Although systems biology is potentially powerful to understand biological timing, current modelling approaches still suffer from several limitations because they were not initially developed for genetic networks involving chronometric time while parameter estimation remains challenging. HyClock gathers a multidisciplinary team to develop novel formal methods and hybrid modelling frameworks and apply them to the circadian clock and the cell cycle.
The general objective of HyClock project is (i) to offer the proof of principle that hybrid modelling outperforms classical formal methods for studying the properties of the mammalian circadian timing system and (ii) to apply this approach to better understand the circadian clock-cell cycle-cancer connection and their potential impact on cancer chronopharamcology and chronotherapeutics.
Computer sciences teams develop new formal methods and use hybrid logics where continuous time cohabits with discrete states. Experimental teams use technologies that allow the real time monitoring of he circadian clock and the cell cycle at the whole organism, cell population or single cell levels.
Hyclock has obtained a first generation hybrid model for the mammalian cell cycle. Recent advances have also been made with new approaches for the modelling of the mammalian circadian clock network. Finally, the modelling of coupled oscillators show how the cell cycle could influence
the circadian clock.
HyClock is expected to provide a general and innovative approach as well as invaluable tools and information for both the modelling of biological time and for the forthcoming personalization of chronotherapy.
1. Behaegel J, Comet JP, Bernot G, Cornillon E and, Delaunay F. A hybrid model of cell cycle in mammals. J Bioinform Comput Biol. 2016; Feb;14(1):1640001.
2. Ribeiro T, Magnin M, Inoue K and, Sakama C, «Learning Delayed Influences of Biological Systems«, Frontiers in Bioengineering and Biotechnology, 2015; vol 2, 81,
3. Feillet C, van der Horst GT, Levi F, Rand DA, Delaunay F. Coupling between the Circadian Clock and Cell Cycle Oscillators: Implication for Healthy Cells and Malignant Growth. Front Neurol. 2015; vol 6:96.
The mammalian circadian timing system rhythmically controls most aspects of behaviour and physiology over the 24 h. The underlying basic component of this system is a molecular clock present in virtually every cell and controlled by a genetic network. Self-sustained oscillations of these circadian clocks are synchronised by external or internal time cues and in turn coordinate key cellular processes such as signalling, cell cycle, and metabolism. While the molecular makeup of circadian clock is relatively well known, we are still far from fully understanding how the clock mechanism is integrated with other important processes to ensure optimal temporal coordination at the molecular, cellular and physiological levels. This is a critical issue because circadian misalignment or disruption as observed for example in workers exposed to rotating shift work compromise health and wellbeing. Indeed, experimental and clinical evidence increasingly supports the hypothesis that poor circadian coordination is a risk factor for major pathologies such as cancer, cardiovascular, metabolic, inflammatory and sleep disorders. In addition, tolerability and efficacy of treatments is strongly influenced by the time of administration because the circadian system also controls key drug pharmacology determinants. Accordingly, the concept of chronotherapy aims at integrating circadian timing and pharmacology in order to improve the therapeutic index of drugs through appropriate timing of delivery. The network and the dynamic nature of the circadian clock mechanism makes it difficult to investigate and understand its behaviour when coupled with input and output pathways or other genetic or biochemical networks, using experimental approaches exclusively. We have in two previous projects successfully combined experimental and mathematical modelling approaches to (i) provide the proof of principle that circadian data based modelling can predict optimal timing of irinotecan delivery leading to improved tolerability in a preclinical setting and (ii) demonstrate the consequences of the coupling between the clock and the cell cycle on the dynamical behaviour of the system in proliferating cells. Although such systems biology approach is potentially powerful, current modelling approaches still suffer from several limitations because they were not initially developed for genetic networks involving chronometric time while parameter estimation remains challenging. The HyClock project gathers a multidisciplinary team of experts in computer sciences, mathematical modelling, chronobiology and chronopharmacology to develop novel formal methods and hybrid modelling frameworks and apply them to the analysis and understanding of circadian clock function in mammals. This novel modelling strategy will be first used to predict and analyse how the coupled circadian clock-cell cycle network responds to physiological synchronisation in healthy cells with consequences on proliferation. Second, we will investigate in vivo using experimental design guided by these hybrid modelling approach how we can reinforce circadian timing system coordination of the host through synchronisation, in order to improve the tolerability to treatments using the widely used anticancer targeted agent everolimus (mTOR inhibitor) and cytostatic chemotherapeutic agent irinotecan (Top1 inhibitor) as model drugs. HyClock is expected to provide a general and innovative approach as well as invaluable tools and information for both the modelling of biological time and for the forthcoming personalization of chronotherapy.
Monsieur Franck DELAUNAY (Institut de Biologie Valrose)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IRCCyN Institut de Recherche en Communications et Cybernétique de Nantes
Inria Paris-Rocquencourt Institut National de la Recherche en Informatique et Automatique
I3S Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis
INSERM Rythmes Biologiques et Cancer
CNRS IBV Institut de Biologie Valrose
Help of the ANR 551,996 euros
Beginning and duration of the scientific project: September 2014 - 36 Months