A Computational Investigation Of The Cell Cycle Compensation And Synchronization Mechanisms

The time period required for a cell to divide it into two cells is called a cell cycle. A cell cycle contains a series of events, and in most cases, can be divided into four distinct phases:G1(gap1phase), S (DNA systhesis), G2(gap2phase), and M (mitotic phase). A full cell cycle contains four phases. The events that regulate cell cycle activities repeat themselves periodically in a strict order, ensuring that a cell either reliably completes a round of division or does nothing. Multiple developmental signals, jointly or separately, regulate the expression of genes and the modifications of proteins, making cell cycle regulation a complex network.The key feature of the cell cycle regulation mechanism is that different protein kinases are activated in specific phases, which, in turn, phosphorylate the corresponding substrates to promote the next phase. Cyclins, so named due to their cyclic expression and degradation, are the most basic components of the cell cycle regulation machinary. In correspondence, there are cyclin-dependent kinases, which, when bound and activated by cyclins, become driving components for cell cycle progression. Different cyclin/Cdks complexes successively phosphorylate different substrates at different phases to control the ordered molecular interactions. There are also cyclin-dependent kinases inhibitors, which bind and inactivate cyclin/Cdks complexes and negatively regulate cell cycle activities. To ensure strictly ordered and irreversible activities during a round of division, cell must also go through a series of checkpoints (including start checkpoint, G2/M checkpoint, metaphase-to-anaphase transition), which guarantee irreversibility of cell cycle phases.Living things need the accurate regulation of cell cycle to support survival, reproduction, growth and heredity. Simple creatures, such as bacteria and yeasts, regulate the cell cycle to adjust the rate of reproduction to adapt to external environment. Complex creatures, including all advanced metazoans, should correctly respond not only to signals from external environment but also signals from neighboring cells and tissues. This is required for the complex growth and patterning of tissues and organs. Dysregulation of cell cycle is associated with a variety of human disease. Especially, uncontrolled cell divisions are the key feature of all tumors and cancers.Since the19th century, scientists have made considerable efforts to uncover the mechanisms of cell division regulation. From abundant experimental observations to a riche family of theoretical concepts, tremendous progress has been made in this field. In2001, Leland Hartwell, Paul Nurse and Timothy Hunt were awarded the2001Nobel Prize in Physiology and Medicine for their discovery of key cell cycle regulators. The three pioneers’ works uncovered molecular details of cell cycle regulation and promoted considerable basic research of cancers. With the increasing evidence of cell cycle regulation and the rapid development of computational biology, researchers now use mathematical models to look into quantitative details of the regulatory mechanisms. This thesis presents a computational study of cell cycle activities based on a model of four cell cycle phases with novel features.Because it is a hard work to use a set of mathematical equations to describe the activities of a large number of genes and proteins, computational researchers have so far mainly focused on two subsystems of the cell cycle. One is the different feedbacks in the G1/S phase (gap1and DNA systhesis phase) or the G2/M phase (gap2and mitosis), such as the Rb/E2F1feedback that controls the cell cycle start point and the string/Weel/CDKB positive and negative feedbacks that control cell mitosis. The other is the nonlinear properties of important feedbacks, for example, the regulation of CDKE/A/B by phosphorylation and dephosphorylation. Very few models have been reported on the regulation of the full cell cycle.A prominent feature of all biological systems, including the cell cycle regulation system, is their impressive robustness. In simple words, robustness means that when a biology system is perturbed by external or internal signals, it can maintain its structure and function. An important and interesting aspect of the robustness of the cell cycle regulation system is that, when a cell is perturbed by an external or internal signal that an impact on a specific phase (for example, to reduce the duration of the phase), the cell can prolong the durations of other phases to maintain the whole cell cycle unchanged or slightly changed.This thesis describes our computational study of the cell cycle regulation system in Drosophila. Based on an integration of experimental findings, we built a new computational model of the complete cell cycle. The model covers all key components in regulatory feedbacks, including two cyclin-dependent kinases inhibitors. The23ordinary-differential-equations (ODEs) in each cell were solved using the second-order Runge-Kutta method with adaptive time step. In addition to computing continuous changes of molecular concentrations as conventionally performed in previous studies, we defined and captured discrete events of molecular interactions. Analysis of the sequences and orders of discrete events reveals some novel aspects of the cell cycle regulation mechanism. Before simulation, a through examination of parameters was made. The model showed high robustness agaist significant changes of parameter values. In a recognized sense, this gives the model necessary justification. We then specifically explored the mechanisms of the cell cycle compensation and cell cycle synchronization happened in population of3x3cells.The main points of the methods1are as follows:a) Identify all important molecules in the cell cycle regulation system.b) Simplify the complex regulation system into a concise network.c) Use an ordinary differential equation to describe the interactions of a molecule with others and compute the concentration of the molecule.d) Use the facilities of a modeling platform to solve the23ODEs using the second-order Runge-Kutta method with adaptive time step.e) Define and capture discrete events of molecule interactions.f) Adjust equations and tune parameters to refine the model, making its simulation results agreeing with experimental observations.g) Increase and decrease each parameter50%to check if the model is sensitive to parameters changes.h) Simulate the phenomenon of cell cycle compensation.i) Simulate the phenomenon of cell synchronization.j) Analyze the sequences and orders of discrete signaling events. k) Examine the impact of important molecules, including E2F1, Dap and Rux, on cell cycle regulation.The main points of the results are as follows:a) We found that overexpression of Dap, a cyclin E/Cdk2-specific inhibitor, causes prolonged G1/S phase with shortened G2/M phase, and overexpression of Weel, a Cdkl inhibitor, causes prolonged G2/M phase with shortened G1/S phase. In both cases while the whole cell cycle was only slightly changed.b) E2F1is the pivotal component controlling the long-range G1/S and G2/M compensatory mechanism.c) During cell cycle synchronization, the length of G2or G1phase of some cells is significantly adjusted by the decrease of growth factors and/or the increase of cell cycle inhibitors. E2F1, again, plays an important role in this situation. It turns out that cell cycle synchronization is a special case of cell cycle compensation.