Abstract
Type 2 diabetes (T2D) is a global health issue characterized by abnormal blood glucose levels and is often associated with excessive hepatic gluconeogenesis. Increased circulating non-essential amino acids (NEAAs) are consistently observed in individuals with T2D; however, the specific contribution of each amino acid to T2D pathogenesis remains less understood. Here, we report an unexpected role of the NEAA proline in coordinating hepatic glucose metabolism by modulating paraspeckle, a nuclear structure scaffolded by the long non-coding RNA Neat1. Mechanistically, proline diminished paraspeckles in hepatocytes, liberating the retained mRNA species into cytoplasm for translation, including the mRNAs of Ppargc1a and Foxo1, contributing to enhanced gluconeogenesis and hyperglycaemia. We further demonstrated that the proline–paraspeckle–mRNA retention axis existed in diabetic liver samples, and intervening in this axis via paraspeckle restoration substantially alleviated hyperglycaemia in both female and male diabetic mouse models. Collectively, our results not only delineated a previously unappreciated proline-instigated, paraspeckle-dependent mRNA-retention mechanism regulating gluconeogenesis, but also spotlighted proline and paraspeckle as potential targets for managing hyperglycaemia.
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Data availability
The lncRNA–seq and RIP–seq data have been deposited in the NCBI’s Gene Expression Omnibus (GEO) under accession number GSE252452 (including GSE252451 and GSE252450). This paper does not report original code. Any additional information required to reanalyse the data reported in this paper is available from the lead contact on request. Source data are provided with this paper.
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Acknowledgements
This work was supported by grants from National Natural Science Foundation of China (32200960 to Y. Zhao, 32071289 to J.S., 91957105 to J.S.), Fundamental Research Funds for the Zhejiang Provincial Universities (226-2024-00206 to J.S., 226-2024-00134 to J.S.) and the Leading Innovation and Entrepreneur Team of Hangzhou (TD2020006 to J.S.). We thank Y. Mao at the Liangzhu Laboratory of Zhejiang University for assistance with RIP–seq data analysis. We thank S. Liu and G. Xiao at the Core Facilities of Zhejiang University School of Medicine for technical assistance in microscopy analyses.
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J.S., C.L., Z.X. and Y. Zhao conceptualized the project, designed the experiments and wrote the manuscript. Y. Zhao, X.C., Y. Zhu, R.D., J.H., L.X. and J.C. performed the experiments and analysed the data. Y. Zhao and J.P. conducted bioinformatics analysis. Y. Zhao and S.L. collected the diabetes-risk cohort data and did statistical analysis. All of the authors edited the manuscript and approved the final manuscript.
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Nature Metabolism thanks Shaodong Guo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Revati Dewal, in collaboration with the Nature Metabolism team.
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Extended data
Extended Data Fig. 1 NEAA inhibits Neat1 expression in hepatocytes.
a, Differential lncRNAs expression analysis in NEAA-treated (NEAA) vs. control (Ctrl) hepatocytes. b, Expression levels of the top ten significantly altered lncRNAs in NEAA-treated hepatocytes, as determined by BioGPS analysis (www.biogs.org). c, Schematic diagram illustrating the two splice variants of Neat1, with the positions of primers used for qPCR or probes for FISH indicated. d, Neat1_1/2 and Neat1_2 levels in NEAA-treated hepatocytes relative to controls, n = 4 independent experiments. e, Representative fluorescence images of cells stained for Neat1 (green) RNA in control and NEAA-treated hepatocytes. Nuclei are stained with DAPI (blue). f, Quantification Neat1 dots in hepatocytes, n = 40 cells per group. Box plots are as described in Fig. 1. g, The dose-dependent effect of proline on Neat1 level in hepatocytes from male and female mice, n = 3 independent experiments. h, Nono mRNA levels in control siRNA (siScr) and Nono knockdown (siNono) hepatocytes, n = 3 independent experiments. i, Control or Nono knockdown hepatocytes were treated with or without proline for 24 h and then exposed to actinomycin D (ActD) at indicated time points to assess the half-lives of Neat1, n = 3 independent experiments. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (a), (b), (d), (f) and (h); one-way ANOVA in (g); two-way ANOVA in (i).
Extended Data Fig. 2 NEAA and proline do not alter the total mRNA levels of Ppargc1a and Foxo1.
a, Total Ppargc1a and Foxo1 mRNA levels in hepatocytes treated with NEAA or proline, n = 4 independent experiments. b, Total Ppargc1a and Foxo1 mRNA levels in hepatocytes treated with different concentrations of proline, n = 3 independent experiments. c, U1 and Gapdh mRNA levels in nuclear and cytoplasmic fractions, n = 4 independent experiments. d, Representative immunoblots for Lamin B1 and GAPDH protein levels. e, Nuclear-to-cytoplasmic ratio of Ppargc1a and Foxo1 in hepatocytes treated with different concentration of proline, n = 3 independent experiments. f,g, Neat1, Ppargc1a, and Foxo1 mRNA levels in hepatocytes, n = 4 independent experiments. Data are presented as means ± SD. Statistical significance was determined using one-way ANOVA in (a), (b), and (e); two-tailed Student’s t test in (c), (f), and (g).
Extended Data Fig. 3 PMO-mediated increase Neat1_2 level enhances paraspeckle formation and inhibits gluconeogenesis.
a, Schematic diagram illustrating the binding site of PMO within the Neat1 RNA transcript. b,c, Neat1_2 level (b) and ratio of Neat1_2/Neat1 (c) in hepatocytes transfected with PMO control sequence (Ctrl) and PMO Neat1 target sequence (PMO), n = 3 independent experiments. d, Representative fluorescence images of cells stained for total Neat1 (green, upper panel) and Neat1_2 (green, lower panel) in hepatocytes. e, Quantification of Neat1 and Neat1_2 foci in hepatocytes, n = 40 cells per group. Box plots are as described in Fig. 1. f, Representative images showing cellular distribution of Neat1_2 (green) and NONO (red) in hepatocytes. Nuclei are stained with DAPI (blue). The white boxes show enlarged areas for detailed observation. The graph plots the fluorescence intensity of each probe or protein (y-axis) vs. distance (x-axis) for the corresponding white line. g, Quantification of paraspeckle numbers in hepatocytes, n = 40 cells per group. Box plots are as described in Fig. 1. h,i, Total Ppargc1a and Foxo1 mRNA levels (h) and Nuclear-to-cytoplasmic ratio of Ppargc1a and Foxo1 (i) in hepatocytes, n = 3 independent experiments. j, Promoter activities of G6pc and Pck1 in hepatocytes, n = 3 independent experiments. k, G6pc and Pck1 mRNA levels in hepatocytes, n = 3 independent experiments. l, Glucose production in hepatocytes, n = 3 independent experiments. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (b), (c), (e), (g), (h), (i), (j), (k), and (l).
Extended Data Fig. 4 Knockdown of Ppargc1a alleviates proline-induced gluconeogenesis.
a, Ppargc1a mRNA and protein level in control siRNA (siScr) and Ppargc1a knockdown (siPpargc1a) hepatocytes, n = 3 independent experiments. b, Representative immunoblots for PGC1α protein levels. α-Tubulin as a loading control. c,f, G6pc and Pck1 mRNA levels in hepatocytes, n = 4 independent experiments. d,e,g, Glucose production in hepatocytes, n = 3 independent experiments in (d) and (e); n= 4 independent experiments in (g). Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (a); two-way ANOVA in (c), (d), (f), and (g); one-way ANOVA in (e).
Extended Data Fig. 5 Silencing of Neat1 promotes gluconeogenesis through the paraspeckle mRNA retention axis in vivo.
a, Schematic diagram illustrating the target site for knockdown of Neat1 (shNeat1#1/sh#1 and shNeat1#2/sh#2), n = 5 mice per group. b, Neat1 level in control mice (shScr) and Neat1 knockdown mice, n = 5 mice per group. c, Water intake and food consumption, n = 5 mice per group. d, Body weight, n = 5 mice per group. e, Liver weight, n = 5 mice per group. f, Representative image of hematoxylin and eosin (H&E) staining of liver sections. g, Serum AST and ALT level, n = 5 mice per group. h, mRNA levels of Neat1, U1 and Gapdh in nuclear and cytoplasmic fractions, n = 5 mice per group. i, Representative immunoblots for Lamin B1 and GAPDH protein levels. j, Gpt and Gpt2 mRNA levels, n = 5 mice per group. k,l, G6PC and PCK1 protein levels (k) or enzymatic activity (l), n = 5 mice per group. m, Urine glucose levels, n = 5 mice per group. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (b), (c), (d), (e), (g), (h), (j), (k), (l), and (m).
Extended Data Fig. 6 Neat1 overexpression suppresses gluconeogenesis through the paraspeckle mRNA retention axis in vivo.
a,b,c,d, Water intake and food consumption (a), body weight (b), liver weight (c), and representative image of hematoxylin and eosin (H&E) staining of liver sections (d), caScr, n = 7 mice; caNeat1, n = 7 mice; caScr+Pro, n = 7 mice; caNeat1+Pro, n = 6 mice. e, Neat1 RNA level, n = 4 mice. f, Representative images showing cellular localization of Neat1 (green) in liver. Nuclei are stained with DAPI (blue). g, Quantification of fluorescence intensity of Neat1 in (f), n = 4 mice. h,i, G6PC and PCK1 protein levels (h) or enzymatic activity (i), n = 4 mice. Data are presented as means ± SD. Statistical significance was determined using a two-way ANOVA in (a), (b), (c), (e), (g), (h), and (i).
Extended Data Fig. 7 Paraspeckle ameliorates hyperglycaemia by modulating hepatic gluconeogenesis in diabetic mice.
a, Neat1 level in the liver from WT or ob/ob mice, n = 6 mice. b, Representative images showing cellular localization of Neat1 (green) in the liver from WT or ob/ob mice. Nuclei are stained with DAPI (blue). c, Quantitation of fluorescence intensity of Neat1, n = 4 mice. d, mRNA levels of Sfpq, Nono, and Pspc1 in liver from WT or ob/ob mice, n = 6 mice. e, Representative immunoblots for SFPQ, NONO, and PSPC1 protein levels in liver from WT or ob/ob mice. α-Tubulin as a loading control. f, Total Ppargc1a and Foxo1 mRNA levels in liver from WT or ob/ob mice, n = 6 mice. g, Nuclear and cytoplasmic Ppargc1a and Foxo1 mRNA levels, n = 4 mice. h, Representative immunoblots for PGC1α and FOXO1 protein levels. α-Tubulin as a loading control. i, G6pc and Pck1 mRNA levels in WT and ob/ob mice, n = 4 mice. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (a), (c), (d), (f), (g), and (i).
Extended Data Fig. 8 Neat1 overexpression ameliorates hyperglycaemia in obesity mice.
a, Water intake and food consumption of ob/ob (n = 5 per group) or db/db (n = 7 per group) mice, with and without Neat1 activation. b-, Body weight, n = 5 ob/ob mice per group; n = 7 db/db mice per group. c, Liver weight, n = 5 ob/ob mice per group; n = 7 db/db mice per group. d, Representative image of hematoxylin and eosin (H&E) staining of liver sections. e, Serum AST and ALT levels, n = 5 ob/ob mice per group; n = 7 db/db mice per group. f, Hemoglobin A1c (HbA1c) levels in whole blood, n = 5 ob/ob mice per group; n = 7 db/db mice per group. g,h, Ppargc1a, Foxo1 (g) Gpt and Gpt2 mRNA levels (h) in liver, n = 5 ob/ob mice per group; n = 7 db/db mice per group. i,j, G6PC and PCK1 protein levels (i) or enzymatic activity (j), n = 5 ob/ob mice per group; n = 7 db/db mice per group. k, Urine glucose levels, n = 7 mice per group. l, Random blood glucose levels, n = 7 mice per group. m, Insulin tolerance tests (ITT) after fasting and statistical analysis of AOC (Area of the curve; subtracting the baseline) for the ITT, n = 5 mice per group. n, Glucose tolerance tests (GTT) after fasting and statistical analysis of AOC for the GTT, n = 7 mice per group. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (a), (b), (c), (e), (f), (g), (h), (i), (j), (k), (l), (m), and (n).
Extended Data Fig. 9 Liver gluconeogenic metabolite tracing and gene expression profiles.
a, Isotopologue abundances of liver TCA cycle and gluconeogenesis-related metabolites in liver from ob/ob mice, n = 4 mice. b, mRNA levels of genes associated with inflammation and lipid metabolism in liver from ob/ob or db/db mice, with and without Neat1 activation, ob/ob, n = 5 mice; db/db, n = 7 mice. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (a) and (b).
Extended Data Fig. 10 Paraspeckle ameliorates hyperglycaemia by modulating hepatic gluconeogenesis in female ob/ob mice.
a, Schematic illustration of the experimental design to evaluate the effect of Neat1 overexpression in ob/ob female mice, n=5 per group. b, Water intake and food consumption, n = 5 mice per group. c, Body weight, n = 5 mice per group. d, Liver weight, n = 5 mice per group. e, Representative image of hematoxylin and eosin (H&E) staining of liver sections. f, Serum AST and ALT level, n = 5 mice per group. g, HbA1c levels in whole blood, n = 5 mice per group. h, Neat1 RNA level in liver, n = 5 mice per group. i, Representative images showing cellular localization of Neat1 (green) in liver. DAPI staining (blue) marks the nucleus. Quantitation of fluorescence intensity of Neat1 (right panel). j,k, Total Ppargc1a and Foxo1 mRNA levels (j), Nuclear-to-cytoplasmic ratio of Ppargc1a and Foxo1 (k) in liver, n = 5 mice per group. l, Representative immunoblots for PGC1α and FOXO1 protein levels. α-Tubulin as a loading control. m,n, G6pc, Pck1 (m), Gpt, and Gpt2 (n) mRNA levels, n = 5 mice per group. o,p, G6PC and PCK1 protein levels (o) or enzymatic activity (p) in liver, n = 5 mice per group. q, PTT after fasting and statistical analysis of AUC for the PTT, n = 5 mice per group. r, Fasting blood glucose levels, n = 5 mice per group. s, Urine glucose levels, n = 5 mice per group. Data are presented as means ± SD. Statistical significance was determined using a two-tailed Student’s t test in (b), (c), (d), (f), (g), (h), (i), (j), (k), (m), (n), (o), (p), (q), (r), and (s).
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Zhao, Y., Chai, X., Peng, J. et al. Proline exacerbates hepatic gluconeogenesis via paraspeckle-dependent mRNA retention. Nat Metab 7, 367–382 (2025). https://doi.org/10.1038/s42255-024-01206-5
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DOI: https://doi.org/10.1038/s42255-024-01206-5
