Models

Dataset Information

0

DallePezze2014 - Cellular senescene-induced mitochondrial dysfunction


ABSTRACT: DallePazze2014 - Cellular senescene-induced mitochondrial dysfunction This model is described in the article: Dynamic modelling of pathways to cellular senescence reveals strategies for targeted interventions. Dalle Pezze P, Nelson G, Otten EG, Korolchuk VI, Kirkwood TB, von Zglinicki T, Shanley DP. PLoS Comput. Biol. 2014 Aug; 10(8): e1003728 Abstract: Cellular senescence, a state of irreversible cell cycle arrest, is thought to help protect an organism from cancer, yet also contributes to ageing. The changes which occur in senescence are controlled by networks of multiple signalling and feedback pathways at the cellular level, and the interplay between these is difficult to predict and understand. To unravel the intrinsic challenges of understanding such a highly networked system, we have taken a systems biology approach to cellular senescence. We report a detailed analysis of senescence signalling via DNA damage, insulin-TOR, FoxO3a transcription factors, oxidative stress response, mitochondrial regulation and mitophagy. We show in silico and in vitro that inhibition of reactive oxygen species can prevent loss of mitochondrial membrane potential, whilst inhibition of mTOR shows a partial rescue of mitochondrial mass changes during establishment of senescence. Dual inhibition of ROS and mTOR in vitro confirmed computational model predictions that it was possible to further reduce senescence-induced mitochondrial dysfunction and DNA double-strand breaks. However, these interventions were unable to abrogate the senescence-induced mitochondrial dysfunction completely, and we identified decreased mitochondrial fission as the potential driving force for increased mitochondrial mass via prevention of mitophagy. Dynamic sensitivity analysis of the model showed the network stabilised at a new late state of cellular senescence. This was characterised by poor network sensitivity, high signalling noise, low cellular energy, high inflammation and permanent cell cycle arrest suggesting an unsatisfactory outcome for treatments aiming to delay or reverse cellular senescence at late time points. Combinatorial targeted interventions are therefore possible for intervening in the cellular pathway to senescence, but in the cases identified here, are only capable of delaying senescence onset. This model is hosted on BioModels Database and identified by: BIOMD0000000582. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Piero Dalle Pezze  

PROVIDER: BIOMD0000000582 | BioModels | 2024-09-02

REPOSITORIES: BioModels

altmetric image

Publications

Dynamic modelling of pathways to cellular senescence reveals strategies for targeted interventions.

Dalle Pezze Piero P   Nelson Glyn G   Otten Elsje G EG   Korolchuk Viktor I VI   Kirkwood Thomas B L TB   von Zglinicki Thomas T   Shanley Daryl P DP  

PLoS computational biology 20140828 8


Cellular senescence, a state of irreversible cell cycle arrest, is thought to help protect an organism from cancer, yet also contributes to ageing. The changes which occur in senescence are controlled by networks of multiple signalling and feedback pathways at the cellular level, and the interplay between these is difficult to predict and understand. To unravel the intrinsic challenges of understanding such a highly networked system, we have taken a systems biology approach to cellular senescenc  ...[more]

Similar Datasets

2023-11-17 | GSE244434 | GEO
2024-09-02 | BIOMD0000000287 | BioModels
2023-08-16 | GSE235225 | GEO
2018-05-05 | GSE114054 | GEO
2024-10-02 | GSE262514 | GEO
2023-08-16 | GSE196610 | GEO
2024-07-09 | GSE218684 | GEO
2024-07-09 | GSE218683 | GEO
2024-07-09 | GSE218682 | GEO
2008-06-13 | E-GEOD-5332 | biostudies-arrayexpress