A comprehensive mechanistic model of adipocyte signaling with layers of confidence
Abstract Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellul...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-023-00282-9 |
| _version_ | 1797806672064806912 |
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| author | William Lövfors Rasmus Magnusson Cecilia Jönsson Mika Gustafsson Charlotta S. Olofsson Gunnar Cedersund Elin Nyman |
| author_facet | William Lövfors Rasmus Magnusson Cecilia Jönsson Mika Gustafsson Charlotta S. Olofsson Gunnar Cedersund Elin Nyman |
| author_sort | William Lövfors |
| collection | DOAJ |
| description | Abstract Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70–90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes. |
| first_indexed | 2024-03-13T06:10:50Z |
| format | Article |
| id | doaj.art-cc9cf96f241a478db28a7eef0063ae70 |
| institution | Directory Open Access Journal |
| issn | 2056-7189 |
| language | English |
| last_indexed | 2024-03-13T06:10:50Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj.art-cc9cf96f241a478db28a7eef0063ae702023-06-11T11:17:31ZengNature Portfolionpj Systems Biology and Applications2056-71892023-06-019111510.1038/s41540-023-00282-9A comprehensive mechanistic model of adipocyte signaling with layers of confidenceWilliam Lövfors0Rasmus Magnusson1Cecilia Jönsson2Mika Gustafsson3Charlotta S. Olofsson4Gunnar Cedersund5Elin Nyman6Department of Biomedical Engineering, Linköping UniversitySchool of Bioscience, Systems Biology Research Center, University of SkövdeDepartment of Biomedical Engineering, Linköping UniversityDepartment of Physics, Chemistry and Biology, Linköping UniversityDepartment of Physiology/Metabolic Physiology, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of GothenburgDepartment of Biomedical Engineering, Linköping UniversityDepartment of Biomedical Engineering, Linköping UniversityAbstract Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70–90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes.https://doi.org/10.1038/s41540-023-00282-9 |
| spellingShingle | William Lövfors Rasmus Magnusson Cecilia Jönsson Mika Gustafsson Charlotta S. Olofsson Gunnar Cedersund Elin Nyman A comprehensive mechanistic model of adipocyte signaling with layers of confidence npj Systems Biology and Applications |
| title | A comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| title_full | A comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| title_fullStr | A comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| title_full_unstemmed | A comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| title_short | A comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| title_sort | comprehensive mechanistic model of adipocyte signaling with layers of confidence |
| url | https://doi.org/10.1038/s41540-023-00282-9 |
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