Shiue-Cheng Tang1,2,3, Chia-Ning Shen4,5, Pei-Yu Lin6,7, Shih-Jung Peng8,9, Hung-Jen Chien9, Ya-Hsien Chou9, Chester E Chamberlain10, Pankaj J Pasricha11. 1. Connectomics Research Center, National Tsing Hua University, Hsinchu, Taiwan. sctang@life.nthu.edu.tw. 2. Institute of Biotechnology, National Tsing Hua University, Hsinchu, Taiwan. sctang@life.nthu.edu.tw. 3. Department of Medical Science, National Tsing Hua University, 101, Sec. 2, Kuang Fu Rd, Hsinchu, 30013, Taiwan. sctang@life.nthu.edu.tw. 4. Genomics Research Center, Academia Sinica, 128, Sec. 2, Academia Rd, Taipei, 11529, Taiwan. cnshen@gate.sinica.edu.tw. 5. Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan. cnshen@gate.sinica.edu.tw. 6. Genomics Research Center, Academia Sinica, 128, Sec. 2, Academia Rd, Taipei, 11529, Taiwan. 7. Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan. 8. Connectomics Research Center, National Tsing Hua University, Hsinchu, Taiwan. 9. Institute of Biotechnology, National Tsing Hua University, Hsinchu, Taiwan. 10. Diabetes Center, University of California at San Francisco, San Francisco, CA, USA. 11. Johns Hopkins Center for Neurogastroenterology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract
AIMS/HYPOTHESIS: It has been proposed that the neuro-insular network enables rapid, synchronised insulin secretion. However, to date, acquiring the pancreatic tissue map to study the neural network remains a challenging task as there is a lack of feasible approaches for large-scale tissue analysis at the organ level. Here, we have developed 3-dimensional (3D) panoramic histology to characterise the pancreatic neuro-insular network in young mice. METHODS: Pancreases harvested from young wild-type B6 mice (3 and 8 weeks old) and db/db mice (3 weeks old; db/db vs db/+) were used to develop 3D panoramic histology. Transparent pancreases were prepared by optical clearing to enable deep-tissue, tile-scanning microscopy for qualitative and quantitative analyses of islets and the pancreatic tissue network in space. RESULTS: 3D panoramic histology reveals the pancreatic neurovascular network and the coupling of ganglionic and islet populations via the network. This integration is identified in both 3- and 8-week-old mice, featuring the peri-arteriolar neuro-insular network and islet-ganglionic aggregation. In weaning hyperphagic db/db mice, the 3D image data identifies the associated increases in weight, adipose tissue attached to the pancreas, density of large islets (major axis > 150 μm) and pancreatic sympathetic innervation compared with db/+ mice. CONCLUSIONS/ INTERPRETATION: Our work provides insight into the neuro-insular integration at the organ level and demonstrates a new approach for investigating previously unknown details of the pancreatic tissue network in health and disease.
AIMS/HYPOTHESIS: It has been proposed that the neuro-insular network enables rapid, synchronised insulin secretion. However, to date, acquiring the pancreatic tissue map to study the neural network remains a challenging task as there is a lack of feasible approaches for large-scale tissue analysis at the organ level. Here, we have developed 3-dimensional (3D) panoramic histology to characterise the pancreatic neuro-insular network in young mice. METHODS: Pancreases harvested from young wild-type B6 mice (3 and 8 weeks old) and db/db mice (3 weeks old; db/db vs db/+) were used to develop 3D panoramic histology. Transparent pancreases were prepared by optical clearing to enable deep-tissue, tile-scanning microscopy for qualitative and quantitative analyses of islets and the pancreatic tissue network in space. RESULTS: 3D panoramic histology reveals the pancreatic neurovascular network and the coupling of ganglionic and islet populations via the network. This integration is identified in both 3- and 8-week-old mice, featuring the peri-arteriolar neuro-insular network and islet-ganglionic aggregation. In weaning hyperphagic db/db mice, the 3D image data identifies the associated increases in weight, adipose tissue attached to the pancreas, density of large islets (major axis > 150 μm) and pancreatic sympathetic innervation compared with db/+ mice. CONCLUSIONS/ INTERPRETATION: Our work provides insight into the neuro-insular integration at the organ level and demonstrates a new approach for investigating previously unknown details of the pancreatic tissue network in health and disease.
Authors: Michaël Noë; Neda Rezaee; Kaushal Asrani; Michael Skaro; Vincent P Groot; Pei-Hsun Wu; Matthew T Olson; Seung-Mo Hong; Sung Joo Kim; Matthew J Weiss; Christopher L Wolfgang; Martin A Makary; Jin He; John L Cameron; Denis Wirtz; Nicholas J Roberts; G Johan A Offerhaus; Lodewijk A A Brosens; Laura D Wood; Ralph H Hruban Journal: Am J Pathol Date: 2018-04-22 Impact factor: 4.307
Authors: Shiue-Cheng Tang; Luc Baeyens; Chia-Ning Shen; Shih-Jung Peng; Hung-Jen Chien; David W Scheel; Chester E Chamberlain; Michael S German Journal: Diabetologia Date: 2017-08-29 Impact factor: 10.122