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PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans

Manifest diabetes, but also conditions of increased insulin resistance such as pregnancy or obesity can lead to islet architecture remodeling. The contributing mechanisms are as poorly understood as the consequences of altered cell arrangement. For the quantification of the different cell types but...

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Autores principales: Asuaje Pfeifer, Melissa, Langehein, Hans, Grupe, Katharina, Müller, Steffi, Seyda, Joana, Liebmann, Moritz, Rustenbeck, Ingo, Scherneck, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523144/
https://www.ncbi.nlm.nih.gov/pubmed/37772078
http://dx.doi.org/10.3389/fendo.2023.1250023
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author Asuaje Pfeifer, Melissa
Langehein, Hans
Grupe, Katharina
Müller, Steffi
Seyda, Joana
Liebmann, Moritz
Rustenbeck, Ingo
Scherneck, Stephan
author_facet Asuaje Pfeifer, Melissa
Langehein, Hans
Grupe, Katharina
Müller, Steffi
Seyda, Joana
Liebmann, Moritz
Rustenbeck, Ingo
Scherneck, Stephan
author_sort Asuaje Pfeifer, Melissa
collection PubMed
description Manifest diabetes, but also conditions of increased insulin resistance such as pregnancy or obesity can lead to islet architecture remodeling. The contributing mechanisms are as poorly understood as the consequences of altered cell arrangement. For the quantification of the different cell types but also the frequency of different cell-cell contacts within the islets, different approaches exist. However, few methods are available to characterize islet cell distribution in a statistically valid manner. Here we describe PyCreas, an open-source tool written in Python that allows semi-automated analysis of islet cell distribution based on images of pancreatic sections stained by immunohistochemistry or immunofluorescence. To ensure that the PyCreas tool is suitable for quantitative analysis of cell distribution in the islets at different metabolic states, we studied the localization and distribution of alpha, beta, and delta cells during gestation and prediabetes. We compared the islet cell distribution of pancreatic islets from metabolically healthy NMRI mice with that of New Zealand obese (NZO) mice, which exhibit impaired glucose tolerance (IGT) both preconceptionally and during gestation, and from C57BL/6 N (B6) mice, which acquire this IGT only during gestation. Since substrain(s) of the NZO mice are known to show a variant in the Abcc8 gene, we additionally examined preconceptional SUR1 knock-out (SUR1-KO) mice. PyCreas provided quantitative evidence that alterations in the Abcc8 gene are associated with an altered distribution pattern of islet cells. Moreover, our data indicate that this cannot be a consequence of prolonged hyperglycemia, as islet architecture is already altered in the prediabetic state. Furthermore, the quantitative analysis suggests that states of transient IGT, such as during common gestational diabetes mellitus (GDM), are not associated with changes in islet architecture as observed during long-term IGT. PyCreas provides the ability to systematically analyze the localization and distribution of islet cells at different stages of metabolic disease to better understand the underlying pathophysiology.
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spelling pubmed-105231442023-09-28 PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans Asuaje Pfeifer, Melissa Langehein, Hans Grupe, Katharina Müller, Steffi Seyda, Joana Liebmann, Moritz Rustenbeck, Ingo Scherneck, Stephan Front Endocrinol (Lausanne) Endocrinology Manifest diabetes, but also conditions of increased insulin resistance such as pregnancy or obesity can lead to islet architecture remodeling. The contributing mechanisms are as poorly understood as the consequences of altered cell arrangement. For the quantification of the different cell types but also the frequency of different cell-cell contacts within the islets, different approaches exist. However, few methods are available to characterize islet cell distribution in a statistically valid manner. Here we describe PyCreas, an open-source tool written in Python that allows semi-automated analysis of islet cell distribution based on images of pancreatic sections stained by immunohistochemistry or immunofluorescence. To ensure that the PyCreas tool is suitable for quantitative analysis of cell distribution in the islets at different metabolic states, we studied the localization and distribution of alpha, beta, and delta cells during gestation and prediabetes. We compared the islet cell distribution of pancreatic islets from metabolically healthy NMRI mice with that of New Zealand obese (NZO) mice, which exhibit impaired glucose tolerance (IGT) both preconceptionally and during gestation, and from C57BL/6 N (B6) mice, which acquire this IGT only during gestation. Since substrain(s) of the NZO mice are known to show a variant in the Abcc8 gene, we additionally examined preconceptional SUR1 knock-out (SUR1-KO) mice. PyCreas provided quantitative evidence that alterations in the Abcc8 gene are associated with an altered distribution pattern of islet cells. Moreover, our data indicate that this cannot be a consequence of prolonged hyperglycemia, as islet architecture is already altered in the prediabetic state. Furthermore, the quantitative analysis suggests that states of transient IGT, such as during common gestational diabetes mellitus (GDM), are not associated with changes in islet architecture as observed during long-term IGT. PyCreas provides the ability to systematically analyze the localization and distribution of islet cells at different stages of metabolic disease to better understand the underlying pathophysiology. Frontiers Media S.A. 2023-09-12 /pmc/articles/PMC10523144/ /pubmed/37772078 http://dx.doi.org/10.3389/fendo.2023.1250023 Text en Copyright © 2023 Asuaje Pfeifer, Langehein, Grupe, Müller, Seyda, Liebmann, Rustenbeck and Scherneck https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Asuaje Pfeifer, Melissa
Langehein, Hans
Grupe, Katharina
Müller, Steffi
Seyda, Joana
Liebmann, Moritz
Rustenbeck, Ingo
Scherneck, Stephan
PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title_full PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title_fullStr PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title_full_unstemmed PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title_short PyCreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of Langerhans
title_sort pycreas: a tool for quantification of localization and distribution of endocrine cell types in the islets of langerhans
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523144/
https://www.ncbi.nlm.nih.gov/pubmed/37772078
http://dx.doi.org/10.3389/fendo.2023.1250023
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