Investigating pancreatic tissue and diabetes
A better understanding of how type 1 diabetes (T1D) starts is the first step toward potentially developing new and improved therapies capable of preventing or permanently reversing T1D . Due to the inaccessibility to human pancreatic tissue, our knowledge of the disease in humans is limited. The network for Pancreatic Organ donors with Diabetes (nPOD) was established with the idea of providing valuable tissues from healthy and diabetic donors to answer basic questions about T1D pathogenesis . One interest of scientists in this field is to identify cytokine proteins, such as those of the Interleukin-17 (IL-17) family of proinflammatory cytokines [3,4], in pancreatic tissue specimens of T1D cases. Because T1D is an autoimmune disease, where insulin-producing pancreatic beta cells are attacked by the immune system, understanding the cytokine milieu in the pancreas of T1D patients will help lead to more insights about the T1D pathogenesis and contribute towards improved therapies.
Challenges when imaging islets
Imaging of these pancreatic islets for this type of research is typically done using confocal microscopy to characterize their cytokine expression. It is extremely time consuming as they are commonly imaged using a 63x objective and extensive z-stacks. In the past, widefield microscopy would be insufficient to image these islets due to the inherent haze associated with widefield imaging, especially when dealing with thicker specimens [5,6].
Human islets were obtained from a non-diabetic cadaveric donor through IIDP (Integrated Islet Distribution Program) . Isolated human pancreatic islet tissue was used for this study to experimentally examine the expression of an IL-17 cytokine protein. The tissue was labelled with the following markers: AF488 (green) indicates insulin, AF555 (red) glucagon, AF647 (magenta) IL17, and Hoechst (blue) nuclei. The pancreatic tissue was imaged with a THUNDER Imager 3D Assay using a 63x,1.4 NA (numerical aperture) oil-immersion objective. Instant Computational Clearing (ICC) was also applied [5,6]. Images were acquired at the speed of widefield microscopy. Extended depth of field (EDoF) projections were reconstructed from a 92-step, 18-µm Z stack after ICC. Tile scans of an entire human pancreatic islet were also obtained.
THUNDER images with highly enhanced contrast and resolution are seen in figure 1 below. ICC removed the out-of-focus blur or haze seen in the raw image [5,6]. Insulin producing cells (green) are easily resolved and the other markers are readily visualized .
The fluorescence signals of IL-17 cytokine proteins, as well as insulin and glucagon, in human islet tissue were more clearly revealed in images attained with a THUNDER Imager 3D Assay and Instant Computational Clearing (ICC) compared to conventional widefield microscope images.
- B.J. von Scholten, F.F. Kreiner, S.C.L. Gough, M. von Herrath, Current and future therapies for type 1 diabetes, Diabetologia (2021) vol. 64, pp. 1037–1048, DOI: 10.1007/s00125-021-05398-3.
- M. Campbell-Thompson, C. Wasserfall, J. Kaddis, A. Albanese-O'Neill, T. Staeva, C. Nierras, J. Moraski, P. Rowe, R. Gianani, G. Eisenbarth, J. Crawford, D. Schatz, A. Pugliese, M. Atkinson, Network for Pancreatic Organ Donors with Diabetes (nPOD): developing a tissue biobank for type 1 diabetes, Diabetes/Metabolism Research and Reviews (2012) vol. 28, iss. 7, pp. 608-617, DOI: 10.1002/dmrr.2316.
- S. Rajendran, E. Quesada-Masachs, S. Zilberman, M. Graef, W.B. Kiosses, T. Chu, M.A. Benkahla, J.-H. Mason Lee, M. von Herrath, IL-17 is expressed on beta and alpha cells of donors with type 1 and type 2 diabetes, J. Autoimmunity (2021) vol. 123, ISSN 0896-8411, DOI: 10.1016/j.jaut.2021.102708.
- J.K. Kolls, A. Lindén, Interleukin-17 Family Members and Inflammation, Immunity (2004) vol. 21, iss. 4, pp. 467-476, DOI: 10.1016/j.immuni.2004.08.018.
- J. Schumacher, L. Bertrand, Real time images of 3D specimens with sharp contrast free of haze: Technology Note THUNDER Imagers: How Do They Really Work? Science Lab (2019) Leica Microsystems.
- L. Felts, V. Kohli, J.M. Marr, J. Schumacher, O. Schlicker, An Introduction to Computational Clearing: A New Method to Remove Out-of-Focus Blur, Science Lab (2020) Leica Microsystems.
- M. Brissova, J.C. Niland, J. Cravens, B. Olack, J. Sowinski, C. Evans-Molina, The Integrated Islet Distribution Program Answers the Call for Improved Human Islet Phenotyping and Reporting of Human Islet Characteristics in Research Articles, Diabetes (2019) vol. 68, iss. 7, pp. 1363–1365, DOI: 10.2337/dbi19-0019.
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