Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
Abstract Background Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the in...
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| Format: | Article |
| Language: | English |
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BMC
2020-03-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-020-3394-0 |
| _version_ | 1819097885653860352 |
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| author | Gianluca Ascolani Timothy M. Skerry Damien Lacroix Enrico Dall’Ara Aban Shuaib |
| author_facet | Gianluca Ascolani Timothy M. Skerry Damien Lacroix Enrico Dall’Ara Aban Shuaib |
| author_sort | Gianluca Ascolani |
| collection | DOAJ |
| description | Abstract Background Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis. Results A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system’s state. Conclusions The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation. |
| first_indexed | 2024-12-22T00:22:12Z |
| format | Article |
| id | doaj.art-97f32c103f1740fe9197199562079813 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-22T00:22:12Z |
| publishDate | 2020-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-97f32c103f1740fe91971995620798132022-12-21T18:45:08ZengBMCBMC Bioinformatics1471-21052020-03-0121111910.1186/s12859-020-3394-0Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical eventsGianluca Ascolani0Timothy M. Skerry1Damien Lacroix2Enrico Dall’Ara3Aban Shuaib4Department of Oncology and Metabolism, University of SheffieldDepartment of Oncology and Metabolism, University of SheffieldInsigneo Institute of In Silico Medicine, University of SheffieldDepartment of Oncology and Metabolism, University of SheffieldDepartment of Oncology and Metabolism, University of SheffieldAbstract Background Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis. Results A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system’s state. Conclusions The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation.http://link.springer.com/article/10.1186/s12859-020-3394-0Osteoblast mechanotransductionMolecular networkFluctuationsSubordination theoryDirecting processWaiting time distribution |
| spellingShingle | Gianluca Ascolani Timothy M. Skerry Damien Lacroix Enrico Dall’Ara Aban Shuaib Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events BMC Bioinformatics Osteoblast mechanotransduction Molecular network Fluctuations Subordination theory Directing process Waiting time distribution |
| title | Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events |
| title_full | Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events |
| title_fullStr | Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events |
| title_full_unstemmed | Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events |
| title_short | Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events |
| title_sort | revealing hidden information in osteoblast s mechanotransduction through analysis of time patterns of critical events |
| topic | Osteoblast mechanotransduction Molecular network Fluctuations Subordination theory Directing process Waiting time distribution |
| url | http://link.springer.com/article/10.1186/s12859-020-3394-0 |
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