A quantitative model of cellular decision making in direct neuronal reprogramming
(2021) In Scientific Reports 11(1).- Abstract
- The direct reprogramming of adult skin fibroblasts to neurons is thought to be controlled by a small set of interacting gene regulators. Here, we investigate how the interaction dynamics between these regulating factors coordinate cellular decision making in direct neuronal reprogramming. We put forward a quantitative model of the governing gene regulatory system, supported by measurements of mRNA expression. We found that nPTB needs to feed back into the direct neural conversion network most likely via PTB in order to accurately capture quantitative gene interaction dynamics and correctly predict the outcome of various overexpression and knockdown experiments. This was experimentally validated by nPTB knockdown leading to successful... (More)
- The direct reprogramming of adult skin fibroblasts to neurons is thought to be controlled by a small set of interacting gene regulators. Here, we investigate how the interaction dynamics between these regulating factors coordinate cellular decision making in direct neuronal reprogramming. We put forward a quantitative model of the governing gene regulatory system, supported by measurements of mRNA expression. We found that nPTB needs to feed back into the direct neural conversion network most likely via PTB in order to accurately capture quantitative gene interaction dynamics and correctly predict the outcome of various overexpression and knockdown experiments. This was experimentally validated by nPTB knockdown leading to successful neural conversion. We also proposed a novel analytical technique to dissect system behaviour and reveal the influence of individual factors on resulting gene expression. Overall, we demonstrate that computational analysis is a powerful tool for understanding the mechanisms of direct (neuronal) reprogramming, paving the way for future models that can help improve cell conversion strategies. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/95a53d5b-7315-4a36-b243-c4cfd24dfd7d
- author
- Merlevede, Adriaan LU ; Legault, Emilie M. ; Drugge, Viktor ; Barker, Roger A LU ; Drouin-Ouellet, Janelle LU and Olariu, Victor LU
- organization
- publishing date
- 2021-01-15
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- direct reprogramming, neuron, fibroblast, PTB, nPTB, miR-124, REST
- in
- Scientific Reports
- volume
- 11
- issue
- 1
- article number
- 1514
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:33452356
- scopus:85100124336
- ISSN
- 2045-2322
- DOI
- 10.1038/s41598-021-81089-8
- project
- Computational Science for Health and Environment
- Modelling cellular decision making in direct reprogramming to neurons
- Systems Biology of In Vitro Neuron and Microglia Formation
- language
- English
- LU publication?
- yes
- id
- 95a53d5b-7315-4a36-b243-c4cfd24dfd7d
- date added to LUP
- 2020-04-01 12:09:33
- date last changed
- 2024-08-07 16:18:32
@article{95a53d5b-7315-4a36-b243-c4cfd24dfd7d, abstract = {{The direct reprogramming of adult skin fibroblasts to neurons is thought to be controlled by a small set of interacting gene regulators. Here, we investigate how the interaction dynamics between these regulating factors coordinate cellular decision making in direct neuronal reprogramming. We put forward a quantitative model of the governing gene regulatory system, supported by measurements of mRNA expression. We found that nPTB needs to feed back into the direct neural conversion network most likely via PTB in order to accurately capture quantitative gene interaction dynamics and correctly predict the outcome of various overexpression and knockdown experiments. This was experimentally validated by nPTB knockdown leading to successful neural conversion. We also proposed a novel analytical technique to dissect system behaviour and reveal the influence of individual factors on resulting gene expression. Overall, we demonstrate that computational analysis is a powerful tool for understanding the mechanisms of direct (neuronal) reprogramming, paving the way for future models that can help improve cell conversion strategies.}}, author = {{Merlevede, Adriaan and Legault, Emilie M. and Drugge, Viktor and Barker, Roger A and Drouin-Ouellet, Janelle and Olariu, Victor}}, issn = {{2045-2322}}, keywords = {{direct reprogramming; neuron; fibroblast; PTB; nPTB; miR-124; REST}}, language = {{eng}}, month = {{01}}, number = {{1}}, publisher = {{Nature Publishing Group}}, series = {{Scientific Reports}}, title = {{A quantitative model of cellular decision making in direct neuronal reprogramming}}, url = {{http://dx.doi.org/10.1038/s41598-021-81089-8}}, doi = {{10.1038/s41598-021-81089-8}}, volume = {{11}}, year = {{2021}}, }