Restoration of PKM1 improves functional maturation of human stem-cell derived-β cell by regulating PEP metabolism

Domain: biology
Published: 2025-12-21
Editorial outcome: major_revision

Abstract
Human stem cell-derived β (SC-β) cells still exhibit limited glucose response required for insulin secretion due to glycolytic bottlenecks, yet how these metabolic abnormalities impact glucose response and functional maturation of SC-β cells remains unclear. In this study, we identify a metabolic checkpoint located at PEP accumulation that impedes the functional maturation, which is rescued by restoration of pyruvate kinase M1 (PKM1). Glucose-tracing metabolomics in human stem cell-derived islets reveal abnormal glycolytic PEP accumulation at resting condition, associated with impaired calcium response and insulin secretion upon high glucose or glycolytic metabolite stimulation. Mechanistically, elevated PEP significantly raises intracellular basal calcium levels and downregulates expression of genes involved in TCA cycle as elucidated by single cell transcriptomics. Furthermore, the activity of pyruvate kinase, which metabolizes PEP, is notably reduced due to low PKM1 expression. Overexpression of PKM1 alleviates PEP accumulation, restores TCA-related gene expression, and enhances glucose-stimulated calcium responses and insulin secretion. Together, our findings reveal a critical role of PKM1-regulated PEP metabolism in SC-β cell functional maturation and highlight the importance of metabolic reprogramming for advancing stem cell-based therapies for diabetes.

Introduction
Functionally mature stem cell-derived β (SC-β) cells are essential for ensuring the effectiveness of SC-β cell transplantation therapy for diabetes treatment. One of the most critical characteristics of pancreatic β cell functional maturation is glucose-stimulated insulin secretion (GSIS). While recent protocols have shown improvements in GSIS in SC-β cells, these cells still exhibit significantly reduced GSIS compared to native human β cells, presenting a barrier to the effectiveness of β cell replacement therapies1,2.

In native β cells, glucose metabolism generates ATP through glycolysis and oxidative phosphorylation (OXPHOS), leading to the closure of KATP channels, Ca²⁺ influx, and subsequent insulin release3. While SC-β cells can secrete insulin in response to TCA cycle metabolites and depolarization, they are less responsive to high glucose levels, possibly due to a metabolic defect located at the glycolytic GAPDH and PGK1 proteins1,4,5. Additionally, inhibition of GAPDH leads to the accumulation of upstream metabolites, which impairs the OXPHOS necessary for insulin secretion in diabetic β-cells via mTORC1 signaling remodeling6, a pathway also involved SC-β cell maturation7. However, attempts to enhance GAPDH and PGK1 expression in SC-β cells have not restored GSIS4, suggesting the presence of unidentified downstream metabolic bottlenecks that may decouple glycolysis from OXPHOS8.

Impaired PEP metabolism is a metabolic obstacle hampering SC-β from achieving a proper glucose response1,4. Recently, PEP from glycolysis has gained attention for its role in generating ATP via pyruvate kinase (PK) to initiate KATP closure, Ca2+ influx, and triggering ATP pathway9–11. Although this is still controversial12–15, abnormal PEP metabolism would inevitably impair downstream metabolism required for insulin release16. In SC-β cells, bypassing the PEP with extracellular PEP, oxaloacetic acid (OAA), and other permeable metabolites has significantly increased insulin secretion4,17. However, the role of PEP in SC-β function and maturation remain unclear.

The two main splicing isoforms of pyruvate kinase muscle (PKM), PKM1 and PKM2, catalyze the conversion of PEP to pyruvate. Beyond this, they exert distinct, isoform-specific effects on cell differentiation and function18. While PKM2 activity accounts for only 10% of PK activity in mature β cells, the constitutively active PKM1 accounts for 90%. Both PK isoforms are essential for PEP metabolism and insulin secretion11. Due to their sequence similarity, most transcriptomic and proteomic studies cannot distinguish between PKM1 and PKM2, leaving it unclear whether a deficiency in either isoform or PK activity could affect glucose metabolism and functional maturation via regulating PEP in SC-β cells.

In this study, we explore the metabolic bottlenecks that uncouple glucose sensing from functional maturation in SC-β cells. We found that PEP abnormally accumulates at basal glucose level, which interferes with basal glucose responsiveness and gene expression programs. Restoration of PKM1, which was markedly lower in SC-β cells compared to primary β cells, was able to partially restore GSIS, enhance Ca²⁺ responses, and normalize the expression of glycolytic and OXPHOS genes affected by PEP imbalance. Together, these findings highlight PEP accumulation as a metabolic checkpoint that impairs functional maturation of SC-β cells.

Results
Metabolomic profiling of SC-islets
We first generated SC-islets following established protocols (Supplementary Fig. 1A and Supplementary Data 1)2,19,20. In agreement with previous studies, SC-islets differentiated from human embryonic stem cell lines H1 and H9 showed increased β-cell-specific gene expression (INS, NKX6.1, MAFA) and relatively uniform size (Supplementary Fig. 1B, C). However, SC-islets displayed limited GSIS compared to mouse islets (Supplementary Fig. 1D).

To investigate glucose metabolic defect in SC-islets, we compared glucose metabolic fate between mouse- and SC-islets by performing metabolite tracing experiment with labeled [U-¹³C₆]-glucose (Fig. 1A). Key glycolytic intermediates—glucose 6-phosphate (G6P), fructose 6-phosphate (F6P), dihydroxyacetone phosphate (DHAP), and 3-phosphoglycerate (3-PG)/2-phosphoglycerate (2-PG)—showed similar glucose-dependent increases in both mouse and SC-islets, indicating that glucose metabolism from glucose through to the 3-PG/2-PG stage remains relatively intact (Fig. 1B–E). Interestingly, while high glucose-induced PEP levels were comparable between mouse and SC-islets, basal PEP levels at low glucose were significantly higher in SC-islets with lower stimulating index, as were pyruvate levels (Fig. 1F, G) and other TCA metabolites (Fig. 1H). In addition, glutamate was preferably metabolized to glutamine (Gln) rather than GSH, and ATP production was much lower in SC-islets (Fig. 1I), indicating that the disrupted glucose metabolism originated from dysregulated glycolytic metabolism downstream of PEP (Fig. 1J).

Bottleneck downstream of PEP limits glucose-dependent function
To further investigate whether glycolytic bottlenecks downstream of PEP impedes glucose responsiveness, we assessed the effects of PEP and its upstream metabolites on SC-β cells. Cell-permeable metabolites upstream of PEP, including glyceraldehyde (GLA, a precursor to glyceraldehyde 3-phosphate) and dihydroxyacetone (DHA, a precursor to DHAP), elicited minimal insulin secretion (Fig. 2A, B) and calcium responses (Fig. 2C, D) in SC-β cells compared to mouse β cells. Glyceric acid (GA, a non-phosphorylated precursor to 3-PG and 2-PG4) also produced negligible effects in SC-β cells (Fig. 2E and Supplementary Fig. 2A), indicating a metabolic blockage downstream of 2-PG. Consistently, although 3-PG was not permeable to induce substantial calcium responses in mouse-β cells (Fig. 2F)4, the infusion (dialysis) of 50 μM 3-PG, 2-PG, or K⁺-PEP into the cell cytosol via whole-cell patch clamp significantly enhanced depolarization-induced exocytosis by (~fivefold) compared to the control group in mouse-β cells. In contrast, SC-β cells, generated from CRISPR-Cas9 method and identified by EGFP (Supplementary Fig. 2B–D), showed no metabolite-dependent changes in exocytosis (Fig. 2G). Remarkably, this was because under control conditions, SC-β cells already exhibited a tenfold higher exocytosis compared to mouse β-cells, limiting further amplification by these metabolites (Fig. 2G). Additionally, SC-β cells displayed greater depolarization-induced calcium entry across various conditions compared to mouse β-cells (Fig. 2H). Together, these findings suggest that the saturating effect of metabolite accumulation downstream of PEP at basal glucose levels prevents additional metabolite- or glucose-dependent enhancement of exocytosis.

Basal PEP metabolites elevates Ca²⁺ and hinders SC-β cell maturation
Since basal PEP and its downstream metabolites were upregulated in SC-β cell, we next examined their effects on cellular function. As expected, Na⁺-PEP (trisodium salt), which is expected to not freely permeable to the plasma membrane, failed to elicit a calcium response in mouse β cells (Fig. 3A). In contrast, Na⁺-PEP triggered calcium responses in CD49a-based magnetically sorted SC-β cells, which was blocked by KATP channel opener diazoxide (Dia), mitochondrial complex III inhibitor antimycin A and PKM2 inhibitor PKM2-IN-1 (PKi) (Fig. 3B–D and Supplementary Fig. 2E, F), suggesting that unlike mouse β cells, Na⁺-PEP can be transported into SC-β cells and metabolized to promote calcium influx via KATP channel. Similarly, although OAA, which was upregulated in SC-islets (Fig. 1H), did not evoke calcium responses in mouse β cells (Fig. 3E), but induced Dia- and antimycin A-sensitive calcium responses in sorted SC-β cells that were not inhibited by PKi (Fig. 3F–H). Permeable methyl-pyruvate (MP) can also induce a diazoxide- and antimycin A-dependent calcium response in SC-β cells (Supplementary Fig. 2G–J), albeit with lower sensitivity compared to mouse β cells (Supplementary Fig. 2J). Accordingly, Na+-PEP, OAA, and MP can trigger significant insulin secretion in SC-islets (Fig. 3I, J).

Due to the elevated basal PEP as the starting point of abnormal downstream TCA metabolism and its effects on calcium response, we further investigated the impact of PEP on SC-β cells differentiation. Since K⁺-PEP is the monopotassium salt of PEP, we used KCl as a control to eliminate the potential effect of K⁺. SC-islets were cultured with 50/500 μM KCl or K⁺-PEP throughout Stage 6/7 and collected for single cell RNA sequencing at S7D14. Integration with human adult islet datasets yielded a combined atlas of 77,623 cells, including 19,126 adult islet cells21. Clustering by cell identity revealed distinct transcriptional profiles of SC-β cells compared with adult β cells. Although most cells differentiated from our protocol were annotated as SC-β cells, a significant fraction showed high similarity to adult β and α cells (Fig. 3K). Notably, PEP treatment reduced the proportion of adult β, adult α, and endocrine progenitor cells, while increasing the proportion of SC-β, SC-α, SC-EC, and polyhormonal populations (Fig. 3L). We then focused on SC-β and adult β cell subpopulations to investigate the transcriptional changes associated with the PEP effect. Treatment with 50 μM PEP disrupted the expression of β-cell-specific genes (INS, INS-IGF2) and genes essential for insulin secretion and mitochondrial OXPHOS, including mitochondrial complex I (MT-ND1-5), complex III (MT-CYB), complex IV (MT-CO1-3), and Complex V (MT-ATP6, MT-ATP8)22 (Fig. 3M (left), Supplementary Data 2). Consistent with these findings, gene set enrichment analysis (GSEA) revealed downregulation of the TCA cycle, the respiratory transport chain, and mitochondrial complex I biogenesis, all critical for OXPHOS-driven insulin secretion23. ROBO signaling, which regulates islet morphology, cell identity, and insulin secretion24–26, was also downregulated following PEP treatment. Conversely, PEP treatment induced a neuronal-like transcriptional program involving calcium signaling (ERBB4, PRKCB, CACNA1E), a characteristic of immature β-cells, and the removal of this signature was essential for their maturation (Fig. 3M (right), Supplementary Data 2)27. Similarly, 500 μM PEP impaired genes related to β-cell identity and function (Fig. 3N and Supplementary Data 3). Together, these results demonstrate that while PEP enhances calcium responses and insulin secretion, it simultaneously drives transcriptional programs that hinder the further maturation of SC-β cells.

SC-β cells show absence of PKM1 expression
To assess whether PEP accumulation results from altered production or consumption, we examined glycolytic enzymes in SC-islets. ALDOA, PGK1, and PGAM1 showed a trend of reduction in SC-islets, while enolase (ENO1 and ENO2), which directly produced PEP from upstream metabolites, were comparable between mouse- and SC-islets. Remarkably, PKM1 gene expression, which metabolized PEP to pyruvate, was ~100-fold lower in SC-islets compared to mouse islets (Fig. 4A) and nearly absent as demonstrated by western blotting (Fig. 4B). Interestingly, PKM2 expression was higher in SC-islets (Fig. 4A) and seemed to be prone to complete denaturation compared to mouse islets (Fig. 4B). Immunostaining confirmed that mouse β cells expressed both PKM1 and PKM2, whereas SC-β cells expressed much less PKM1 compared to mouse islets (Fig. 4C, D) and human islets (Supplementary Fig. 3A–C). Notably, PKM1 was highly expressed in human islets relative to surrounding exocrine tissues (Supplementary Fig. 3A). Accordingly, PK activity, rather than PGK1 and GAPDH, was markedly reduced in SC-islets but restored by PKM1 overexpression (Fig. 4E, F). These findings suggest that loss of PKM1 might limit PEP consumption and drive its accumulation in SC-β cells.

PKM1 reverses PEP-induced changes and promoted maturation
Given that PEP impaired SC-β cell maturation at the transcriptomic level, we asked whether PKM1 overexpression could reverse these effects. PKM1-overexpressing SC-islets were cultured with 50 μM K⁺-PEP throughout Stage 6/7 and profiled by single-cell RNA-seq at S7D14. Integration with datasets from KCl- or K⁺-PEP-treated SC-islets and human islets (59,833 cells) revealed that PKM1 overexpression restored the proportions of “Adult β” and “Adult α” cells while reducing “SC-β” cells (Fig. 5A and Supplementary Fig. 4A–C). Since PKM1 cannot be distinguished from PKM2 in sequencing data, we used mCherry expression as an indicator of successful PKM1 overexpression. PKM1 promoted genes related to β-cell-specific genes (INS, INS-IGF2), and mitochondrial OXPHOS, including mitochondrial complex I (MT-ND1-5), complex III (MT-CYB), complex IV (MT-CO1-3), and Complex V (MT-ATP6, MT-ATP8) (Fig. 5B and Supplementary Data 4). Consistently, genes in TCA cycle and ROBO signaling pathway were upregulated while genes related to neuronal system was downregulated (Fig. 5C and Supplementary Data 4). Similarly, in SC-islets exposed to higher K⁺-PEP (5 mM) for a shorter period (Stage 6 and collected at S7D1), PKM1-overexpression restored PEP-induced genes and pathways linked to β-cell identity, insulin secretion, glucose metabolism, and TCA cycle (Supplementary Fig. 5A–E and Supplementary Data 5). Functionally, PKM1-overexpressing SC-islets displayed enhanced GSIS (Fig. 5D), oxygen consumption rate (Fig. 5E), and calcium responses (Fig. 5F). To further examine if this effect was due to the metabolism of SC-β cell, SC-β cells were magnetically sorted based on CD49a and reaggregated. Sorted CD49a⁺ SC-β cells with PKM1 overexpression showed reduced basal insulin release, leading to a greater glucose-dependent fold increase (Fig. 5G), and restored glucose-dependent exocytosis (Fig. 5H) with preserved calcium entry (Fig. 5I). Metabolically, CD49a⁺-sorted PKM1-overexpressing SC-β cells showed a glucose-dependent increase in F6P, DHAP, and 3-PG/2-PG comparable to controls (Supplementary Fig. 6A–C), but with lower basal PEP and pyruvate levels, resulting in greater glucose-dependent changes (Supplementary Fig. 6D, E). Downstream metabolites, including citrate, malate, and succinate, also displayed modest improvements in glucose dependency (Supplementary Fig. 6F–H). However, ATP increased only at basal glucose (Supplementary Fig. 6I), and no further improvements were observed in other metabolites (Supplementary Fig. 6J–L). FBP, an upstream glycolytic metabolite and activator of PKM2, could induce higher insulin secretion and calcium response in PKM1-overexpressing SC-islets (Supplementary Fig. 7A, B), but these effects cannot be inhibited by PKi, antimycin A, or diazoxide (Supplementary Fig. 7C–E). Acute treatment of PKM2 agonist TEPP-46 (PKa), can only modestly but not significantly enhance insulin (Supplementary Fig. 7F) or calcium responses (Supplementary Fig. 7G) in both control and PKM1-overexpressing SC-islets. Overall, PKM1 overexpression improved glucose-stimulated function in SC-β cells.

To further explore the transcriptional changes induced by PKM1, single-cell sequencing datasets generated from control islets and PKM1-overexpressing islets collected at S7D1 and S7D14 were integrated with adult islets dataset21 (43,866 cells). The cell dataset was clustered according to cell identity. A total of twelve major cell-type classes with marker genes were identified (Supplementary Fig. 8A–D), including around 25% SC-β cells across SC-islets dataset (Supplementary Fig. 8B). To maintain condition across PKM1-non-expressing and -expressing cells more consistent, only PKM1-overexpressing islets collected at S7D1 and S7D14 were integrated with human adult islets for downstream analysis and categorized into four groups based on time of origin and PKM1-overexpression (6,264 cells): S7D1PKM1−, S7D1PKM1⁺, S7D14PKM1−, and S7D14PKM1⁺ (Fig. 6A). Compared to S7D1PKM1−, as expected, extended culture of SC-islets to S7D14PKM1− showed a more mature β-cell gene profile (INS, IAPP, HOPX) accompanied by higher gene expression related to insulin secretion (PCSK1, FXYD2, CPE, RBP4, FFAR1, PCSK1N, TTR)1 and OXPHOS pathway (Aerobic respiration and respiratory electron transport) (Fig. 6B and Supplementary Data 6), most of which were recapitulated by the comparison between S7D1PKM1⁺ and S7D14PKM1⁺ (Fig. 6C and Supplementary Data 6). Notably, S7D1PKM1⁺, compared to S7D1PKM1−, induced similar transcriptional changes and enriched pathways, including aerobic respiration and respiratory electron transport pathway (Fig. 6D and Supplementary Data 6), which were further demonstrated in the comparison between S7D14PKM1− and S7D14PKM1⁺ (Fig. 6E and Supplementary Data 6). As shown in (Fig. 6F), genes related to β cell identity, insulin secretion, glycolysis, OXPHOS, and exocytosis, such as INS, PCSK1N, PKM, MT-CO1, and VAMP2 showed a trend of culture time- and PKM1-dependent increase. Consistently, PKM expression in adult β-cells, including PKM1 and PKM2, was significantly higher than in non-PKM1-overexpressing cells and comparable to the PKM1-overexpressing group. Taken together, PKM1 overexpression triggered a transcriptional program that supports both β-cell functional maturation.

Methods
Cell culture and differentiation of SC-β cells
In vitro differentiation of H1 and H9. H1 or H9 human embryonic stem cells (hESC) were cultured on 1:100 diluted Matrigel (Corning, 354277) in mTeSR medium (Stemcell, 85850). After rinsing with Mg2+/Ca2+-free DPBS (Thermo Fisher, 14190250) and digestion with TrypLE Express Enzyme (1×) (Thermo Fisher, 12605028) for 3 min at 37°C, the digestion was stopped with mTeSR. Single cells were collected and spun at 300×g for 5 min. The cell pellet was resuspended in mTeSR medium supplemented with Y-27632 (10 μM; MCE, HY-10583), and single cells were seeded at approximately 1×105 cells/well on Matrigel-coated surfaces. Cells were fed with mTeSR medium daily and differentiated after 48 h at approximately 90% confluency. The differentiation protocol was modified based on previous protocols2,19 (see also Supplementary Data 1). The Institutional Review Board of Guangzhou National Laboratory and People’s Hospital of Xinjiang Uygur Autonomous Region reviewed and approved all work involving human pluripotent stem cells carried out in this manuscript.

S1: Definitive endoderm (3d). Undifferentiated pluripotent stem cells plated on 1:100 Matrigel-coated surfaces were cultured in MCDB 131 medium (Reprocell, PM151210) with 0.5% BSA (fatty acid-free BSA, Proliant, 69760), 1.7×g/l sodium bicarbonate (SIAL, S6014), 10 mM final glucose concentration (Sigma, G7528), 0.25 mM Vitamin C (Sigma, A1300000), 1% Glutamax (Thermo Fisher Scientific, 35050061), 1% Penicillin-Streptomycin (Thermo Fisher Scientific, 15140122), 100 ng/ml Activin A (MCE, HY-P70311), 3 μM ChIR99021 (MCE, HY-10182), 50 nM PI-103 (Selleck, S1038), and 10 μM Y-27632 for day 1 only. For day 2, cells were cultured in MCDB 131 with 0.5% BSA, 1.7×g/l sodium bicarbonate, 10 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), 50 ng/ml Activin A, and 0.1 μM ChiR99021. On day three, cells were cultured in MCDB with 0.5% BSA, 1.7×g/l sodium bicarbonate, 10 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), and 50 ng/ml Activin A.

S2: Primitive gut tube (2d). S1 cells were transferred to MCDB 131 medium containing 0.5% BSA, 1.7×g/l sodium bicarbonate, 10 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), and 50 ng/ml FGF7 (Stemcell, 78046.2) for 2 days.

S3: Posterior foregut (2d). S2 cells were cultured for an additional 2 days in MCDB 131 medium supplemented with 2% BSA, 2.5×g/l sodium bicarbonate, 10 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), 1:200 ITS-X (Reprocell, pb180431), 50 ng/ml FGF7, 2 μM retinoic acid (Sigma, R2625), 0.25 μM SANT-1 (MCE, HY-100224), 100 nM LDN193189 (BMP receptor inhibitor, MCE, HY-12071), 500 nM PdBu (Millipore, 524390), and 10 μM Y-27632.

S4: Pancreatic endoderm (4d). S3 cells were further differentiated in MCDB 131 medium supplemented with 2% BSA, 2.5×g/l sodium bicarbonate, 10 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), 1:200 ITS-X, 2 ng/ml FGF7, 2 μM RA, 0.25 μM SANT-1, 100 nM LDN193189, 100 nM PdBu, 10 μM Y27632, 10 μM ALK5 inhibitor II (Selleck, s7223), 100 ng/ml EGF (MCE, HY-P7109), and 10 mM Nicotinamide (Sigma-Aldrich, N0636) for 4 days.

S5: pancreatic endocrine precursors (3d). On the last day of S4 culture, cells were treated with accutase (Stemcell, 7920) for 8 min at 37°C, followed by gentle pipetting to break into single cell suspension. Next, cell suspension were transferred into low-attached 6-well culture plate in suspension at 300×g with S5 medium, which consisted of MCDB 131 medium with 2% BSA, 2×g/l sodium bicarbonate, 20.6 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), 1:200 ITS-X, 0.05 μM RA, 0.25 μM SANT-1, 100 nM LDN193189, 10 μM zinc sulfate (ZnSO4, Sigma, Z0251), 10 μM ALK5 inhibitor II, 1 μM T3 (MCE, HY-A0070), 1 μM compound E (MCE, HY-14176), 20 ng/ml Betacellulin (Stemcell, 78105), 10 μg/ml Heparin (Sigma, H3149), 10 μM Isoxazole 9 (ISX9, MCE, HY-12323) and 100 nM Wnt-C59 (MCE, 1243243-89-1) for 3 dads. For lentivirus infection, mCherry or PKM1-mCherry lentivirus were added at S5D1, achieving stable PKM1 expression at S5D3. After 48 h, lentivirus media was replaced with new S5 media.

S6: S6 cells, characterized by NKX6.1 and insulin expression, were cultured for 5 days. The culture medium consisted of MCDB 131 supplemented with 2% BSA, 1.8×g/l sodium bicarbonate, 20.6 mM glucose, 0.25 mM Vitamin C, 1% Glutamax, 1% Pen-Strep (Gibco), 1:200 ITS-X, 100 nM LDN193189, 10 μM ZnSO4, 10 μM ALK5 inhibitor II, 1 μM T3, 0.1 μM compound E, 10 μg/ml Heparin, 100 nM Wnt-C59, and 1 mM N-acetylcysteine (Sigma, A9165) for 5 days. For PEP treatment, 5 mM PEP was added to media and media pH was corrected with NaHCO3 as that of S6 media.

S7: S7 cells, characterized by NKX6.1, insulin, and MAFA expression, were cultured for 14-21 days. The culture medium consisted of MCDB 131 supplemented with 2% BSA, 1.5×g/l sodium bicarbonate, 5.6 mM glucose, 1% Glutamax, 1% Pen-Strep (Gibco), 1:200 ITS-X, 10 μM ZnSO4, 10 μM ALK5 inhibitor II, 1 μM T3, 10 μg/ml Heparin, 1 mM N-ace, 10 μM Trolox (Sigma, T3251), 1:2000 Trace element A (Corning, 25-021-CI), 1:2000 Trace element B (Corning, 25-022-CI), 2 μM R428 (Selleck Chem, S2841), 1:2000 chemically defined lipid concentrate (lipid, Gibco, 11905031), and 10 μM Forskolin (Aladdin, 66575-29-9).

Generation of reporter cell line
H1-Ins-EGFP wase generated as previously reported for H1-Ins-jGCaMP7f46. We utilized low off-target CRISPR/Cas9n technology for in situ insertion of the EGFP gene in hESC (H1). By employing the Cas9 D10A nickase (PX335, Addgene #42335) with dual sgRNAs targeting each side of the insulin gene stop codon, we inserted P2A-EGFP-PGK-Puro-pA. This insertion enables simultaneous insulin protein expression for identifying insulin-producing cells in differentiated pancreatic endocrine cells. Cells were transfected at 70% confluence using Lipofectamine™ Stem Reagent (STEM00008), with puromycin added after 24 h at 1µg/ml to select for successful insertions, ensuring elimination of non-transfected cells.

Generation of lentivirus
All overexpression lentiviral plasmids were constructed via homologous recombination. During the construction process, the following steps were undertaken: 1. puc57 was consistently used as the plasmid backbone; 2. The lentiviral integration site from the lentiCRISPR v2 plasmid (addgene: #52961) was utilized; 3. The EF1a promoter was employed to enhance gene expression, followed by the target gene’s ORF (with the stop codon removed), linked to P2A and mCherry for monitoring plasmid transfection efficiency and viral overexpression in 293T cells; 4. All plasmids were recombined using the EZ-HiFi Seamless Cloning Kit (Genstar #T196), and the accuracy of the sequences was verified by DNA sequencing. Pspax2, VSVG, and PLV were mixed in a ratio of 1:0.5:1 for transfection of 293T cells using PEI. 12 h post-transfection, the medium was replaced with DMEM containing 5% FBS and antibiotics. At 48- and 72-h post-transfection, the supernatants were collected, centrifuged at 2000 rcf for 10 min to remove cell debris, sterile filtered through a Millex 0.22 µm filter, and the viruses were finally concentrated using an Amicon® Ultrafilter (#UFC9100).

13C-glucose labeling metabolomics
All animal studies were conducted with approval from Institutional Animal Care and Use Committee of Guangzhou Medical University. ~400 primary mouse islets or SC-islets were used for each replicate with at least 3 biological replicates and preincubated at KRB solution with 2.8 mM glucose for 60 min, followed by incubation at 2.8 (low) or 16.7 mM (high) [U-¹³C₆] glucose (Cambridge Isotope Laboratories, CLM 1396) for 60 min at 37°C and 5% CO2. Afterwards, islets were washed with PBS 3 times and added 50μL “extraction solution” (Acetonitrile/Methanol/Aqueous=4:4:2 kept at −20 °C overnight. The mixture was kept in ice to sonicate for 5 min followed by future centrifugation at 12,000×g for 5 min. Supernatant was transferred to vials and run with 4μL injection volume by LC-MS MS system. Chromatographic separation was performed using an Agilent 1290 II ultra-high-pressure liquid chromatography system equipped with 6546 quadrupole time-of-flight (QTOF) mass spectrometry. A Waters ACQUITY UPLC BEH Amide column (2.1 mm × 100 mm × 1.7 μm) and guard column (2.1 mm × 5 mm × 1.7 μm) at 35°C was used to separate metabolites with mobile phase A: 100% aqueous containing 15 mM ammonium acetate and 0.3% ammonium hydroxy and mobile phase B: 90% acetonitrile (v/v) aqueous containing 15 mM ammonium acetate and 0.3% ammonium hydroxy. The linear gradient was set as follows: 10% A (0.0–8.0 min), 50% A (8.0–10.0 min), 50% A (10.0–11.0 min), and 10% A (11.0–20.0 min). The total run time was 20 min and flow rate was 0.3 mL/min. The mass spectrometer was equipped with Agilent Jetstream source operating in negative and positive ion mode with source parameters set as follow: Nebulizer gas, 45 psi; Sheath gas temperature, 325°C; Sheath gas flow, 10 L/min; Dry gas temperature, 280°C; Dry gas flow, 8 L/min; Capillary voltage, 3500 V for two ion modes and nozzle voltage, 500 V for positive and 1000 V for negative mode. The QTOF scan parameters were set as follows: Scan speed, 1.5 scan/s; scan range, 50–1700 m/z and ion fragmentor voltage, 140 v. The acquired data quality was monitored by Amino Acid standards (Merck, Sigma-Aldrich Production GmbH, Switzerland), mix-samples quality controls, and blanks. Peak integration and metabolite isotopologue identification was accomplished using Profinder 10.0 (Agilent). Natural abundance was assayed using non-labelled samples and removed to avoid any possible confounding effect.

Patch clamp analysis
Patch Clamp experiment was performed as previously reported47,48. Briefly, dispersed single cells cultured on 35 mm dishes overnight were preincubated at 2.8 mM glucose for 1 hour and patched in bath solution containing (in mM): 118 NaCl, 5.6 KCl, 20 TEA, 1.2 MgCl2, 2.6 CaCl2, 5 HEPES at indicated glucose level with a pH of 7.4 (adjusted by NaOH) at 32–35°C. Whole-cell capacitance was recorded with the sine+DC lock-in function of an EPC10 amplifier and PatchMaster software (HEKA Electronics). Exocytotic responses and inward Ca2+ currents were measured 1–2 min after obtaining the whole-cell configuration in response to ten 500 ms depolarizations to 0 mV from a holding potential of −70 mV. Changes in capacitance and integrated Ca2+ charge entry were normalized to cell size (fF/pF and pC/pF, respectively). The intracellular solution contained (in mM): 125 Cs-Glutamate, 10 CsCl, 10 NaCl, 1 MgCl2, 5 HEPES, 0.05 EGTA, 3 MgATP, and 0.1 cAMP with pH=7.15 (pH adjusted with CsOH). For dialysis/infusion experiment, metabolites were added to pipette solution (pH-corrected) as indicated. Measurement was performed 3 min after whole cell mode, which achieved homogenous distribution of metabolites. SC-β cells were identified by EGFP fluorescent signal. Mouse β cells were identified by size (>4pF) and a Na+ channel half-maximal inactivation at around −90 mV.

Enzymatic activity measurement
PK activity was measured using the CheKine™ Micro PK Assay Kit (KTB1120) according to the manual. PK catalyzes phosphoenolpyruvate and ADP reaction into ATP and pyruvate, and lactate dehydrogenase further catalyzes the production of lactic acid and NAD+ by NADH and pyruvate. The rate of NADH decline at 340 nm can reflect PK activity. Cell lysates from 400 islets were sonicated on ice using the provided Extraction Buffer and quantified by BCA assay. 10μL sample, 10μL Working Reagent and 180μL Substrate Mix Working Reagent were mixed and added to the 96-well UV plate. Measure the absorbance value at 340 nm with a microplate reader. The data shown represent the first ten data points of NADH consumption in this reaction.
PGK1 activity was measured using the Grace Biotech Micro PGK Assay Kit (G0885W) according to the manual. Phosphoglycerate kinase (PGK) catalyzes the reaction between 3-PG and ATP to produce 1,3-bisphosphoglycerate and ADP. In a subsequent reaction, 1,3-bisphosphoglycerate is catalyzed by glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and reacts with NADH to generate 3-phosphoglyceraldehyde, NAD⁺, and inorganic phosphate. Since NADH absorbs light at 340 nm, the decrease in NADH concentration during the reaction results in a reduction in absorbance at this wavelength. This absorbance change at 340 nm can be used to monitor PGK activity. Cell lysates from 400 islets were sonicated on ice using the provided Extraction Buffer and quantified by BCA assay. 20μL sample was mixed with the Working Reagent added to the 96-well UV plate. After 10 minutes, measure the absorbance value at 340 nm with a microplate reader. The data shown represent the first ten data points of NADH consumption in this reaction.
GAPDH activity was determined using the Abcam GAPDH colorimetric assay kit (ab204732) as previously reported4. This assay tracks the conversion of the substrate glyceraldehyde-3-phosphate to 1,3-bisphosphoglycerate along with NADH production. NADH, generated by GAPDH activity present in cell lysates, is linked to a proprietary developer included in the kit, which utilizes the NADH from GAPDH to initiate a secondary colorimetric reaction in each well. Cell lysates from 400 islets were sonicated on ice using the provided Extraction Buffer and quantified by BCA assay. After adding 50µL sample into the reaction mix, the plate was incubated at 37°C for the assay duration. NADH accumulation was indirectly measured at 450 nm by monitoring the developer reaction product in kinetic mode over a 10-min period. The data presented display the raw conversion values for the first 10 time points of the reaction.

Oxygen consumption
The Agilent Seahorse XFE24 Analyzer with islet capture microplates was used, following a protocol previously outlined49. Specifically, 70 islets were loaded per well and treated sequentially with 2 mM glucose, 20 mM glucose, 5µM oligomycin, 5µM FCCP, and 5µM rotenone/antimycin A. For each data point, the experiment included a 3-min mixing phase, a 2-min waiting phase, and a 3-min measurement phase. Each biological sample had 3~4 technical replicates, and the oxygen consumption rate was normalized islet protein content.

scRNA sequencing analysis
Briefly, approximately 10,000 cells were captured, reverse-transcribed, barcoded, and amplified50. cDNA libraries were prepared using 10× Genomics Chromium Single Cell Reagent Kits v3 or DNBelab CSeries High-throughput Single-Cell RNA Library Preparation Set V3.0 (MGI, #940-001818-00), quantified with Qubit 3.0, analyzed on Agilent 2100, and sequenced on the Illumina NovaSeq 6000 (PE150) by Annoroad Gene Technology or high-throughput DNBSEQ-T7RS sequencer at the Advanced Cell Technology Core Facility, Guangzhou National Laboratory (Guangzhou, China) with read length 30bp for read 1, 100bp for read 2, and 10bp for sample index. Raw FASTQ files were processed with Cell Ranger (v4.0.0) (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/advanced/references) using default settings, aligning reads to the GRCh38 human genome. We included 12 samples of primary adult human pancreatic islets as reference scRNAseq dataset for further analysis21. High quality cells (>300 genes, <10% mitochondrial genes, <3% red blood cell gene expression) were selected for data normalization, scaling, and principal component analysis with default methods. Top 3000 variable genes were identified from each sample. The Harmony method was applied on the first 30 principal components, using sample as a covariate to integrate different samples51. The integrated principal components were used to construct the UMAP, identify neighboring cells (via shared nearest neighbor), and define cell clusters using default Seurat methods. The clustering resolution was adjusted to 0.5. Differentially expressed genes among clusters were identified using Seurat’s FindMarkers function. The annotation of the clusters was performed using the GPT Celltype package according to the known marker genes52. Adult and SC-β cells were used for identifying differentially expressed gene with an adjusted P value<0.005 and log2 fold change >0.15. We performed gene set enrichment analysis using Reactome53 and Metascape v. 3.554 with an adjusted P value cutoff of <0.05. Detailed analytical result related to differentially genes and enrichment can be seen in Supplementary Data 2–6.

Fluorescence activated cell sorting
For SC-β (H1-Ins-EGFP) cell sorting, cell aggregates were dissociated into a single-cell suspension using Accutase and resuspended in S7 media containing 10 μM Y27632. EGFP-positive cells were sorted into 15 ml Falcon tubes containing S7 medium and 10 μM Y27632 using a tube sorting mode (MA900, Sony).

Magnetics sorting of SC-β cells (CD49a⁺) cells
SC-β cells were sorted as previously described55. Briefly, organoid spheres were dissociated into single cells by Accutase (37°C, 20–30 min) with gentle pipetting. Cells were collected by centrifugation (300g, 5 min). The pellet was resuspended in 10 mL sorting buffer (DPBS supplemented with 1% BSA and 2 mM EDTA) and passed through a 37-µm cell strainer to remove residual aggregates. Approximately 1×107 cells were obtained, counted, and pelleted for downstream sorting. Cells were resuspended in sorting buffer at 3.33×107 cells/mL and incubated with anti-human CD49a-PE antibody (1:100 dilution) for 20 min at room temperature in the dark, with gentle mixing. After three washes, cells were incubated with anti-PE UltraPure magnetic beads (40 μL per 1×107 cells) for 15 min at 4°C with intermittent mixing. Cells were washed three additional times with sorting buffer, counted, and resuspended at 5–6×107 cells/mL. An MS column (Miltenyi Biotec) was pre-equilibrated with 0.5 mL sorting buffer and placed in a magnetic separator prior to cell loading. The labeled cell suspension was applied to the column, followed by three washes with 1 mL sorting buffer, allowing the liquid to flow through completely each time. The column was then transferred to a clean 15-mL tube, and CD49a⁺ cells were eluted with 1 mL sorting buffer using the supplied plunger. Eluted cells were counted, centrifuged, and resuspended in S7 medium. For reaggregation, 1.5×106 cells per well were seeded into AggreWell™ 400 plates (24-well format; STEMCELL Technologies), yielding ~1200 reaggregated spheres per well.

Quantitative RT-PCR
RNA was extracted with the RNeasy Mini Kit (Qiagen) and treated with DNase. cDNA was synthesized using the RT reagent Kit with gDNA Eraser (TAKARA). Real-time qPCR was performed with SYBR Premix Ex Taq II (TAKARA) and analyzed using the ΔΔCt method, normalizing expression to GAPDH. Primer details are in Supplementary Data 7.

Western blotting
SC-islets from S7D14 and mouse islets were collected in RIPA lysis buffer with protease inhibitor (Beyotime). Lysates were centrifuged, and supernatants were separated by SDS-PAGE, transferred to PVDF membranes, blocked, and incubated with primary and HRP-conjugated secondary antibodies. Detection was performed using ECL reagent (Millipore) and captured on a G-Box. Protein quantification was done with ImageJ, normalizing target protein intensity to housekeeping proteins (beta-actin). Antibodies are detailed in Supplementary Data 8.

Immunohistochemistry
For cryo-sectioning, S7 organoids were fixed in 4% PFA (Sangon Biotech) at room temperature for 1 h, rinsed with PBS, and incubated overnight at 4°C in 30% sucrose. They were then embedded in OCT, snap-frozen in liquid nitrogen, and stored at −80°C. Sections were cut at 10 μm thickness and mounted on Superfrost Plus slides. For immunostaining of re-plated cells, SC-islets were dissociated, plated on Matrigel-coated confocal dishes and fixed with 4% PFA at 4°C overnight. Cells were then permeabilized with Quickblock™ Blocking Buffer (BEYOTIME) at room temperature for 1 h. Primary antibodies were incubated overnight at 4°C, followed by PBS washes, and staining with secondary antibodies and Hoechst 33342 (Thermo Fisher Scientific) for 2 h at room temperature. Imaging was done on a NIKON A1 confocal microscope. Antibody information is listed in Supplementary Data 8. For Paraffin-embedded islet sections immunostaining, the procedure were performed as previously described47. Donor information is listed in Supplementary Data 9.

Insulin secretion
For dynamic insulin secretion, 25 (mouse islets) or (SC-islets) were handpicked into home-made organoid chip for dynamic insulin secretion as previously described56. Islets were pre-perifused for 1 h at KRB solution with 2 mM or 2.8 mM glucose followed by stimulation of different levels of glucose, permeable metabolites and drugs at a sample collection rate of 10 ml/min every 3–6 min. For static insulin secretion, 15 islets per triplicates were preincubated with 2.8 mM for 1 h followed by stimulation of indicated conditions for 1 h. The pH of all solutions containing metabolites or drugs was adjusted to 7.4 using NaOH. D-mannitol (Aladdin Scientific, Shanghai, China) was used to balance the osmolarity of KRB solutions as previously reported57. The samples and lysates of islets were stored at −80°C until further assayed by Insulin Detection Kit (STELLUX® Chemi Rodent Insulin ELISA kit; STELLUX® Chemi Human Insulin ELISA kit, Alpco). The total Na⁺ concentration in the KRB solution was adjusted to its original value by including the sodium contributed by sodium salts of metabolites (e.g., Na⁺-PEP) and NaOH used for correcting pH at 7.4. Information of metabolites and drug is listed in Supplementary Data 10.

Intracellular Ca2+ and membrane potential imaging
For Ca2+ imaging, islets or dissociated cells cultured on 35 mm glass bottom were loaded with Cal-500AM (2.5 μM, AAT Bioquest, USA) or Fluo-8AM (2.5 μM, AAT Bioquest, USA) for 30 min and perifused with pH-corrected (NaOH) and osmolarity-balanced KRB solution at indicated conditions. D-mannitol (Aladdin Scientific, Shanghai, China) was used to balance the osmolarity of KRB solutions as previously reported57. The fluorescence signal was excited and detected at an excitation/emission wavelength of 405 nm/500 nm for Cal-500AM, and at 490 nm/514 nm for both Fluo-8AM cells. Ca2+ were imaged at 1 Hz on an inverted confocal microscope (Carl Zeiss LSM980) for single cells and an upright confocal microscope (Carl Zeiss LSM980 NLO) for whole islets58. Mouse β cells were marked and identified by immunostaining and SC-β cells were identified by using H1-Ins-EGFP for experiment. Fluorescence ratios were calculated using a toolbox from Matlab with indicated analytical method (average fluorescence and smooth dynamics)59. The total Na⁺ concentration in the KRB solution was adjusted to its original value by including the sodium contributed by sodium salts of metabolites (e.g., Na⁺-PEP, Na+-FBP) and NaOH used for correcting pH at 7.4. Information of metabolites and drug is listed in Supplementary Data 10.

Statistics and reproducibility
Data analysis was conducted using FitMaster (HEKA Electronik) and GraphPad Prism (v10.0c). Statistical outliers were identified and removed using the unbiased robust regression and outlier identification test. For normally distributed data, statistical comparisons were made using a 2-tailed Student’s t-test (for two groups) or ANOVA followed by Sidak’s multiple comparisons test, as specified in the figure legends.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
Raw data and count matrices of scRNA-seq data are available under the accession number GSE281603. Metabolomics data are available under the accession number PRJCA051828. All other data are available from the corresponding authors upon request. Source data are provided with this paper.

Code availability
The code for analyzing 10× Genomics sequencing data is available at Seurat (https://satijalab.org/seurat/). Additional detailed code for specific data analysis steps can be provided upon request.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The paper by Lin et al. shows that PKM1 overexpression can improve the maturation and function of stem-cell derived beta cells (SCBCs), showing that metabolic reprogramming may be beneficial therapeutically. This proof-of-concept cell therapy is an advance over prior work on SCBCs, which identified bottlenecks at GAPDH and used cell-permeant metabolites to overcome it after overexpression of GAPDH and PGK1 had no effect (Ref. 4); and found no effect of extracellular phosphoenolpyruvate (PEP) or pyruvate kinase activation on insulin secretion (Ref. 16). In the present study, the authors used metabolic tracing to show abnormally high levels of metabolites at low glucose including PEP. The elevated PEP is notable because PEP and pyruvate kinase have recently been implicated in KATP channel closure and the initiation of insulin secretion, as well as the KATP-independent amplification of secretion (Ref. 9). Advancing this literature, the authors show mechanistically that including high PEP (as well as upstream metabolites 3-PG and 2-PG), increases exocytosis from mouse beta cells and SCBCs at low glucose. The authors then show that PKM1 overexpression improved calcium and insulin secretion, and over time, impacted expression of glycolytic and OxPhos genes in SCBCs. Put in context, the paper presents the premise of a therapeutic strategy for improving diabetes treatment and advances our mechanistic understanding of insulin secretion in primary beta cells.\n\nA major concern is that the effects of applying extracellular potassium phosphoenolpyruvate (K-PEP) are due to K+, which will depolarize the plasma membrane, rather than PEP. This issue doesn’t necessarily dampen enthusiasm for the paper, but it needs to be resolved to properly interpret the data.\n\nMajor\n1. There is a major problem with the studies employing exogenous phosphoenolpyruvate (PEP) application, since the authors used the K+ salt (K-PEP) that will depolarize beta bells independently of metabolism. It seems plausible that all the effects of K-PEP are due to K+ rather than PEP, since the authors demonstrate that 1) K-PEP was found to increase intracellular calcium independently of KATP channels (i.e. in the presence of the KATP opener diazoxide), 2) the effects on secretion were dependent on extracellular calcium, 3) the effects on calcium are not blocked by diazoxide, 4) the effects of K-PEP are not mimicked by DHA or glyceraldehyde. Thus, the effect of K-PEP is precisely the effect of applying KCl to beta cells (e.g., Fig. 3B in PMID: 20655835 shows that adding 5 and 20 mM KCl raises intracellular calcium in the presence of diazoxide); the in present work the authors used 5 and 20 mM K-PEP. The effects of K+ would also explain the effect of K-PEP on HEK cells that have L-type calcium channels that open in response to membrane depolarization. The authors need to repeat all key studies (especially those in Figs. 2-3) that used K-PEP with Na-PEP, which does not depolarize the beta cell.\n(note: the authors should be mindful to replace the NaCl in their solutions with Na-PEP, not simply add Na-PEP, since high osmolarity will pull exogenous insulin off beta cells and cause false GSIS; this artifact plagued the SCBC field in the early 2000s).\n2. Related to the point above, it would also be necessary to demonstrate that extracellular PEP enters the cell, since PEP is not known to be a cell permeant metabolite. PEP could, in principle, act via a receptor, but extracellular PEP only reaches micromolar levels (not 5 or 20mM, which is unlikely to be physiologically relevant even if it proves useful as a tool).\n3. K-PEP was found to impact the expression of glycolytic and OxPhos genes. The authors should determine whether this is due to K+ or PEP. It would be interesting if a feedforward mechanism from calcium influx, which accelerates flow through glycolytic metabolism (Ref. 3), impacts the expression of glycolytic genes.\n4. This sentence is misleading, Line 111-112: “Similarly, the glucose dependent increase in metabolites from the TCA cycle, such as citrate, α-ketoglutarate (α-KG), malate, ATP and GSH, was also absent in SC-islets (Figure 1H)”. The reality is that basal metabolite levels are high.\nSince the tracer studies show that metabolites downstream of PEP accumulate in SCBCs at low glucose, including pyruvate and TCA cycle metabolites, it is not clear why the authors concluded that there is a bottleneck at the pyruvate kinase step of glycolysis in SCBCs. It seems to me that the strongest evidence for a glycolytic bottleneck is the effects of PKM1 overexpression - not the metabolomics data.\n5. The authors apply metabolites extracellularly - including glyceric acid, FBP, and OAA - as if they are freely transported into cells. Perhaps this is true for SCBCs, perhaps not. What is the evidence that glyceric acid is a precursor to 3-PG (Suppl. Fig. 2B,C)? What is the evidence that it can enter cells? How about oxaloacetate (Fig. 3A)? How about FBP (Fig. 5A-C)?\n6. SCBCs exhibit 10-fold higher exocytosis than control beta cells (Fig. 2G) and calcium current is very high (Fig. 3H). This indicates that SCBCs are highly exocytosis-competent, but triggering secretion is a problem. I agree with the author’s assessment that high exocytosis is likely due to high PEP, since high PEP was measured by metabolomics in SCBCs and high PEP was sufficient to increase exocytosis in both mouse and SCBCs. This is an important point and should be discussed.\n7. It is unclear how the authors are measuring PKM1 and PKM2 tetramers using SDS-containing gels (Fig. 4B and Methods). Is this an error?\n8. Line 206: The authors suggest that the failure of TEPP-46 to increase calcium or insulin in PKM1-overexpressing SCBCs “indicates that the FBP-induced calcium and insulin increases in PKM1-overexpressing SC-islets were due to metabolic effects of FBP, rather than its effect on PKM2 activation (30)”. This interpretation is not justified by any data and should be removed.\n9. Line 21: The oxygen consumption rate was “close to significance”. This experiment should be repeated with higher replicates since it is important to understand whether PKM1 overexpression increases oxygen consumption.\n10. A major premise of the paper is that PKM1 overexpression increases insulin release. This is really not clear from the data presented, and could be driven by 2 high data points in the 20G condition (Fig. 5B). The number of replicates should be increased. It would also be helpful to test more physiological glucose levels, such as 8.3 mM glucose.\nMinor\n1. Isn’t it expected that SCBCs have low PKM1 (and high PKM2) relative to mouse islets? PKM2 is often-cited as associated with undifferentiated cells.\n2. Did the authors control for osmolarity when addition 20mM and 80 mM glucose in Fig. 5A? Are the calcium recordings representative or averages?\n3. It is not a foregone conclusion that commercial pyruvate kinase inhibitors actually inhibit pyruvate kinase. If the authors wish to use PKM2-IN-1 or another pyruvate kinase inhibitor in islets they should first an enzyme activity assays to show that it works.\n4. The authors do not provide a source for FBP. Please list all chemicals in Supplementary Data.\nWith kind regards and best wishes,\nMatthew J. Merrins", "reviewer_2": "In this study, Lin et al identifies a critical metabolic bottleneck in the maturation of human pluripotent stem cell-derived β (SC-β) cells, revealing that excessive phosphoenolpyruvate (PEP) accumulation disrupts glucose metabolism, calcium signaling, and insulin secretion. Using glucose-tracing metabolomics and single-cell transcriptomics, the authors demonstrate that elevated PEP increases basal intracellular calcium levels, leading to downregulation of key TCA cycle genes and impairing functional maturation. In addition, they find that low expression of pyruvate kinase 1 (PKM1) contributes to this metabolic dysfunction, as PKM1 deficiency reduces PEP metabolism and limits glucose-stimulated insulin secretion. By overexpressing PKM1, the study successfully restores PEP metabolism, rescues TCA cycle activity, and enhances β cell functionality, underscoring the importance of metabolic reprogramming in SC-β cell maturation. This study is timely and provides valuable insights into overcoming the functional immaturity of SC-β cells, offering a promising strategy for improving stem cell-based therapies for diabetes. However, there are some major concerns that need to be addressed.\n1. Mouse islets were used as a control in all studies. However, mouse and human islets are not same. It is important to include human islets as controls in the key assays.\n2. The dynamic glucose stimulated insulin secretion of control SC-β cells is not as good as the standard protocol of the field (Fig. S1D). Can overexpressing PKM1 in SC-β cells derived using advanced protocol still restores PEP metabolism, rescues TCA cycle activity, and enhances β cell functionality?\n3. For scRNA-seq data, the overall cell numbers of S7D1PKM1+ and S7D14 PKM1+ are lower S7D1PKM1- and S7D14 PKM1- conditions. In addition, the ratio of SC-α cells look higher in S7D14 PKM1+ condition. If the ratio of SC-α cells increase, please provide some explanation?"}, "author_response": "We sincerely thank the reviewers for their insightful comments and valuable\nsuggestions that have helped us to improve and refine our manuscript. We have\ncarefully addressed all concerns and made extensive revisions, including modifications\nto a total of 41 figure panels (27 in the main figures and 14 in the supplementary\nfigures), adding a total of 32 new panels (8 to the main figures and 24 to the\nsupplementary figures) and 3 new supplementary data, along with new analyses and\nexperiments (single-cell RNA-seq, human sample staining, and functional assays).\nKey revisions include:\n1. Demonstrated K -dependent PEP effects in SC-β cells: Using Na⁺-PEP\nATP\nunder balanced Na⁺condition, we show that extracellular PEP induces calcium\ninflux and insulin secretion in SC-β cells. This response is blocked by inhibitors\nof PKM2, mitochondria, and K channels, confirming that PEP must enter the\nATP\ncell to exert metabolic effects and trigger calcium influx via K (Figure 3A-D,\nATP\nFigure 3I).\n2. Validated physiological PEP effects: New patch-clamp experiments and\nsingle-cell RNA-seq under physiological PEP levels corroborate our original\nobservations (Figure 2G, 2H).\n3. Validated PKM1 expression in human tissue: Immunostaining of human\npancreatic sections demonstrates that PKM1 is expressed in primary β cells\n(Supplementary Figure 3).\n4. Improved functional assays: We expanded calcium imaging to include\nadditional metabolites such as OAA and methyl-pyruvate treated with different\ninhibitors (Figure 3E-H, Supplementary Figure 2G-J), and repeated insulin\nsecretion assays under more physiological glucose conditions (Figure 5D, 5G)\nwith increased replicates in Seahorse experiments (Figure 5F), thereby\nenhancing robustness and reproducibility.\n5. Additional functional and metabolic rescue in sorted β cells: CD49a-\nsorted β cells (Supplementary Figure 2E-F) show that PKM1 overexpression\nlowers basal secretion, enhances glucose-dependent secretion (Figure 5G),\nand partially restores PEP/TCA metabolism (Supplementary Figure 6).\n6. PKM1 not the sole bottleneck: PKM1 overexpression partially rescues TCA\nand OXPHOS (Supplementary Figure 6), but additional bottlenecks (e.g.,\nimpaired OXPHOS) remain; we revised the tone throughout the manuscript\naccordingly.\n7. Expanded discussion of PKM1/PEP mechanism and effects on cell fate:\nWe now discuss how PKM1/PEP may affect both β- and α-cell differentiation\nand function, underscoring its broader role in SC-islet maturation.\nA point-by-point response to each reviewer’s comments is provided below. The\nrelated references can be found on page 24 of this document.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe paper by Lin et al. shows that PKM1 overexpression can improve the maturation\nand function of stem-cell derived beta cells (SCBCs), showing that metabolic\nreprogramming may be beneficial therapeutically. This proof-of-concept cell therapy is\nan advance over prior work on SCBCs, which identified bottlenecks at GAPDH and\nused cell-permeant metabolites to overcome it after overexpression of GAPDH and\nPGK1 had no effect (Ref. 4); and found no effect of extracellular phosphoenolpyruvate\n(PEP) or pyruvate kinase activation on insulin secretion (Ref. 16). In the present study,\nthe authors used metabolic tracing to show abnormally high levels of metabolites at\nlow glucose including PEP. The elevated PEP is notable because PEP and pyruvate\nkinase have recently been implicated in KATP channel closure and the initiation of\ninsulin secretion, as well as the K -independent amplification of secretion (Ref. 9).\nATP\nAdvancing this literature, the authors show mechanistically that including high PEP (as\nwell as upstream metabolites 3-PG and 2-PG), increases exocytosis from mouse beta\ncells and SCBCs at low glucose. The authors then show that PKM1 overexpression\nimproved calcium and insulin secretion, and over time, impacted expression of\nglycolytic and OxPhos genes in SCBCs. Put in context, the paper presents the premise\nof a therapeutic strategy for improving diabetes treatment and advances our\nmechanistic understanding of insulin secretion in primary beta cells.\n\nA major concern is that the effects of applying extracellular potassium\nphosphoenolpyruvate (K-PEP) are due to K+, which will depolarize the plasma\nmembrane, rather than PEP. This issue doesn’t necessarily dampen enthusiasm for\nthe paper, but it needs to be resolved to properly interpret the data.\n\nWe thank the reviewer for raising this important concern. We agree that the effects\nobserved with potassium phosphoenolpyruvate (K⁺-PEP) could, in principle, be partly\nattributable to K⁺ rather than PEP itself. To directly address this point and demonstrate\nthat PEP exerts specific effects, we performed three complementary sets of\nexperiments:\n1. Na+-PEP substitution: We applied extracellular sodium salts of PEP (Na+-PEP)\nin KRB buffer with balanced Na+ concentration. Na+-PEP elicited calcium influx\nand insulin secretion in SC-β cells, but not in primary mouse β cells. Importantly,\nPEP-induced calcium response is dependent on PKM2, mitochondrial\nmetabolism and K channel (Figure 3A-D, Figure 3I), indicating that\nATP\nextracellular PEP can be metabolized uniquely to modulate SC-β cell function.\n2. Physiological concentrations in patch clamp: We reduced K+-PEP from 5\nmM to 50 μM in patch clamp studies, thereby minimizing the effect of K+ while\napproximating cytosolic PEP levels. Under these conditions, we still observed\neffects consistent with enhanced exocytosis (Figure 2G, 2H).\n3. Physiological concentrations in single cell RNAseq: We compared the\neffects of 50 μM KCl and K+-PEP on gene expression, which supports a PEP-\nspecific contribution on gene expression (Figure 3K-N) and this can be\nrestored by PKM1 overexpression (Figure 5A-C, Supplementary Figure 4)\nTogether, these results clarify that extracellular PEP itself has metabolic effects on\nSC-β cells. We have revised the manuscript accordingly to distinguish the contributions\nof K+ and PEP, and to emphasize that the unique responsiveness of SC-β cells to PEP\nprovides insight into their metabolic regulation and maturation. For clarity, additional\nexperimental details and results are outlined point-by-point below.\nMajor\n1. There is a major problem with the studies employing exogenous\nphosphoenolpyruvate (PEP) application, since the authors used the K+ salt (K-PEP)\nthat will depolarize beta bells independently of metabolism. It seems plausible that all\nthe effects of K-PEP are due to K+ rather than PEP, since the authors demonstrate\nthat 1) K-PEP was found to increase intracellular calcium independently of KATP\nchannels (i.e. in the presence of the KATP opener diazoxide), 2) the effects on\nsecretion were dependent on extracellular calcium, 3) the effects on calcium are not\nblocked by diazoxide, 4) the effects of K-PEP are not mimicked by DHA or\nglyceraldehyde. Thus, the effect of K-PEP is precisely the effect of applying KCl to beta\ncells (e.g., Fig. 3B in PMID: 20655835 shows that adding 5 and 20 mM KCl raises\nintracellular calcium in the presence of diazoxide); the in present work the authors used\n5 and 20 mM K-PEP. The effects of K+ would also explain the effect of K-PEP on HEK\ncells that have L-type calcium channels that open in response to membrane\ndepolarization. The authors need to repeat all key studies (especially those in Figs. 2-\n3) that used K-PEP with Na-PEP, which does not depolarize the beta cell. (note: the\nauthors should be mindful to replace the NaCl in their solutions with Na-PEP, not simply\nadd Na-PEP, since high osmolarity will pull exogenous insulin off beta cells and cause\nfalse GSIS; this artifact plagued the SCBC field in the early 2000s).\nResponse\nWe thank the reviewer for raising this important concern. We agree that the effects\nobserved with potassium phosphoenolpyruvate (K⁺-PEP) could, in principle, be partly\nattributable to K⁺ rather than PEP itself. To address this, we repeated the key\nexperiments in the original Figure 2-3 using the sodium salt of PEP (Na⁺-PEP)\naccording to reviewer’s suggestions, carefully adjusting the KRB buffer by replacing\nequimolar NaCl and accounting for Na⁺ introduced from both Na⁺-PEP and NaOH\n(used for pH adjustment). This approach avoided artifacts from Na+ depolarization and\nosmolarity, and yielded important results:\n1. While 20 mM Na+-PEP failed to elicit any calcium response or insulin secretion in\nmouse β cells (Figure 3A, 3I), it triggers a significant calcium response and insulin\nsecretion in SC-β cells (Figure 3B, 3I).\n(Figure 3A-B) (Figure 3I)\n2. Unlike the response elicited by K+-PEP which increase intracellular calcium\nindependently of K channels (i.e. in the presence of the K opener diazoxide),\nATP ATP\nthe response induced by Na+-PEP is inhibited by K channel opener diazoxide,\nATP\nmitochondrial complex III inhibitor antimycin A and PKM2 inhibitor PKM2-IN-1 (PKi) \nin sorted SC-β cells (Figure 3B-D, Supplementary Figure 2E-F).\n(Figure 3C-D)\nTherefore, unlike our previous conclusion that K+-PEP depolarize beta bells\nindependently of metabolism, our data with Na⁺-PEP demonstrate that PEP can be\nmetabolized to drive calcium responses via PKM2, mitochondrial metabolism, and K\nATP\nchannels. This strongly supports a mechanism involving metabolic processing of PEP\nfor K channel inhibition, rather than a non-specific K⁺-induced depolarization, in SC-\nATP\nβ cells. This mechanism is also consistent with previous studies (PMID: 35997256)1.\nWe now describe, in the “Results” section of the revised manuscript (page 5) that:\n“Na⁺-PEP (trisodium salt), which is expected to not freely permeable to the plasma\nmembrane, failed to elicit a calcium response in mouse β cells (Figure 3A). In contrast,\nNa⁺-PEP triggered calcium responses in CD49a-based magnetically sorted SC-β cells,\nwhich was blocked by K channel opener diazoxide (Dia), mitochondrial complex III\nATP\ninhibitor antimycin A and PKM2 inhibitor PKM2-IN-1 (PKi) (Figure 3B-D,\nSupplementary Figure 2E-F), suggesting that unlike mouse β cells, Na⁺-PEP can be\ntransported into SC-β cells and metabolized to promote calcium influx via K channel.”\nATP\nGiven the different interpretations that arise from using K⁺-PEP versus Na⁺-PEP,\nwe have revised the manuscript to clearly indicate which form was used in Figure 2\nand 3. Specifically, the use of K⁺-PEP (Figure 2C-F) serves only to confirm that the\ncells were viable and responsive to KCl, which is now described in the figure legend\n(Figure 2) as:\n“To demonstrate the functional viability of β cells and response to KCl, 5 mM KCl\nand 20 mM K+-PEP (Phosphoenol-pyruvate PEP, monopotassium salt) were added at\nthe end of [Ca2+] recording.”\ni\nFurthermore, we repeated the whole cell patch-clamp experiments (Figure 2G-H)\nwith intracellular infusion of different metabolites (3-PG, 2-PG, K+-PEP) at a more\nphysiological concentration (50 μM), thereby avoiding unwanted artifacts from K+.\nSimilar to previous observation, SC-β cells show higher basal exocytosis and calcium\nentry, therefore these metabolites cannot further increase the exocytosis. We now\ndescribe, in the “Results” section of the revised manuscript (page 5) that:\n“the infusion (dialysis) of 50 M 3-PG, 2-PG, or K+-PEP into the cell cytosol via\nwhole-cell patch clamp significantly enhanced depolarization-induced exocytosis by\n(~5-fold) compared to the contro𝜇𝜇l group in mouse-β cells. In contrast, SC-β cells,\ngenerated from CRISPR-Cas9 method and identified by EGFP (Supplementary Figure\n2B-D), showed no metabolite-dependent changes in exocytosis (Figure 2G).\nRemarkably, this was because under control conditions, SC-β cells already exhibited\na 10-fold higher exocytosis compared to mouse β-cells, limiting further amplification by\nthese metabolites (Figure 2G). Additionally, SC-β cells displayed greater\ndepolarization-induced calcium entry across various conditions compared to mouse β-\ncells (Figure 2H).”\n(Figure 2C-F)\n2. Related to the point above, it would also be necessary to demonstrate that\nextracellular PEP enters the cell, since PEP is not known to be a cell permeant\nmetabolite. PEP could, in principle, act via a receptor, but extracellular PEP only\nreaches micromolar levels (not 5 or 20mM, which is unlikely to be physiologically\nrelevant even if it proves useful as a tool).\nResponse\nWe appreciate this important point. It is true that PEP is not generally considered a\ncell-permeant metabolite, and consistent with this, Na⁺-PEP did not elicit calcium influx\nor insulin secretion in mouse islets (Figure 3A, 3I). Nevertheless, several reports\nindicate that PEP can cross the plasma membrane in specific cell types, including red\nblood cells (PMID: 629781)2 via an anion-transport protein. It can also enter human\nmesenchymal stem cells (PMID: 30992510)3 and Th17 cells (PMID: 36857180)4 to\nregulate their differentiation. These findings suggest that SC-β cells may also possess\nmechanisms to internalize PEP. Importantly, Na⁺-PEP–induced calcium influx was\nstrongly attenuated by activation of K channels (diazoxide), mitochondrial\nATP\nrespiration (antimycin A), and PKM2 activity (PKM2-IN-1), indicating that intracellular\nmetabolism of PEP is required for its effect (Figure 3B-D).\n(Figure 3A) (Figure 3I)\n(Figure 3B-D)\nRegarding the concentrations (5–20 mM) exceed physiological plasma levels, our\naim, however, was not to mimic circulating metabolite concentrations, but to establish\nwhether exogenous PEP can serve as a metabolic substrate to probe β cell function.\nSimilar proof-of-concept approaches using supraphysiological levels of pyruvate,\nlactate, or fructose-1,6-bisphosphate have been widely applied to study metabolite\ntransport and downstream metabolic activity (PMID: 32402282, 38933536, 35241836,\n37058408)5–8. Thus, we interpret our findings as evidence that β cells are capable of\ninternalizing and metabolizing PEP in a regulated manner, although the precise\ntransport mechanism remains to be determined and is discussed in detail in the\nDiscussion section (page 10):\n“Unlike mouse islets, SC-β cells appear permeable to several metabolites,\nincluding PEP and OAA, consistent with previous studies (17). High concentrations of\nthese metabolites elicit significant insulin secretion and calcium responses, which are\nblocked by inhibitors of pyruvate kinase, mitochondrial metabolism, and K channels,\nATP\nindicating that the metabolites enter SC-β cells and are metabolized intracellularly.\nAlthough the specific transporter for PEP and OAA remains unknown, several reports\nindicate that PEP can cross the plasma membrane in specific cell types, including red\nblood cells (34) via an anion-transport protein, as well as human mesenchymal stem\ncells (35) and Th17 cells (36), where it can influence differentiation. This suggests\nthere might be a transporter particularly active in immature SC-islets but not in mature\nislets, which could potentially be exploited for metabolic programming.”\n3. K-PEP was found to impact the expression of glycolytic and OxPhos genes. The\nauthors should determine whether this is due to K+ or PEP. It would be interesting if a\nfeedforward mechanism from calcium influx, which accelerates flow through glycolytic\nmetabolism (Ref. 3), impacts the expression of glycolytic genes.\nResponse\nWe thank the reviewer for raising this important point regarding the potential\ncontribution of K⁺-induced depolarization and Ca²⁺-dependent feedforward activation\nof glycolysis. To address this, we performed the following experiments and analyses:\n1. Single-cell RNA seq to examine the effects of low-dose PEP treatments\n(50/500 μM). Since PEP can enter cells to induce significant calcium response\n(see response to point 2), we applied non-depolarizing concentrations of K⁺-\nPEP (50 or 500 μM) and equimolar KCl as controls extracellularly to culture\nSC-β cells. At both concentrations, K+-PEP suppressed β cell differentiation by\nreducing the proportion of mature “Adult Beta/Alpha” cells and increasing\nimmature SC-β cells (Figure 3L). K-PEP also downregulated OxPhos (e.g.,\nMT-CO1, MT-ND1, NDUF7) (Figure 3M, 3N) and glycolytic genes (e.g.,\nPGAM1, TPI1) (Figure 3N) relative to equimolar KCl.\n(Figure 3L-M)\n2. PKM1 rescue experiments. PKM1 overexpression rescued the proportion of\nmature β cells (Adult β cells) and reduced the fraction of immature SC-β\ncells induced by 50 μM PEP (Figure 5A). Consistently, PKM1 overexpression\nimproved the OxPhos metabolic pathway and suppressed genes related to the\nneuronal system (Figure 5B-C). Similar effects were also observed under high-\ndose PEP treatment (5 mM) (Supplementary Figure 5).\n(Figure 5A-C)\n3. Metabolomic and functional validation. PKM1 overexpression decreased\nbasal PEP (Supplementary Figure 6D), lowered basal insulin secretion from\nsorted β cells (Figure 5G) and improved glycolytic gene expression (Figure\n6F), further supporting that intracellular PEP acts as a negative regulator of β\ncell differentiation.\nPEP\n100\n80\n60\n40\n20\nS\nβ\nC\nH\n-\nG\nβ\nLG\nS\nP\nC\nK\n-\nM\nβ\n(Supplementary Figure 5D) (Figure 5G)\nTogether, these findings indicate that PEP, rather than K⁺, exerts a direct effect on\nβ cell gene expression and differentiation.\nPossible mechanism for PEP effects :\nPrior studies suggest that PEP can locally generate ATP to inhibit K channels and\nATP\nmodulate Ca²⁺ entry (PMID: 38768366, 33147484)9,10. Although 50–500 μM PEP is\nnon-depolarizing, elevated extracellular PEP may increase basal Ca²⁺ levels, pushing\ncells closer to the threshold for depolarization. Consistently, PEP upregulated calcium-\nesoculg-C31morf\ngnilebal\n%\n✱ ✱✱✱\nD\nand potassium-channel genes (CACNA1E, CACNA2D1, CACNA2D3) while\ndownregulating OxPhos and glucose metabolism pathways (Figures 3M–N). Thus,\nPEP may engage both metabolic/transcriptional mechanisms and a feedforward Ca²⁺\n-dependent pathway to influence β cell maturation. In summary, our results support a\nmodel in which intracellular PEP directly regulates β cell gene expression and\ndifferentiation via a Ca²⁺-dependent feedforward mechanisms. This is discussed in\ndetail in the revised Discussion section (page 11):\n“Although this concentration cannot elicit overt depolarization, its effects may still\nbe mediated through disrupted Ca²⁺ handling and signaling (37). PEP may increase\nbasal Ca²⁺ levels, pushing cells closer to the threshold for depolarization. Consistently,\nPEP upregulated calcium- and potassium-channel genes (CACNA1E, CACNA2D1,\nCACNA2D3) while downregulating OxPhos and glucose metabolism pathways. Thus,\nPEP may engage both metabolic/transcriptional mechanisms and a feedforward Ca²⁺\n-dependent pathway to influence β cell maturation. Glucose-stimulated calcium influx\nis not only a hallmark of functional maturation in β cells but also a crucial event in\nregulating β cell maturation (16, 38). During pancreatic β cell maturation, the calcium\ninflux induced by glucose stimulation precedes the acquisition of insulin secretion\nability (39). As glucose metabolism matures, proper glucose metabolism triggers\ncalcium influx, activating the calcium-dependent phosphatase Calcineurin (CaN). This\nactivation promotes the dephosphorylation and nuclear translocation of nuclear factor\nof activated T cells (NFAT), which binds to β cell-specific DNA and regulates\ntranscription of specific genes, promoting insulin vesicle formation and functional\nmaturation in β cells (40–42). However, excessive and sustained calcium influx can\ndelink NFAT transcriptional activity, leading to β cell dedifferentiation (43). Therefore,\ncalcium mishandling by PEP in SC-β cells may be a key factor impeding functional\nmaturation.”\n4. This sentence is misleading, Line 111-112: “Similarly, the glucose dependent increase in metabolites from the TCA cycle, such as citrate, α-ketoglutarate (α-KG), malate, ATP and GSH, was also absent in SC-islets (Figure 1H)”. The reality is that basal metabolite levels are high.\nResponse\nThanks for the suggestion. We have revised the sentence for clarity. It now reads\n(page 4):\n“Interestingly, while high glucose-induced PEP levels were comparable between\nmouse and SC-islets, basal PEP levels at low glucose were significantly higher in\nSC-islets with lower stimulating index, as were pyruvate levels (Figure 1F-G) and\nother TCA metabolites (Figure 1H).”\nSince the tracer studies show that metabolites downstream of PEP accumulate in SCBCs at low glucose, including pyruvate and TCA cycle metabolites, it is not clear why the authors concluded that there is a bottleneck at the pyruvate kinase step of glycolysis in SCBCs. It seems to me that the strongest evidence for a glycolytic bottleneck is the effects of PKM1 overexpression - not the metabolomics data.\nResponse\nWe thank the reviewer for raising this important point. We agree that metabolomics\ndata cannot fully establish a bottleneck at the pyruvate kinase step. Instead, it can only\nindicate a bottleneck downstream of PEP. For clarity, we have revised the text to state\n(page 4):\n“In addition, glutamate was preferentially metabolized to glutamine (Gln) rather\nthan GSH, and ATP production was much lower in SC-islets (Figure 1I), indicating that\ndisrupted glucose metabolism originated from dysregulated glycolytic metabolism\ndownstream of PEP (Figure 1J).”\nTo reach a conclusion a bottleneck at the pyruvate kinase step, it is based on\nseveral lines of evidence: (i) PKM1 expression is markedly lower in SC-β cells\ncompared to primary β cells, and pyruvate kinase enzymatic activity is reduced (Figure\n4); (ii) tracer studies showed abnormal PEP accumulation at basal glucose; and (iii)\nmost importantly, we performed additional tracer studies and insulin secretion in sorted\nSC-β cells showing that PKM1 overexpression reduced PEP accumulation, restored\npartial TCA flux (Supplementary Figure 6D-I), and lowered basal insulin secretion\n(Figure 5G). Together, these findings strongly suggest a bottleneck at the pyruvate\nkinase step.\n(Supplementary Figure 6D-L)\nWe also acknowledge that PKM1 overexpression only partially restores SC-β cell\nfunction. For instance, PKM1 did not significantly increase insulin secretion (Figure\n5D) or fully rescue ATP labeling at high glucose, and TCA cycle activity remained only\npartially improved (Supplementary Figure 6F-I) in sorted SC-β cells. These results\nindicate that while the pyruvate kinase step represents a key bottleneck, additional\ndefects, particularly at the level of OXPHOS (PMID: 37556323)11, also contribute to\nmetabolic immaturity and upstream metabolite accumulation. This is also discussed in also discussed in\ndetail (page 10):\n“Despite promoting pyruvate flux into TCA, enhancing OXPHOS-related gene\nexpression, and lowering basal PEP, PKM1 overexpression in sorted SC-β cells does\nnot fully increase ATP or insulin secretion at high glucose. This reflects a persistent\nmitochondrial bottleneck: TCA cycle flux and OXPHOS remain limited, so extra\npyruvate cannot be fully converted into ATP. As a result, PKM1 primarily expands the\ndynamic range of GSIS by lowering basal insulin secretion rather than increasing\ninsulin secretion at high glucose. Thus, PEP accumulation represents one, but not the\nonly, block in the metabolic network. A previous study identified a metabolic bottleneck\nat the GAPDH and PGK1 steps (4). However, in our study GAPDH and PGK activity\nshowed only a slight decrease. Additionally, the glucose-dependent increase in 3-\nPG/2-PG was still maintained. Similar to PEP metabolism, pyruvate metabolism also\nexhibited elevated basal pyruvate level and loss of glucose-stimulated increase.\nPyruvate cycling is essential in insulin secretion (23, 31, 32). Recent study reports that\npyruvate metabolism is also mediated by LDHB, which is required for inhibiting basal\ninsulin secretion (33). However, LDHB level is much lower in SC-islets (Figure 6F),\nindicative of a pyruvate metabolic bottleneck. Therefore, functional immaturity of SC-β\ncells is likely a consequence of multiple metabolic bottlenecks at both glycolytic and\nmitochondrial levels (5).”\n5. The authors apply metabolites extracellularly - including glyceric acid, FBP, and OAA\n- as if they are freely transported into cells. Perhaps this is true for SCBCs, perhaps not. What is the evidence that glyceric acid is a precursor to 3-PG (Suppl. Fig. 2B,C)? What is the evidence that it can enter cells? How about oxaloacetate (Fig. 3A)? How about FBP (Fig. 5A-C)?\nResponse\nFor glyceric acid, we cited the study by Davis et al. (PMID: 32402282)5, which\nreported that glyceric acid can act as a precursor of 3-phosphoglycerate (3-PG) and\ndirectly stimulate insulin secretion in human cadaveric islets (see Figure S3D in that\nreference, PMID: 32402282)5. These findings suggest that glyceric acid can, at least\nunder certain conditions, be taken up and metabolized within β cells. However, we\nacknowledge that the mechanisms of its cellular uptake remain incompletely\nunderstood, and additional studies will be required to definitively establish its transport\nand metabolic fate in SC-β cells.\n[Redacted]\n(Figure S3D, PMID: 32402282) 5\nFor oxaloacetate (OAA), while no calcium response was observed in mouse islets\n(Figure 3E), OAA elicited a significant calcium influx in SC-islets, which was blocked\nby diazoxide, antimycin A (Figure 3F–G). These inhibitory effects suggest that OAA\nmust enter the cell and be metabolized to induce the observed calcium response.\n[Redacted]\n(Figure. 3E-G)\nFor fructose-1,6-bisphosphate (FBP), the situation is less clear. Although the\nsodium salts from FBP were balanced, FBP induced insulin secretion and calcium\nresponse in SC-islets, particularly in PKM1-overexpressing cells, but the calcium\nresponse was not blocked by PKM2 inhibitor, mitochondria inhibitor or K channel\nATP\nactivation (Supplementary Figure. 7C–E). This indicates that FBP can trigger insulin\nsecretion, but whether this requires direct cellular uptake or occurs via an alternative\nmechanism remains uncertain. We also mention this in the “Result” (page 8) and\n“Discussion” (page 12):\n“FBP, an upstream glycolytic metabolite and activator of PKM2, could induce\nhigher insulin secretion and calcium response in PKM1-overexpressing SC-islets\n(Supplementary Figure. 7 A-B), but these effects cannot be inhibited by PKi,\nantimycin A or diazoxide (Supplementary Figure 7C-E).“\n“Additionally, although FBP seemed to enhance insulin secretion in PKM1-\noverexpressing islets, this effect was likely due to enhanced functional maturation\nrather than PKM2 activation, as acute exposure to TEPP-46 did not produce a\nsignificant effect and the precise mechanism by which FBP modulated insulin secretion\nremains unknown.”\n(Supplementary Figure. 7C-E).\nTogether, these findings suggest that at least some of the applied metabolites\n(glyceric acid, OAA) are able to enter and be metabolized in β cells, although the\nprecise mechanisms of uptake remain to be fully established.\n6. SCBCs exhibit 10-fold higher exocytosis than control beta cells (Fig. 2G) and\ncalcium current is very high (Fig. 3H). This indicates that SCBCs are highly exocytosis-\ncompetent, but triggering secretion is a problem. I agree with the author’s assessment\nthat high exocytosis is likely due to high PEP, since high PEP was measured by\nmetabolomics in SCBCs and high PEP was sufficient to increase exocytosis in both\nmouse and SCBCs. This is an important point and should be discussed.\nResponse\nWe thank the reviewer for this insightful comment. We agree that the high exocytosis\nobserved in SC-β cells, together with elevated calcium current (Figure. 2G-H in the\nrevised manuscript), suggests that the exocytotic machinery is intact and even\nhyperactive, but that stimulus–secretion coupling is defective. Now the underlying\nmechanism is discussed (page 9):\n“These findings indicate that SC-β cells are highly exocytosis-competent, but\nremain unable to properly trigger glucose-stimulated secretion. Previous studies have\nreported that, at basal glucose, immature SC-β cells exhibit spontaneous action\npotentials and elevated exocytosis (30). Elevated PEP may not only amplify basal\nexocytosis but also locally increase ATP (10), thereby triggering calcium influx even at\nlow glucose. This pre-activation of the triggering machinery can limit the dynamic range\nof glucose-stimulated responses and even impede maturation. Similarly, PKM1\noverexpression, which should enhance glycolytic flux into ATP, actually reduce basal\ninsulin secretion. This can be explained by a difference between global versus local\nATP pools (10). In SC-β cells lacking PKM1, residual PKM2 activity can metabolize the\nabnormally high basal PEP to generate localized ATP in microdomains near KATP\nchannels. This local ATP is sufficient to close K channels, elevate basal Ca²⁺ influx,\nATP\nand drive inappropriate basal exocytosis. By contrast, PKM1 efficiently consumes PEP,\npreventing its abnormal accumulation and thereby suppressing the local ATP\ngeneration for triggering insulin secretion at low glucose. While PKM1 also increases\npyruvate flux into mitochondria and elevates basal mitochondrial ATP, this global ATP\npool is less effective at triggering secretion than PEP-driven local ATP at low glucose\n(12).”\n7. It is unclear how the authors are measuring PKM1 and PKM2 tetramers using SDS-\ncontaining gels (Fig. 4B and Methods). Is this an error?\nResponse\nWe thank the reviewer for pointing out this error. We agree that SDS-containing gels\nare not suitable for the detection of native tetramers or dimers. In Figure 4B, our aim\nwas to examine the relative expression levels of PKM1 and PKM2 monomers. The\nhigher molecular weight bands occasionally observed are likely due to incomplete\ndenaturation or protein aggregation during sample preparation, rather than true\noligomeric species. We have revised the Figure 4B and figure legend to clarify this\npoint (page 26):\n(Figure 4B)\n“Western blotting of PKM1 with normalized band intensity calculation (top) and\nPKM2 with normalized band intensity calculation (bottom) of mouse- and SC-\nislets from S7D14 (n=3). The major bands represent monomeric forms and the\nbands with higher molecular weight likely result from incomplete denaturation or\naggregation.”\n8. Line 206: The authors suggest that the failure of TEPP-46 to increase calcium or\ninsulin in PKM1-overexpressing SCBCs “indicates that the FBP-induced calcium and\ninsulin increases in PKM1-overexpressing SC-islets were due to metabolic effects of\nFBP, rather than its effect on PKM2 activation (30)”. This interpretation is not justified\nby any data and should be removed.\nResponse\nWe thank the reviewer for this comment. We agree with the concern and have removed\nthe statement regarding TEPP-46 and PKM2 activation from the manuscript. In the\nrevised text, we present the experimental findings objectively and without\noverstatement (page 8):\n“FBP, an upstream glycolytic metabolite and activator of PKM2, induced higher insulin\nsecretion and calcium responses in PKM1-overexpressing SC-islets (Supplementary\nFigure. 7A–B). However, FBP-induced calcium responses were not inhibited by PKi,\nantimycin A, or diazoxide, indicating that the effect is independent of glucose\nmetabolism or K channel activity (Supplementary Figure. 7C–E). Furthermore,\nATP\nacute treatment with the PKM2 agonist TEPP-46 modestly but not significantly\nenhanced insulin secretion (Supplementary Figure. 7F) or calcium responses\n(Supplementary Figure. 7G) in both control and PKM1-overexpressing SC-islets.”\n9. Line 21: The oxygen consumption rate was “close to significance”. This experiment\nshould be repeated with higher replicates since it is important to understand whether\nPKM1 overexpression increases oxygen consumption.\nResponse\nWe thank the reviewer for highlighting this important point. To address this, we\nrepeated the Seahorse assay with an increased number of biological replicates (n = 8\nCTR, 8 PKM1 in at least triplicate now). The results now demonstrate that PKM1\noverexpression significantly increases oxygen consumption rate (OCR), supporting its\nrole in enhancing oxidative metabolism (Figure 5E).\n(Figure 5E)\n10. A major premise of the paper is that PKM1 overexpression increases insulin\nrelease. This is really not clear from the data presented, and could be driven by 2 high\ndata points in the 20G condition (Fig. 5B). The number of replicates should be\nincreased. It would also be helpful to test more physiological glucose levels, such as\n8.3 mM glucose.\nResponse\nWe thank the reviewer for this valuable suggestion. To further strengthen our\nconclusion, we repeated the insulin secretion experiments using a more physiological\nglucose range (1, 11, and 20 mM) in SC-islets. In line with initial findings, PKM1\noverexpression tended to enhance glucose-stimulated insulin secretion (Figure 5D\nnow). To better assess whether this effect was specifically attributable to PKM1 in SC-\nβ cells, we enriched SC-β cells by CD49a-based magnetic sorting. In these sorted cells,\nPKM1 overexpression was associated with reduced basal insulin secretion at low\nglucose, while showing an improved glucose-dependent increase in insulin secretion\n(Figure 5G). The original Figure 5B now is moved to supplementary figure 7A.\nTogether, these results provide additional support that PKM1 promotes more\nphysiologically regulated insulin secretion, although we fully acknowledge that\noverexpression of PKM1 in other cell types, such as α cells, might also contribute to\nthe glucose-stimulated insulin secretion. This is also discussed in the revised\nmanuscript (page 12):\n“Sorted β cells overexpressing PKM1 primarily showed reduced basal insulin\nsecretion without a notable increase in glucose-stimulated response. Therefore,\nenhanced insulin secretion in whole SC-islets at high glucose may reflect indirect\neffects of PKM1 on other cell types, including α cells, where altered glucagon\nsecretion could further modulate β cell function (45). PKM1 appears to regulate insulin\nsecretion in SC-islets not only through direct modulation of β cell glycolytic and\nmetabolic fluxes, but also indirectly via α cell–mediated mechanisms. Further\ninvestigation is needed to elucidate the specific role of PKM1 in α cell function.”\n(Figure 5D) (Figure 5G)\nMinor\n1. Isn’t it expected that SCBCs have low PKM1 (and high PKM2) relative to mouse\nislets? PKM2 is often-cited as associated with undifferentiated cells.\nResponse\nWe thank the reviewer for this insightful comment. Our observation that SC-β cells\nexpress lower levels of PKM1 and higher levels of PKM2 compared to primary mouse\nislets aligns with the well-established paradigm that PKM2 is enriched in proliferative\nand less differentiated cell states. To better contextualize the functional significance of\nthese isoforms for the reader, we have revised the introduction as follows (page 3):\n“The two main splicing isoforms of pyruvate kinase muscle (PKM), PKM1 and\nPKM2, catalyze the conversion of PEP to pyruvate. Beyond this, they exert distinct,\nisoform-specific effects on cell differentiation and function (18).”\nWe also believe our study extends this concept by demonstrating that restoring\nPKM1 expression in SC-β cells not only alters metabolic flux but also promotes\nfunctional maturation, including improved glucose-responsive insulin secretion. Thus,\nwhile the expression pattern itself is expected, our findings highlight the functional\nconsequences of manipulating PKM isoform balance in the context of SC-β cell\nmaturation.\n2. Did the authors control for osmolarity when addition 20mM and 80 mM glucose in\nFig. 5A? Are the calcium recordings representative or averages?\nResponse\nWe thank the reviewer for this important point. Osmolarity was controlled in all\nexperiments, using mannitol to balance osmotic pressure as described in the Methods\n(page 21).\n“D-mannitol (Aladdin Scientific, Shanghai, China) was used to balance the\nosmolarity of KRB solutions as previously reported (57).”\nThe calcium traces (Figure 5A, now Figure 5F in the revised manuscript) \nrepresent averaged recordings from multiple cells across independent experiments.\nNow the figure legend has been revised accordingly for clarity (page 27):\n“(F) Average [Ca2+] recordings to different concentration of glucose level and 20\ni\nmM K+-PEP from CTR and PKM1-overexpressing SC-β”\n3. It is not a foregone conclusion that commercial pyruvate kinase inhibitors actually\ninhibit pyruvate kinase. If the authors wish to use PKM2-IN-1 or another pyruvate\nkinase inhibitor in islets they should first an enzyme activity assays to show that it\nworks.\nResponse\nWe thank the reviewer for this valuable suggestion. To confirm that PKM2-IN-1\nfunctions as expected in our system, we tested its effect on PEP-induced responses.\nTreatment with PKM2-IN-1 significantly reduced the calcium response triggered by\nexogenous PEP, consistent with inhibition of pyruvate kinase activity in islets. While\nwe did not perform a direct enzymatic activity assay in this study, these functional\nresults provide supportive evidence that PKM2-IN-1 is active under our experimental\nconditions.\n(Figure 3D)\n4. The authors do not provide a source for FBP. Please list all chemicals in\nSupplementary Data.\nResponse\nWe thank the reviewer for pointing this out. We have now included the source\ninformation for FBP (D-Fructose 1,6-bisphosphate Trisodium Salt Hydrate, zrbiorise)\nas well as all other chemicals in Supplementary Data 10. In addition, for experiments\ninvolving FBP (Supplementary Figure 7A-F) and other metabolites such as PEP and\nOAA, we carefully accounted for sodium contributed by FBP and by NaOH (used for\npH adjustment) to ensure that sodium levels were balanced across conditions.\n(Supplementary Data 10)\nWith kind regards and best wishes,\nMatthew J. Merrins\nReviewer #2 (Remarks to the Author):\nIn this study, Lin et al identifies a critical metabolic bottleneck in the maturation of\nhuman pluripotent stem cell-derived β (SC-β) cells, revealing that excessive\nphosphoenolpyruvate (PEP) accumulation disrupts glucose metabolism, calcium\nsignaling, and insulin secretion. Using glucose-tracing metabolomics and single-cell\ntranscriptomics, the authors demonstrate that elevated PEP increases basal\nintracellular calcium levels, leading to downregulation of key TCA cycle genes and\nimpairing functional maturation. In addition, they find that low expression of pyruvate\nkinase 1 (PKM1) contributes to this metabolic dysfunction, as PKM1 deficiency\nreduces PEP metabolism and limits glucose-stimulated insulin secretion. By\noverexpressing PKM1, the study successfully restores PEP metabolism, rescues TCA\ncycle activity, and enhances β cell functionality, underscoring the importance of\nmetabolic reprogramming in SC-β cell maturation. This study is timely and provides\nvaluable insights into overcoming the functional immaturity of SC-β cells, offering a\npromising strategy for improving stem cell-based therapies for diabetes. However,\nthere are some major concerns that need to be addressed.\n1. Mouse islets were used as a control in all studies. However, mouse and human islets\nare not same. It is important to include human islets as controls in the key assays.\nResponse\nWe agree with the reviewer that including human islets as controls would strengthen\nthe study. To address this limitation:\n1. Human tissue evidence: We used human pancreatic tissue sections as\ncontrol to examine PKM1 expression and found that PKM1 is expressed at in\nmature human islets. Interestingly, it is higher in islets compared to surrounding\nexocrine tissue (Supplementary Figure. 3).\n2. Transcriptomic evidence: Our analysis also incorporated publicly available\nsingle-cell RNA-seq datasets of human islets as controls (Figure. 3K,\nSupplementary Figure 4A, 5A, 8A).\n3. Independent validation: Several previous studies have demonstrated the\npresence and functional importance of pyruvate kinase in human islets (PMID:\n35997256)1 as well as the effects of PEP on β-cell physiology (PMID: 38607916,\n33147484)10,12.\nTogether, while the availability of live human islets is limited and not all functional\nassays were repeated with human islets as controls, our histological, transcriptomic,\nand published data consistently support the relevance of PKM1 to human β-cell\nmaturation.\n(Supplementary figure 3)\n2. The dynamic glucose stimulated insulin secretion of control SC-β cells is not as good\nas the standard protocol of the field (Fig. S1D). Can overexpressing PKM1 in SC-β\ncells derived using advanced protocol still restores PEP metabolism, rescues TCA\ncycle activity, and enhances β cell functionality?\nResponse\nWe thank the reviewer for this important comment. We acknowledge that the dynamic\nglucose-stimulated insulin secretion (GSIS) of control SC-β cells in our dataset may\nnot fully match results reported with the most advanced differentiation protocols. Our\ndifferentiation protocol, however, has been carefully optimized based on previously\npublished standard protocols in the field (PMID: 35241836, 35115708, 25211370)7,13,14.\nAs is common for SC-islet differentiation, we do observe batch-to-batch variability.\nWhile some batches display relatively modest GSIS, others exhibit robust glucose\nresponsiveness. To better illustrate this, we separated the original data into the four\nleast responsive and the four most responsive batches (Supplementary Figure 1D).\n(Supplementary Figure 1D)\n30\n20\n10\n0\n0 20 40 60 80\nTime (min)\n(Supplementary Figure 1D, 4 least responsive)\n(Supplementary Figure 1D, 4 most responsive)\nPrevious studies have shown that purified β cells can display more robust GSIS\ncompared to mixed SC-islet populations (PMID: 30710150)15. Consistent with this,\nwhen we sorted SC-β cells using CD49a-based magnetic sorting (PMID: 40400171,\n31068696)16,17, we observed improved glucose dependency in PEP metabolism, TCA\nesaeler\nnilusnI\n)egnahc\ndloF(\nLG HG LG KCl\n30\n20\n10\n0\n0 20 40 60 80\nTime (min)\nesaeler\nnilusnI\n)egnahc\ndloF(\nLG HG LG KCl\ncycle activity (Supplementary Figure 6D-I), and insulin secretion (Figure 5F; 1.3-fold\nincrease between 1G and 11G, and 1.5-fold increase between 1G and 20G). These\nresults suggest that our protocol is comparable to existing advanced approaches in\nthe field.\n4\n2\n0\n1G 11G 20G KCl\n(Supplementary Figure 6D-I) (Figure 5F)\nImportantly, PKM1 overexpression in sorted SC-β cells further enhanced PEP\nmetabolism and partially improved TCA cycle activity (Supplementary Figure 6D-I).\nMoreover, PKM1 overexpression reduced basal insulin secretion and yielded a more\nglucose-dependent increase in insulin secretion (Figure 5G), supporting its role in\nimproving β cell functionality. Together, these findings demonstrate that our protocol\nachieves performance comparable to the most advanced approaches currently\navailable.\n3. For scRNA-seq data, the overall cell numbers of S7D1PKM1+ and S7D14 PKM1+\nare lower S7D1PKM1- and S7D14 PKM1- conditions. In addition, the ratio of SC-α\ncells look higher in S7D14 PKM1+ condition. If the ratio of SC-α cells increase,\nplease provide some explanation?\nResponse\nWe thank the reviewer for this observation. The lower overall cell numbers in the\nPKM1-overexpressing groups (S7D1 PKM1+ and S7D14 PKM1+) are primarily due to\nthe transduction efficiency, as PKM1 overexpression was achieved in ~20% of the cells\nin this batch, leading to reduced cell representation in the scRNA-seq dataset.\nRegarding the relatively higher ratio of SC-α cells in the S7D14 PKM1+ condition,\nre-analysis of our single-cell data suggests that during extended differentiation, a\nfraction of progenitor-like cells, including SC-ECs, may gradually adopt an α cell fate\n(Supplementary Figure 8B). This phenomenon has also been reported previously\n(Figure 4B from PMID: 37040771)18.\nesaeleR\nnilusnI\n)tnetnoc\nfo\n%(\nSorted β-cells\nmCherry\nPKM1\n✱✱\n✱✱\n1.5 fold change\n1.3 fold change\n(\n[Redacted]\nSupplementary Figure 8B) (Figure 4B, PMID: 37040771)18\nIn addition, our data raise the possibility that altered PEP metabolism and PKM1\nmight influence lineage allocation toward α cells (Figure 5A). The presence of α cells\nafter PKM1 overexpression might also contribute to the enhanced glucose-stimulated\ninsulin secretion observed in SC-islets (Figure 5D), which is reported previously (PMID:\n30720465)19. Consistent with this, sorted β cells with PKM1-overexpression primarily\nshowed reduced basal insulin secretion (Figure 5G). We have incorporated this\nexplanation into the revised Discussion section (page12):\n“Interestingly, SC-islets with PKM1-overexpression showed a higher proportion of\nSC- α cells. During extended differentiation, some progenitor-like populations,\nincluding SC-ECs, may progressively adopt an α cell fate (Supplementary Figure 8B)\n(44). Our data further suggest that altered PEP metabolism and PKM1 activity may\ninfluence α cell differentiation (Figure 5A) and function (9). Sorted β cells\noverexpressing PKM1 primarily showed reduced basal insulin secretion without a\nnotable increase in glucose-stimulated response. Therefore, enhanced insulin\nsecretion in whole SC-islets at high glucose may reflect indirect effects of PKM1 on\nother cell types, including α cells, where altered glucagon secretion could further\nmodulate β cell function (45). PKM1 appears to regulate insulin secretion in SC-islets n\not only through direct modulation of β cell glycolytic and metabolic fluxes, but also in\ndirectly via α cell– mediated mechanisms. Further investigation is needed to el\nucidate the specific role of PKM1 in α cell function.”\n[Redacted]\n(Figure 5A) (Figure 5D) (Figure 5G)\nReferences\n1. Foster, H.R., Ho, T., Potapenko, E., Sdao, S.M., Huang, S.M., Lewandowski, S.L., VanDeusen, H.R.,\nDavidson, S.M., Cardone, R.L., Prentki, M., et al. (2022). β-cell deletion of the PKm1 and PKm2 isoforms\nof pyruvate kinase in mice reveals their essential role as nutrient sensors for the KATP channel. eLife 11,\ne79422. https://doi.org/10.7554/eLife.79422.\n2. Hamasaki, N., Hardjono, I.S., and Minakami, S. (1978). 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Zhu, H., Wang, G., Nguyen-Ngoc, K.-V., Kim, D., Miller, M., Goss, G., Kovsky, J., Harrington, A.R.,\nSaunders, D.C., Hopkirk, A.L., et al. (2023). Understanding cell fate acquisition in stem-cell-derived\npancreatic islets using single-cell multiome-inferred regulomes. Developmental Cell 58, 727-743.e11.\nhttps://doi.org/10.1016/j.devcel.2023.03.011.\n19. Capozzi, M.E., Svendsen, B., Encisco, S.E., Lewandowski, S.L., Martin, M.D., Lin, H., Jaffe, J.L.,\nCoch, R.W., Haldeman, J.M., MacDonald, P.E., et al. (2019). β Cell tone is defined by proglucagon\npeptides through cAMP signaling. JCI Insight 4, 126742. https://doi.org/10.1172/jci.insight.126742."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I greatly appreciate that the authors performed the recommended experiments,\nespecially with Na-PEP that now separate the effects of K+ depolarization (in K-PEP)\nfrom the effects of PEP itself. The paper reveals many interesting differences between\nmature mouse and SCBCs. I have only a few minor comments.\nMinor\nLine 36, abstract: the “M” is missing in pyruvate kinase M1 (PKM1).\n\nThe conclusions describing Supplementary Figures 2G-I (lines 144-147) need to be\nmodified or removed, since methyl-pyruvate (MP) closes KATP channels directly\n(PMID: 12350226). Alternatively, the authors could redo the experiments with\npyruvate, assuming it enters SCBCs.\n\nLines 271-277 of the discussion: the authors speculate that there are 2 pools of PEP\ncontrolled by PKM1 and PKM2, which is an interesting model, but the wording of the\ndiscussion makes it sound like this was demonstrated instead of proposed.\nRefs 9-12 indicate that locally generated ATP is sufficient to close KATP, but they do not show\nthat there are 2 distinct pools of PK that are dependent on PKM1 and PKM2, or show\nthat local ATP is better at triggering KATP closure than global ATP (although that is\nprobably the case). To avoid confusion between what was demonstrated, either here\nor in the referenced papers, I recommend citing Refs 9-12 on line 270, and removing\nRef 12 from line 277. I also recommend changing “is less effective” to “may be\nless effective” on line 276, since this was not experimentally demonstrated.\nKind regards,\nMatthew J. Merrins\nYale University", "reviewer_2": "Most of this reviewer's concerns have been addressed."}, "author_response": "We thank the reviewer for pointing out this mistake. We have corrected “pyruvate\nkinase 1 (PK1)” to “pyruvate kinase M1 (PKM1)” in the Abstract at line 36 as suggested.\n\nWe thank the reviewer for this valuable comment. We have removed the conclusions\ndescribing Supplementary Figures 2G–I and retained only an objective description of\nthe results to avoid any confusion. The revised text (page 6) now reads:\n“Permeable methyl-pyruvate (MP) can induce diazoxide- and antimycin A-\ndependent calcium responses in SC-β cells (Supplementary Figures 2G–J),\nalbeit with lower sensitivity compared to mouse β cells (Supplementary Figure 2J).”\n\nWe thank the reviewer for this helpful suggestion. The revised text (page 10) now reads:\n“This can be explained by a difference between global versus local ATP pools\n(9–12). In SC-β cells lacking PKM1, residual PKM2 activity can metabolize the\nabnormally high basal PEP to generate localized ATP in microdomains near KATP\nchannels. This local ATP is sufficient to close KATP channels, elevate basal Ca²⁺ influx,\nand drive inappropriate basal exocytosis. By contrast, PKM1 efficiently consumes PEP,\npreventing its abnormal accumulation and thereby suppressing the local ATP\ngeneration for triggering insulin secretion at low glucose. While PKM1 also increases\npyruvate flux into mitochondria and elevates basal mitochondrial ATP, this global ATP\npool may be less effective at triggering secretion than PEP-driven local ATP at low\nglucose.”"}]

Decision letter