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Individual islet respirometry reveals functional diversity within the islet population of mice and human donors.
Citation | “Individual Islet Respirometry Reveals Functional Diversity Within The Islet Population Of Mice And Human Donors.”. Molecular Metabolism, pp. 150-159. . |
Center | UCSD-UCLA |
Author | Evan P Taddeo, Linsey Stiles, Samuel Sereda, Eleni Ritou, Dane M Wolf, Muhamad Abdullah, Zachary Swanson, Josh Wilhelm, Melena Bellin, Patrick McDonald, Kacey Caradonna, Andrew Neilson, Marc Liesa, Orian S Shirihai |
Keywords | glucose, islets, mitochondria, Respirometry |
Abstract |
OBJECTIVE: Islets from the same pancreas show remarkable variability in glucose sensitivity. While mitochondrial respiration is essential for glucose-stimulated insulin secretion, little is known regarding heterogeneity in mitochondrial function at the individual islet level. This is due in part to a lack of high-throughput and non-invasive methods for detecting single islet function. METHODS: We have developed a novel non-invasive, high-throughput methodology capable of assessing mitochondrial respiration in large-sized individual islets using the XF96 analyzer (Agilent Technologies). RESULTS: By increasing measurement sensitivity, we have reduced the minimal size of mouse and human islets needed to assess mitochondrial respiration to single large islets of >35,000 μm area (∼210 μm diameter). In addition, we have measured heterogeneous glucose-stimulated mitochondrial respiration among individual human and mouse islets from the same pancreas, allowing population analyses of islet mitochondrial function for the first time. CONCLUSIONS: We have developed a novel methodology capable of analyzing mitochondrial function in large-sized individual islets. By highlighting islet functional heterogeneity, we hope this methodology can significantly advance islet research. |
Year of Publication |
2018
|
Journal |
Molecular metabolism
|
Volume |
16
|
Number of Pages |
150-159
|
Date Published |
12/2018
|
ISSN Number |
2212-8778
|
DOI |
10.1016/j.molmet.2018.07.003
|
Alternate Journal |
Mol Metab
|
PMID |
30098928
|
PMCID |
PMC6157638
|
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