Abstract
How the network around ROS protects against oxidative stress and Parkinson’s disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased α-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for “life-extending interventions”: mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.
| Original language | English |
|---|---|
| Article number | 34 |
| Pages (from-to) | 1-20 |
| Number of pages | 20 |
| Journal | npj Systems Biology and Applications |
| Volume | 6 |
| Issue number | 1 |
| Early online date | 26 Oct 2020 |
| DOIs | |
| Publication status | Published - 1 Dec 2020 |
Funding
We cordially thank Nathan Price and Evangelos Simeonidis from ISB (Seattle), Nilgün Sahin from the VU University Amsterdam, and Ewelina Weglarz-Tomczak of the University of Amsterdam for highly influential discussions and support. We thank Stephan Gebel for his great help with the PD map and Olga Krebs for her help with FAIRDOMHub. A.K. acknowledges funding from the Luxembourg BioTech Initiative and LCSB; A.K. and A.I. acknowledge the financial support from an FNR grant for the Ph.D. project ROSIM. H.V.W. thanks the EU, the BBSRC, EPSRC, and NWO for extensive research support throughout many years, such as in grants BB/F003528/1, BB/ C008219/1, BB/F003528/1, BB/G530225/1, BB/I004696/1, BB/I017186/1, BB/I00470X/1, BB/I004688/1, BB/J500422/1, BB/J003883/1, BB/J020060/1, and the EU-FP7 projects SYNPOL, EC-MOAN, NUCSYS, UNI-CELLSYS, ITFoM, BioSiM, and EPIPredict. M.B. acknowledges the Systems Biology Grants of the University of Surrey and of the Swammerdam Institute for Life Science Starting Grant of the University of Amsterdam. This work was further supported by the Corbel EU-H2020 through Hans V. Westerhoff and Anna M Colangelo; and grants from the Italian Ministry of University and Research (MIUR): SYSBIO-Italian ROADMAP ESFRI Infrastructures to L.A., A.M.C., and M.P.; MIUR ALISEI-IVASCOMAR-Italian National Cluster to A.M.C., and grant Dipartimenti di Eccellenza-2017 to the University of Milano-Bicocca Department of Biotechnology and Biosciences.
| Funders | Funder number |
|---|---|
| University of Surrey | |
| Biotechnology and Biological Sciences Research Council | |
| European Commission | |
| University of Milano-Bicocca Department of Biotechnology and Biosciences | |
| EU-H2020 | |
| EU-FP7 | |
| Engineering and Physical Sciences Research Council | |
| LCSB | |
| Universiteit van Amsterdam | |
| Ministero dell’Istruzione, dell’Università e della Ricerca | SYSBIO-Italian ROADMAP ESFRI Infrastructures |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | BB/J500422/1, BB/F003528/1, BB/ C008219/1, BB/I017186/1, BB/I00470X/1, BB/I004688/1, BB/G530225/1, BB/J003883/1, BB/I004696/1 |
| FP7 Health | ITFoM, BioSiM, UNI-CELLSYS, NUCSYS, EPIPredict, SYNPOL, EC-MOAN |
| UK Research and Innovation | BB/J020060/1 |
| Fonds De La Recherche Scientifique - FNRS | ROSIM |
| Fonds National de la Recherche Luxembourg | Luxembourg BioTech Initiative |