000007701 001__ 7701 000007701 005__ 20240523043417.0 000007701 02470 $$ahttps://doi.org/10.1371/journal.pcbi.1004423$$2doi 000007701 037__ $$aTEXTUAL$$bArticle 000007701 041__ $$aeng 000007701 245__ $$aThe Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans 000007701 269__ $$a2015-08-12 000007701 336__ $$aArticle 000007701 520__ $$aPancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets. 000007701 536__ $$oNIDDK$$aIntramural Research Program 000007701 540__ $$a<p>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the <a href="https://creativecommons.org/publicdomain/zero/1.0/" target="_blank">Creative Commons CC0</a> public domain dedication.</p> 000007701 594__ $$aAll relevant data are within the paper and its Supporting Information files. 000007701 690__ $$aBiological Sciences Division 000007701 691__ $$aMedicine 000007701 7001_ $$aStriegel, Deborah A.$$uNational Institute of Diabetes and Digestive and Kidney Diseases 000007701 7001_ $$aHara, Manami$$uUniversity of Chicago 000007701 7001_ $$aPeriwal, Vipul$$uNational Institute of Diabetes and Digestive and Kidney Diseases 000007701 773__ $$tPLOS Computational Biology 000007701 8564_ $$yArticle$$9651a7a17-3393-4007-a254-35d3a7e9ef18$$s6483132$$uhttps://knowledge.uchicago.edu/record/7701/files/journal.pcbi.1004423.pdf$$ePublic 000007701 8564_ $$ySupporting information$$9ca5312ed-0e8e-4245-bfa8-1c0306440c24$$s7263829$$uhttps://knowledge.uchicago.edu/record/7701/files/pcbi.1004423.zip$$ePublic 000007701 908__ $$aI agree 000007701 909CO $$ooai:uchicago.tind.io:7701$$pGLOBAL_SET 000007701 983__ $$aArticle