Dimerization of transcription factors in gene expression models: the control of Hmp synthesis by NsrR as a case of study
University of Lethbridge. Faculty of Arts and Science
Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry
Many transcription factors act as dimers or higher oligomers. The effects of dimerization of transcription factors in gene expression models are not well studied. However, explicit consideration of dimers and, especially, of their regulation, may affect the dynamical behavior of a model. In the present work, I study how the effects of dimerization of transcriptional factors impact gene expression and compare the results between models for the control of transcription assuming monomeric or dimeric transcription factors. NsrR is a nitric oxide (NO) sensor and a key regulator of NO metabolism in a number of bacterial species. NsrR uses an iron-sulfur cluster to sense NO. NsrR binds to gene promoters as a dimer. In Streptomyces, NsrR acts a repressor to regulate only two independent copies of the hmp gene and the nsrR gene. Nitrosylation of an iron-sulfur cluster in each NsrR monomer affects the ability of NsrR to bind to the promoters of these genes. Hmp catalyzes the detoxifying reaction of NO to the less toxic nitrate ion. In this study, I have built a base model in which NsrR acts as a (theoretical) monomer, and then I have generated two models where NsrR is a dimer that differ in the assumed effects of uneven nitrosylation of the two monomers in a dimer. Most of the parameters were estimated from the literature. The model equations for the three models were generated by using the rule-based modelling software BioNetGen. The monomer and dimer models behave essentially identically either at the default parameters estimated from the literature, or with changes in most of the parameters. However, by changing binding parameters for NsrR-promoter complexes or the rate of recycling of nitrosylated NsrR to the intact holo-protein, the monomer and dimer models can be made to behave differently.
Rule-base modelling , BioNetGen , Hmp synthesis , Transcription factor , NsrR , Dimer , Monomer