand assembly of AGSR on effector cells without genetic engineering, which is functionally analogous to human-wearable glycemic-controlling devices (e.g., artificial pancreas). In contrast to macroscopic wearables that physically couple discrete components (glucometer/algorithm processor/insulin pump) [24] , CWGN exploits dynamic DNA nanotechnology to miniaturize the glucose sensing, threshold-based decision-making, and metabolism-regulating actuation within a single DNA nanomachine to customize hepatic/myocytic receptor-mediated quick glucose uptake with precisely tunable glycemic-responsive thresholds. To address three critical challenges in conventional insulin-dependent synthetic cell strategies for diabetes management, including therapeutic inefficacy in insulin-resistant T2D, delayed response kinetics due to insulin gene expression, and hypoglycemia risks from insulin overdosing, we propose three targeted principles in AGSR design: (1) a DNA-based receptor-signaling agonism mechanism that bypasses insulin receptor (IR) dependence to directly stimulate glucose uptake, overcoming insulin resistance in T2D; (2) an effector cell-targeted DNA nanodevice integrating a synthetic closed-loop molecular circuit that directly couples glucose sensing to receptor signaling, enabling minute-level rapid glucose uptake response; (3) a threshold-tunable, concentration-responsive molecular mechanism ensuring precise hyperglycemic activation to eliminate hypoglycemic risks. We demonstrate that AGSR can improve glucose tolerance without causing hypoglycemia risk not only in mice models of both type 1 and type 2 diabetes, but also in a diabetic dog model, a large animal model highly relevant to human pathophysiology. This work establishes a novel synthetic strategy for intelligent homeostasis control, holding great promise for precision cellular therapeutics. Results Design of the AGSR Figure 1 presents a schematic illustration of AGSR-mediated glucose regulation. Unlike existing genetic-engineered synthetic cell or electronic wearable strategies that functionally mimic pancreatic β-cells to reconstruct insulin-mediated glucose sensor-effector multicellular close-looped glucose-regulating circuits, our strategy nongenetically equips glucose-uptake effector cells (hepatocytes/myocytes) with synthetic CWGN nanodevices to form AGSRs that directly enables them to function as single-cell autonomous glycemic-regulators with a complete glucose sense-decide-actuate closed-loop. The AGSR rewires endogenous receptor-mediated glucose metabolism to hyperglycemia-induced responsiveness via artificial receptor reprogramming. As a proof-of-concept, we target CWGN to hepatocyte growth factor receptor (c-Met), an RTK with a kinase domain structurally analogous to that of the IR [25] . c-Met signaling can modulate glucose uptake and metabolic flux in glucose-uptake effector cells (hepatocytes/myocytes) [26, 27, 28, 29, 30] , making it a promising candidate for compensatory glucose regulation in insulin-resistant T2D. While native and engineered c-Met receptors are glucose-independent, we rationally design a glucose-stimulated functional DNA structure-switch to trigger cascade DNA dynamic reactions in AGSR, mediating c-Met activation. This establishes a new interplay between external glycemic level and endogenous c-Met receptor-mediated glucose-uptake signaling via dynamic DNA nanotechnology. CWGN is a bi-modular nanodevice comprising a sensing-and-decision-making (SD) subunit and an actuation (A) subunit, which are “worn” on living cells to form two functionally distinct AGSR monomers via specific anchoring of their receptor-targeted aptameric regions on c-Met. The SD subunit integrates three key functions: (1) glucose sensing via a recognition aptamer strand (R G ) [31] , (2) glycemic level threshold analysis through a concentration-dependent structure switch in the trans-duplex aptamer region (R G /H S duplex), and (3) a receptor-activation initiator (the toehold part of H S caged by R G ), which is conditionally activated by glucose-induced conformational changes to interact with the A module (Supplementary Fig. 1 and Supplementary Table 1). Upon hyperglycemia, CWGN is activated by glucose-binding-induced structural change in the trans-duplex aptamer region, releasing R G and unmasking the toehold of H S . This initiates a toehold-mediated strand displacement reaction between SD and A, leading to the hybridization of receptor-hooking strands (H S and H A ) and displacement of blocking strands (B S and B A ). This glucose-induced heterodimerization of SD and A brings two c-Met receptors into proximity, inducing AGSR activation by c-Met autophosphorylation-triggered downstream signaling cascades to regulate glucose uptake and metabolism (Fig. 1b and Fig. 3a). Like the reversible wearability of human-wearable devices, CWGN can be removed from cells via strand displacement, providing a safety latch to modulate or deactivate AGSR functionality. Thus, AGSR represents a bottom-up approach to create a closed-loop engineered receptor activated by hyperglycemia to restore glucose homeostasis through endogenous metabolic regulation. Regulation of Glucose Metabolism by DNA Aptameric Motif Establishing AGSR necessitates the development of functional nucleic acid actuators for regulating non-insulin-receptor-dependent glucose metabolism, a biochemical bottleneck that remains unexplored. We therefore first investigated whether the dimeric c-Met-specific aptamer [32, 33, 34] , the key output structure in CWGN's glucose-responsive cascade, can activate glucose uptake signaling and subsequent metabolic reprogramming. Using 2-deoxyglucose (2-DG) uptake assays in c-Met-high Buffalo Rat Liver (BRL-3A) cells, we observed that 50 nM aptameric dimer triggered a 19.3-fold glucose uptake enhancement, comparable to the effect of HGF, the native ligand of c-Met (20.8-fold) (Fig. 2a). Given that glucose transporter 2 (GLUT2) constitutes a major portion of insulin-stimulated hepatic glucose uptake which is switched on by its membrane translocation [10] , we assessed its redistribution via immunofluorescence staining with an antibody that specifically recognizes the extracellular domain of GLUT2, ensuring detection of membrane-localized GLUT2 without cell permeabilization. Confocal laser scanning microscopy (CLSM) imaging and flow cytometry analysis showed an 83% increase in membrane GLUT2 in the aptameric dimer-treated group, comparable to HGF (85%) (Fig. 2b, Supplementary Fig. 2). In-cell western analysis revealed sequential phosphorylation of c-Met, insulin receptor substrate 2 (IRS2), and protein kinase B (Akt), confirming aptameric dimer-induced activation of IRS2 and downstream Akt kinase, the key nodes of glucose-uptake signaling (Fig. 2c, Supplementary Fig. 3). Phosphorylated Akt inhibitor MK2206 abolished aptameric dimer-induced GLUT2-mediated glucose uptake (Fig. 2d), demonstrating that the aptameric dimer stimulates glucose uptake via the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway, analogous to the signaling mechanism of HGF and even insulin [30] . Parallel experiments in C2C12 myoblasts verified aptameric dimer's capacity to activate Met-Akt signaling, driving glucose transporter 4 (GLUT4)-mediated glucose uptake in muscle cells (Extended Data Fig. 1). Collectively, these results established the aptameric dimer as a functional nucleic acid capable of initiating insulin-independent Met-Akt signaling to enhance GLUT2/4 translocation for glucose uptake in hepatic and muscular effector cells. Given the aptameric dimer-induced glucose uptake could reshape intracellular metabolism, we systematically profiled the metabolic alterations using liquid chromatography-mass spectrometry (LC−MS)-based untargeted metabolomics in BRL-3A cells. 391 identified metabolites were used for subsequent statistical analyses. Principal component analysis (PCA) revealed profound differences in the cellular metabolome between the treatment groups (aptameric dimer or insulin) and the control (Fig. 2e). Strikingly, the aptamer dimer recapitulated 86% of insulin's metabolic shifts (61/71 dysregulated metabolites: 13 up-regulated, 48 down-regulated), including congruent upregulation of nucleotide derivatives (IMP/uridine/cytidine/UMP) and downregulation of glucose derivatives, gluconeogenic precursors (pyruvate/lactate), and glucogenic amino acids (glycine, histidine, tryptophan, etc.) (Fig. 2f-g, Supplementary Fig. 4). Pathway enrichment analysis demonstrated coordinated upregulation of pyrimidine/purine metabolism and downregulation of multiple pathways, including glycolysis/gluconeogenesis and glycine-serine-threonine pathways (Fig. 2h). Moreover, the aptameric dimer downregulated mRNA levels of gluconeogenic enzymes phosphoenolpyruvate carboxykinase 1 ( Pck1 ) and glucose 6-phosphatase ( G6pc ) (Fig. 2i and Supplementary Table 2), mirroring insulin's transcriptional repression of gluconeogenic enzymes [35] . Notably, Periodic Acid-Schiff (PAS) staining of intracellular glycogen deposition showed that the aptameric dimer significantly enhanced glycogen biosynthesis, with the aptameric dimer (10 nM) achieving similar efficacy to insulin (50 nM) (Fig. 2j, Supplementary Fig. 5). These results demonstrate that the aptameric dimer mimics insulin's metabolic regulatory functions by promoting glucose uptake, suppressing gluconeogenesis, and enhancing glycogen storage, providing a novel insulin-independent metabolism-regulating motif for AGSR development. Constructing CWGN for AGSR Engineering We next constructed an autonomous CWGN by splitting the metabolic-regulatory aptameric dimer to integrate with the glucose-responsive SD and A modules, respectively. SD and A subunits, bearing c-Met-specific aptameric monomers, were selectively anchored on effector cells (BRL-3A/C2C12) surfaces to form AGSR through c-Met targeting, but were unable to functionalize c-Met-negative NIH/3T3 cells (Extended Data Fig. 2). Glucose binding to SD's aptamer region (R G ) induced allosteric switch-triggered cascade of strand displacement between SD and A, inducing c-Met agonistic dimer formation (Fig. 3a). Dual-fluorophore tracking via live-cell CLSM imaging revealed glucose-responsive dynamics of AGSR: glucose recognition by AGSR induces FAM-tagged R G release, causing remarkable cell-surface FAM signal decay (glucose-sensing readout), and a sequential cascade reaction to form dimerizing motifs (Cy3-H S /Cy5-H A ) for c-Met agonism, indicated by a significant increase in the Cy5/Cy3 fluorescence ratio (glucose-actuation readout) within 10 minutes in CWGN-equipped BRL-3A cells (Fig. 3b, Extended Data Fig. 3a-b and Supplementary Table 3). Flow cytometry analysis confirmed these results (Extended Data Fig. 3c), while mutant CWGN with scrambled R G sequence abolished glucose responsiveness (Supplementary Fig. 6). To further confirm that the glucose-responsive AGSR activation, we identified that glucose addition caused 5.2-fold-enhanced c-Met phosphorylation (Y1234/Y1235) in the AGSR-engineered cells versus controls using immunofluorescence flow cytometry (Extended Data Fig. 4a-b), with strict glucose specificity over various sugar analogs and other metabolites (Fig. 3e and Extended Data Fig. 4c). Thus, CWGN can be worn on glucose‑uptake effector cells, coupling extracellular glucose sensing to intracellular c‑Met signaling as the desired AGSR output. To achieve reversible wearability, each CWGN subunit includes an extended toehold domain in its receptor-anchoring motif for detachment. Glucose-stimulated AGSR activation can be reversed by the specifically complementary strand (C H ) via strand displacement, detaching CWGN from cells to deactivate AGSR functionality (Extended Data Fig. 5a and Supplementary Table 1). CLSM imaging and flow cytometry confirmed the removal of CWGN after C H treatment (Fig. 3c and Extended Data Fig. 5b-c). C H treatment dose-dependently attenuated and finally abolished glucose-responsive AGSR signaling (Fig. 3d and Extended Data Fig. 5d), highlighting the controllable detachability as a safety mechanism to flexibly modulate and deactivate AGSR. AGSR -Driven Glucose Uptake Regulation We further evaluated the downstream signaling and glucose uptake regulation mediated by AGSR. In-cell western analysis confirmed glucose-dependent activation of the Met-Akt pathway in the CWGN-equipped cells (Fig. 3f and Extended Data Fig. 6a-b), while non-treated or scrambled mCWGN-equipped cells showed no response (Extended Data Fig. 6c). Given that PI3K/Akt signaling promotes GLUT4 trafficking to the cell membrane, we transfected AGSR-engineered cells with a GLUT4-EGFP [36] fusion construct to monitor GLUT4 translocation at the single-cell level. Structured illumination microscopy (SIM) imaging revealed glucose-stimulated GLUT4 membrane translocation in CWGN-equipped cells, confirming functional coupling between the AGSR activation and endogenous trafficking machinery (Fig. 3g and Extended Data Fig. 7). Furthermore, live-cell CLSM imaging demonstrated rapid AGSR activation within 2 minutes, followed by noticeable GLUT4 membrane translocation starting at 2 minutes, peaking at 4 minutes (Fig. 3i and Supplementary Fig. 7). A 2-DG uptake assay revealed a rapid onset of the glucose uptake response, beginning at just 2 minutes. After 30 minutes of glucose treatment, these AGSR-engineered hepatic BRL-3A cells exhibited a remarkable 19.3-fold enhancement in glucose internalization (Fig. 3h and Supplementary Fig. 8). Similarly, glucose enhanced AGSR-mediated glucose uptake in CWGN-equipped C2C12 skeletal muscle cells via the Met-Akt pathway (Extended Data Fig. 8). Thus, AGSR integrates glucose sensing with endogenous cellular signaling in effector cells, regulating rapid glucose uptake in a closed-loop manner. AGSR with Tunable Glucose Sensitivity One key feature of AGSR is its built-in, dose-responsive decision module that programs glucose-sensing thresholds to activate glucose uptake. To achieve this goal, we precisely tuned glucose-binding affinity of AGSR by rationally modulating the stability of trans-duplexed aptamer region (R G /H S duplex) via systematic truncation of the allosteric inhibition domain [37] (ID, yellow segment of H S , 10-18 nt) (Fig. 4a, Supplementary Fig. 9 and Supplementary Table 4). The dose-response curve, generated by measuring phosphorylated Met via immunofluorescence flow cytometry, revealed that increasing ID length shifted receptor activation dynamics. AGSR with short ID (<14 nt) induced basal activation leakage due to suboptimal duplex stability, while AGSR with 14-18 nt IDs achieved glucose-threshold-gated responses with half-maximal concentration ( EC 50 ) values of 6.7, 8.2, and 10.3 mM, respectively. Notably, the AGSR with 14 nt ID exhibited the largest dynamic range (7.4-fold) (Fig. 4b, Supplementary Fig. 10 and Supplementary Table 5). Moreover, downstream Akt phosphorylation profiles indicated that AGSR with long ID (>14 nt) exhibited less than 50% of the maximal activation response under hyperglycemic conditions (> 11.1 mM glucose), while the AGSR with 14 nt ID showed 80% activation at hyperglycemia, and negligible activity below normoglycemia (5.6 mM) (Fig. 4c and Supplementary Fig. 11). Further functional validation using myotube models differentiated from C2C12 myoblasts revealed that AGSR with 14 nt ID regulated 2-DG uptake of myotubes with a threshold-gated dose-response profile, switching on above normoglycemia (5.6 mM) and peaking at hyperglycemia (> 11.1 mM) with an EC 50 of 7.8 mM (Fig. 4d and Supplementary Fig. 12). Interestingly, this mirrored c-Met/Akt signaling activation responses but with a narrower dynamic range, demonstrating the potential for precise glycemic control with reduced hypoglycemia risk. Given these results, AGSR with a 14 nt ID was selected for in vivo studies. Together, AGSR established a synthetic thresholding framework to precisely regulate glucose uptake with fine-tuned dynamic range. AGSR-Mediated Glucose Homeostasis Regulation in T1D and T2D Mice Before in vivo evaluation of AGSR-mediated glycemic control in diabetic animal models, we assessed its biosafety, stability, and targeting capability. CWGN treatment did not affect cell viability in BRL-3A and C2C12 cells (Fig. 5a and Extended Data Fig. 9a). In mice receiving 3 nmol CWGN, liver damage markers remained unchanged at 24 hours (P > 0.05) (Fig. 5a), and histological analysis (H&E staining) of major organs (heart, liver, spleen, lung, kidney, muscle) showed no damage (Extended Data Fig. 9d). Furthermore, even after prolonged incubation in serum medium for up to 12 hours, the cell binding activity of CWGN remained unaffected, indicating high stability (Extended Data Fig. 9b-c). Intravenous injection of Cy5-labeled CWGN (0.5 nmol) revealed predominant accumulation in the liver and muscles, attributed to their high c-Met expression, confirming its effector cells-targeting capability (Fig. 5b, Extended Data Fig. 9e-f and Supplementary Table 6). These results demonstrated that CWGN is biocompatible, stable, and tissue-selective, validating its readiness for in vivo glycemic regulation. We further validated AGSR's glycemic regulation capability in streptozotocin (STZ)-induced T1D mice [38] , where STZ-caused pancreatic β-cell destruction abolished endogenous insulin production. Male C57BL/6 mice receiving four STZ doses (50 mg/kg) on alternating-day developed hallmark diabetic phenotypes including 6.8% body weight loss, an increase in fasting blood glucose levels (BGL) from 6.64 mmol/L to 16.32 mmol/L, and impaired glucose tolerance shown by intraperitoneal glucose tolerance tests (IPGTT) (Extended Data Fig. 10a-e). CWGN administration (0.5 nmol) in these T1D mice significantly improved glucose homeostasis compared to scrambled mCWGN controls, evidenced by a 16% decrease in maximum BGL amplitude, a 1.3-fold reduction in the area under the curve (AUC) of IPGTT within 120 min, and a 20.9-fold greater glucose-lowering efficiency under hyperglycemic conditions (Fig. 5c-d and Supplementary Fig. 13). Notably, CWGN did not induce significant hypoglycemia under normoglycemic conditions due to its threshold-gated response, unlike insulin treatment with a rapid BGL decline to 2.5 mmol/L, leading to fainting (Fig. 5e). Furthermore, hypoglycemic index (HI) [39] quantification confirmed CWGN's superior safety with 6.8-fold smaller HI versus insulin (Fig. 5f), indicating its significantly lower risk of hypoglycemia. These findings demonstrated that CWGN's ability to effectively regulate blood glucose levels and improve glucose tolerance in T1D mice while minimizing hypoglycemia risk. T2D, accounting for over 90% of diabetes cases, primarily arises from insulin resistance in effector cells [40, 41] . We next sought to demonstrate that AGSR could circumvent insulin insensitivity by directly enhancing glucose uptake via the non-canonical Met-Akt pathway. In palmitate-treated BRL-3A cells modeling insulin resistance [42] , insulin-stimulated 2-DG uptake was reduced by 88.3%, whereas AGSR maintained 91.3% uptake capacity versus controls, demonstrating its efficacy in insulin-resistant cells (Fig. 5g). To validate the therapeutic efficacy of AGSR in vivo , we established a T2D mouse model [43] by treatment with STZ (50 mg/kg) on three alternating days and high-fat/high-sugar feeding for 2 months. Successful modeling of T2D mice with insulin resistance was confirmed by an increase in the mice's weight (21.02 to 22.49g), an increase in fasting BGL (6.02 to 14.07 mmol/L), and marked reduction in insulin sensitivity indicated by insulin tolerance tests (ITT) (Fig. 5h and Extended Data Fig. 10f-j). AGSR-engineered mice exhibited 24.7% lower AUC than mCWGN controls in IPGTT, demonstrating robust glycemic control of AGSR in T2D models (Supplementary Fig. 14). Dose-dependent efficacy of CWGN was evidenced by progressive attenuation of post-injection hyperglycemia, accelerated glucose clearance, and reduced AUCs of IPGTT (Fig. 5i-j). To assess continuous glycemic control, we performed three IPGTTs after a single CWGN administration (3 nmol) to stimulate glycemic fluctuations by daily tri-meal. Results showed that AGSR maintained effective glucose control across three sequential glucose challenges, achieving a 29.5% lower cumulative AUC versus controls, indicating sustained glycemic regulation throughout the three meals in T2D mice (Fig. 5k and Supplementary Fig. 15). Collectively, AGSR offers a novel therapeutic modality for durable glycemic regulation through insulin-independent pathways, directly addressing insulin-resistant dysregulation in T2D. AGSR Efficacy in Diabetic Dog s Large animal models, particularly diabetic dogs, offer critical translational insights into human diabetes pathophysiology due to conserved glycemic regulatory mechanisms and phenotypic fidelity [44] . We further extended functional validation of AGSR to alloxan (ALX)-induced diabetic beagles [45] , a dog model simulating human T1D progression through β-cell destruction. In vitro , AGSR activated Met/Akt-dependent 2-DG uptake in dog-derived c-Met-positive MDCK cells (Fig. 6a-c), confirming its cross-species efficacy, likely attributable to evolutionary conservation of its glucose regulatory mechanism across mammalian species. For in vivo assessment, we successfully established the diabetic beagle model, confirmed by a significant fasting BGL increase from 3.04 to 24.08 mmol/L, accompanied by inter-individual body-weight fluctuations (11.1 to 10.46 kg) consistent with ALX-induced early‑stage T1D dog phenotypes (Fig. 6d-f). Intravenous glucose tolerance tests (IVGTT) were conducted after intravenous injection of CWGN (20 nmol). AGSR significantly reduced peak post-glucose levels by 40.1% versus controls (12.12 vs 20.24 mM, P = 0.0015) and a 44.8% reduction in the 120-min AUC (1179.4 vs 2137 mM·min), indicating significantly improved glucose tolerance (Fig. 6g-i). Notably, AGSR maintained glycemic stability under normoglycemia, with a hypoglycemic index 8.6-fold lower than insulin (Fig. 6j). These results highlight the AGSR's potential for robust glycemic control without causing hypoglycemia, validated in a clinically relevant large animal model. Discussion In summary, we present a de novo design strategy to engineer glucose-uptake effector cells with artificial glucose-sensing receptors (AGSRs). This approach establishes a glucose sensing-uptake closed-loop at the single-cell level, distinct from conventional multicellular coordinated systems relying on pancreatic β-cell sensing and insulin-mediated effector cells regulation [11] . To achieve this, we developed non-genetic DNA-protein semi-synthetic AGSRs via rational integration of glucose-responsive DNA nanodevices to endogenous uptake-regulatory receptors, circumventing the poorly understood glucose-sensing mechanisms of the natural counterparts. Furthermore, AGSRs incorporate a highly specific glucose-recognition aptameric module, overcoming the promiscuous ligand selectivity of natural glucose-sensing receptors. Moreover, AGSR provides a closed-loop glycemic regulation solely implemented by effector cells. This novel strategy potentially addresses three key problems in traditional glycemic-regulating approaches. First, AGSR circumvents insulin resistance by activating alternative RTK pathways (e.g., c-Met) to drive glucose uptake in insulin-desensitized cells. Second, AGSR directly activates effector cell glucose uptake and downstream metabolism, enabling a rapid response within 2 minutes, outperforming both synthetic cells relying on insulin-gene-expression (≥1 h) and translation-regulated insulin production (≥30 min) [16, 17, 19] . Third, AGSR allows precise tuning of glucose-response thresholds via rational DNA molecular engineering, as shown by adjustable c-Met activity, Akt signaling, and glucose uptake (Fig. 4), along with hyperglycemia-specific activation in diabetic models (Fig. 5d and Fig. 5e). Both indicated the substantially improved safety of AGSR by mitigating hypoglycemia risks. Furthermore, the cross-species efficacy of AGSR was validated across T1D/T2D models in mice and dogs, further demonstrating its universal physiological compatibility. Our non-genetic, plug-and-play strategy uses CWGNs to assemble AGSRs directly in effector cells, enabling reversible, controllable, and gene-editing-free therapeutic installation. This allows single-cell-level closed-loop glucose regulation, transforming the conventional "monitor-and-treat" paradigm into an intracellular synthetic circuit. Additionally, the AGSR is highly modular, and its signaling-actuation motifs are compatible with FGFR aptamers and even recently reported insulin-receptor-specific aptamers if insulin resistance circumvention is non-obligatory [46, 47] . Crucially, our AGSR presents a proof-of-concept of DNA nanotechnology-enabled programmable cellular regulator, opening an avenue for engineering artificial receptor-based cell-autonomous therapeutics beyond diabetes. For instance, replacing glucose aptamers with lipid/creatinine sensors could engineer "cellular wearables" targeting hepatic steatosis or renal disorders [48, 49] , while dual-input logic gates (e.g. protein biomarker and pH) might address cancer-associated acidosis, coupled with development of corresponding DNA signal-activating modules to achieve feedback-controlled activation of therapeutic artificial receptor-mediated signaling pathways. Looking forward, future efforts will focus on improving AGSR’s stability, CWGN’s targeting-specificity, and pharmacokinetics for chronic administration, alongside integrating multiplexed biosensing for systemic metabolic regulation, which is crucial for realizing programmable cellular therapeutics. In summary, in vivo equipping desired cells with therapeutic artificial receptors via cell-wearables will provide new chemical biological toolkits for next-generation precision therapy, in which synthetic circuits symbiotically interface with native physiology. Declarations Data availability All data supporting the findings of this study are available within the article and its Supplementary Information. Source data are provided with this paper. Acknowledgments We thank Z.-J. Zhu and Y. Cai (Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences) for their technical support in the LC−MS-based untargeted metabolomics and data analysis. We thank N. Cai (Cellway Biotechnology Co., Ltd) for technical discussions in the construction of EGFP-GLUT4 and diabetic mice model. We thank the Analytical Instrumentation Center of Hunan University for Structured Illumination Microscopy (SIM). This research was supported by the National Key Research and Development Program of China (2024YFA0916700 to N.Z.), the National Natural Science Foundation of China (22034002 and 92253304 to N.Z., 22177030 to H.h.W., 22425404 to Z.-J. Z., 22407044 to F.H.), National Key R&D Program of China (2022YFC3400702), Shanghai Key Laboratory of Aging Studies (19DZ2260400), Shanghai Municipal Science and Technology Major Project, and Shanghai Basic Research Pioneer Project. Author contributions Z.N. conceived and designed the project. F.H., H.h.W. and Z.N. designed, and F.H. performed the experiments. Z.-J. Z and Y.p.C. provided technical assistance for untargeted metabolomics-related experiments. F.H., M.W, Y.W., H.h.W. and Z.N. analyzed the data. Z.N., H.h.W, and F.H. wrote the manuscript and supervised the project. All authors read and commented on the manuscript. Competing interests The authors declare no competing interests. References Kojima, R., Aubel, D. & Fussenegger, M. 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Palmitate induces insulin resistance in human HepG2 hepatocytes by enhancing ubiquitination and proteasomal degradation of key insulin signaling molecules. Arch. Biochem. Biophys . 566 , 26-35 (2015). Kleinert, M. et al. Animal models of obesity and diabetes mellitus. Nat. Rev. Endocrinol. 14 , 140-162 (2018). Lutz, T. A. Mammalian models of diabetes mellitus, with a focus on type 2 diabetes mellitus. Nat. Rev. Endocrinol. 19 , 350-360 (2023). Engerman, R. L. & Kramer, J. W. Dogs with induced or spontaneous diabetes as models for the study of human diabetes mellitus. Diabetes 31 , 26-29 (1982). Ueki, R. et al. DNA aptamer assemblies as fibroblast growth factor mimics and their application in stem cell culture. Chem. Commun. (Camb) 55 , 2672-2675 (2019). Yunn, N.-O. et al. An aptamer agonist of the insulin receptor acts as a positive or negative allosteric modulator, depending on its concentration. Exp. Mol. Med. 54 , 531-541 (2022). Tian, L. et al. Albumin-binding lipid-aptamer conjugates for cancer immunoimaging and immunotherapy. Sci. China Chem. 65 , 574-583 (2022). Das, C. et al. Selective and naked eye colorimetric detection of creatinine through aptamer-based target-induced passivation of gold nanoparticles. RSC Adv. 14 , 33784-33793 (2024). Methods Oligonucleotides The oligonucleotides used for constructing and characterizing the cell-wearable glucose-regulating nanodevice (CWGN) (detailed sequences listed in Supplementary Tables 1, 3, 4), and quantitative real-time PCR experiments (detailed sequences listed in Supplementary Table 2) were custom-synthesized by Sangon Biotech Co., Ltd. The oligonucleotides for animal and biodistribution experiments (Supplementary Table 1, 6) were custom-synthesized by Shanghai DNA Bioscience Co. Ltd. Cell culture and transfection All cell lines were cultured in a 5% CO 2 incubator (Thermo Fisher, USA) at 37 ℃. BRL-3A cells (Servicebio, cat. no. STCC30016) were cultured in a specialized medium (Servicebio, cat. no. STCC30016P). C2C12 cells (ATCC, cat. no. CRL-1772), HepG2 (ATCC, cat. no. HB-8065), HEK293T (ATCC, cat. no. CRL-3519), NIH/3T3 cells (ATCC, cat. no. CRL-1658) and MDCK cells (ATCC, cat. no. CCL-34) were cultured in DMEM with 10% FBS (Biological Industries, cat. no. 04-001-1A) and 1% penicillin and streptomycin (NCM Biotech, cat. no. C125C8). To visualize the GLUT4 translocation, a GLUT4-EGFP plasmid was constructed by fusing the carboxyl terminal of GLUT4 with the coding sequence of Enhanced Green Fluorescent Protein (EGFP) as described by Dobson et al. [36] . HEK293T cells and HepG2 cells were transfected with the EGFP-GLUT4 plasmid using Lipo8000 (Beyotime, cat. no. C0533) transfection reagent according to the manufacturer's protocol. Afterward, the cells were incubated with 200 nM CWGN in HEPES buffered saline solution for 10 minutes. Real-time live-cell images were collected at 488 nm and 561 nm with CLSM (Nikon Ti-E controlled by NIS Elements AR) using a 60× oil immersion objective after adding 10 mM glucose. Glucose u ptake a ssays Glucose uptake was detected with the Glucose Uptake-Glo™ Assay kit (Promega, J1343) according to the manufacturer’s instructions. One day prior to the assay, the medium was removed and replaced with 100 μL DMEM without serum. On the day of the assay, the medium was replaced with 100 μL PBS containing aptameric dimer and incubated for 30 minutes at 37°C in 5% CO 2 . The medium was then removed and 50 μL of 0.1 mM 2-DG in PBS was added and incubated for 10 minutes at 25 °C. Next, 25 μL of Stop Buffer was added, followed by brief shaking and addition of 25 μL Neutralization Buffer. Finally, 100 μL of 2DG6P Detection Reagent was added, shaken briefly and incubated for 1 hour at 25 °C. Luminescence was recorded on a SynergyTM Mx multi-mode microplate reader (BioTek, USA). Measurement of plasma membrane GLUT2/4 by immunofluorescence and flow cytometry The effects of aptameric dimer and HGF on glucose transporter GLUT2/4 in glucose-uptaking cells (hepatocytes/myocytes) were evaluated through immunofluorescence [50] . BRL-3A and C2C12 cells were seeded to confocal dishes and starved in medium containing 0.2% FBS for 24 hours. Cells were then stimulated with 50 nM aptameric dimer and 1 nM HGF in PBS at 37 °C for 30 minutes, and subsequently fixed with 4% paraformaldehyde for 30 minutes. Samples were incubated in 5% normal goat serum in PBS for 30 minutes at room temperature, then incubated with primary antibody overnight at 4 °C. After rinsing, samples were incubated with a fluorochrome-conjugated secondary antibody for 1 hour at 37°C in the dark. The primary antibodies of GLUT2 Polyclonal antibody, (cat. no. 20436-1-AP, 1:500) and GLUT4 Monoclonal antibody (cat. no. 66846-1-Ig, 1:500) were obtained from Proteintech. The Goat anti-Rabbit IgG (H+L) Secondary Antibody, Alexa Fluor 594 (cat. no. AWS0006, 1:1000) was purchased from Abiowell and the Rabbit anti-Mouse IgG H&L (FITC) (cat. no. ab6724, 1:1000) was purchased from Abcam. After that, we incubated samples with Hoechst 33342 (Beyotime, cat. no. C1022). Finally, immunofluorescence images were collected at 488 nm and 561 nm with CLSM (Nikon Ti-E controlled by NIS Elements AR) using a 60× oil immersion objective. Cells were reseeded to 12-well plates for 1 day before use in experiments and starved in DMEM without fetal bovine serum for 24 hours before stimulation. Stimulus was added directly to the wells. After treatment in the presence or absence of aptameric dimer or HGF, cells were quickly transferred to 4 °C and washed with cold phosphate-buffered saline (PBS) containing 0.9 mM Ca 2+ and 0.5 mM Mg 2+ . All subsequent steps were carried out at 4 °C, and staining of GLUT2/4 was done on adherent cells. Cells were incubated with a 1:200 dilution of anti-GLUT2/4 for 1.5 hours after 2% bovine serum albumin (BSA) for 1 hour. Cells were then washed twice in PBS for 5 minutes each time. They were then incubated for 1 hour in secondary antibody. Cells were rinsed twice in PBS, and resuspended by gentle scraping in PBS with 2% BSA for flow cytometry. LC−MS based untargeted metabolomics analyses Metabolite extraction of BRL-3A cell samples followed the standard procedures (www.zhulab.cn/articles/64.html). Extracts were dried in a vacuum concentrator at 4 °C and analyzed by liquid chromatography-mass spectrometry (LC−MS). Data were acquired using a UHPLC system (Vanquish, Thermo Scientific) coupled to an orbitrap mass spectrometer (Exploris 480, Thermo Scientific). A Waters BEH amide column (1.7 μm; 100 mm × 2.1 mm (i.d.)) and a Phenomenex Kinetex C18 column (2.6 μm, 2.1 × 100 mm × 2.1 mm (i.d.)) were used for LC separation. The mobile phases, linear gradient elution, and ESI source parameters followed those described in a previous publication [ 51 ] . Metabolite annotation was performed using MetDNA (http://metdna.zhulab.cn/) [ 52 , 53 ] . Q uantitative real-time PCR The expression levels of gluconeogenic genes, phosphoenolpyruvate carboxykinase ( Pck1 ) and glucose 6-phosphatase ( G6pc ), were determined by quantitative real-time PCR using β-actin as an internal reference [54] . Cells grown on a 6-cm dish were starved in a medium supplemented with 0.2% FBS for 24 hours and then stimulated with 10 nM aptameric dimer and 10 nM insulin for 4 hours at 5% CO 2 and 37 °C. Total RNAs were extracted using the AG RNAex Pro RNA extraction kit (Accurate Biology, AG21101) by following the manufacturer’s instructions. The extracted RNAs were quantified using the Nanodrop spectrophotometer and then reverse-transcribed to complementary DNAs using Evo M-MLV Reverse Transcriptase Synthesis Kit (Accurate Biology, AG11728). Quantitative real-time PCR was performed using 2× SupRealQ Purple Universal SYBR qPCR Master Mix (U + ) (Vazyme, cat. no. 7E0511G4) on an Applied Biosystems QuantStudioTM 7 Flex. mRNA expression levels were normalized to housekeeping genes β-actin and calculated using the 2^(-ΔΔCt) method. The sequences of primers are listed in Supplementary Table 2. Periodic Acid-Schiff (PAS) staining BRL-3A cells were cultured in 6 well plates and subjected to starvation treatment with DMEM containing 0.2% FBS for 18 hours. Then, the cells were treated with the aptameric dimer, insulin, and HGF for 4 hours and stained using a glycogen-specific PAS staining kit (Bioss, S0126). Fluorescent images of PAS-stained hepatocytes were captured using a fluorescent imaging microscope (Olympus, IX-73). Cell imaging For cell imaging, the cells were seeded in 35 mm confocal dish with complete medium and incubated for 24 hours at 5% CO 2 and 37 °C. BRL-3A cells were first washed with HEPES (1×) and incubated with CWGN (100 nM) in 200 μL HEPES buffer at 37 °C for 10 minutes. Subsequently, the cells were washed twice with HEPES buffer, and 200 μL HEPES buffer containing 10 mM glucose was added. Real-time live cell imaging was performed using a confocal laser scanning microscope (CLSM) (Nikon, Eclipse TE2000-E, Japan) with a 60 × oil immersion objective. Excitation wavelength and emission filters were set as follows: FAM channel (excitation 488 nm, emission 525 nm), Cy3 channel (excitation 550 nm and emission 570 nm), Cy5 channel (excitation 640 nm and emission 670 nm). Fluorescence intensity on the cell surface was analyzed and quantified using the Image J software. SIM image HEK293T cells were transfected with the EGFP-GLUT4 plasmid using Lipo8000 (Beyotime, cat. no. C0533) transfection reagent according to the manufacturer's protocol. Afterward, the cells were incubated with 200 nM CWGN in HEPES buffered saline solution for 10 minutes. Subsequently, the cells were washed twice with HEPES buffer, and 200 μL HEPES buffer containing a 10 mM glucose was added for 15 minutes. Cells were then fixed with 4% paraformaldehyde (PFA) for 15 minutes and stained with Hoechst for 5 minutes. Images of the AGSR-activation event and GLUT4 translocation of CWGN-equipped HEK293T cells in the presence and absence of glucose were acquired by Structured Illumination Microscopy (SIM) (Nikon ECLIPSE Ti2) and treated with deconvolution. Excitation wavelength and emission filters: Hoechst channel (excitation 405 nm and emission 430-475 nm, Laser power 5%), EGFP channel (excitation 488 nm, emission 502-546 nm, Laser power 8%), Cy5 channel (excitation 638 nm and emission 666-732 nm, Laser power 5%). Flow cytometry Flow cytometry was used to assess the performance of AGSR on live cell membranes. BRL-3A cells were harvested in cell dissociation buffer to prepare cell suspensions. Subsequently, 1×10 5 cells were incubated with 100 nM CWGN at 37 °C for 10 minutes. Afterward, the cells were washed twice with 200 μL PBS and then incubated with 10 mM glucose at 37 °C for 15 minutes. Finally, cells were suspended in 200 μL PBS and analyzed by flow cytometry (BD Accuri TM C6 Plus, USA). Immunofluorescence flow cytometry analysis BRL-3A cells were digested with trypsin to form suspended single cells, and washed three times with PBS to remove intercellular connections caused by trypsin. Cells were treated with aptameric dimer, CWGN, and mCWGN, respectively at 37 ℃ for 10 minutes, and unreacted DNA was removed by centrifugation. Then, different concentrations of glucose were added and reacted for 30 minutes. Cells were then fixed and permeabilized with 4% PFA containing 0.1% TritonX-100 for 15 minutes. Finally, BRL-3A cells were incubated with the Rabbit Anti-phospho-Met (Tyr1234)/FITC Conjugated antibody (Bioss, bs-18798R-FITC; 1:2000 dilution) on ice for 1 hour, and analyzed using the flow cytometer (BD Accuri TM C6 Plus, USA). In - cell western assay Cells were seeded in 96-well plates (Corning Costar) and incubated until confluence. Cells were starved for 24 hours in DMEM supplemented with 0.2% FBS, and then incubated with CWGN for 10 minutes. After replacing the medium, cells were stimulated by glucose for another 15 minutes, and then fixed with 4% formaldehyde for 30 minutes at 37 °C. Next, cells were permeabilized with 0.1% Triton X-100 washing solution, and blocked with Odyssey® Blocking Buffer (LI-COR) for 1.5 hours at room temperature with moderate shaking. The blocking buffer was removed by aspiration, and 50 µl of the desired primary antibody (1:250 dilution) was added to the wells and incubated overnight at 4 °C. The plate was then washed three times with 0.1% Tween-20 washing solution with gently shaking for 5 minutes at room temperature. Next, 50 µl of the secondary antibody (1:1000 dilution) solution was added to each well and incubated away from light for 60 minutes with gentle shaking at room temperature. Again, the plate was washed three times with 0.1% tween-20 washing solution with gentle shaking for 5 minutes at room temperature. After the final wash, the images were acquired on the LI-COR Odyssey® Infrared Imaging System (Lincoln, Nebraska, USA). The primary antibodies of phospho-Met (Y1234/Y1235) (3126S), phospho-Akt (S473) (4060S) and α-tubulin (3873S) were obtained from Cell Signaling Technology. The primary antibody of phospho-IRS2 (Ser731) (bs-5397R) was purchased from Bioss. The IRDye secondary antibodies, including IRDye® 800CW Goat anti-Mouse Secondary Antibody (LI-COR P/N 925-32210 or 926-32210) and IRDye® 680RD Goat anti-Rabbit Secondary Antibody (LI-COR P/N 925-68071 or 926-68071) were obtained from LI-COR (Lincoln, Nebraska, USA). Immunoblotting MDCK cells were seeded in 35 mm dishes. When the cells reached 80% confluence, they were starved for 24 hours in DMEM supplemented with 0.2% FBS. Subsequently, the medium was changed and incubated with CWGN for 10 minutes in the incubator. The medium was then replaced and the cells were stimulated by 10 mM glucose for 15 minutes. The dishes were then placed on ice to stop the stimulation and washed twice by pre-cooled PBS. Subsequently, the cells were lysed with RIPA lysis buffer (containing 1% phosphatase inhibitors and protease inhibitors). The cell lysates were centrifuged at 14000 rcf for 10 minutes, and the supernatant was retained and stored at -20 °C until use. The cell lysates were separated by 8% SDS-PAGE in the electrophoresis experiment, then transferred to a nitrocellulose membrane by semi-dry electrophoretic transfer unit for 16 minutes. After blocking with a 5% BSA in the PBST solution (1× PBS with 0.1% Tween-20) for 1 hour, the membrane was reacted with primary antibody (1:1000 dilution) overnight at 4 °C and then with secondary antibody (1:5000 dilution) for 1 hour at room temperature. The secondary antibodies, including goat anti-rabbit IgG (H&L)-HRP and goat anti-mouse IgG (H&L)-HRP, were obtained from Invitrogen. Before imaging, the membranes were treated with ECL substrate solution (NCM Biotech Co. Ltd). Chemiluminescent images were obtained using multifunctional molecular imaging system (Azure Biosystems 600). Construction of i nsulin r esistance c ell m odel An insulin resistance cell model was established by free fatty acids [42] . BRL-3A cells were stimulated by 0.5 mM palmitate for 24 hours. C2C12 m yoblasts differentiate into myotubes On Day 1, C2C12 cells (5×10 3 per 100 μL) in DMEM containing 10% fetal bovine serum were seeded in a 96-well plate. Replace medium every 2-3 days. On Day 5, remove media and initiate differentiation by adding 100 μL DMEM containing 2% horse serum (Gibco, cat. no. 16050122). The medium was replaced daily. Myotubes reached maturity after 3-5 days of low serum treatment. Stability of CWGN CWGN (500 nM) was incubated in PBS (pH 7.4) buffer containing 10% FBS for different durations. Samples were then analyzed by 8% native PAGE. Animal studies Animals were maintained under pathogen-free conditions, and all experiments were conducted in accordance with the Regulations for the Management of Laboratory Animals of the Ministry of Science and Technology of the People's Republic of China. All procedures involving animals were reviewed and approved by the Experimental Animal Ethics Committee of Hunan University (HNUBIO202102006) and the Committee on the Ethics of Animal Experiments of Hunan Provincial Laboratory Animal Center [SYXK (Xiang) 2018–0006]. Adult male C57BL/6 mice (4-6 weeks old) were purchased from Hunan SJA Laboratory Animal Co., Ltd and housed in viral- and pathogen-free conditions, with a maximum of five animals per cage. Mice were provided with food and water ad libitum and housed in a controlled environment with a 12-h light / 12-h dark cycle. Biodistribution of CWGN Mice were intravenously injected with Cy5-labeled CWGN (0.5 nanomolar) via the tail vein. After 30 minutes and 120 minutes, the mice were perfused with 4% paraformaldehyde (PFA) and major organs (heart, liver, spleen, lung, kidney, muscle) were excised at an appropriate time. The excised organs were imaged using an IVIS Spectrum CT with excitation at 640 nm and emission at 680 nm. STZ-induced type 1 diabetes mice model To build the type 1 diabetes model [38] , streptozocin (STZ dissolved in 0.1 M citrate buffer solution, 10 mg/mL) was intraperitoneally injected into mice for 8 weeks with a dose of 120 mg/kg after fasting 12 hours but allowing free access to water. Then, mice were recovered to normal food supply. One week later, body weight and blood glucose levels of the mice were measured. Mice with blood glucose higher than 11.1 mmol/L were regarded as diabetic mice. High-sugar and high-fat diet- induced type 2 diabetic mice model To develop the type 2 diabetes model [43] , firstly streptozocin (STZ; dissolved in 0.1 M citrate buffer solution, 10 mg/mL) was injected intraperitoneally into mice for 8 weeks with a dose of 50 mg/kg after fasting 12 hours but allowing free access to water for three times every other day. Each time after injection the mice were fed with high-sugar and high-fat diet. Then after all the injection finished, the mice were continually raised with high-sugar and high-fat diet. Two months later, the weight and the blood glucose level were measured. Mice with a blood glucose level higher than 11.1 mmol/L were considered diabetic. ALX-induced diabetic dog model To build the alloxan (ALX)-induced diabetic dogs [45] , 50 mg/kg freshly prepared ALX solution (200 g/L) was injected into the superficial vein of the lower limbs, and the weight and blood glucose level of dogs were measured after 7 consecutive days of injection. The modeling process was completed by Beijing Sinogene Biotechnology Co., Ltd. Glucose tolerance test (GTT) Prior to the glucose tolerance test, all animals were fasted overnight for 12 hours with free access to water. The body weight of each diabetic mouse and diabetic dog was measured before the test to accurately calculate the glucose dosage (2 g/kg for mice, 1 g/kg for dogs), and the initial blood glucose levels were recorded at the end of the fasting period. For diabetic mice, an intraperitoneal glucose tolerance test (IPGTT) was conducted. Mice received an intraperitoneal injection of CWGN, followed by an intraperitoneal injection of glucose. For diabetic dogs, an intravenous glucose tolerance test (IVGTT) was performed. Dogs received an intravenous injection of CWGN, followed by an intravenous glucose injection. The timing of the test began immediately after glucose administration. Blood glucose levels of each diabetic mouse/dog were measured at specific time points, including 30 minutes, 60 minutes, 90 minutes, 120 minutes, 150 minutes, and 180 minutes after the glucose injection. Insulin tolerance test (ITT) After a 4-hour fasting period, the body weight and initial blood glucose levels of the mice were measured. Subsequently, CWGN was injected, followed by insulin injection (0.5 U/kg) 30 minutes later. Timing began immediately after the insulin injection. Blood glucose levels of each diabetic mouse were measured at specific time points, including 30 minutes, 60 minutes, 90 minutes, 120 minutes, 150 minutes, and 180 minutes after the insulin injection. Cytotoxicity analysis BRL-3A cells and C2C12 cells (1×10 4 ) were cultured in a 96-well plate for 24 hours. The medium was then replaced with either fresh medium alone or medium containing different concentrations of CWGN, and the cells were incubated for an additional 24 or 48 hours. After washing twice with PBS, the Cell Counting Kit-8 (Beyotime, cat. no. C0039) assay reagent was added to each well according to the manufacturer’s instructions. After 1 hour incubation, cell viability was determined by measuring the absorbance at 450 nm using a microplate reader. Liver function assessment CWGN was injected into the tail vein of normal mice, and serum was collected after 24 hours. Serum was separated immediately after centrifugation of the blood sample at 4,000 rpm for 15 minutes at 4 °C. Then, serum levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were measured using the test kit according to the manufacturer’s instructions (Jiancheng Biotech. Co., Ltd). Hematoxylin and eosin (H&E) staining Mice subjected to different treatments were sacrificed 24 hours later, and the organs were excised and fixed in 4% paraformaldehyde for 48 hours. Subsequently, the tissues were dehydrated in a sucrose solution for an additional 48 hours and embedded in Optimal Cutting Temperature compound (OCT). The 5-mm-thick sections were prepared and stained with H&E solution (Beyotime, cat. no. C0105). Images of H&E-stained sections were acquired using a binocular biological microscope (Leica, DM500, Germany). Statistical analysis Data are represented as mean ± standard deviation (S.D.) from at least three biologically independent experiments. Statistical significance was determined using unpaired two-tailed Student’s t-test , and P < 0.05 was considered statistically significant. References Bogan, J.S., McKee, A.E. & Lodish, H.F. Insulin-responsive compartments containing GLUT4 in 3T3-L1 and CHO cells: regulation by amino acid concentrations. Mol . Cell . Biol. 21 , 4785-4806 (2001). Wang, R. et al. Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging drosophila. Nat. Commun. 13 , 3518 (2022). Zhou, Z. et al. Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking. Nat. Commun. 13 , 6656 (2022). Shen, X. et al. Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics. Nat. Commun. 10 , 1516 (2019). Arden, C. et al. Elevated glucose represses liver glucokinase and induces its regulatory protein to safeguard hepatic phosphate homeostasis. Diabetes 60 , 3110-20 (2011). Additional Declarations There is NO Competing Interest. Supplementary Files Supportinginformation.docx SUPPLEMENTARY INFORMATION ExtendedDataFigure.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7115886","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":497721859,"identity":"d5f66133-fcaa-4602-83b2-0ce6c94fa6df","order_by":0,"name":"zhou nie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYDACZjBiYDBgYGB8AKR5+EjRwmwA0sJGpEVgLWwSIAZBLebszIc/F1QcZjCX7jGr/JpjJ8PGwPzw0Q08Wiyb2RKMZ5w5zGA554zZbdltyUCHsRkb5+DRYnCYxyCZt+0wg8GNHLPbktuYgVp42KTxa+H/cBimpVhyWz0xWngYm2FaGD9uO0yMFjZjZp4z6TwGN9KKpRm3HedhYybkl/OHH3/mqbCWM7iRvPHjz23V9vzszQ8f49MCAzwgghlCEqEcDhh/kKJ6FIyCUTAKRgwAANh/PzDV+HXnAAAAAElFTkSuQmCC","orcid":"","institution":"Hunan University","correspondingAuthor":true,"prefix":"","firstName":"zhou","middleName":"","lastName":"nie","suffix":""},{"id":497721860,"identity":"b560276c-cf60-4bee-bf16-b130a4ba6af4","order_by":1,"name":"Fang He","email":"","orcid":"","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"He","suffix":""},{"id":497721861,"identity":"479e1f46-1f1a-4aa1-b22d-c9f1d5e997b1","order_by":2,"name":"Meixia Wang","email":"","orcid":"","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Meixia","middleName":"","lastName":"Wang","suffix":""},{"id":497721862,"identity":"9798e7e6-f3ce-4b3f-b234-48fa544bb66a","order_by":3,"name":"Yiyu Wang","email":"","orcid":"","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Yiyu","middleName":"","lastName":"Wang","suffix":""},{"id":497721863,"identity":"6d79d03a-af51-4168-98d8-fac422cd7b4d","order_by":4,"name":"Yuping Cai","email":"","orcid":"","institution":"Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yuping","middleName":"","lastName":"Cai","suffix":""},{"id":497721864,"identity":"84df4ace-46ff-4805-819a-88f8a3fc05bb","order_by":5,"name":"Zheng-jiang Zhu","email":"","orcid":"","institution":"Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zheng-jiang","middleName":"","lastName":"Zhu","suffix":""},{"id":497721865,"identity":"52d3f4fe-4dc2-4636-892a-52eef687fd6e","order_by":6,"name":"Hong-Hui Wang","email":"","orcid":"https://orcid.org/0000-0002-4420-9733","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Hong-Hui","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-07-14 01:20:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7115886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7115886/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88761026,"identity":"fb113db0-1171-4b5b-9e98-2cb99bc91e3f","added_by":"auto","created_at":"2025-08-11 08:06:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1096848,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of the artificial glucose-sensing receptor (AGSR). AGSR consists of a sensing-and-decision-making (SD) subunit and an actuation (A) subunit. It regulates blood glucose homeostasis by activating glucose uptake signaling in natural glucose-uptaking effectors (hepatocytes/myocytes), which represents a universal strategy for glucose homeostasis regulation in type 1 and type 2 diabetic dog/mice models. AGSR is an all-in-one nanodevice that achieves a closed-loop molecular circuit on effector cells, enabling a tunableglucose-responsivedynamic range and ensuring safety through reversible attachment to effector cells.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/f2090a96318ba10237ef4374.png"},{"id":88761031,"identity":"e6ac5f30-b0d3-46a7-988a-f804f436b096","added_by":"auto","created_at":"2025-08-11 08:06:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1828398,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegulation of glucose metabolism by DNA aptameric dimer. a\u003c/strong\u003e. Evaluation of glucose uptake mediated by aptameric dimer (50 nM) and HGF (1 nM) in BRL-3A cells using the Glucose Uptake-Glo™ Assay kit (Promega, J1343) following the manufacturer’s instructions. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003eb\u003c/strong\u003e. Translocation of GLUT2 in BRL-3A cells treated with aptameric dimer (50 nM) or HGF (1 nM). Immunofluorescence (\u003cem\u003eleft\u003c/em\u003e) and flow cytometry (\u003cem\u003eright\u003c/em\u003e) were used to visualize and quantify GLUT2 translocation. Data are presented as mean ± S.D. (n = 3). Scale bar: 50 μm. \u003cstrong\u003ec\u003c/strong\u003e. Activation of signal transduction mediated by aptameric dimer and HGF. The BRL-3A cells were treated with the aptameric dimer (50 nM) or HGF (1 nM), respectively. The phosphorylation levels of Met (Y1234/1235), IRS2 (Ser731) and Akt (Ser473) were investigated using in-cell western assay (data please see Supplementary Figure 3) and analyzed using ImageJ software. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ed\u003c/strong\u003e. GLUT2-mediated glucose uptake stimulated by the aptameric dimer was diminished in the presence of the p-Akt inhibitor MK2206. \u003cstrong\u003ee\u003c/strong\u003e. Principal component analysis (PCA) of distinctive metabolomics profiles of BRL-3A cells treated with culture medium, aptameric dimer (10 nM), or insulin (10 nM) for 4 hours. Data are presented as mean ± S.D. (n = 6). \u003cstrong\u003ef\u003c/strong\u003e. Volcano plots showed differential metabolites in BRL-3A cells treated with 10 nM aptameric dimer (\u003cem\u003eleft\u003c/em\u003e) or 10 nM insulin (\u003cem\u003eright\u003c/em\u003e) relative to control group. \u003cstrong\u003eg\u003c/strong\u003e. Heatmap of shared and significantly changed metabolites (P \u0026lt; 0.05, | log\u003csub\u003e2\u003c/sub\u003e(fold change) | \u0026gt; 0.26) in hepatocyte treated with aptameric dimer and insulin. \u003cstrong\u003eh\u003c/strong\u003e. Pathway enrichment analysis of significantly changed metabolites using MetaboAnalyst6.0. \u003cstrong\u003ei\u003c/strong\u003e. mRNA levels of the Pck1 (\u003cem\u003eleft\u003c/em\u003e) and G6pc (\u003cem\u003eright\u003c/em\u003e). \u003cstrong\u003ej\u003c/strong\u003e. Effect of the aptameric dimer (10 nM), or insulin (50 nM) on glycogen storage in BRL-3A cells. Glycogen storage was visualized using Periodic Acid-Schiff (PAS) staining, and the quantification of glycogen expression was shown in the \u003cem\u003eDown\u003c/em\u003e images. Data are presented as mean ± S.D. (n = 3). P values were calculated by unpaired two-tailed Student’s\u003cem\u003e t-test\u003c/em\u003e. Scale bar: 100 µm.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/9d8e4b9467bb77db81821a70.png"},{"id":88761027,"identity":"c053c1aa-9657-4e1d-b5d3-5c2e3dcea3c2","added_by":"auto","created_at":"2025-08-11 08:06:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1483149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConstructing cell-wearable glucose-regulating nanodevice (CWGN) for artificial glucose-sensing receptor (AGSR) Engineering.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e. Schematic diagram of glucose uptake regulation mediated by AGSR. \u003cstrong\u003eb\u003c/strong\u003e.\u003cem\u003e Left\u003c/em\u003e: Real-time live cell imaging of CWGN-equipped BRL-3A cells in response to glucose. Scale bar: 20 μm. \u003cem\u003eRight\u003c/em\u003e: Quantification of fluorescence intensity from the left panel. Data are presented as mean ± S.D. (n = 10) \u003cstrong\u003ec\u003c/strong\u003e. Flow cytometry and CLSM fluorescence imaging of CWGN anchored on the membrane of BRL-3A cells after adding complementary chains of H\u003csub\u003eA \u003c/sub\u003e(C\u003csub\u003eH\u003c/sub\u003e). Scale bar: 20 μm. \u003cstrong\u003ed\u003c/strong\u003e. Wearable and removable characteristics of CWGN in BRL-3A cells were measured using immunofluorescence flow cytometry. Response activation of p-Met was quantified by normalizing the FITC-p-Met fluorescence intensity on CWGN-equipped BRL-3A cells with or without treatment of different concentration C\u003csub\u003eH\u003c/sub\u003e for 10 minutes. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ee\u003c/strong\u003e. Glucose response specificity of CWGN. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ef\u003c/strong\u003e. Activation of Met-Akt signal mediated by AGSR. CWGN-equipped BRL-3A cells were treated with glucose (10 mM), and the phosphorylation of Met (Y1234/1235) and Akt (S473) was investigated using in-cell western assay and analyzed by ImageJ software. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003eg\u003c/strong\u003e. Analysis of AGSR-activation event and GLUT4 translocation of CWGN-equipped HEK293T cells transfected with GLUT4-EGFP plasmids for 24 hours in the presence and absence of glucose using Structured Illumination Microscopy (SIM) (Nikon ECLIPSE Ti2). Scale bar: 10 µm. \u003cstrong\u003eh\u003c/strong\u003e. Assessment of glucose uptake capacity in CWGN-equipped BRL-3A cells using the 2-DG assay. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ei\u003c/strong\u003e. Quantitative analysis of the TAMRA and GLUT4-EGFP fluorescence at the indicated time points (data please see Supplementary Fig. 7). Relative fluorescence levels were quantified by taking 10 regions in cell membrane and cytoplasmic using ImageJ software (n = 10). P values were calculated by unpaired two-tailed Student’s\u003cem\u003e t-test\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/6facda9c4ca035a7247d1d9a.png"},{"id":88762081,"identity":"19cc6a54-5d23-44e1-a6cf-7fca37389511","added_by":"auto","created_at":"2025-08-11 08:14:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1132631,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAGSR with tunable glucose sensitivity. a. \u003c/strong\u003eTunability of glucose responsiveness of designer AGSR. \u003cstrong\u003eb\u003c/strong\u003e. Phosphorylation of Met (Y1234/1235) in BRL-3A cells engineered by AGSR with different IDs was determined using immunofluorescence flow cytometry analysis under different concentrations of glucose treatment. The dose-response curves showed the relative phosphorylation level of Met. The relative phosphorylation level was obtained by normalizing the ratio of p-Met fluorescence to α-tubulin fluorescence, with an average value of 0 for the mCWGN group and 1 for the aptameric dimer group. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ec\u003c/strong\u003e.Phosphorylationof Akt (S473) in BRL-3A cells engineered by AGSR with different IDs were determined using in-cell western assay under different concentrations of glucose treatment. The dose-response curves showed the relative phosphorylation level of Akt. The relative phosphorylation level was obtained by normalizing the ratio of p-Akt fluorescence to α-tubulin fluorescence (data please see Supplementary Fig. 11). Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ed\u003c/strong\u003e. \u003cem\u003eLeft\u003c/em\u003e: The detailed diagram of C2C12 cells differentiation into myotube and representative imaging of C2C12 myotubes under bright field microscopy. Scale bar: 10 μm. \u003cem\u003eRight\u003c/em\u003e: Glucose uptake in C2C12 myotubes engineered by AGSR with 14-nt ID under varying glucose concentrations was determined using the Glucose Uptake-Glo™ Assay kit. Data are presented as mean ± S.D. (n = 3).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/050179f1e633ddd26aefc57b.png"},{"id":88761030,"identity":"443ce26f-a2ed-4a25-826a-de963190d72c","added_by":"auto","created_at":"2025-08-11 08:06:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1167062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e evaluation of AGSR in diabetic mice models.\u003c/strong\u003e \u003cstrong\u003ea.\u003c/strong\u003e \u003cem\u003eLeft\u003c/em\u003e: Viability of BRL-3A and C2C12cells after 48-hour incubation with CWGN at various concentrations. Data are presented as mean ± S.D. (n = 3). \u003cem\u003eRight\u003c/em\u003e: Evaluation of liver function following a single intravenous injection of CWGN (3 nmol) in mice. Serum AST and ALT levels were measured using standard assay kits. Data are presented as mean ± S.D. (n = 10). \u003cstrong\u003eb\u003c/strong\u003e. Biodistribution of CWGN \u003cem\u003ein vivo\u003c/em\u003e. Mice were intravenously injected with a single dose of Cy5-labeled CWGN (0.5 nmol) via tail vein and sacrificed 0.5 h post-injection. Major organs (heart, liver, spleen, lung, kidney, muscle) were harvested and subjected to \u003cem\u003eex vivo\u003c/em\u003eimaging using the IVIS Spectrum CT system. \u003cstrong\u003ec\u003c/strong\u003e. IPGTT in T1D mice at 30 minutes post-administration of CWGN (0.5 nmol) or mCWGN (0.5 nmol). Data are represented as mean ± S.D. (n = 10). \u003cstrong\u003ed\u003c/strong\u003e. Regulation of blood glucose homeostasis by CWGN in hyperglycemic mice (BGL \u0026gt; 11.1 mmol/L). \u003cstrong\u003ee\u003c/strong\u003e. Evaluation of hypoglycemia risk. Blood glucose levels in normoglycemic mice (BGL \u0026lt; 11.1 mmol/L) were monitored before and 1 hour after tail vein injection of CWGN (1 nmol) or insulin (0.5 IU/kg). Data are presented as mean ± S.D. (n = 4). \u003cstrong\u003ef\u003c/strong\u003e. Assessment of\u003cem\u003e \u003c/em\u003ehypoglycemia.\u003cem\u003e \u003c/em\u003eQuantitative comparison of hypoglycemia index between CWGN and insulin, which was determined from the difference between the initial and nadir blood glucose readings divided by the time at which nadir (i.e., lowest observed value) was reached. Data are presented as mean ± S.D. (n = 4). \u003cstrong\u003eg\u003c/strong\u003e. \u003cem\u003eTop\u003c/em\u003e: Schematic illustration of the impact of AGSR on glucose uptake in palmitate-induced insulin-resistant cells. \u003cem\u003eBottom\u003c/em\u003e: Evaluation of AGSR-mediated improvement in insulin resistance using the Glucose Uptake-Glo™ Assay kit. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003eh\u003c/strong\u003e. \u003cem\u003eTop\u003c/em\u003e: Detailed schematic diagram of T2D mice modeling. \u003cem\u003eBottom Left\u003c/em\u003e: Insulin tolerance tests (ITT) in T2D mice at 30 minutes post-administration of CWGN. \u003cem\u003eBottom Right:\u003c/em\u003e AUC analysis of the ITT data from (\u003cem\u003eBottom Left\u003c/em\u003e). Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ei\u003c/strong\u003e.IPGTT in T2D mice at 30 minutes post-administration of CWGN with different concentrations.\u003cstrong\u003e j\u003c/strong\u003e. AUC analysis of the IPGTT data from (i). Data are represented as mean ± S.D. (n = 3). \u003cstrong\u003ek\u003c/strong\u003e. CWGN was injected at a dose of 3 nmol at the beginning of the experiment, with a series of IPGTTs performed at 0, 3, and 6 h after 30 minutes of CWGN administration (red arrow). Data are presented as mean ± S.D. (n = 3). P values were calculated by unpaired two-tailed Student’s \u003cem\u003et-test\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/8183cb570d94058d7f0b3898.png"},{"id":88761033,"identity":"60dcdd78-9071-46dd-be22-c48aa5e2e78f","added_by":"auto","created_at":"2025-08-11 08:06:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":693036,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e evaluation of AGSR in an ALX-induced diabetic dog model\u003c/strong\u003e. \u003cstrong\u003ea\u003c/strong\u003e. Schematic illustration of AGSR-mediated signal activation and glucose uptake in diabetic dogs. \u003cstrong\u003eb\u003c/strong\u003e. Activation of Met-Akt signal is mediated by AGSR. CWGN-equipped MDCK cells were treated with glucose and phosphorylation of Met (Y1234/1235) and Akt (S473) were analyzed via western blotting assay using specific antibodies. The α-tubulin was used as an internal reference. \u003cstrong\u003ec\u003c/strong\u003e. Evaluation of AGSR-mediated glucose uptake using the 2-DG assay. Data are presented as mean ± S.D. (n = 3). \u003cstrong\u003ed\u003c/strong\u003e. Schematic diagram of the ALX-induced diabetic dog model establishment. \u003cstrong\u003ee\u003c/strong\u003e. Monitoring of blood glucose levels (BGL) in beagle dogs before and after ALX-induced diabetes. Data are presented as mean ± S.D. (n = 5). \u003cstrong\u003ef\u003c/strong\u003e. Body weight changes in beagle dogs before and after ALX treatment. Data are presented as mean ± S.D. (n = 5). \u003cstrong\u003eg\u003c/strong\u003e. Schematic representation of the intravenous glucose tolerance test (IVGTT) protocol in diabetic dogs. \u003cstrong\u003eh\u003c/strong\u003e. IVGTT in diabetic dogs at 30 minutes post-administration of CWGN. \u003cstrong\u003ei\u003c/strong\u003e. AUC analysis of the IVGTT data from (g). Data are presented as mean ± S.D. (n = 5). \u003cstrong\u003ej\u003c/strong\u003e. Quantitative comparison of hypoglycemia index between CWGN and insulin, which was determined from the difference between the initial and nadir blood glucose readings divided by the time at which nadir (i.e., lowest observed value) was reached. Data are presented as mean ± S.D. (n = 3). P values were calculated by unpaired two-tailed Student’s \u003cem\u003et-test\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/3dd3b7bd86e6ded9dbe91c15.png"},{"id":88762470,"identity":"db22ca2e-a2f8-4de2-8174-123f08f599e3","added_by":"auto","created_at":"2025-08-11 08:22:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9232690,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/b7c79a70-2ba4-48cf-b00c-f9492de5af5b.pdf"},{"id":88762082,"identity":"bc12521b-fd1f-40ec-b568-6794ef588682","added_by":"auto","created_at":"2025-08-11 08:14:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2711424,"visible":true,"origin":"","legend":"SUPPLEMENTARY INFORMATION","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/45c596f722a0eb12260d96b3.docx"},{"id":88762083,"identity":"3ad857bb-7499-4185-bd7f-3f7b67d75c65","added_by":"auto","created_at":"2025-08-11 08:14:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3884172,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendedDataFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-7115886/v1/a528443d3551591a61ad4807.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Programmable Artificial Glucose-sensing Receptor for Autonomous Single-Cell Closed-loop Glycemic Control","fulltext":[{"header":"Main","content":"\u003cp\u003eEngineering cellular sensing capabilities to enable biomarker-driven diagnostic and therapeutic outputs holds significant potential for precision medicine \u003csup\u003e[1, 2, 3]\u003c/sup\u003e. An important strategy to achieve this goal is synthetic receptor engineering, which endows cells with customizable input recognition and programmable signaling responses \u003csup\u003e[4, 5, 6]\u003c/sup\u003e, exemplified clinically by chimeric antigen receptor (CAR) T cells \u003csup\u003e[7]\u003c/sup\u003e. While synthetic receptors have greatly advanced applications in cancer immunotherapy and autoimmune disorder treatments \u003csup\u003e[7, 8]\u003c/sup\u003e, their development for metabolic regulation remains nascent. This underscores an urgent need to develop novel synthetic receptor platforms capable of restoring or maintaining metabolic homeostasis.\u003c/p\u003e\n\u003cp\u003eGlucose metabolism plays a central role in human metabolic networks, with systemic homeostasis maintained through multi-organ closed-loop regulation \u003csup\u003e[9, 10]\u003c/sup\u003e. Pancreatic \u0026beta;-cells act as glucose-sensing hubs, detecting glycemia and secreting insulin to direct peripheral effector cells (hepatocytes/myocytes) to promote glucose uptake and storage \u003csup\u003e[11]\u003c/sup\u003e. Dysfunction in this axis leads to diabetes mellitus (DM), either through \u0026beta;-cell destruction (type 1 diabetes, T1D) \u003csup\u003e[12]\u003c/sup\u003e or insulin resistance in effector tissues (type 2 diabetes, T2D) \u003csup\u003e[13]\u003c/sup\u003e. Current glucose-responsive synthetic \u0026beta;-cell strategies mimic \u0026beta;-cells\u0026rsquo; metabolism-dependent pathway by coupling glucose metabolism to insulin transgene expression\u0026nbsp;\u003csup\u003e[14, 15]\u003c/sup\u003e. However, these systems are constrained by delayed response kinetics (hour-scale transcriptional activation) and the inability to address insulin resistance \u003csup\u003e[16, 17, 18]\u003c/sup\u003e. While translational-level switches enable faster insulin release, these synthetic cell designs lack glucose responsiveness for closed-loop glycemic regulation \u003csup\u003e[19, 20]\u003c/sup\u003e. Notably, emerging evidence reveals glucose-sensing receptors (GSR) \u003csup\u003e[21]\u003c/sup\u003e, e.g. T1R2/T1R3 receptors \u003csup\u003e[22]\u003c/sup\u003e and ADGRL1 receptors \u003csup\u003e[23]\u003c/sup\u003e, involved in metabolism-independent rapid glycemia detection. However, their limited understanding and intrinsic constraints, including promiscuous ligand selectivity, undefined glucose-binding kinetics, and incomplete mapping of downstream signaling, hinder their application in synthetic closed-loop glucose regulation.\u003c/p\u003e\n\u003cp\u003eHerein, we report a \u003cem\u003ede novo\u003c/em\u003e-designed artificial glucose-sensing receptor (AGSR) to directly transform effector cells (hepatocytes/myocytes) into self-contained closed-loop glycemic regulators. Unlike natural GSRs, AGSR adopts a semi-synthetic DNA-protein biohybrid architecture featuring a molecularly defined cell-wearable glucose-regulating DNA nanodevice (CWGN) capable of selectively attaching to endogenous cell-surface receptors to reprogram their function for glucose-responsive signaling. CWGN enables plug-and-play receptor functionalization via reversible integration, allowing \u003cem\u003ein situ\u003c/em\u003e on-demand assembly of AGSR on effector cells without genetic engineering, which is functionally analogous to human-wearable glycemic-controlling devices (e.g., artificial pancreas). In contrast to macroscopic wearables that physically couple discrete components (glucometer/algorithm processor/insulin pump) \u003csup\u003e[24]\u003c/sup\u003e, CWGN exploits dynamic DNA nanotechnology to miniaturize the glucose sensing, threshold-based decision-making, and metabolism-regulating actuation within a single DNA nanomachine to customize hepatic/myocytic receptor-mediated quick glucose uptake with precisely tunable glycemic-responsive thresholds. To address three critical challenges in conventional insulin-dependent synthetic cell strategies for diabetes management, including therapeutic inefficacy in insulin-resistant T2D, delayed response kinetics due to insulin gene expression, and hypoglycemia risks from insulin overdosing, we propose three targeted principles in AGSR design: (1) a DNA-based receptor-signaling agonism mechanism that bypasses insulin receptor (IR) dependence to directly stimulate glucose uptake, overcoming insulin resistance in T2D; (2) an effector cell-targeted DNA nanodevice integrating a synthetic closed-loop molecular circuit that directly couples glucose sensing to receptor signaling, enabling minute-level rapid glucose uptake response; (3) a threshold-tunable, concentration-responsive molecular mechanism ensuring precise hyperglycemic activation to eliminate hypoglycemic risks. We demonstrate that AGSR can improve glucose tolerance without causing hypoglycemia risk not only in mice models of both type 1 and type 2 diabetes, but also in a diabetic dog model, a large animal model highly relevant to human pathophysiology. This work establishes a novel synthetic strategy for intelligent homeostasis control, holding great promise for precision cellular therapeutics.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDesign of the\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAGSR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 presents a schematic illustration of AGSR-mediated glucose regulation. Unlike existing genetic-engineered synthetic cell or electronic wearable strategies that functionally mimic pancreatic \u0026beta;-cells to reconstruct insulin-mediated glucose sensor-effector multicellular close-looped glucose-regulating circuits, our strategy nongenetically equips glucose-uptake effector cells (hepatocytes/myocytes) with synthetic CWGN nanodevices to form AGSRs that directly enables them to function as single-cell autonomous glycemic-regulators with a complete glucose sense-decide-actuate closed-loop. The AGSR rewires endogenous receptor-mediated glucose metabolism to hyperglycemia-induced responsiveness via artificial receptor reprogramming. As a proof-of-concept, we target CWGN to hepatocyte growth factor receptor (c-Met), an RTK with a kinase domain structurally analogous to that of the IR \u003csup\u003e[25]\u003c/sup\u003e. c-Met signaling can modulate glucose uptake and metabolic flux in glucose-uptake effector cells (hepatocytes/myocytes) \u003csup\u003e[26, 27, 28, 29, 30]\u003c/sup\u003e, making it a promising candidate for compensatory glucose regulation in insulin-resistant T2D. While native and engineered c-Met receptors are glucose-independent, we rationally design a glucose-stimulated functional DNA structure-switch to trigger cascade DNA dynamic reactions in AGSR, mediating c-Met activation. This establishes a new interplay between external glycemic level and endogenous c-Met receptor-mediated glucose-uptake signaling via dynamic DNA nanotechnology.\u003c/p\u003e\n\u003cp\u003eCWGN is a bi-modular nanodevice comprising a sensing-and-decision-making (SD) subunit and an actuation (A) subunit, which are \u0026ldquo;worn\u0026rdquo; on living cells to form two functionally distinct AGSR monomers via specific anchoring of their receptor-targeted aptameric regions on c-Met. The SD subunit integrates three key functions: (1) glucose sensing via a recognition aptamer strand (R\u003csub\u003eG\u003c/sub\u003e) \u003csup\u003e[31]\u003c/sup\u003e, (2) glycemic level threshold analysis through a concentration-dependent structure switch in the trans-duplex aptamer region (R\u003csub\u003eG\u003c/sub\u003e/H\u003csub\u003eS\u003c/sub\u003e duplex), and (3) a receptor-activation initiator (the toehold part of H\u003csub\u003eS\u003c/sub\u003e caged by R\u003csub\u003eG\u003c/sub\u003e), which is conditionally activated by glucose-induced conformational changes to interact with the A module (Supplementary Fig. 1 and Supplementary Table 1). Upon hyperglycemia, CWGN is activated by glucose-binding-induced structural change in the trans-duplex aptamer region, releasing R\u003csub\u003eG\u003c/sub\u003e and unmasking the toehold of H\u003csub\u003eS\u003c/sub\u003e. This initiates a toehold-mediated strand displacement reaction between SD and A, leading to the hybridization of receptor-hooking strands (H\u003csub\u003eS\u003c/sub\u003e and H\u003csub\u003eA\u003c/sub\u003e) and displacement of blocking strands (B\u003csub\u003eS\u003c/sub\u003e and B\u003csub\u003eA\u003c/sub\u003e). This glucose-induced heterodimerization of SD and A brings two c-Met receptors into proximity, inducing AGSR activation by c-Met autophosphorylation-triggered downstream signaling cascades to regulate glucose uptake and metabolism (Fig. 1b and Fig. 3a). Like the reversible wearability of human-wearable devices, CWGN can be removed from cells via strand displacement, providing a safety latch to modulate or deactivate AGSR functionality. Thus, AGSR represents a bottom-up approach to create a closed-loop engineered receptor activated by hyperglycemia to restore glucose homeostasis through endogenous metabolic regulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegulation of Glucose Metabolism by\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDNA Aptameric Motif\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEstablishing AGSR necessitates the development of functional nucleic acid actuators for regulating non-insulin-receptor-dependent glucose metabolism, a biochemical bottleneck that remains unexplored. We therefore first investigated whether the dimeric c-Met-specific aptamer \u003csup\u003e[32, 33, 34]\u003c/sup\u003e, the key output structure in CWGN\u0026apos;s glucose-responsive cascade, can activate glucose uptake signaling and subsequent metabolic reprogramming. Using 2-deoxyglucose (2-DG) uptake assays in c-Met-high Buffalo Rat Liver (BRL-3A) cells, we observed that 50 nM aptameric dimer triggered a 19.3-fold glucose uptake enhancement, comparable to the effect of HGF, the native ligand of c-Met (20.8-fold) (Fig. 2a). Given that glucose transporter 2 (GLUT2) constitutes a major portion of insulin-stimulated hepatic glucose uptake which is switched on by its membrane translocation \u003csup\u003e[10]\u003c/sup\u003e, we assessed its redistribution via immunofluorescence staining with an antibody that specifically recognizes the extracellular domain of GLUT2, ensuring detection of membrane-localized GLUT2 without cell permeabilization. Confocal laser scanning microscopy (CLSM) imaging and flow cytometry analysis showed an 83% increase in membrane GLUT2 in the\u0026nbsp;aptameric dimer-treated\u0026nbsp;group, comparable to HGF (85%) (Fig. 2b, Supplementary Fig. 2). In-cell western analysis revealed sequential phosphorylation of c-Met, insulin receptor substrate\u0026nbsp;2\u0026nbsp;(IRS2), and\u0026nbsp;protein\u0026nbsp;kinase B\u0026nbsp;(Akt), confirming\u0026nbsp;aptameric dimer-induced activation of IRS2\u0026nbsp;and downstream Akt\u0026nbsp;kinase, the key nodes of glucose-uptake signaling (Fig. 2c, Supplementary Fig. 3).\u0026nbsp;Phosphorylated Akt inhibitor MK2206 abolished aptameric dimer-induced\u0026nbsp;GLUT2-mediated\u0026nbsp;glucose\u0026nbsp;uptake (Fig. 2d), demonstrating\u0026nbsp;that the aptameric dimer stimulates glucose uptake via the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway, analogous to the signaling mechanism of HGF and even insulin \u003csup\u003e[30]\u003c/sup\u003e. Parallel experiments in C2C12 myoblasts verified aptameric dimer\u0026apos;s capacity to activate Met-Akt\u0026nbsp;signaling, driving glucose transporter\u0026nbsp;4\u0026nbsp;(GLUT4)-mediated glucose uptake in muscle cells (Extended Data Fig. 1). Collectively, these results established\u0026nbsp;the\u0026nbsp;aptameric dimer as\u0026nbsp;a\u0026nbsp;functional nucleic acid capable of initiating insulin-independent Met-Akt\u0026nbsp;signaling to enhance GLUT2/4 translocation\u0026nbsp;for glucose uptake\u0026nbsp;in hepatic\u0026nbsp;and\u0026nbsp;muscular effector cells.\u003c/p\u003e\n\u003cp\u003eGiven the aptameric dimer-induced glucose uptake could reshape intracellular metabolism, we systematically profiled the metabolic alterations using liquid chromatography-mass spectrometry (LC\u0026minus;MS)-based untargeted metabolomics in BRL-3A cells.\u0026nbsp;391 identified metabolites were used for subsequent statistical analyses. Principal component analysis (PCA) revealed profound differences in the cellular metabolome between the treatment groups (aptameric dimer or insulin) and the control\u0026nbsp;(Fig. 2e). Strikingly,\u0026nbsp;the aptamer dimer\u0026nbsp;recapitulated 86% of insulin\u0026apos;s metabolic shifts (61/71\u0026nbsp;dysregulated\u0026nbsp;metabolites: 13 up-regulated, 48 down-regulated), including congruent upregulation of nucleotide derivatives (IMP/uridine/cytidine/UMP) and downregulation of glucose derivatives, gluconeogenic precursors (pyruvate/lactate), and glucogenic amino acids (glycine, histidine, tryptophan, etc.) (Fig. 2f-g, Supplementary Fig. 4). Pathway enrichment analysis demonstrated coordinated upregulation of pyrimidine/purine metabolism and\u0026nbsp;downregulation\u0026nbsp;of multiple pathways, including glycolysis/gluconeogenesis and glycine-serine-threonine pathways (Fig. 2h). Moreover,\u0026nbsp;the aptameric dimer\u0026nbsp;downregulated\u0026nbsp;mRNA levels\u0026nbsp;of gluconeogenic\u0026nbsp;enzymes phosphoenolpyruvate carboxykinase 1\u0026nbsp;(\u003cem\u003ePck1\u003c/em\u003e)\u0026nbsp;and glucose 6-phosphatase\u0026nbsp;(\u003cem\u003eG6pc\u003c/em\u003e)\u0026nbsp;(Fig. 2i and Supplementary Table 2), mirroring insulin\u0026apos;s transcriptional repression of gluconeogenic enzymes\u0026nbsp;\u003csup\u003e[35]\u003c/sup\u003e. Notably, Periodic Acid-Schiff (PAS) staining of intracellular glycogen deposition showed that\u0026nbsp;the aptameric dimer\u0026nbsp;significantly enhanced glycogen biosynthesis, with\u0026nbsp;the aptameric dimer\u0026nbsp;(10 nM) achieving similar efficacy to insulin (50 nM) (Fig. 2j, Supplementary Fig. 5). These\u0026nbsp;results\u0026nbsp;demonstrate that\u0026nbsp;the aptameric dimer\u0026nbsp;mimics\u0026nbsp;insulin\u0026apos;s metabolic regulatory functions by\u0026nbsp;promoting glucose\u0026nbsp;uptake, suppressing\u0026nbsp;gluconeogenesis, and enhancing glycogen storage, providing a novel insulin-independent metabolism-regulating\u0026nbsp;motif\u0026nbsp;for AGSR development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstructing\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCWGN\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efor AGSR\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEngineering\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next constructed an autonomous CWGN by splitting the metabolic-regulatory aptameric dimer to integrate with the glucose-responsive SD and A modules, respectively. SD and A subunits, bearing c-Met-specific aptameric monomers, were selectively anchored on effector cells (BRL-3A/C2C12) surfaces to form AGSR through c-Met targeting, but were unable to functionalize c-Met-negative NIH/3T3 cells (Extended Data Fig. 2). Glucose binding to SD\u0026apos;s aptamer region (R\u003csub\u003eG\u003c/sub\u003e) induced allosteric switch-triggered cascade of strand displacement between SD and A, inducing c-Met agonistic dimer formation (Fig. 3a). Dual-fluorophore tracking via live-cell CLSM imaging revealed glucose-responsive dynamics of AGSR: glucose recognition by AGSR induces FAM-tagged R\u003csub\u003eG\u003c/sub\u003e release, causing remarkable cell-surface FAM signal decay (glucose-sensing readout), and a sequential cascade reaction to form dimerizing motifs (Cy3-H\u003csub\u003eS\u003c/sub\u003e/Cy5-H\u003csub\u003eA\u003c/sub\u003e) for c-Met agonism, indicated by a significant increase in the Cy5/Cy3 fluorescence ratio (glucose-actuation readout) within 10 minutes in CWGN-equipped BRL-3A cells (Fig. 3b, Extended Data Fig. 3a-b and Supplementary Table 3). Flow cytometry analysis confirmed these results (Extended Data Fig. 3c), while mutant CWGN with scrambled R\u003csub\u003eG\u003c/sub\u003e sequence abolished glucose responsiveness (Supplementary Fig. 6). To further confirm that the glucose-responsive AGSR activation, we identified that glucose addition caused 5.2-fold-enhanced c-Met phosphorylation (Y1234/Y1235) in the AGSR-engineered cells versus controls using immunofluorescence flow cytometry (Extended Data Fig. 4a-b), with strict glucose specificity over various sugar analogs and other metabolites (Fig. 3e and Extended Data Fig. 4c). Thus, CWGN can be worn on glucose‑uptake effector cells, coupling extracellular glucose sensing to intracellular c‑Met signaling as the desired AGSR output.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo achieve reversible wearability, each CWGN subunit includes an extended toehold domain in its receptor-anchoring motif for detachment. Glucose-stimulated AGSR activation can be reversed by the specifically complementary strand (C\u003csub\u003eH\u003c/sub\u003e) via strand displacement, detaching CWGN from cells to deactivate AGSR functionality (Extended Data Fig. 5a and Supplementary Table 1). CLSM imaging and flow cytometry confirmed the removal of CWGN after C\u003csub\u003eH\u003c/sub\u003e treatment (Fig. 3c and Extended Data Fig. 5b-c). C\u003csub\u003eH\u003c/sub\u003e treatment dose-dependently attenuated and finally abolished glucose-responsive AGSR signaling (Fig. 3d and Extended Data Fig. 5d), highlighting the controllable detachability as a safety mechanism to flexibly modulate and deactivate AGSR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAGSR\u003c/strong\u003e\u003cstrong\u003e-Driven Glucose Uptake Regulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe further evaluated the downstream signaling and glucose uptake regulation mediated by AGSR. In-cell western analysis confirmed glucose-dependent activation of the Met-Akt pathway in the CWGN-equipped cells (Fig. 3f and Extended Data Fig. 6a-b), while non-treated or scrambled mCWGN-equipped cells showed no response (Extended Data Fig. 6c). Given that PI3K/Akt signaling promotes GLUT4 trafficking to the cell membrane, we transfected AGSR-engineered cells with a GLUT4-EGFP \u003csup\u003e[36]\u003c/sup\u003e fusion construct to monitor GLUT4 translocation at the single-cell level. Structured illumination microscopy (SIM) imaging revealed glucose-stimulated GLUT4 membrane translocation in CWGN-equipped cells, confirming functional coupling between the AGSR activation and endogenous trafficking machinery (Fig. 3g and Extended Data Fig. 7). Furthermore, live-cell CLSM imaging demonstrated rapid AGSR activation within 2 minutes, followed by noticeable GLUT4 membrane translocation starting at 2 minutes, peaking at 4 minutes (Fig. 3i and Supplementary Fig. 7). A 2-DG uptake assay revealed a rapid onset of the glucose uptake response, beginning at just 2 minutes. After 30 minutes of glucose treatment, these AGSR-engineered hepatic BRL-3A cells exhibited a remarkable 19.3-fold enhancement in glucose internalization (Fig. 3h and Supplementary Fig. 8). Similarly, glucose enhanced AGSR-mediated glucose uptake in CWGN-equipped C2C12 skeletal muscle cells via the Met-Akt pathway (Extended Data Fig. 8). Thus, AGSR integrates glucose sensing with endogenous cellular signaling in effector cells, regulating rapid glucose uptake in a closed-loop manner.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAGSR with Tunable Glucose Sensitivity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne key feature of AGSR is its built-in, dose-responsive decision module that programs glucose-sensing thresholds to activate glucose uptake. To achieve this goal, we precisely tuned glucose-binding affinity of AGSR by rationally modulating the stability of trans-duplexed aptamer region (R\u003csub\u003eG\u003c/sub\u003e/H\u003csub\u003eS\u003c/sub\u003e duplex) via systematic truncation of the allosteric inhibition domain \u003csup\u003e[37]\u003c/sup\u003e (ID, yellow segment of H\u003csub\u003eS\u003c/sub\u003e, 10-18 nt) (Fig. 4a, Supplementary Fig. 9 and Supplementary Table 4). The dose-response curve, generated by measuring phosphorylated Met via immunofluorescence flow cytometry, revealed that increasing ID length shifted receptor activation dynamics. AGSR with short ID (\u0026lt;14 nt) induced basal activation leakage due to suboptimal duplex stability, while AGSR with 14-18 nt IDs achieved glucose-threshold-gated responses with half-maximal concentration (\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e50\u003c/sub\u003e) values of 6.7, 8.2, and 10.3 mM, respectively. Notably, the AGSR with 14 nt ID exhibited the largest dynamic range (7.4-fold) (Fig. 4b, Supplementary Fig. 10 and Supplementary Table 5). Moreover, downstream Akt phosphorylation profiles indicated that AGSR with long ID (\u0026gt;14 nt) exhibited less than 50% of the maximal activation response under hyperglycemic conditions (\u0026gt; 11.1 mM glucose), while the AGSR with 14 nt ID showed 80% activation at hyperglycemia, and negligible activity below normoglycemia (5.6 mM) (Fig. 4c and Supplementary Fig. 11). Further functional validation using myotube models differentiated from C2C12 myoblasts revealed that AGSR with 14 nt ID regulated 2-DG uptake of myotubes with a threshold-gated dose-response profile, switching on above normoglycemia (5.6 mM) and peaking at hyperglycemia (\u0026gt; 11.1 mM) with an \u003cem\u003eEC\u003c/em\u003e\u003csub\u003e50\u003c/sub\u003e of 7.8 mM (Fig. 4d and Supplementary Fig. 12). Interestingly, this mirrored c-Met/Akt signaling activation responses but with a narrower dynamic range, demonstrating the potential for precise glycemic control with reduced hypoglycemia risk. Given these results, AGSR with a 14 nt ID was selected for \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003estudies. Together,\u0026nbsp;AGSR\u0026nbsp;established\u0026nbsp;a synthetic thresholding framework to precisely regulate glucose uptake with fine-tuned dynamic range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAGSR-Mediated Glucose Homeostasis Regulation in T1D and T2D Mice\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore \u003cem\u003ein vivo\u003c/em\u003e evaluation of AGSR-mediated glycemic control in diabetic animal models, we assessed its biosafety, stability, and targeting capability. CWGN treatment did not affect cell viability in BRL-3A and C2C12 cells (Fig. 5a and Extended Data Fig. 9a). In mice receiving 3 nmol CWGN, liver damage markers remained unchanged at 24 hours (P \u0026gt; 0.05) (Fig. 5a), and histological analysis (H\u0026amp;E staining) of major organs (heart, liver, spleen, lung, kidney, muscle) showed no damage (Extended Data Fig. 9d). Furthermore, even after prolonged incubation in serum medium for up to 12 hours, the cell binding activity of CWGN remained unaffected, indicating high stability (Extended Data Fig. 9b-c). Intravenous injection of Cy5-labeled CWGN (0.5 nmol) revealed predominant accumulation in the liver and muscles, attributed to their high c-Met expression, confirming its effector cells-targeting capability (Fig. 5b, Extended Data Fig. 9e-f and Supplementary Table\u0026nbsp;6). These results demonstrated\u0026nbsp;that\u0026nbsp;CWGN\u0026nbsp;is biocompatible, stable, and tissue-selective, validating its readiness for \u003cem\u003ein vivo\u003c/em\u003e glycemic regulation.\u003c/p\u003e\n\u003cp\u003eWe further validated AGSR\u0026apos;s glycemic regulation capability in streptozotocin (STZ)-induced T1D mice \u003csup\u003e[38]\u003c/sup\u003e, where STZ-caused pancreatic \u0026beta;-cell destruction abolished endogenous insulin production. Male C57BL/6 mice receiving four STZ doses (50 mg/kg) on alternating-day developed hallmark diabetic phenotypes including 6.8% body weight loss, an increase in fasting blood glucose levels (BGL) from 6.64 mmol/L to 16.32 mmol/L, and impaired glucose tolerance shown by intraperitoneal glucose tolerance tests (IPGTT) (Extended Data Fig. 10a-e). CWGN administration (0.5 nmol) in these T1D mice significantly improved glucose homeostasis compared to scrambled mCWGN controls, evidenced by a 16% decrease in maximum BGL amplitude, a 1.3-fold reduction in the area under the curve (AUC) of IPGTT within 120 min, and a 20.9-fold greater glucose-lowering efficiency under hyperglycemic conditions (Fig. 5c-d and Supplementary Fig. 13). Notably, CWGN did not induce significant hypoglycemia under normoglycemic conditions due to its threshold-gated response, unlike insulin treatment with a rapid BGL decline to 2.5 mmol/L, leading to fainting (Fig. 5e). Furthermore, hypoglycemic index (HI) \u003csup\u003e[39]\u003c/sup\u003e quantification confirmed CWGN\u0026apos;s superior safety with 6.8-fold smaller HI versus insulin (Fig. 5f), indicating its significantly lower risk of hypoglycemia. These findings demonstrated that CWGN\u0026apos;s ability to effectively regulate blood glucose levels and improve glucose tolerance in T1D mice while minimizing hypoglycemia risk.\u003c/p\u003e\n\u003cp\u003eT2D, accounting for over 90% of diabetes cases, primarily arises from insulin resistance in effector cells \u003csup\u003e[40, 41]\u003c/sup\u003e. We next sought to demonstrate that AGSR could circumvent insulin insensitivity by directly enhancing glucose uptake via the non-canonical Met-Akt pathway. In palmitate-treated BRL-3A cells modeling insulin resistance \u003csup\u003e[42]\u003c/sup\u003e, insulin-stimulated 2-DG uptake was reduced by 88.3%, whereas AGSR maintained 91.3% uptake capacity versus controls, demonstrating its efficacy\u0026nbsp;in insulin-resistant cells (Fig. 5g). To validate\u0026nbsp;the\u0026nbsp;therapeutic efficacy\u0026nbsp;of AGSR\u0026nbsp;\u003cem\u003ein vivo\u003c/em\u003e, we established\u0026nbsp;a\u0026nbsp;T2D mouse model\u0026nbsp;\u003csup\u003e[43]\u003c/sup\u003e by treatment\u0026nbsp;with\u0026nbsp;STZ (50 mg/kg)\u0026nbsp;on\u0026nbsp;three alternating\u0026nbsp;days\u0026nbsp;and high-fat/high-sugar feeding for 2 months. Successful modeling of T2D mice with insulin resistance was confirmed by an increase in the mice\u0026apos;s weight (21.02 to 22.49g), an increase in fasting BGL (6.02 to 14.07\u0026nbsp;mmol/L), and marked reduction in insulin sensitivity indicated by insulin tolerance tests (ITT) (Fig. 5h\u0026nbsp;and Extended Data Fig. 10f-j).\u0026nbsp;AGSR-engineered mice\u0026nbsp;exhibited\u0026nbsp;24.7% lower AUC than mCWGN controls in\u0026nbsp;IPGTT, demonstrating robust glycemic control\u0026nbsp;of AGSR\u0026nbsp;in T2D models (Supplementary Fig. 14). Dose-dependent efficacy of\u0026nbsp;CWGN\u0026nbsp;was evidenced by progressive attenuation of post-injection hyperglycemia, accelerated glucose clearance, and reduced AUCs of\u0026nbsp;IPGTT (Fig. 5i-j). To assess continuous glycemic control, we performed three\u0026nbsp;IPGTTs after a single\u0026nbsp;CWGN\u0026nbsp;administration (3 nmol) to stimulate glycemic fluctuations by daily tri-meal. Results showed that AGSR maintained effective glucose control across three sequential glucose challenges, achieving\u0026nbsp;a\u0026nbsp;29.5%\u0026nbsp;lower\u0026nbsp;cumulative AUC versus controls, indicating sustained glycemic regulation throughout the three meals in T2D mice (Fig. 5k and\u0026nbsp;Supplementary Fig. 15). Collectively, AGSR offers a novel therapeutic modality for durable glycemic regulation through insulin-independent pathways, directly addressing insulin-resistant dysregulation in T2D.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAGSR Efficacy in Diabetic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDog\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLarge animal models, particularly diabetic dogs, offer critical translational insights into human diabetes pathophysiology due to conserved glycemic regulatory mechanisms and phenotypic fidelity \u003csup\u003e[44]\u003c/sup\u003e. We further extended functional validation of AGSR to alloxan (ALX)-induced diabetic beagles \u003csup\u003e[45]\u003c/sup\u003e, a dog model simulating human T1D progression through \u0026beta;-cell destruction. \u003cem\u003eIn vitro\u003c/em\u003e, AGSR activated Met/Akt-dependent 2-DG uptake in dog-derived c-Met-positive MDCK cells (Fig. 6a-c), confirming its cross-species efficacy, likely attributable to evolutionary conservation of its glucose regulatory mechanism across mammalian species. For \u003cem\u003ein vivo\u003c/em\u003e assessment, we successfully established the diabetic beagle model, confirmed by a significant fasting BGL increase from 3.04 to 24.08 mmol/L,\u0026nbsp;accompanied by inter-individual body-weight fluctuations\u0026nbsp;(11.1 to 10.46 kg)\u0026nbsp;consistent with\u0026nbsp;ALX-induced early‑stage\u0026nbsp;T1D\u0026nbsp;dog\u0026nbsp;phenotypes (Fig.\u0026nbsp;6d-f). Intravenous glucose tolerance tests (IVGTT) were conducted after intravenous injection of\u0026nbsp;CWGN\u0026nbsp;(20 nmol).\u0026nbsp;AGSR\u0026nbsp;significantly reduced peak post-glucose\u0026nbsp;levels\u0026nbsp;by 40.1% versus controls (12.12 vs 20.24 mM, P = 0.0015)\u0026nbsp;and a\u0026nbsp;44.8% reduction in the 120-min AUC (1179.4 vs\u003cem\u003e\u0026nbsp;\u003c/em\u003e2137 mM\u0026middot;min), indicating significantly improved glucose tolerance (Fig. 6g-i). Notably, AGSR maintained glycemic stability under normoglycemia, with a hypoglycemic index 8.6-fold lower than insulin (Fig. 6j). These results highlight the AGSR\u0026apos;s potential for robust glycemic control without causing hypoglycemia, validated in a clinically relevant large animal model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn summary, we present a \u003cem\u003ede novo\u003c/em\u003e design strategy to engineer glucose-uptake effector cells with artificial glucose-sensing receptors (AGSRs). This approach establishes a glucose sensing-uptake closed-loop at the single-cell level, distinct from conventional multicellular coordinated systems relying on pancreatic \u0026beta;-cell sensing and insulin-mediated effector cells regulation\u003csup\u003e\u0026nbsp;[11]\u003c/sup\u003e.\u0026nbsp;To achieve this, we developed non-genetic DNA-protein semi-synthetic AGSRs via rational integration of glucose-responsive DNA nanodevices to endogenous uptake-regulatory receptors, circumventing the poorly understood glucose-sensing mechanisms of the natural counterparts. Furthermore, AGSRs incorporate a highly specific glucose-recognition aptameric module, overcoming the promiscuous ligand selectivity of natural glucose-sensing receptors.\u003c/p\u003e\n\u003cp\u003eMoreover, AGSR provides a closed-loop glycemic regulation solely implemented by effector cells. This novel strategy potentially addresses three key problems in traditional glycemic-regulating approaches. First, AGSR circumvents insulin resistance by activating alternative RTK pathways (e.g., c-Met) to drive glucose uptake in insulin-desensitized cells. Second, AGSR directly activates effector cell glucose uptake and downstream metabolism, enabling a rapid response within 2 minutes, outperforming both synthetic cells relying on insulin-gene-expression (\u0026ge;1 h) and translation-regulated insulin production (\u0026ge;30 min) \u003csup\u003e[16, 17, 19]\u003c/sup\u003e. Third, AGSR allows precise tuning of glucose-response thresholds via rational DNA molecular engineering, as shown by adjustable c-Met activity, Akt signaling, and glucose uptake (Fig. 4), along with hyperglycemia-specific activation in diabetic models (Fig. 5d and Fig. 5e). Both indicated the substantially improved safety of AGSR by mitigating hypoglycemia risks. Furthermore, the cross-species efficacy of AGSR was validated across T1D/T2D models in mice and dogs, further demonstrating its universal physiological compatibility.\u003c/p\u003e\n\u003cp\u003eOur non-genetic, plug-and-play strategy uses CWGNs to assemble AGSRs directly in effector cells, enabling reversible, controllable, and gene-editing-free therapeutic installation. This allows single-cell-level closed-loop glucose regulation, transforming the conventional \u0026quot;monitor-and-treat\u0026quot; paradigm into an intracellular synthetic circuit. Additionally, the AGSR is highly modular, and its signaling-actuation motifs are compatible with FGFR aptamers and even recently reported insulin-receptor-specific aptamers if insulin resistance circumvention is non-obligatory \u003csup\u003e[46, 47]\u003c/sup\u003e. Crucially, our AGSR presents a proof-of-concept of DNA nanotechnology-enabled programmable cellular regulator, opening an avenue for engineering artificial receptor-based cell-autonomous therapeutics beyond diabetes. For instance, replacing glucose aptamers with lipid/creatinine sensors could engineer \u0026quot;cellular wearables\u0026quot; targeting hepatic steatosis or renal disorders \u003csup\u003e[48, 49]\u003c/sup\u003e, while dual-input logic gates (e.g. protein biomarker and pH) might address cancer-associated acidosis, coupled with development of corresponding DNA signal-activating modules to achieve feedback-controlled activation of therapeutic artificial receptor-mediated signaling pathways. Looking forward, future efforts will focus on improving AGSR\u0026rsquo;s stability, CWGN\u0026rsquo;s targeting-specificity, and pharmacokinetics for chronic administration, alongside integrating multiplexed biosensing for systemic metabolic regulation, which is crucial for realizing programmable cellular therapeutics. In summary, \u003cem\u003ein vivo\u003c/em\u003e equipping desired cells with therapeutic artificial receptors via cell-wearables will provide new chemical biological toolkits for next-generation precision therapy, in which synthetic circuits symbiotically interface with native physiology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are available within the article and its Supplementary Information. Source data are provided with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Z.-J. Zhu and Y. Cai (Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences) for their technical support in the LC\u0026minus;MS-based untargeted metabolomics and data analysis. We thank N. Cai (Cellway Biotechnology Co., Ltd) for technical discussions in the construction of EGFP-GLUT4 and diabetic mice model. We thank the Analytical Instrumentation Center of Hunan University for Structured Illumination Microscopy (SIM). This research was supported by the National Key Research and Development Program of China (2024YFA0916700 to N.Z.), the National Natural Science Foundation of China (22034002 and 92253304 to N.Z., 22177030 to H.h.W., 22425404 to Z.-J. Z., 22407044 to F.H.), National Key R\u0026amp;D Program of China (2022YFC3400702), Shanghai Key Laboratory of Aging Studies (19DZ2260400), Shanghai Municipal Science and Technology Major Project, and Shanghai Basic Research Pioneer Project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ.N. conceived and designed the project. F.H., H.h.W. and Z.N. designed, and F.H. performed the experiments. Z.-J. Z and Y.p.C. provided technical assistance for untargeted metabolomics-related experiments. F.H., M.W, Y.W., H.h.W. and Z.N. analyzed the data. Z.N., H.h.W, and F.H. wrote the manuscript and supervised the project. All authors read and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKojima, R., Aubel, D. \u0026amp; Fussenegger, M. Building sophisticated sensors of extracellular cues that enable mammalian cells to work as \u0026quot;doctors\u0026quot; in the body. \u003cem\u003eCell. Mol. Life Sci.\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 3567-3581 (2020).\u003c/li\u003e\n\u003cli\u003eMahameed, M. \u0026amp; Fussenegger, M. Engineering autonomous closed-loop designer cells for disease therapy. \u003cem\u003eiScience\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 103834 (2022).\u003c/li\u003e\n\u003cli\u003eStefanov B.-A. \u0026amp; Fussenegger, M. 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Selective and naked eye colorimetric detection of creatinine through aptamer-based target-induced passivation of gold nanoparticles. \u003cem\u003eRSC Adv.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 33784-33793 (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eOligonucleotides\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe oligonucleotides used for constructing and characterizing the cell-wearable glucose-regulating nanodevice (CWGN) (detailed sequences listed in Supplementary Tables 1, 3, 4), and quantitative real-time PCR experiments (detailed sequences listed in Supplementary Table 2) were custom-synthesized by Sangon Biotech Co., Ltd. The oligonucleotides for animal and biodistribution experiments (Supplementary Table 1, 6) were custom-synthesized by Shanghai DNA Bioscience Co. Ltd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture and transfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll cell lines were cultured in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator (Thermo Fisher, USA) at 37 ℃. BRL-3A cells (Servicebio, cat. no. STCC30016) were cultured in a specialized medium (Servicebio, cat. no. STCC30016P). C2C12 cells (ATCC, cat. no. CRL-1772), HepG2 (ATCC, cat. no. HB-8065), HEK293T (ATCC, cat. no. CRL-3519), NIH/3T3 cells (ATCC, cat. no. CRL-1658) and MDCK cells (ATCC, cat. no. CCL-34) were cultured in DMEM with 10% FBS (Biological Industries, cat. no. 04-001-1A) and 1% penicillin and streptomycin (NCM Biotech, cat. no. C125C8).\u003c/p\u003e\n\u003cp\u003eTo visualize the GLUT4 translocation, a GLUT4-EGFP plasmid was constructed by fusing the carboxyl terminal of GLUT4 with the coding sequence of Enhanced Green Fluorescent Protein (EGFP) as described by Dobson et al. \u003csup\u003e[36]\u003c/sup\u003e. HEK293T cells and HepG2 cells were transfected with the EGFP-GLUT4 plasmid using Lipo8000 (Beyotime, cat. no. C0533) transfection reagent according to the manufacturer\u0026apos;s protocol. Afterward, the cells were incubated with 200\u0026thinsp;nM CWGN in HEPES buffered saline solution for 10\u0026thinsp;minutes. Real-time live-cell images were collected at 488 nm and 561\u0026thinsp;nm with CLSM (Nikon Ti-E controlled by NIS Elements AR) using a 60\u0026times; oil immersion objective after adding 10 mM glucose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlucose\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eu\u003c/strong\u003e\u003cstrong\u003eptake\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003cstrong\u003essays\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGlucose uptake was detected with the Glucose Uptake-Glo\u0026trade; Assay kit (Promega, J1343) according to the manufacturer\u0026rsquo;s instructions. One day prior to the assay, the medium was removed and replaced with 100 \u0026mu;L DMEM without serum. On the day of the assay, the medium was replaced with 100 \u0026mu;L PBS containing aptameric dimer and incubated for 30 minutes at 37\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e. The medium was then removed and 50 \u0026mu;L of 0.1 mM 2-DG in PBS was added and incubated for 10 minutes at 25 \u0026deg;C. Next, 25 \u0026mu;L of Stop Buffer was added, followed by brief shaking and addition of 25 \u0026mu;L Neutralization Buffer. Finally, 100 \u0026mu;L of 2DG6P Detection Reagent was added, shaken briefly and incubated for 1 hour at 25 \u0026deg;C. Luminescence was recorded on a SynergyTM Mx multi-mode microplate reader (BioTek, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of plasma membrane GLUT2/4 by immunofluorescence and flow cytometry\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effects of aptameric dimer and HGF on glucose transporter GLUT2/4 in glucose-uptaking cells (hepatocytes/myocytes) were evaluated through immunofluorescence \u003csup\u003e[50]\u003c/sup\u003e. BRL-3A and C2C12 cells were seeded to confocal dishes and starved in medium containing 0.2% FBS for 24 hours. Cells were then stimulated with 50 nM aptameric dimer and 1 nM HGF in PBS at 37 \u0026deg;C for 30 minutes, and subsequently fixed with 4% paraformaldehyde for 30 minutes. Samples were incubated in 5% normal goat serum in PBS for 30 minutes at room temperature, then incubated with primary antibody overnight at 4 \u0026deg;C. After rinsing, samples were incubated with a fluorochrome-conjugated secondary antibody for 1 hour at 37\u0026deg;C in the dark. The primary antibodies of GLUT2 Polyclonal antibody, (cat. no. 20436-1-AP, 1:500) and GLUT4 Monoclonal antibody (cat. no. 66846-1-Ig, 1:500) were obtained from Proteintech. The Goat anti-Rabbit IgG (H+L) Secondary Antibody, Alexa Fluor 594 (cat. no. AWS0006, 1:1000) was purchased from Abiowell and the Rabbit anti-Mouse IgG H\u0026amp;L (FITC) (cat. no. ab6724, 1:1000) was purchased from Abcam. After that, we incubated samples with Hoechst 33342 (Beyotime, cat. no. C1022). Finally, immunofluorescence images were collected at 488 nm and 561\u0026thinsp;nm with CLSM (Nikon Ti-E controlled by NIS Elements AR) using a 60\u0026times; oil immersion objective.\u003c/p\u003e\n\u003cp\u003eCells were reseeded to 12-well plates for 1 day before use in experiments and starved in DMEM without fetal bovine serum for 24 hours before stimulation. Stimulus was added directly to the wells. After treatment in the presence or absence of aptameric dimer or HGF, cells were quickly transferred to 4 \u0026deg;C and washed with cold phosphate-buffered saline (PBS) containing 0.9 mM Ca\u003csup\u003e2+\u003c/sup\u003e and 0.5 mM Mg\u003csup\u003e2+\u003c/sup\u003e. All subsequent steps were carried out at 4 \u0026deg;C, and staining of GLUT2/4 was done on adherent cells. Cells were incubated with a 1:200 dilution of anti-GLUT2/4 for 1.5 hours after 2% bovine serum albumin (BSA) for 1 hour. Cells were then washed twice in PBS for 5 minutes each time. They were then incubated for 1 hour in secondary antibody. Cells were rinsed twice in PBS, and resuspended by gentle scraping in PBS with 2% BSA for flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLC\u0026minus;MS\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;based untargeted metabolomics\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eanalyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMetabolite extraction of BRL-3A cell samples followed the standard procedures (www.zhulab.cn/articles/64.html). Extracts were dried in a vacuum concentrator at 4 \u0026deg;C and analyzed by liquid chromatography-mass spectrometry (LC\u0026minus;MS). Data were acquired using a UHPLC system (Vanquish, Thermo Scientific) coupled to an orbitrap mass spectrometer (Exploris 480, Thermo Scientific). A Waters BEH amide column (1.7 \u0026mu;m; 100 mm \u0026times; 2.1 mm (i.d.)) \u0026nbsp;and a Phenomenex Kinetex C18 column (2.6 \u0026mu;m, 2.1 \u0026times; 100 mm \u0026times; 2.1 mm (i.d.)) were used for LC separation. The mobile phases, linear gradient elution, and ESI source parameters followed those described in a previous publication\u003csup\u003e\u0026nbsp;[\u003c/sup\u003e\u003csup\u003e51\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e. Metabolite annotation was performed using MetDNA (http://metdna.zhulab.cn/) \u003csup\u003e[\u003c/sup\u003e\u003csup\u003e52\u003c/sup\u003e\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u003csup\u003e53\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ\u003c/strong\u003e\u003cstrong\u003euantitative real-time PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expression levels of gluconeogenic genes, phosphoenolpyruvate carboxykinase (\u003cem\u003ePck1\u003c/em\u003e) and glucose 6-phosphatase (\u003cem\u003eG6pc\u003c/em\u003e), were determined by quantitative real-time PCR using \u0026beta;-actin as an internal reference \u003csup\u003e[54]\u003c/sup\u003e. Cells grown on a 6-cm dish were starved in a medium supplemented with 0.2% FBS for 24\u0026thinsp;hours and then stimulated with 10 nM aptameric dimer and 10 nM insulin for 4\u0026thinsp;hours at 5% CO\u003csub\u003e2\u003c/sub\u003e and 37\u0026thinsp;\u0026deg;C. Total RNAs were extracted using the AG RNAex Pro RNA extraction kit (Accurate Biology, AG21101) by following the manufacturer\u0026rsquo;s instructions. The extracted RNAs were quantified using the Nanodrop spectrophotometer and then reverse-transcribed to complementary DNAs using Evo M-MLV Reverse Transcriptase Synthesis Kit (Accurate Biology, AG11728). Quantitative real-time PCR was performed using 2\u0026times; SupRealQ Purple Universal SYBR qPCR Master Mix (U\u003csup\u003e+\u003c/sup\u003e) (Vazyme, cat. no. 7E0511G4) on an Applied Biosystems QuantStudioTM 7 Flex. mRNA expression levels were normalized to housekeeping genes \u0026beta;-actin and calculated using the 2^(-\u0026Delta;\u0026Delta;Ct) method. The sequences of primers are listed in Supplementary Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeriodic Acid-Schiff (PAS) staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBRL-3A cells were cultured in 6 well plates and subjected to starvation treatment with DMEM containing 0.2% FBS for 18 hours. Then, the cells were treated with the aptameric dimer, insulin, and HGF for 4 hours and stained using a glycogen-specific PAS staining kit (Bioss, S0126). Fluorescent images of PAS-stained hepatocytes were captured using a fluorescent imaging microscope (Olympus, IX-73).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell imaging\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor cell imaging, the cells were seeded in 35 mm confocal dish with complete medium and incubated for 24 hours at 5% CO\u003csub\u003e2\u003c/sub\u003e and 37 \u0026deg;C. BRL-3A cells were first washed with HEPES (1\u0026times;) and incubated with CWGN (100 nM) in 200 \u0026mu;L HEPES buffer at 37 \u0026deg;C for 10 minutes. Subsequently, the cells were washed twice with HEPES buffer, and 200 \u0026mu;L HEPES buffer containing 10 mM glucose was added. Real-time live cell imaging was performed using a confocal laser scanning microscope (CLSM) (Nikon, Eclipse TE2000-E, Japan) with a 60 \u0026times; oil immersion objective. Excitation wavelength and emission filters were set as follows: FAM channel (excitation 488 nm, emission 525 nm), Cy3 channel (excitation 550 nm and emission 570 nm), Cy5 channel (excitation 640 nm and emission 670 nm). Fluorescence intensity on the cell surface was analyzed and quantified using the Image J software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSIM image\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHEK293T cells were transfected with the EGFP-GLUT4 plasmid using Lipo8000 (Beyotime, cat. no. C0533) transfection reagent according to the manufacturer\u0026apos;s protocol. Afterward, the cells were incubated with 200\u0026thinsp;nM CWGN in HEPES buffered saline solution for 10\u0026thinsp;minutes. Subsequently, the cells were washed twice with HEPES buffer, and 200 \u0026mu;L HEPES buffer containing a 10 mM glucose was added for 15 minutes. Cells were then fixed with 4% paraformaldehyde (PFA) for 15 minutes and stained with Hoechst for 5 minutes. Images of the AGSR-activation event and GLUT4 translocation of CWGN-equipped HEK293T cells in the presence and absence of glucose were acquired by Structured Illumination Microscopy (SIM) (Nikon ECLIPSE Ti2) and treated with deconvolution. Excitation wavelength and emission filters: Hoechst channel (excitation 405 nm and emission 430-475 nm, Laser power 5%), EGFP channel (excitation 488 nm, emission 502-546 nm, Laser power 8%), Cy5 channel (excitation 638 nm and emission 666-732 nm, Laser power 5%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlow cytometry was used to assess the performance of AGSR on live cell membranes. BRL-3A cells were harvested in cell dissociation buffer to prepare cell suspensions. Subsequently, 1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were incubated with 100 nM CWGN at 37 \u0026deg;C for 10 minutes. Afterward, the cells were washed twice with 200 \u0026mu;L PBS and then incubated with 10 mM glucose at 37 \u0026deg;C for 15 minutes. Finally, cells were suspended in 200 \u0026mu;L PBS and analyzed by flow cytometry (BD Accuri TM C6 Plus, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence flow cytometry analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBRL-3A cells were digested with trypsin to form suspended single cells, and washed three times with PBS to remove intercellular connections caused by trypsin. Cells were treated with aptameric dimer, CWGN, and mCWGN, respectively at 37 ℃ for 10 minutes, and unreacted DNA was removed by centrifugation. Then, different concentrations of glucose were added and reacted for 30 minutes. Cells were then fixed and permeabilized with 4% PFA containing 0.1% TritonX-100 for 15 minutes. Finally, BRL-3A cells were incubated with the Rabbit Anti-phospho-Met (Tyr1234)/FITC Conjugated antibody (Bioss, bs-18798R-FITC; 1:2000 dilution) on ice for 1 hour, and analyzed using the flow cytometer (BD Accuri TM C6 Plus, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003ecell western assay\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were seeded in 96-well plates (Corning Costar) and incubated until confluence. Cells were starved for 24 hours in DMEM supplemented with 0.2% FBS, and then incubated with CWGN for 10 minutes. After replacing the medium, cells were stimulated by glucose for another 15 minutes, and then fixed with 4% formaldehyde for 30 minutes at 37 \u0026deg;C. Next, cells were permeabilized with 0.1% Triton X-100 washing solution, and blocked with Odyssey\u0026reg; Blocking Buffer (LI-COR) for 1.5 hours at room temperature with moderate shaking. The blocking buffer was removed by aspiration, and 50 \u0026micro;l of the desired primary antibody (1:250 dilution) was added to the wells and incubated overnight at 4 \u0026deg;C. The plate was then washed three times with 0.1% Tween-20 washing solution with gently shaking for 5 minutes at room temperature. Next, 50 \u0026micro;l of the secondary antibody (1:1000 dilution) solution was added to each well and incubated away from light for 60 minutes with gentle shaking at room temperature. Again, the plate was washed three times with 0.1% tween-20 washing solution with gentle shaking for 5 minutes at room temperature. After the final wash, the images were acquired on the LI-COR Odyssey\u0026reg; Infrared Imaging System (Lincoln, Nebraska, USA). The primary antibodies of phospho-Met (Y1234/Y1235) (3126S), phospho-Akt (S473) (4060S) and \u0026alpha;-tubulin (3873S) were obtained from Cell Signaling Technology. The primary antibody of phospho-IRS2 (Ser731) (bs-5397R) was purchased from Bioss. The IRDye secondary antibodies, including IRDye\u0026reg; 800CW Goat anti-Mouse Secondary Antibody (LI-COR P/N 925-32210 or 926-32210) and IRDye\u0026reg; 680RD Goat anti-Rabbit Secondary Antibody (LI-COR P/N 925-68071 or 926-68071) were obtained from LI-COR (Lincoln, Nebraska, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoblotting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMDCK cells were seeded in 35 mm dishes. When the cells reached 80% confluence, they were starved for 24 hours in DMEM supplemented with 0.2% FBS. Subsequently, the medium was changed and incubated with CWGN for 10 minutes in the incubator. The medium was then replaced and the cells were stimulated by 10 mM glucose for 15 minutes. The dishes were then placed on ice to stop the stimulation and washed twice by pre-cooled PBS. Subsequently, the cells were lysed with RIPA lysis buffer (containing 1% phosphatase inhibitors and protease inhibitors). The cell lysates were centrifuged at 14000 rcf for 10 minutes, and the supernatant was retained and stored at -20 \u0026deg;C until use.\u003c/p\u003e\n\u003cp\u003eThe cell lysates were separated by 8% SDS-PAGE in the electrophoresis experiment, then transferred to a nitrocellulose membrane by semi-dry electrophoretic transfer unit for 16 minutes. After blocking with a 5% BSA in the PBST solution (1\u0026times; PBS with 0.1% Tween-20) for 1 hour, the membrane was reacted with primary antibody (1:1000 dilution) overnight at 4 \u0026deg;C and then with secondary antibody (1:5000 dilution) for 1 hour at room temperature. The secondary antibodies, including goat anti-rabbit IgG (H\u0026amp;L)-HRP and goat anti-mouse IgG (H\u0026amp;L)-HRP, were obtained from Invitrogen. Before imaging, the membranes were treated with ECL substrate solution (NCM Biotech Co. Ltd). Chemiluminescent images were obtained using multifunctional molecular imaging system (Azure Biosystems 600).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ei\u003c/strong\u003e\u003cstrong\u003ensulin\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003er\u003c/strong\u003e\u003cstrong\u003eesistance\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003cstrong\u003eell\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003em\u003c/strong\u003e\u003cstrong\u003eodel\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn insulin resistance cell model was established by free fatty acids \u003csup\u003e[42]\u003c/sup\u003e. BRL-3A cells were stimulated by 0.5 mM palmitate for 24 hours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC2C12\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003em\u003c/strong\u003e\u003cstrong\u003eyoblasts differentiate into myotubes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn Day 1, C2C12 cells (5\u0026times;10\u003csup\u003e3\u003c/sup\u003e per 100 \u0026mu;L) in DMEM containing 10% fetal bovine serum were seeded in a 96-well plate. Replace medium every 2-3 days. On Day 5, remove media and initiate differentiation by adding 100 \u0026mu;L DMEM containing 2% horse serum (Gibco, cat. no. 16050122). The medium was replaced daily. Myotubes reached maturity after 3-5 days of low serum treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStability of CWGN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCWGN (500 nM) was incubated in PBS (pH 7.4) buffer containing 10% FBS for different durations. Samples were then analyzed by 8% native PAGE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal studies\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnimals were maintained under pathogen-free conditions, and all experiments were conducted in accordance with the Regulations for the Management of Laboratory Animals of the Ministry of Science and Technology of the People\u0026apos;s Republic of China. All procedures involving animals were reviewed and approved by the Experimental Animal Ethics Committee of Hunan University (HNUBIO202102006) and the Committee on the Ethics of Animal Experiments of Hunan Provincial Laboratory Animal Center [SYXK (Xiang) 2018\u0026ndash;0006]. Adult male C57BL/6 mice (4-6 weeks old) were purchased from Hunan SJA Laboratory Animal Co., Ltd and housed in viral- and pathogen-free conditions, with a maximum of five animals per cage. Mice were provided with food and water ad libitum and housed in a controlled environment with a 12-h light / 12-h dark cycle.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiodistribution of CWGN\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMice were intravenously injected with Cy5-labeled CWGN (0.5 nanomolar) via the tail vein. After 30 minutes and 120 minutes, the mice were perfused with 4% paraformaldehyde (PFA) and major organs (heart, liver, spleen, lung, kidney, muscle) were excised at an appropriate time. The excised organs were imaged using an IVIS Spectrum CT with excitation at 640 nm and emission at 680 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSTZ-induced type\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;diabetes mice model\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo build the type 1 diabetes model \u003csup\u003e[38]\u003c/sup\u003e, streptozocin (STZ dissolved in 0.1 M citrate buffer solution, 10 mg/mL) was intraperitoneally injected into mice for 8 weeks with a dose of 120 mg/kg after fasting 12 hours but allowing free access to water. Then, mice were recovered to normal food supply. One week later, body weight and blood glucose levels of the mice were measured. Mice with blood glucose higher than 11.1 mmol/L were regarded as diabetic mice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh-sugar and high-fat\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ediet-\u003c/strong\u003e\u003cstrong\u003einduced type\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;diabetic mice model\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo develop the type 2 diabetes model \u003csup\u003e[43]\u003c/sup\u003e, firstly streptozocin (STZ; dissolved in 0.1 M citrate buffer solution, 10 mg/mL) was injected intraperitoneally into mice for 8 weeks with a dose of 50 mg/kg after fasting 12 hours but allowing free access to water for three times every other day. Each time after injection the mice were fed with high-sugar and high-fat diet. Then after all the injection finished, the mice were continually raised with high-sugar and high-fat diet. Two months later, the weight and the blood glucose level were measured. Mice with a blood glucose level higher than 11.1 mmol/L were considered diabetic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eALX-induced diabetic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edog\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;model\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo build the alloxan (ALX)-induced diabetic dogs \u003csup\u003e[45]\u003c/sup\u003e, 50 mg/kg freshly prepared ALX solution (200 g/L) was injected into the superficial vein of the lower limbs, and the weight and blood glucose level of dogs were measured after 7 consecutive days of injection. The modeling process was completed by Beijing Sinogene Biotechnology Co., Ltd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlucose tolerance test (GTT)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrior to the glucose tolerance test, all animals were fasted overnight for 12 hours with free access to water. The body weight of each diabetic mouse and diabetic dog was measured before the test to accurately calculate the glucose dosage (2 g/kg for mice, 1 g/kg for dogs), and the initial blood glucose levels were recorded at the end of the fasting period. For diabetic mice, an intraperitoneal glucose tolerance test (IPGTT) was conducted. Mice received an intraperitoneal injection of CWGN, followed by an intraperitoneal injection of glucose. For diabetic dogs, an intravenous glucose tolerance test (IVGTT) was performed. Dogs received an intravenous injection of CWGN, followed by an intravenous glucose injection. The timing of the test began immediately after glucose administration. Blood glucose levels of each diabetic mouse/dog were measured at specific time points, including 30 minutes, 60 minutes, 90 minutes, 120 minutes, 150 minutes, and 180 minutes after the glucose injection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInsulin tolerance test (ITT)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter a 4-hour fasting period, the body weight and initial blood glucose levels of the mice were measured. Subsequently, CWGN was injected, followed by insulin injection (0.5 U/kg) 30 minutes later. Timing began immediately after the insulin injection. Blood glucose levels of each diabetic mouse were measured at specific time points, including 30 minutes, 60 minutes, 90 minutes, 120 minutes, 150 minutes, and 180 minutes after the insulin injection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCytotoxicity analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBRL-3A cells and C2C12 cells (1\u0026times;10\u003csup\u003e4\u003c/sup\u003e) were cultured in a 96-well plate for 24 hours. The medium was then replaced with either fresh medium alone or medium containing different concentrations of CWGN, and the cells were incubated for an additional 24 or 48 hours. After washing twice with PBS, the Cell Counting Kit-8 (Beyotime, cat. no. C0039) assay reagent was added to each well according to the manufacturer\u0026rsquo;s instructions. After 1 hour incubation, cell viability was determined by measuring the absorbance at 450 nm using a microplate reader.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLiver function assessment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCWGN was injected into the tail vein of normal mice, and serum was collected after 24 hours. Serum was separated immediately after centrifugation of the blood sample at 4,000 rpm for 15 minutes at 4 \u0026deg;C. Then, serum levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were measured using the test kit according to the manufacturer\u0026rsquo;s instructions (Jiancheng Biotech. Co., Ltd).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHematoxylin and eosin (H\u0026amp;E) staining\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMice subjected to different treatments were sacrificed 24 hours later, and the organs were excised and fixed in 4% paraformaldehyde for 48 hours. Subsequently, the tissues were dehydrated in a sucrose solution for an additional 48 hours and embedded in Optimal Cutting Temperature compound (OCT). The 5-mm-thick sections were prepared and stained with H\u0026amp;E solution (Beyotime, cat. no. C0105). Images of H\u0026amp;E-stained sections were acquired using a binocular biological microscope (Leica, DM500, Germany).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are represented as mean \u0026plusmn; standard deviation (S.D.) from at least three biologically independent experiments. Statistical significance was determined using unpaired two-tailed Student\u0026rsquo;s \u003cem\u003et-test\u003c/em\u003e, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n\u003col start=\"50\"\u003e\n\u003cli\u003eBogan, J.S., McKee, A.E. \u0026amp; Lodish, H.F. Insulin-responsive compartments containing GLUT4 in 3T3-L1 and CHO cells: regulation by amino acid concentrations. \u003cem\u003eMol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Cell\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Biol.\u003c/em\u003e\u003cstrong\u003e21\u003c/strong\u003e, 4785-4806 (2001).\u003c/li\u003e\n\u003cli\u003eWang, R. et al. Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging drosophila. \u003cem\u003eNat. Commun.\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 3518 (2022). \u003c/li\u003e\n\u003cli\u003eZhou, Z. et al. Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking.\u003cem\u003e Nat. Commun. \u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 6656 (2022). \u003c/li\u003e\n\u003cli\u003eShen, X. et al. Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics.\u003cem\u003e Nat. Commun. \u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 1516 (2019).\u003c/li\u003e\n\u003cli\u003eArden, C. et al. Elevated glucose represses liver glucokinase and induces its regulatory protein to safeguard hepatic phosphate homeostasis. \u003cem\u003eDiabetes\u003c/em\u003e\u003cstrong\u003e60\u003c/strong\u003e, 3110-20 (2011).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7115886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7115886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Synthetic receptors enable programmable cellular functions, but their metabolism-regulating applications remain underexplored. Current synthetic cell strategies for glycemic control mimic pancreatic β-cell glucose-responsive insulin output to mediate peripheral glucose-uptake effector cells via multicellular closed-loop coordination, yet incurring delayed responses and limited efficacy under insulin resistance. Herein, we present a de novo-designed artificial glucose-sensing receptor (AGSR) enabling glucose-uptake effector cells (hepatocytes/myocytes) to sense glucose directly and achieve autonomous single-cell closed-loop glycemic regulation. AGSR is formed through equipping a cell-wearable glucose-regulating DNA nanodevice (CWGN) onto endogenous c-Met receptors, integrating glucose sensing, threshold-based decision-making, and c-Met-mediated metabolism-modulating actuation within a CWGN-built-in DNA molecular circuit. AGSR exhibits precise hyperglycemia-specific responsiveness, minute-level activation of glucose uptake, and sustained efficacy in insulin-resistant settings due to its insulin receptor-independence. In type 1 and type 2 diabetic mice/dog models, AGSR significantly improves glucose tolerance without hypoglycemia risk, highlighting the potential of DNA nanotechnology-based precision treatment of metabolic disorders.","manuscriptTitle":"Programmable Artificial Glucose-sensing Receptor for Autonomous Single-Cell Closed-loop Glycemic Control","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 08:06:38","doi":"10.21203/rs.3.rs-7115886/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-biomedical-engineering","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"natbiomedeng","sideBox":"Learn more about [Nature Biomedical Engineering](http://www.nature.com/natbiomedeng/)","snPcode":"41551","submissionUrl":"https://mts-natbiomedeng.nature.com/cgi-bin/main.plex","title":"Nature Biomedical Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"80abec0c-c1ad-4422-a80f-71976d0c74e6","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":52875592,"name":"Physical sciences/Nanoscience and technology/DNA nanotechnology"},{"id":52875593,"name":"Biological sciences/Chemical biology/DNA"},{"id":52875594,"name":"Biological sciences/Cell biology/Cell signalling"},{"id":52875595,"name":"Biological sciences/Chemical biology/Synthetic biology"},{"id":52875596,"name":"Physical sciences/Engineering/Biomedical engineering"}],"tags":[],"updatedAt":"2026-05-12T15:37:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 08:06:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7115886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7115886","identity":"rs-7115886","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}