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High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry
Type 2 diabetes (T2D) is a metabolic disorder characterized by loss of pancreatic β-cell function, decreased insulin secretion and increased insulin resistance, that affects more than 537 million people worldwide. Although several treatments are proposed to patients suffering from T2D, long-term con...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047017/ https://www.ncbi.nlm.nih.gov/pubmed/36980190 http://dx.doi.org/10.3390/cells12060849 |
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author | Delannoy, Clément Philippe Heuson, Egon Herledan, Adrien Oger, Frederik Thiroux, Bryan Chevalier, Mickaël Gromada, Xavier Rolland, Laure Froguel, Philippe Deprez, Benoit Paul, Sébastien Annicotte, Jean-Sébastien |
author_facet | Delannoy, Clément Philippe Heuson, Egon Herledan, Adrien Oger, Frederik Thiroux, Bryan Chevalier, Mickaël Gromada, Xavier Rolland, Laure Froguel, Philippe Deprez, Benoit Paul, Sébastien Annicotte, Jean-Sébastien |
author_sort | Delannoy, Clément Philippe |
collection | PubMed |
description | Type 2 diabetes (T2D) is a metabolic disorder characterized by loss of pancreatic β-cell function, decreased insulin secretion and increased insulin resistance, that affects more than 537 million people worldwide. Although several treatments are proposed to patients suffering from T2D, long-term control of glycemia remains a challenge. Therefore, identifying new potential drugs and targets that positively affect β-cell function and insulin secretion remains crucial. Here, we developed an automated approach to allow the identification of new compounds or genes potentially involved in β-cell function in a 384-well plate format, using the murine β-cell model Min6. By using MALDI-TOF mass spectrometry, we implemented a high-throughput screening (HTS) strategy based on the automation of a cellular assay allowing the detection of insulin secretion in response to glucose, i.e., the quantitative detection of insulin, in a miniaturized system. As a proof of concept, we screened siRNA targeting well-know β-cell genes and 1600 chemical compounds and identified several molecules as potential regulators of insulin secretion and/or synthesis, demonstrating that our approach allows HTS of insulin secretion in vitro. |
format | Online Article Text |
id | pubmed-10047017 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100470172023-03-29 High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry Delannoy, Clément Philippe Heuson, Egon Herledan, Adrien Oger, Frederik Thiroux, Bryan Chevalier, Mickaël Gromada, Xavier Rolland, Laure Froguel, Philippe Deprez, Benoit Paul, Sébastien Annicotte, Jean-Sébastien Cells Article Type 2 diabetes (T2D) is a metabolic disorder characterized by loss of pancreatic β-cell function, decreased insulin secretion and increased insulin resistance, that affects more than 537 million people worldwide. Although several treatments are proposed to patients suffering from T2D, long-term control of glycemia remains a challenge. Therefore, identifying new potential drugs and targets that positively affect β-cell function and insulin secretion remains crucial. Here, we developed an automated approach to allow the identification of new compounds or genes potentially involved in β-cell function in a 384-well plate format, using the murine β-cell model Min6. By using MALDI-TOF mass spectrometry, we implemented a high-throughput screening (HTS) strategy based on the automation of a cellular assay allowing the detection of insulin secretion in response to glucose, i.e., the quantitative detection of insulin, in a miniaturized system. As a proof of concept, we screened siRNA targeting well-know β-cell genes and 1600 chemical compounds and identified several molecules as potential regulators of insulin secretion and/or synthesis, demonstrating that our approach allows HTS of insulin secretion in vitro. MDPI 2023-03-09 /pmc/articles/PMC10047017/ /pubmed/36980190 http://dx.doi.org/10.3390/cells12060849 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Delannoy, Clément Philippe Heuson, Egon Herledan, Adrien Oger, Frederik Thiroux, Bryan Chevalier, Mickaël Gromada, Xavier Rolland, Laure Froguel, Philippe Deprez, Benoit Paul, Sébastien Annicotte, Jean-Sébastien High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title | High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title_full | High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title_fullStr | High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title_full_unstemmed | High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title_short | High-Throughput Quantitative Screening of Glucose-Stimulated Insulin Secretion and Insulin Content Using Automated MALDI-TOF Mass Spectrometry |
title_sort | high-throughput quantitative screening of glucose-stimulated insulin secretion and insulin content using automated maldi-tof mass spectrometry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047017/ https://www.ncbi.nlm.nih.gov/pubmed/36980190 http://dx.doi.org/10.3390/cells12060849 |
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