Leader β-cells coordinate Ca2+ dynamics across pancreatic islets in vivo


Pancreatic β-cells form highly connected networks within isolated islets. Whether this behaviour pertains to the situation in vivo, after innervation and during continuous perfusion with blood, is unclear. In the present study, we used the recombinant Ca2+ sensor GCaMP6 to assess glucose-regulated connectivity in living zebrafish Danio rerio, and in murine or human islets transplanted into the anterior eye chamber. In each setting, Ca2+ waves emanated from temporally defined leader β-cells, and three-dimensional connectivity across the islet increased with glucose stimulation. Photoablation of zebrafish leader cells disrupted pan-islet signalling, identifying these as likely pacemakers. Correspondingly, in engrafted mouse islets, connectivity was sustained during prolonged glucose exposure, and super-connected ‘hub’ cells were identified. Granger causality analysis revealed a controlling role for temporally defined leaders, and transcriptomic analyses revealed a discrete hub cell fingerprint. We thus define a population of regulatory β-cells within coordinated islet networks in vivo. This population may drive Ca2+ dynamics and pulsatile insulin secretion.

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Fig. 1: Glucose-stimulated Ca2+ influx imaged in vivo in living zebrafish.
Fig. 2: Ca2+ dynamics and connectivity in zebrafish: slow imaging acquisition (frame rate 0.1 Hz).
Fig. 3: Ca2+ dynamics and connectivity examined in zebrafish during rapid image acquisition.
Fig. 4: Ablation of temporally defined ‘leader’ cells (but not ‘follower’ cells) alters islet responsivity to glucose in vivo in zebrafish.
Fig. 5: Ca2+ waves and connectivity revealed using islets expressing GCaMP6f throughout the cell population under insulin promoter control.
Fig. 6: Binarized and Granger causality analysis corroborate the existence of super-connected leader cells in mouse islets in vivo.

Data availability

The data that support the findings of this study and the MATLAB codes for the various connectivity analyses described above are available from the corresponding authors upon request. Zebrafish islet RNA-seq data are deposited at the Gene Expression Omnibus repository with accession no. GSE123662.


  1. 1.

    DeFronzo, R. A., Ferrannini, E., Zimmet, P. & Alberti, G. International Textbook of Diabetes Mellitus 4th edn (Wiley-Blackwell, 2015).

  2. 2.

    Rutter, G. A., Pullen, T. J., Hodson, D. J. & Martinez-Sanchez, A. Pancreatic beta cell identity, glucose sensing and the control of insulin secretion. Biochem. J. 466, 202–218 (2015).

    Article  Google Scholar 

  3. 3.

    Tarasov, A. I. et al. The mitochondrial Ca2+ uniporter MCU is essential for glucose-induced ATP increases in pancreatic β-cells. PLoS ONE 7, e39722 (2012).

    CAS  Article  Google Scholar 

  4. 4.

    Xin, Y. et al. RNA sequencing of single human islet cells reveals type 2 diabetes genes. Cell Metab. 24, 608–615 (2016).

    CAS  Article  Google Scholar 

  5. 5.

    Segerstolpe, A. et al. Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metab. 24, 593–607 (2016).

    CAS  Article  Google Scholar 

  6. 6.

    Li, J. et al. Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types. EMBO Rep. 17, 178–187 (2016).

    CAS  Article  Google Scholar 

  7. 7.

    Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).

    CAS  Article  Google Scholar 

  8. 8.

    Kiekens, R. et al. Differences in glucose recognition by individual rat pancreatic B cells are associated with intercellular differences in glucose-induced biosynthetic activity. J. Clin. Invest. 89, 117–125 (1992).

    CAS  Article  Google Scholar 

  9. 9.

    Ammala, C. et al. Inositol trisphosphate-dependent periodic activation of a Ca2+-activated K+ conductance in glucose-stimulated pancreatic β-cells. Nature 353, 849–852 (1991).

    CAS  Article  Google Scholar 

  10. 10.

    Benninger, R. K. & Piston, D. W. Cellular communication and heterogeneity in pancreatic islet insulin secretion dynamics. Trends Endocrinol. Metab. 25, 399–406 (2014).

    CAS  Article  Google Scholar 

  11. 11.

    Meda, P. et al. The topography of electrical synchrony among beta-cells in the mouse islet of Langerhans. Q. J. Exp. Physiol. 69, 719–735 (1984).

    CAS  Article  Google Scholar 

  12. 12.

    Palti, Y., David, G. B., Lachov, E., Mida, Y. H. & Schatzberger, R. Islets of Langerhans generate wavelike electric activity modulated by glucose concentration. Diabetes 45, 595–601 (1996).

    CAS  Article  Google Scholar 

  13. 13.

    Benninger, R. K., Zhang, M., Head, W. S., Satin, L. S. & Piston, D. W. Gap junction coupling and calcium waves in the pancreatic islet. Biophys. J. 95, 5048–5061 (2008).

    CAS  Article  Google Scholar 

  14. 14.

    Head, W. S. et al. Connexin-36 gap junctions regulate in vivo first- and second-phase insulin secretion dynamics and glucose tolerance in the conscious mouse. Diabetes 61, 1700–1707 (2012).

    CAS  Article  Google Scholar 

  15. 15.

    Meda, P., Kohen, E., Kohen, C., Rabinovitch, A. & Orci, L. Direct communication of homologous and heterologous endocrine islet cells in culture. J. Cell Biol. 92, 221–226 (1982).

    CAS  Article  Google Scholar 

  16. 16.

    Meda, P., Santos, R. M. & Atwater, I. Direct identification of electrophysiologically monitored cells within intact mouse islets of Langerhans. Diabetes 35, 232–236 (1986).

    CAS  Article  Google Scholar 

  17. 17.

    Rutter, G. A. & Hodson, D. J. Beta cell connectivity in pancreatic islets: a type 2 diabetes target? Cell Mol. Life Sci. 72, 453–467 (2015).

    CAS  Article  Google Scholar 

  18. 18.

    Hodson, D. J. et al. Lipotoxicity disrupts incretin-regulated human beta cell connectivity. J. Clin. Invest. 123, 4182–4194 (2013).

    CAS  Article  Google Scholar 

  19. 19.

    Stozer, A. et al. Functional connectivity in islets of Langerhans from mouse pancreas tissue slices. PLoS Comput. Biol. 9, e1002923 (2013).

    CAS  Article  Google Scholar 

  20. 20.

    Hodson, D. J. et al. Existence of long-lasting experience-dependent plasticity in endocrine cell networks. Nat. Commun. 3, 605 (2012).

    Article  Google Scholar 

  21. 21.

    Johnston, N. R. et al. Beta cell hubs dictate pancreatic islet responses to glucose. Cell Metab. 24, 389–401 (2016).

    CAS  Article  Google Scholar 

  22. 22.

    Speier, S. et al. Noninvasive in vivo imaging of pancreatic islet cell biology. Nat. Med. 14, 574–578 (2008).

    CAS  Article  Google Scholar 

  23. 23.

    Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881 (2009).

    CAS  Article  Google Scholar 

  24. 24.

    van der Meulen, T. et al. Virgin beta cells persist throughout life at a neogenic niche within pancreatic islets. Cell Metab. 25, 911–926 (2017).

    Article  Google Scholar 

  25. 25.

    Chen, C. et al. Alterations in beta-cell calcium dynamics and efficacy outweigh islet mass adaptation in compensation of insulin resistance and prediabetes onset. Diabetes. 65, 2676–2685 (2016).

    CAS  Article  Google Scholar 

  26. 26.

    Singh, S. P. et al. Different developmental histories of beta-cells generate functional and proliferative heterogeneity during islet growth. Nat. Commun. 8, 664–00461 (2017).

    Article  Google Scholar 

  27. 27.

    Kimmel, R. A. & Meyer, D. Zebrafish pancreas as a model for development and disease. Methods Cell Biol. 134, 431–461 (2016).

    CAS  Article  Google Scholar 

  28. 28.

    Steiner, D. J., Kim, A., Miller, K. & Hara, M. Pancreatic islet plasticity: interspecies comparison of islet architecture and composition. Islets 2, 135–145 (2010).

    Article  Google Scholar 

  29. 29.

    Bosco, D. et al. Unique arrangement of alpha- and beta-cells in human islets of Langerhans. Diabetes 59, 1202–1210 (2010).

    CAS  Article  Google Scholar 

  30. 30.

    Prince, V. E., Anderson, R. M. & Dalgin, G. Zebrafish pancreas development and regeneration: fishing for diabetes therapies. Curr. Top. Dev. Biol. 124, 235–276 (2017).

    Article  Google Scholar 

  31. 31.

    Ninov, N. et al. Metabolic regulation of cellular plasticity in the pancreas. Curr. Biol. 23, 1242–1250 (2013).

    CAS  Article  Google Scholar 

  32. 32.

    Granger, C. W. J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438 (1969).

    Article  Google Scholar 

  33. 33.

    Barnett, L. & Seth, A. K. The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference. J. Neurosci. Methods 223, 50–68 (2014).

    Article  Google Scholar 

  34. 34.

    Janjuha, S., Pal, S. S. & Ninov, N. Analysis of beta-cell function using single-cell resolution calcium imaging in zebrafish islets. J. Vis. Exp. 10, e57851 (2018).

  35. 35.

    Gut, P. et al. Whole-organism screening for gluconeogenesis identifies activators of fasting metabolism. Nat. Chem. Biol. 9, 97–104 (2013).

    CAS  Article  Google Scholar 

  36. 36.

    Markovic, R. et al. Progressive glucose stimulation of islet beta cells reveals a transition from segregated to integrated modular functional connectivity patterns. Sci. Rep. 5, 7845 (2015).

    CAS  Article  Google Scholar 

  37. 37.

    Hesselson, D., Anderson, R. M., Beinat, M. & Stainier, D. Y. Distinct populations of quiescent and proliferative pancreatic beta-cells identified by HOTcre mediated labeling. Proc. Natl Acad. Sci. USA 106, 14896–14901 (2009).

    CAS  Article  Google Scholar 

  38. 38.

    Diraison, F. et al. Over-expression of sterol-regulatory-element-binding protein-1c (SREBP1c) in rat pancreatic islets induces lipogenesis and decreases glucose-stimulated insulin release: modulation by 5-aminoimidazole-4-carboxamide ribonucleoside (AICAR). Biochem. J. 378, 769–778 (2004).

    CAS  Article  Google Scholar 

  39. 39.

    Kone, M. et al. LKB1 and AMPK differentially regulate pancreatic beta-cell identity. FASEB J. 28, 4972–4985 (2014).

    CAS  Article  Google Scholar 

  40. 40.

    Thorens, B. et al. Ins1 knock-in mice for beta cell-specific gene recombination. Diabetologia 58, 558–656 (2015).

    CAS  Article  Google Scholar 

  41. 41.

    Rodriguez-Diaz, R. et al. Noninvasive in vivo model demonstrating the effects of autonomic innervation on pancreatic islet function. Proc. Natl Acad. Sci. USA 109, 21456–21461 (2012).

    CAS  Article  Google Scholar 

  42. 42.

    Ilegems, E. et al. Light scattering as an intrinsic indicator for pancreatic islet cell mass and secretion. Sci. Rep. 5, 10740 (2015).

    CAS  Article  Google Scholar 

  43. 43.

    Nyqvist, D. et al. Donor islet endothelial cells in pancreatic islet revascularization. Diabetes 60, 2571–2577 (2011).

    CAS  Article  Google Scholar 

  44. 44.

    Westacott, M. J., Ludin, N. W. F. & Benninger, R. K. P. Spatially organized beta-cell subpopulations control electrical dynamics across islets of Langerhans. Biophys. J. 113, 1093–1108 (2017).

    CAS  Article  Google Scholar 

  45. 45.

    Reinbothe, T. M., Safi, F., Axelsson, A. S., Mollet, I. G. & Rosengren, A. H. Optogenetic control of insulin secretion in intact pancreatic islets with beta-cell-specific expression of Channelrhodopsin-2. Islets 6, e28095 (2014).

    Article  Google Scholar 

  46. 46.

    Lorincz, R. et al. In vivo monitoring of intracellular Ca2+ dynamics in the p ancreatic beta-cells of zebrafish embryos. Islets 10, 221–238 (2018).

    CAS  Article  Google Scholar 

  47. 47.

    Gosak, M. et al. Critical and supercritical spatiotemporal calcium dynamics in beta cells. Front. Physiol. 8, 1106 (2017).

    Article  Google Scholar 

  48. 48.

    Ammala, C., Ashcroft, F. M. & Rorsman, P. Calcium-independent potentiation of insulin release by cyclic AMP in single beta-cells. Nature 363, 356–358 (1993).

    CAS  Article  Google Scholar 

  49. 49.

    Lu, T. T. et al. The polycomb-dependent epigenome controls beta cell dysfunction, dedifferentiation, and diabetes. Cell Metab. 27, 1294–1308 (2018).

    CAS  Article  Google Scholar 

  50. 50.

    Mullapudi, S. T. et al. Screening for insulin-independent pathways that modulate glucose homeostasis identifies androgen receptor antagonists. eLife 7, e42209 (2018).

    Article  Google Scholar 

  51. 51.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  Article  Google Scholar 

  52. 52.

    Ollion, J., Cochennec, J., Loll, F., Escude, C. & Boudier, T. TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization. Bioinformatics 29, 1840–1841 (2013).

    CAS  Article  Google Scholar 

  53. 53.

    Preibisch, S., Saalfeld, S., Schindelin, J. & Tomancak, P. Software for bead-based registration of selective plane illumination microscopy data. Nat. Methods 7, 418–419 (2010).

    CAS  Article  Google Scholar 

  54. 54.

    Luo, J. et al. A protocol for rapid generation of recombinant adenoviruses using the AdEasy system. Nat. Protoc. 2, 1236–1247 (2007).

    CAS  Article  Google Scholar 

  55. 55.

    Ravier, M. A. & Rutter, G. A. Isolation and culture of mouse pancreatic islets for ex vivo imaging studies with trappable or recombinant fluorescent probes. Methods Mol. Biol. 633, 171–184 (2010).

    CAS  Article  Google Scholar 

  56. 56.

    Janjuha, S. et al. Age-related islet inflammation marks the proliferative decline of pancreatic beta-cells in zebrafish. eLife 7, 32965 (2018).

    Article  Google Scholar 

  57. 57.

    Zheng, G. X. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).

    CAS  Article  Google Scholar 

  58. 58.

    Baron, M. et al. A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure. Cell Syst. 3, 346–360 (2016).

    CAS  Article  Google Scholar 

  59. 59.

    Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS  Article  Google Scholar 

  60. 60.

    Mi, H. et al. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45, D183–D189 (2017).

    CAS  Article  Google Scholar 

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V.S. was supported by a Diabetes UK Harry Keen Clinician Scientist 15/0005317. G.A.R. was supported by a Wellcome Trust Senior Investigator Award (no. WT098424AIA), Wellcome Trust Investigator Award (212625/Z/18/Z), MRC Programme grants (nos. MR/R022259/1, MR/J0003042/1 and MR/L020149/1) and Experimental Challenge Grant (DIVA, no. MR/L02036X/1), MRC (no. MR/N00275X/1), Diabetes UK (nos. BDA/11/0004210, BDA/15/0005275 and BDA 16/0005485) and Imperial Confidence in Concept grants, and a Royal Society Wolfson Research Merit Award. I.L. was supported by Diabetes UK Project Grant no. 16/0005485 and D.J.H. by a Diabetes UK R.D. Lawrence Fellowship (no. 12/0004431), a Wellcome Trust Institutional Support Award, and Medical Research Council (no. MR/N00275X/1) and Diabetes UK (no. 17/0005681) Project Grants. N.N. received funding from the DFG–Center for Regenerative Therapies Dresden, Cluster of Excellence at TU Dresden and the German Center for Diabetes Research (DZD), as well as research grants from the German Research Foundation (DFG), the European Foundation for the Study of Diabetes, The International Research Training Group (IRTG 2251), and the DZD. L.J.B.B. was supported by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust, no. 201325/Z/16/Z) and a Junior Research Fellowship from Trinity College, Oxford. This project has received funding from the European Research Council (under the European Union’s Horizon 2020 research and innovation programme (Starting Grant no. 715884 to D.J.H.) and from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 115881 (RHAPSODY) to G.A.R. and P.M. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations. We would like to thank P.-O. Berggren (Karolinska Institute, Sweden and Imperial College London), A. Caicedo and R. Rodriguez (University of Miami), and P. Chabosseau, M.-S. Nguyen-Tu and B. Owen (Imperial College London) for valuable advice and support with surgery and imaging. We thank R. Callingham (Imperial College London) for assistance with human islet culture.

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V.S., N.N. and G.A.R. designed and supervised the study. L.D.S. and N.A. performed the zebrafish experiments. V.S., K.S., A.M.A. and I.L. undertook the mouse studies. G.C. and K.S. performed virus preparations. D.C.A.G., S.M.R., K.S., L.D.S. and V.S. developed movement correction macros. E.G., S.N.M.G., N.A., T.S., D.J.H. and L.B. contributed to connectivity analysis. D.J.H. and L.B. provided the code for connectivity analysis. V.S. and W.D. developed connectivity and Granger scripts and undertook all connectivity analyses. P.M. and A.M.J.S. provided human islets. K.S. and V.S. undertook studies on these preparations. T.J.P., N.A. and S.P.S. performed transcriptomic and bioinformatics analyses. G.A.R., V.S., L.D.S. and N.N. wrote the manuscript with contributions from all authors.

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Correspondence to Victoria Salem or Nikolay Ninov or Guy A. Rutter.

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G.A.R. has received grant funding from Servier and is a consultant for Sun Pharma. All others authors declare no competing interests.

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Salem, V., Silva, L.D., Suba, K. et al. Leader β-cells coordinate Ca2+ dynamics across pancreatic islets in vivo. Nat Metab 1, 615–629 (2019). https://doi.org/10.1038/s42255-019-0075-2

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