Modeling And Dynamical Analysis Of Biomolecular Networks

This thesis is devoted to study some related work on the modeling and dynami-cal analysis of biomolecular networks. Firstly, a brief description of relevant researchcontexts is given, including the systems biology and synthetic biology, biomolecularnetworks, microRNA, as well as chemical reactive dynamics and bifurcation theory.Secondly, the research work of the thesis is introduced, which focuses mainly on thefollowing two aspects:(1) Mechanisms generating bistability and oscillations in microRNA-mediated mo-tifsIn the past, it was believed that the regulation of gene expression is a task of reg-ulatory proteins in all organisms, and thus most research on gene regulation focusedmainly on transcriptional and post-translational regulations. In recent years, a post-transcriptional regulation manifested by small noncoding RNAs is being uncovered dueto the development of large-scale experimental and computational techniques. It has beenrecognized that the post-transcriptional regulation plays important roles in the regulationof many cellular processes. MicroRNAs are a class of about22-nucleotide non-codingRNAs. When participating in cellular processes, microRNAs mainly regulate gene ex-pression post-transcriptionally through canonical base pairing to its target mRNAs, ul-timately leading to a reduction in the levels of protein encoded by the target mRNAs.Recently computational and experimental studies have identified an abundance of mo-tifs involving microRNAs and transcriptional factors. The simplest motif is a two-nodemicroRNA-mediated feedback loop (MFL) in which a transcriptional factor regulates anmicroRNA and the transcriptional factor itself is negatively regulated by the microRNA.Here we present a general computational model for the MFL based on biochemical reg-ulations and explore its dynamics by using bifurcation analysis. Our results show thatthe MFL can behave either as switches or as oscillators, depending on the transcrip-tional factor as a repressor or an activator. These functional features are consistent withthe widespread appearance of microRNAs in fate decisions such as proliferation, dif-ferentiation, and apoptosis during development. We found that under the interplay of atranscriptional factor and an microRNA, the MFL model can behave as switches for wideranges of parameters even without cooperative binding of the transcriptional factor. Inaddition, oscillations induced by the microRNA in the MFL model require neither an ad-ditional positive feedback loop, nor self-activation of the gene, nor cooperative bindingof the transcriptional factor, nor saturated degradation. Therefore, the MFL may providea general network structure to induce bistability or oscillations. It is hoped that the resultspresented here will provide a new view on how gene expression is regulated by microR-NAs and further guidance for experiments. Moreover, the insight gained from this studyis also expected to provide a basis for the investigation of more complex biomolecularnetworks assembled by simple building blocks. (2) Coupling switches and oscillators as a means to shape cellular signals inbiomolecular systemsAs biological data on regulatory components and interactions are quickly accu-mulating, biomolecular networks underlying cellular functions are becoming more andmore complicated. Dynamical properties of these complicated biomolecular networksare impossible to understand by intuitive reasoning alone. To understand how a com-plex biomolecular network functions, a decomposition or a reconstruction process of thenetwork is often needed so as to provide new insights into the regulatory mechanismsunderlying various dynamical behaviors and also to gain qualitative knowledge of thenetwork. Unfortunately, it seems that there are still no general rules on how to decom-pose a complex network into simple modules. An alternative resolution is to decomposea complex network into small modules or subsystems with specified functions such asswitches and oscillators and then integrate them by analyzing the interactions betweenthem. The main idea of this approach can be illustrated by consider-ing a bidirectionallycoupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyz-ing the occurrence of various dynamics, although the theoretical principle may hold fora general class of networks. We show that various biomolecular signals can be shapedby regulating the coupling between the subsystems. The approach presented here can beexpected to simplify and analyze even more complex biomolecular networks.