|Keywords:||COPASI; circadian clock; systems biology; Drosophila melanogaster; genetic regulatory networks; circadian rhythms; mathematical molecular modelling; protein; mRNA; kinetic modelling; mass action kinetics; deterministic modelling; ordinary differential equations; clockwork orange; oscillations|
|Full text PDF:||http://hdl.handle.net/10182/6495|
The ability of almost all organisms to change their behaviour on a daily basis is one of the remarkable features of life on earth. This phenomenon which is called circadian rhythm is observed in diverse organisms such as algae, fruit flies and humans and is a response arising due to the rotation of the earth around the axis resulting in an internal time-keeping system. Changes in myriad of biochemical and physiological processes take place in order for an organism to adapt for changes in physical environment. The period of this process is close to 24 hours in duration, hence the name ???circadian rhythms???, from Latin circa diem meaning about a day. In the fruit fly Drosophila melanogaster, due to the increase in knowledge of genetics and molecular biology the molecular components such as genes and proteins involved in circadian rhythm and their roles are well understood. Due to the oscillatory properties of clock components they are an ideal candidate for mathematical models and many such models have been developed in the past. In this study, three new Drosophila circadian rhythm models were developed, each with three transcriptional regulatory feedback loops. Among which, two feedback loops (VRI/PDP1 and PER/TIM) are well known and have been included in earlier models. The main focus of this study is the newly discovered third feedback loops (CWO). The differences between the three models are defined by our conceptualization of three probable actions by which the newly discovered clock component CWO (Clockwork Orange) performs its dual role both as an activator and repressor of per, tim, vri, pdp1 genes, and cwo genes. We included existing in vitro understanding of molecular components and extended it to include probable molecular roles of the newly discovered clock component CWO. We based our hypothesis on discovered in vivo dynamics and by analysing the CWO protein sequence using basic bioinformatics servers. Detailed modelling in the form of probability based transcription factor binding and unbinding processes are used. All three models are expressed by a set of probability based mass action governed ordinary differential equations and the parameters were estimated using modelling tool COPASI. Due to the randomness and variation of different data sets generated for CWO activity by biologists, we made a choice to differ from a traditional approach in modelling, by not over-relaying on data generated from in vitro analysis. The reliance on wet-lab data was scaled down and we include them only to choose manageable mathematical inputs and validate a solved model. This approach gave us a relative degree of space to be innovative and permited us to test different hypothesis at conceptual level in three models. We proceeded to solve the models and validate the oscillations by testing with mutations. Outputs of our simulations will help broaden the research arguments in the field of cricadian biology. In particular our models hypothetically answers the molecular role of CWO protein.