An Inactivation Switch Enables Rhythms in a Neurospora Clock Model

Autonomous endogenous time-keeping is ubiquitous across many living organisms, known as the circadian clock when it has a period of about 24 h. Interestingly, the fundamental design principle with a network of interconnected negative and positive feedback loops is conserved through evolution, although the molecular components differ. Filamentous fungus Neurospora crassa is a well-established chrono-genetics model organism to investigate the underlying mechanisms. The core negative feedback loop of the clock of Neurospora is composed of the transcription activator White Collar Complex (WCC) (heterodimer of WC1 and WC2) and the inhibitory element called FFC complex, which is made of FRQ (Frequency protein), FRH (Frequency interacting RNA Helicase) and CK1a (Casein kinase 1a). While exploring their temporal dynamics, we investigate how limit cycle oscillations arise and how molecular switches support self-sustained rhythms. We develop a mathematical model of 10 variables with 26 parameters to understand the interactions and feedback among WC1 and FFC elements in nuclear and cytoplasmic compartments. We performed control and bifurcation analysis to show that our novel model produces robust oscillations with a wild-type period of 22.5 h. Our model reveals a switch between WC1-induced transcription and FFC-assisted inactivation of WC1. Using the new model, we also study the possible mechanisms of glucose compensation. A fairly simple model with just three nonlinearities helps to elucidate clock dynamics, revealing a mechanism of rhythms' production. The model can further be utilized to study entrainment and temperature compensation

Network properties of the mammalian circadian clock

The biological clock regulates daily and seasonal rhythms in mammals. This clock is located in the suprachiasmatic nuclei (SCN), which are two small nuclei each consisting of 10,000 neurons. The neurons of the SCN endogenously generate a rhythm of approximately 24 hours. Under the influence of the light-dark cycle, the SCN produce a coordinated output that is subjected to daily environmental changes. The adaptation to the light-dark cycle is a property of the neuronal network of the SCN. This neuronal network also explains the adjustment to long summer days and short winter days, and to shifts in the light-dark cycle caused by transatlantic flights or shift work. In this thesis the neuronal network of the SCN is investigated using computational techniques. The computer simulations were directed by experimental results, while, vice versa, new experiments were guided by results from the simulations. These coordinated efforts of computational science and life sciences show how properties emerge at the neuronal network level, that are not present in individual cells.NWO, program grant nr 805.47.212 ‘From Molecule to Cell’ and ASCI graduate schoolUBL - phd migration 201