科技科学

Glucose-responsive probiotics for glycaemic modulation in mice and monkeys

Nature作者：Ningzi Guan2026年8月12日正文已收录本站

Data availability

All data supporting this study are provided in the main text and Supplementary Information. The 16S rRNA gene sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive under BioProject accession number PRJNA1023002. Source data are provided with this paper.

References

  1. Bashor, C. J., Hilton, I. B., Bandukwala, H., Smith, D. M. & Veiseh, O. Engineering the next generation of cell-based therapeutics. Nat. Rev. Drug Discov. 21, 655–675 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Zhou, Y. et al. A small and highly sensitive red/far-red optogenetic switch for applications in mammals. Nat. Biotechnol. 40, 262–272 (2022).

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Xie, M. et al. β-cell-mimetic designer cells provide closed-loop glycemic control. Science 354, 1296–1301 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Roden, M. & Shulman, G. I. The integrative biology of type 2 diabetes. Nature 576, 51–60 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Atkinson, M. A., Eisenbarth, G. S. & Michels, A. W. Type 1 diabetes. Lancet 383, 69–82 (2014).

    Article  PubMed  Google Scholar 

  6. Chatterjee, S., Khunti, K. & Davies, M. J. Type 2 diabetes. Lancet 389, 2239–2251 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Chaudhury, A. et al. Clinical review of antidiabetic drugs: implications for type 2 diabetes mellitus management. Front. Endocrinol. 8, 6 (2017).

    Article  Google Scholar 

  8. Rosenstock, J. et al. Efficacy and safety of a novel dual GIP and GLP-1 receptor agonist tirzepatide in patients with type 2 diabetes (SURPASS-1): a double-blind, randomised, phase 3 trial. Lancet 398, 143–155 (2021).

    Article  CAS  PubMed  Google Scholar 

  9. Parks, M. & Rosebraugh, C. Weighing risks and benefits of liraglutide–the FDA’s review of a new antidiabetic therapy. N. Engl. J. Med. 362, 774–777 (2010).

    Article  CAS  PubMed  Google Scholar 

  10. Zheng, S. L. et al. Association between use of sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 agonists, and dipeptidyl peptidase 4 inhibitors with all-cause mortality in patients with type 2 diabetes: a systematic review and meta-analysis. JAMA 319, 1580–1591 (2018).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Singh, S. et al. Glucagonlike peptide 1-based therapies and risk of hospitalization for acute pancreatitis in type 2 diabetes mellitus: a population-based matched case-control study. JAMA Intern. Med. 173, 534–539 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. Pagliuca, F. W. et al. Generation of functional human pancreatic β cells in vitro. Cell 159, 428–439 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cubillos-Ruiz, A. et al. Engineering living therapeutics with synthetic biology. Nat. Rev. Drug Discov. 20, 941–960 (2021).

    Article  CAS  PubMed  Google Scholar 

  14. Riglar, D. T. et al. Engineered bacteria can function in the mammalian gut long-term as live diagnostics of inflammation. Nat. Biotechnol. 35, 653–658 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  15. Courbet, A., Endy, D., Renard, E., Molina, F. & Bonnet, J. Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates. Sci. Transl. Med. 7, 289ra283 (2015).

    Article  Google Scholar 

  16. Isabella, V. M. et al. Development of a synthetic live bacterial therapeutic for the human metabolic disease phenylketonuria. Nat. Biotechnol. 36, 857–864 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  17. Gao, X. et al. Designer probiotic-based living drugs for uric acid homeostasis control in hyperuricemic mice and rats. Cell Rep. Med. 6, 102379 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Aggarwal, N. et al. Engineered commensals for metabolic modulation of the gut–liver–brain axis. Cell https://doi.org/10.1016/j.cell.2026.03.048 (2026).

    Article  PubMed  Google Scholar 

  19. Pedrolli, D. B., Ribeiro, N. V., Squizato, P. N., de Jesus, V. N. & Cozetto, D. A. Engineering microbial living therapeutics: the synthetic biology toolbox. Trends Biotechnol. 37, 100–115 (2019).

    Article  CAS  PubMed  Google Scholar 

  20. Kim, J., Jeon, C. O. & Park, W. Dual regulation of zwf-1 by both 2-keto-3-deoxy-6-phosphogluconate and oxidative stress in Pseudomonas putida. Microbiology 154, 3905–3916 (2008).

    Article  CAS  PubMed  Google Scholar 

  21. Daddaoua, A., Krell, T. & Ramos, J. L. Regulation of glucose metabolism in Pseudomonas: the phosphorylative branch and entner-doudoroff enzymes are regulated by a repressor containing a sugar isomerase domain. J. Biol. Chem. 284, 21360–21368 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Meyer, M. M. The role of mRNA structure in bacterial translational regulation. WIREs RNA https://doi.org/10.1002/wrna.1370 (2017).

    Article  PubMed  Google Scholar 

  23. Pippitt, K., Li, M. & Gurgle, H. E. Diabetes mellitus: screening and diagnosis. Am. Fam. Physician 93, 103–109 (2016).

    PubMed  Google Scholar 

  24. De la Paz, E. et al. A self-powered ingestible wireless biosensing system for real-time in situ monitoring of gastrointestinal tract metabolites. Nat. Commun. 13, 7405 (2022).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  25. Ye, H., Daoud-El Baba, M., Peng, R.-W. & Fussenegger, M. A synthetic optogenetic transcription device enhances blood-glucose homeostasis in mice. Science 332, 1565–1568 (2011).

    Article  ADS  CAS  PubMed  Google Scholar 

  26. Yoon, S. H., Kim, S. K. & Kim, J. F. Secretory production of recombinant proteins in Escherichia coli. Recent Pat. Biotechnol. 4, 23–29 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Donnelly, D. The structure and function of the glucagon-like peptide-1 receptor and its ligands. Br. J. Pharmacol. 166, 27–41 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhang, T., Perkins, M. H., Chang, H., Han, W. & de Araujo, I. E. An inter-organ neural circuit for appetite suppression. Cell 185, 2478–2494.e2428 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Jastreboff, A. M. et al. Tirzepatide once weekly for the treatment of obesity. N. Engl. J. Med. 387, 205–216 (2022).

    Article  CAS  PubMed  Google Scholar 

  30. Ludwig, M. Q. et al. A genetic map of the mouse dorsal vagal complex and its role in obesity. Nat. Metab. 3, 530–545 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Tanase, D. M. et al. The intricate relationship between type 2 diabetes mellitus (T2DM), insulin resistance (IR), and nonalcoholic fatty liver disease (NAFLD). J. Diabetes Res. 2020, 3920196 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Maconi, G. et al. Glucose intolerance and diabetes mellitus in ulcerative colitis: pathogenetic and therapeutic implications. World J. Gastroenterol. 20, 3507–3515 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Xu, J. et al. Faecalibacterium prausnitzii-derived microbial anti-inflammatory molecule regulates intestinal integrity in diabetes mellitus mice via modulating tight junction protein expression. J. Diabetes 12, 224–236 (2020).

    Article  CAS  PubMed  Google Scholar 

  34. Duan, Y. et al. Bacteriophage targeting of gut bacterium attenuates alcoholic liver disease. Nature 575, 505–511 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  35. Just, S. et al. The gut microbiota drives the impact of bile acids and fat source in diet on mouse metabolism. Microbiome 6, 134 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Bisanz, J. E., Upadhyay, V., Turnbaugh, J. A., Ly, K. & Turnbaugh, P. J. Meta-analysis reveals reproducible gut microbiome alterations in response to a high-fat diet. Cell Host Microbe 26, 265–272.e264 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Shi, J. et al. Probiotic Escherichia coli Nissle 1917-derived outer membrane vesicles modulate the intestinal microbiome and host gut-liver metabolome in obese and diabetic mice. Front. Microbiol. 14, 1219763 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Kosiborod, M. N. et al. Semaglutide in patients with obesity-related heart failure and type 2 diabetes. N. Engl. J. Med. 390, 1394–1407 (2024).

    Article  CAS  PubMed  Google Scholar 

  39. Fineman, M. S., Cirincione, B. B., Maggs, D. & Diamant, M. GLP-1 based therapies: differential effects on fasting and postprandial glucose. Diabetes Obes. Metab. 14, 675–688 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Wang, L. et al. Engineered bacteria of MG1363–pMG36e–GLP-1 attenuated obesity-induced by high fat diet in mice. Front. Cell. Infect. Microbiol. 11, 595575 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Agarwal, P., Khatri, P., Billack, B., Low, W. K. & Shao, J. Oral delivery of glucagon like peptide-1 by a recombinant Lactococcus lactis. Pharm. Res. 31, 3404–3414 (2014).

    Article  CAS  PubMed  Google Scholar 

  42. Snoeck, S., Guidi, C. & De Mey, M. “Metabolic burden” explained: stress symptoms and its related responses induced by (over)expression of (heterologous) proteins in Escherichia coli. Microb. Cell Fact. 23, 96 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kim, J. A. & Yoo, H. J. Exploring the side effects of GLP-1 receptor agonist: to ensure its optimal positioning. Diabetes Metab. J. 49, 525–541 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Holst, J. J., Andersen, D. B. & Grunddal, K. V. Actions of glucagon-like peptide-1 receptor ligands in the gut. Br. J. Pharmacol. 179, 727–742 (2022).

    Article  CAS  PubMed  Google Scholar 

  45. Beutler, L. R. GLP-1 physiology and pharmacology along the gut–brain axis. JCI https://doi.org/10.1172/jci194744 (2026).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Chua, K. J., Kwok, W. C., Aggarwal, N., Sun, T. & Chang, M. W. Designer probiotics for the prevention and treatment of human diseases. Curr. Opin. Chem. Biol. 40, 8–16 (2017).

    Article  CAS  PubMed  Google Scholar 

  47. Zheng, D. W. et al. Prebiotics-encapsulated probiotic spores regulate gut microbiota and suppress colon cancer. Adv. Mater. 32, e2004529 (2020).

    Article  PubMed  Google Scholar 

  48. Sorbara, M. T. & Pamer, E. G. Microbiome-based therapeutics. Nat. Rev. Microbiol. 20, 365–380 (2022).

    Article  CAS  PubMed  Google Scholar 

  49. Miyazaki, K. et al. The usefulness of HbA1c measurement in diabetic mouse models using various devices. Exp. Anim. 74, 319–327 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Nougayrède, J. P. et al. Escherichia coli induces DNA double-strand breaks in eukaryotic cells. Science 313, 848–851 (2006).

    Article  ADS  PubMed  Google Scholar 

  51. Serena, C. et al. Elevated circulating levels of succinate in human obesity are linked to specific gut microbiota. ISME J. 12, 1642–1657 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bourgonje, A. R., Connelly, M. A., van Goor, H., van Dijk, P. R. & Dullaart, R. P. F. Plasma citrate levels are associated with an increased risk of cardiovascular mortality in patients with type 2 diabetes (Zodiac-64). J. Clin. Med. https://doi.org/10.3390/jcm12206670 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Landon, J., Fawcett, J. K. & Wynn, V. Blood pyruvate concentration measured by a specific method in control subjects. J. Clin. Pathol. 15, 579–584 (1962).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Belenguer, A. et al. Impact of pH on lactate formation and utilization by human fecal microbial communities. Appl. Environ. Microbiol. 73, 6526–6533 (2007).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  55. Robergs, R. A. & Griffin, S. E. Glycerol. Biochemistry, pharmacokinetics and clinical and practical applications. Sports Med. 26, 145–167 (1998).

    Article  CAS  PubMed  Google Scholar 

  56. Nelson, J. L., Harmon, M. E. & Robergs, R. A. Identifying plasma glycerol concentration associated with urinary glycerol excretion in trained humans. J. Anal. Toxicol. 35, 617–623 (2011).

    Article  CAS  PubMed  Google Scholar 

  57. Merino, B., Fernández-Díaz, C. M., Cózar-Castellano, I. & Perdomo, G. Intestinal fructose and glucose metabolism in health and disease. Nutrients https://doi.org/10.3390/nu12010094 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Berry, G. T. Classic galactosemia and clinical variant galactosemia. GeneReviews https://www.ncbi.nlm.nih.gov/books/NBK1518/ (2021).

  59. Yang, J. et al. An oral “super probiotics” with versatile self-assembly adventitia for enhanced intestinal colonization by autonomous regulating the pathological microenvironment. Chem. Eng. J. 446, 137204 (2022).

    Article  CAS  Google Scholar 

  60. Long, F. et al. A low-carbohydrate diet induces hepatic insulin resistance and metabolic associated fatty liver disease in mice. Mol. Metab. 69, 101675 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Gilbert, E. R., Fu, Z. & Liu, D. Development of a nongenetic mouse model of type 2 diabetes. Exp. Diabetes Res. 2011, 416254 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Mu, Y. et al. Efficacy and safety of once weekly semaglutide 2.4 mg for weight management in a predominantly east Asian population with overweight or obesity (STEP 7): a double-blind, multicentre, randomised controlled trial. Lancet Diabetes Endocrinol. 12, 184–195 (2024).

    Article  CAS  PubMed  Google Scholar 

  63. Garcia, J., Kimeldorf, D. J. & Koelling, R. A. Conditioned aversion to saccharin resulting from exposure to gamma radiation. Science 122, 157–158 (1955).

    Article  ADS  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank all the laboratory members for their cooperation in this study, especially N. Jian, Z. Wang, and L. Qiao for help with mouse experiments. We thank Y. Liu and X. Zhang for help with the monkey experiments; the ECNU Multifunctional Platform for Innovation (011) for supporting the mice experiments; the ECNU Multifunctional Platform for Innovation (004) for assistance with TEM analysis; and the Instruments Sharing Platform of the School of Life Sciences, ECNU.

Funding

H.Y. discloses support for the research of this work from the National Natural Science Foundation of China (32430064, 32521009 and 32261160373), the Science and Technology Commission of Shanghai Municipality (23HC1410100 and 25HC2830300), and the Fundamental Research Funds for the Central Universities. H.Y. is a SANS Exploration Scholar. N.G. discloses support for the research of this work from the National Key R&D Program of China (2025YFC3408700 and 2025YFA0923300), the National Natural Science Foundation of China (32571656), and the Science and Technology Commission of Shanghai Municipality (25J22800100 and 25ZR1402121). D.K. discloses support for the research of this work from the China Postdoctoral Science Foundation (2025M772641 and BX20250150) and the Science and Technology Commission of Shanghai Municipality (24YF2735700). Y.Z. discloses support for the research of this work from the Young Scientists Fund of the National Natural Science Foundation of China (32300458), the Science and Technology Commission of Shanghai Municipality (23YF1410700) and the Natural Science Foundation of Chongqing (CSTB2023NSCQ-MSX0126).

Author information

Author notes

  1. These authors contributed equally: Ningzi Guan, Deqiang Kong, Xianyun Gao

Authors and Affiliations

  1. Shanghai Key Laboratory of Regulatory Biology, Biomedical Synthetic Biology Research Center, Institute of Biomedical Sciences and School of Life Sciences, Shanghai Academy of Natural Sciences (SANS), East China Normal University, Shanghai, China

    Ningzi Guan  (管宁子), Deqiang Kong  (孔德强), Xianyun Gao  (高纤云), Lingxue Niu  (牛灵雪), Yang Zhou  (周阳), Guiling Yu  (余贵玲), Tian Gao  (高天), Mengyao Liu  (刘梦瑶), Wenbo Ma  (马文博), Yiyu Jin  (金昳雨), Jianli Yin  (尹剑丽) & Haifeng Ye  (叶海峰)

  2. Shanghai Fengxian District Central Hospital, Shanghai, China

    Deqiang Kong  (孔德强)

  3. Shanghai SynBioEra Biotechnology, Shanghai, China

    Deqiang Kong  (孔德强) & Haifeng Ye  (叶海峰)

  4. Sam and Ann Barshop Institute for Longevity and Aging Studies, Division of Endocrinology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA

    Shangang Zhao  (赵善刚)

Authors

  1. Ningzi Guan  (管宁子)
  2. Deqiang Kong  (孔德强)
  3. Xianyun Gao  (高纤云)
  4. Lingxue Niu  (牛灵雪)
  5. Yang Zhou  (周阳)
  6. Guiling Yu  (余贵玲)
  7. Tian Gao  (高天)
  8. Mengyao Liu  (刘梦瑶)
  9. Wenbo Ma  (马文博)
  10. Yiyu Jin  (金昳雨)
  11. Jianli Yin  (尹剑丽)
  12. Shangang Zhao  (赵善刚)
  13. Haifeng Ye  (叶海峰)

Contributions

H.Y. and N.G. conceived the project and designed the experiments. N.G., X.G., M.L., W.M. and Y.J. constructed, optimized and characterized the glucose sensor and performed in vitro validation at the cellular level. D.K. and X.G. performed the kinetic characterization of GIFT in mouse models. N.G., D.K. and X.G. conducted the therapeutic studies in mice and prepared samples for non-human primate experiments. L.N. performed the engineering and efficacy validation of the encapsulation. Y.Z., G.Y., T.G. and J.Y. carried out post-treatment sampling and performed various assays on mouse samples. H.Y., N.G., D.K. and Y.Z. contributed to funding acquisition. H.Y., N.G., D.K., X.G. and S.Z. analysed the results and wrote the manuscript. All authors edited and approved the manuscript.

Corresponding author

Correspondence to Haifeng Ye  (叶海峰).

Ethics declarations

Competing interests

H.Y., N.G. and X.G. are inventors on patent applications submitted by East China Normal University that cover the new glucose sensor, including a Chinese patent application (202210326236.9) and a Patent Cooperation Treaty application (PCT/CN2023/081232), which has entered the national phase in the USA (application no. 18/852,503) and Europe (application no. 23777819.6). The other authors declare no competing interests.

Peer review

Peer review information

Nature thanks Andreas Birkenfeld, Tal Danino, Aleksandar Kostic and the other, anonymous, reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Optimization and characterization of the glucose sensor.

a, Optimization of the constitutive HexR expression level. HexR was controlled by different constitutive promoters with increasing expression strength, including PJ23100, PLac, and PTac. The resulting transrepressor expression vectors were co-transformed with pGN11 (PHexR1-sfGFP) into EcN-competent cells and cultivated for 12 h before the fluorescence intensity of cell culture was quantified. EcN transfected with only pGN11 (-) was used as a control. b, Optimization of the glucose-responsive promoter. The number of tandem operator repeats within PHexR was increased from one (PHexR1) to five (PHexR5). c, Screening of various ribosome binding sites (RBSs) for HexR expression. d, e, Transcriptional profile of genes involved in glucose metabolism in GIFT cells in response to glucose. d, The relative ratios of genes in the Embden-Meyerhof-Parnas (EMP) pathway, Entner-Doudoroff (ED) pathway, and tricarboxylic acid (TCA) cycle are shown for glucose-responsive expression (GIFT with glucose versus GIFT without glucose). e, Differentially expressed genes >2-fold induction (in red) or 2-fold repression (in green) are defined as significant. f, sfGFP expression from the glucose sensor in response to different carbon sources. GIFTGFP cells were cultured with PBS, succinate (45 μM), citrate (0.2 mM), pyruvate (0.1 mM), lactate (3 mM), glycerol (0.15 mM), fructose (0.1 mM), galactose (0.1 mM), or glucose (20 mM) for 12 h. g, Reporter expression from the GIFT cells. sfGFP, RFP, Luciferase, and LacZ were expressed by GIFT induced by 0 to 20 mM glucose for 12 h. Fluorescence images or images of the cell culture were captured using a ChemiScope 4300 Pro imaging equipment after adding D-luciferin (for Luciferase) or X-gal (for LacZ). h, i, Glucose-induced sfGFP expression from the glucose sensor in cells cultured in simulated human intestinal fluid (SIF) under aerobic (h) or microaerobic (i) conditions. Data in a-c, e, f, h, and i are expressed as means ± s.d.; n = 3 independent experiments. Panel g shows representative images from three independent experiments. P-values in f were calculated using one-way ANOVA followed by Dunnett’s multiple comparisons test. ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

Source data

Extended Data Fig. 2 The distribution and colonization of GIFT in mice after oral delivery.

a, b, Bacterial biodistribution in the intestinal tract (a) and major organs (b) of mice. C57BL/6 mice were orally administered with GIFTGFP (109 CFU/mouse/day) continuously for 1, 3, 7, and 15 days, and the intestinal tract and major organs, including heart, liver, spleen, lung, and kidney were collected 24 h after the final administration. The homogenates were plated on an LB solid medium and cultured at 37 °C for 12 h before colony counting. Sample measures in the dash area denote mice where the bacteria were not detectable at a limit of detection of Log10 of 2. c, Colonization of GIFTGFP in mice orally administered with GIFTGFP (109 CFU/mouse/day) continuously for 1, 3, 7, and 15 days. The feces of mice were collected every day for five days after the final administration. The homogenates were plated on an LB solid medium and cultured at 37 °C for 12 h before colony counting. Data are expressed as means ± s.e.m.; n = 5 mice.

Source data

Extended Data Fig. 3 Characterization of GIFT intestinal colonization coated with tannic acid (TA) and poloxamer 188 (F68).

a, Schematic representation of the preparation process for coated GIFT (GIFT@TAF68). GIFTGFP cells were sequentially treated with TA and F68 for 5 min, followed by an additional 25 min of F68 treatment with continuous stirring throughout the encapsulation process. b, Scanning electron microscope (SEM) images of uncoated GIFTGFP and GIFTGFP@TAF68. Scale bar, 1 μm. c, Confocal scanning laser microscopy (CSLM) images of GIFTGFP and GIFTGFP@TAF68. The red channel represents rhodamine B-labeled TA, while the green channel shows sfGFP expressed by GIFTGFP. Scale bar, 10 μm. d, Growth curves of GIFTGFP and GIFTGFP@TAF68 cultured in LB broth at 37 °C. OD600 was recorded using a microplate reader. e, Cell viability of GIFTGFP and GIFTGFP@TAF68. f, Quantification of sfGFP expression by GIFTGFP and GIFTGFP@TAF68 after 12 h of culture with 10 mM glucose. g, Measurement of GLP-1 secretion by GIFTGLP-1 and GIFT GLP-1@TAF68 after 12 h of culture with 15 mM glucose. h-k, Bacterial colony counts in the gastrointestinal tract of mice. C57BL/6 mice were orally administered 109 CFU of either GIFTGFP or GIFTGFP@TAF68 cells. Tissue samples from the stomach, small intestine, colon, and cecum were harvested at 4 (h), 12 (i), 24 (j), and 36 h (k) post-administration, samples were homogenized and plated on LB agar. After 12 h of incubation at 37 °C, bacterial colonies were counted. l, Bioluminescence images of mice. EcN constitutively expressing LuxCDABE (EcN-Lux) (109 CFU) were orally administered to C57BL/6 mice, and imaging was performed at 4, 6, 8, 12, 24, and 36 h using an in vivo imaging system. m, Quantification of bioluminescence signals from l. Panels b, c show representative images from three independent experiments. Data in d-g are expressed as means ± s.d.; n = 3 independent experiments. Data in h-k and m are expressed as means ± s.e.m.; n = 4 mice for h-k, n = 5 mice for m. P-values were calculated by two-way ANOVA followed by Sidak’s multiple comparisons test (d-f), or two-tailed unpaired t-test (g-k, m). NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

Source data

Extended Data Fig. 4 Assessment of the safety of GIFT after oral delivery to mice.

a, Body weight of mice after gavage with 109 CFU of GIFTGFP for 3, 7, and 15 days. b, c, Cytokine abundance for TNF-α (b) and IL-6 (c) from the serum of treated mice. C57BL/6 mice were orally administered with GIFTGFP (109 CFU/mouse/day) continuously for 1, 3, 7, and 15 days. Blood was collected at the indicated time points post-oral administration, and the cytokine abundance was quantified using ELISA kits. d-k, 24 h after the final administration, the blood of mice was collected for complete blood count and blood biochemical analysis. (d) Counts for total red blood cells (RBC), (e) white blood cells (WBC), and (f) hemoglobin (HGB). g, h, kidney function analysis, (g) blood urea nitrogen (BUN), (h) creatinine (CRE). i-k, Hepatic function analysis. (i) alanine aminotransferase (ALT), (j) aspartate aminotransferase (AST), (k) albumin/globulin ratio (A/G). Data are expressed as means ± s.e.m.; n = 6 mice for a-c, n = 5 mice for d-k. P-values in b-k were calculated by one-way ANOVA followed by Tukey’s multiple comparisons test. NS, not significant. Detailed statistics are provided in Supplementary Table 16.

Source data

Extended Data Fig. 5 Characterization of GIFTGLP-1 in vitro and in vivo.

a, Measurement of intestinal glucose concentrations in wild-type and db/db mice. Following a 4-hour fasting period, the blood glucose levels of the mice were measured. The mice were then euthanized, and their intestines were harvested; the mucosal lining of the intestines was collected. Glucose content was measured using a commercial glucose assay kit. b, Time-dependent glucose-inducible GLP-1 expression of GIFTGLP-1. GIFTGLP-1 was induced with 15 mM glucose for different time periods as indicated, and the GLP-1 secreted to the supernatant of culture was analyzed by ELISA kit. c, Schematic representation of biological activity detection of GLP-1 produced by GIFTGLP-1. The GLP-1 produced by GIFTGLP-1 induces a conformational change of the GLP-1 receptor, leading to signaling through the cyclic adenosine monophosphate (cAMP) secondary messenger and, thus, PCRE-driven SEAP production. d, Schematic of the time schedule for detection of the biological activity of GLP-1 produced by GIFTGLP-1. HEK−293T cells were transfected with the GLP-1 receptor (PSV40-GLP1R-pA) and the corresponding reporter (PCRE-SEAP-pA). e, SEAP production of HEK-293T cells treated with the culture supernatant of GIFT induced with (+) or without (−) glucose. f, Blood glucose of db/db mice orally administered with different doses of GIFT. db/db mice were orally administered with PBS, 109, 1010, and 1011 CFU GIFTGLP-1. Blood glucose was detected 12 h following gavage. Data in a and f are expressed as means ± s.e.m.; n = 5 mice for a, n = 4 mice for f. Data in b and e are expressed as means ± s.d.; n = 3 independent experiments. P-values in a, e, f were calculated by two-way ANOVA followed by Sidak’s multiple comparisons test. NS, not significant; ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Extended Data Fig. 6 Effects of long-term oral administration of GIFTGLP-1 on db/db mice.

db/db mice were treated with PBS, GIFTLux, or GIFTGLP−1 cells (orally administered at a dose of 109 CFU/mouse/day) for 30 days. a, Hepatic glycogen levels of db/db mice. b, Epididymal fat to body weight ratio analysis. c, Representative pictures of db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. d-f, Evaluation of body weight, fat mass, and lean mass (d), serum triglycerides (TG) content (e), and serum total cholesterol (T-CHO) content (f) in db/db mice (sampled on day 30). g-q, Metabolic characterization of db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. Mice were individually housed in indirect calorimetry cages. g, Food intake. h, i, Oxygen consumption (VO2). j, k, Carbon dioxide production (VCO2). l, m, Respiratory exchange rate (RER, calculated by dividing VCO2 by VO2). n, o, Energy expenditure. p, q, Regression-based analysis of energy expenditure relative to lean body mass. The black x-axis line segments represent the 12-hour dark phases. Data in a, b, and d-q are expressed as means ± s.e.m.; n = 5 mice. P-values were calculated by one-way ANOVA (a, b, e-g) or two-way ANOVA (d, i, k, m, o) followed by Tukey’s multiple comparisons test, or one-way ANCOVA using lean body mass as a covariate (p, q). NS, not significant; ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Extended Data Fig. 7 Protective effects of GIFTGLP-1 against complications in db/db mice.

a, Representative hematoxylin and eosin (H&E) staining from liver tissue sections. Scale bars, 100 μm or 50 μm. The rectangular frame indicates the area displayed at a higher magnification. b, c, Hepatic TG (b), and T-CHO (c) levels of db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. d, e, Hepatic levels of IL-1β (d) and TNF-α (e) in db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. f-i, Ameliorating effect of GIFTGLP-1 on oxidative stress in diabetic mouse liver. After 30 days of treatment with PBS, GIFTLux, or GIFTGLP−1, livers of db/db mice were harvested and homogenized. The levels of oxidative stress markers were measured, including MDA (f), SOD (g), GSH (h), and T-AOC (i). j, k, Renal levels of IL-1β (j) and TNF-α (k) in db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. l-o, Ameliorating effect of GIFTGLP-1 on oxidative stress in diabetic mouse kidney. After 30 days of treatment with PBS, GIFTLux, or GIFTGLP-1, the kidneys of db/db mice were harvested and homogenized. The levels of oxidative stress markers were measured, including MDA (l), SOD (m), GSH (n), and T-AOC (o). p-u, Effect of GIFTGLP-1 on alleviating renal damage. After 30 days of treatment with PBS, GIFTLux, or GIFTGLP-1, serum levels of creatinine (CRE) (p), blood urea nitrogen (BUN) (q), and urine protein (r) in db/db mice were measured. Kidneys were harvested and weighed, and the kidney-to-body weight ratios (s) were calculated. Histopathological analyses of kidney sections, including H&E staining, Masson’s trichrome staining, and PAS staining (t), were performed. Scale bars, 50 μm. u, Masson’s trichrome staining to quantify glomerular fibrosis (20 glomeruli per mouse were analyzed, n = 5 mice per group). v, w Colonic IL-1β (v), and TNF-α (w) levels of db/db mice treated with PBS, GIFTLux, or GIFTGLP-1 for 30 days. x, Representative H&E staining from colon tissue section. Scale bars, 100 μm. Representative images from three independent experiments with similar results are shown in a, t, x. Data in b-e, j, k, p-s, u-w are expressed as means ± s.e.m.; n = 5 mice. For box-and-whisker plots in f-i, l-o, the centre line denotes the median, the box bounds indicate the 25th and 75th percentiles, and the whiskers extend from the minimum to maximum values. P-values in b-s, u-w were calculated using one-way ANOVA followed by Tukey’s multiple comparisons test. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Extended Data Fig. 8 Impact of oral administration of varying concentrations of glucose and different sugary foods on blood glucose levels and GIFT-mediated gene expression dynamics in wild-type mice.

a, Wild-type mice were orally administered GIFTLux cells (109 CFU). Thirty minutes post-gavage, the mice were administered intragastrically (i.g.) with varying glucose concentrations (0, 0.1, 1, and 5 g/kg). Blood glucose levels (b) and bioluminescence signal intensity (c) were monitored every 15 min. d, Wild-type mice were orally administered GIFTLux cells (109 CFU). Thirty minutes post-gavage, the mice were given either a chow diet or administered intragastrically (i.g.) with 10 μL/g of PBS, diet cola, cola (containing 10.6 g carbohydrates per 100 mL), or chocolate (containing 43 g carbohydrates per 100 g). Blood glucose levels (e) and bioluminescence signal intensity (f) were monitored every 15 min. Data in b, c, e, and f are expressed as means ± s.e.m.; n = 6 mice. P-values in b, c, e, f were calculated by two-way ANOVA followed by Dunnett’s multiple comparisons test. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Extended Data Fig. 9 GIFT-mediated diabetes and obesity management in DIO mice.

a, Schematic timeline for GIFT-mediated long-term glycemic control in DIO mice. Mice were treated with PBS, GIFTLux, or GIFTGLP-1 cells (109 CFU) daily for 30 days. Serum GLP-1 and plasma insulin levels were measured 2 h after the first gavage, and fasting blood glucose was monitored every three days. Lipid profiles and plasma insulin were evaluated 24 h after the final gavage. b-i, Data for DIO mice: fasting blood glucose (b), serum GLP-1 (c), plasma insulin levels 2 h after the first gavage (d) and 24 h after the final gavage (e), body weight (f), fat mass (g), and serum TG (h) and T-CHO levels (i). Data in b-i are expressed as means ± s.e.m.; n = 5 mice. P-values in c-i were calculated by one-way ANOVA followed by Sidak’s multiple comparisons test. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Extended Data Fig. 10 Comparative analysis of adverse effects between semaglutide injection and oral delivery of GIFTGLP-1 in db/db mice.

a, Schematic of the timeline for assessing acute adverse effects. db/db mice were divided into three groups: one received oral GIFTGLP-1, another was injected with semaglutide, and the third group was left untreated. Blood samples were collected at 6 h for serum immunoglobulin E (IgE), interleukin-6 (IL-6), and Interferon beta (IFNβ) analysis, and at 12 and 24 h for complete blood count (CBC), serum biochemical analysis, and calcitonin (CT) measurement. b, Serum IgE levels in db/db mice 6 h after treatment. c-h, Serum levels of CT (c, d), alanine transaminase (ALT) (e, f), and aspartate transaminase (AST) (g, h) in db/db mice 12 and 24 h after treatment. i, j, Serum levels of IL-6 (i) and IFNβ (j) in db/db mice 6 h after treatment. k, Schematic of the timeline for the conditioned taste aversion (CTA) experiment. db/db mice were single-housed with ad libitum access to chow diet and tap water for 48 h, followed by access to 1% sucrose for 24 h. After acclimation, mice given oral GIFTGLP-1 or injected with semaglutide underwent a two-bottle preference test, choosing between tap water and 1% sucrose. Sucrose and water intake were recorded for 24 h. l, Blood glucose levels monitored 4 h after GIFTGLP-1 or semaglutide administration. m, Total sucrose intake. n, Total water intake. o, Body weight, fat mass, and lean mass of db/db mice treated with semaglutide (0.12 mg/kg/week, intramuscular injection), GIFTGLP-1 (109 CFU/day, oral administration), or left untreated for one month. p-s, Serum levels of TNF (p), IFNβ (q), IL-6 (r), and IL-1β (s) in db/db mice after two-month treatment with semaglutide (0.12 mg/kg/week, intramuscular injection), GIFTGLP-1 (109 CFU/day, oral administration), or no treatment. t, u, Serum levels of IgG1 (t) and IgG2c (u) in db/db mice after one-month treatment with PBS, GIFTLux (109 CFU/day), or GIFTGLP-1 (109 CFU/day). Data in b-j and l-u are expressed as means ± s.e.m.; n = 6 mice in b-j and o-s, n = 9 mice in l-n, n = 5 mice in t,u. P-values were calculated using one-way ANOVA (b-j, m, n, p-u) or two-way ANOVA (l, o), followed by Tukey’s multiple comparisons test. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001. Detailed statistics are provided in Supplementary Table 16.

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Guan, N., Kong, D., Gao, X. et al. Glucose-responsive probiotics for glycaemic modulation in mice and monkeys. Nature (2026). https://doi.org/10.1038/s41586-026-10909-6

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