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Kinetics on the Lysogeny/Lysis Switch of Phageλ and Informatics on the Cell Wall Lytic Enzyme

Author: DingHui
Tutor: LuoLiaoFu
School: Inner Mongolia University
Course: Theoretical Physics
Keywords: Lysogenic / cracking change Kinetic model Adiabatic approximation Cell wall lyase Hydrophobic and hydrophilic amino acids
CLC: Q939.4
Type: PhD thesis
Year: 2008
Downloads: 236
Quote: 1
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Abstract

This paper discusses the λ phage lysogenic / pyrolysis kinetic behavior change, and cell wall enzyme cleavage of information studies. This is related to the biological functions and phage two important aspects. Gene regulatory networks in the biological reaction process plays a key role. In order to understand gene regulatory networks of the physical and chemical properties, some researchers have proposed a variety of biochemical reactions models to describe the interaction of gene regulatory networks and use these models to predict the results of biochemical reactions. E. coli infection by phage λ life cycle regulation is a good example of the study of gene regulatory networks. Over the past three decades, scientists have been a large number of experiments on the λ phage infection of E. coli operon regulatory protein interaction and the experimental data. Subsequently, some researchers have proposed a number of models to simulate the system. This chapter presents a operon regulatory proteins interacting with the dynamic model. Using this model of infection by E. coli phage λ state of the system stability and solvent source / cracking properties change. First, according to two regulatory proteins CI ₂, Cro ₂ and RNA polymerase λ phage binding characteristics of the right operon, the regulation of protein interactions with DNA sequence modeled as a chemical reaction equation, in order to build a 40 operon concentration on differential equations. Secondly, the use of the adiabatic approximation to simplify the reaction model. Concentration equation by solving operon obtained mRNA and protein concentrations dynamical evolution of regulatory relations, research and discussion of the system and thus the stability of each state. The results show that the system from the lysogenic state into cracking state physics to go through two bifurcation: a bifurcation from a monostable state to three o'clock; another state from three o'clock to one-shot. By calculating eigenvalues ??of each state and found lysogenic / cracking change the topological properties meet common characteristic theorems (Poincare-Hopf theory). In addition, each state of the system by calculating the entropy production rate found multiple singularities and saddle point state entropy produced stable than the melting point sources and cracking to produce high entropy state. Lysogenic state of low entropy production rate can be explained by its high system stability. Finally, by introducing synergistic effects, a brief discussion on the left operon lysogenic / cleavage transition effects. Calculation results show that both the left and right operon operon combination of CI ₂ Protein synergy between lysogenic state to make the system more stable. When λ phage lysis occurs when the infection of E. coli phage lyase produced will destroy the cell walls of the bacterial cell wall, freeing more progeny phages to infect other bacteria. Lyase is a kind of wall highly evolved, can rapidly destroy the bacterial cell wall proteins. Currently, there are two types of cell wall lyase: endolysins and autolysin. Endolysin encoded by the phage, and the bacteria from the lysin encoded by their own DNA. They are by acting on the cell wall peptidoglycan covalently sites to destroy cell walls. Such enzymes of bacterial cell wall with a high specificity, and therefore this cell wall lysing enzymes to drug development, food industry and agricultural development of a great value, especially those for the treatment of antibiotic resistant bacterial infections. To study how to control bacterial infection, the use of bioinformatics methods to determine whether a cell wall protein cleaving enzyme is essential. In the third chapter in the use of cell wall lyase amino acid hydrophobicity cheap base and amino acid composition characteristics to describe the protein sequence, based on the proposed use of Fisher discriminant (fisher discriminant) to predict the cell wall lyase. When discrimination and non-cell wall cell wall lyase lyase, the predicted results obtained 66.7% of the predicted success rate (sensitivity), but also access to the specificity of 88.6%, the overall accuracy of 80.4%. Further, the use of this method to predicting how two wall lyase: endolysin and autolysin, the overall accuracy of 92.9%. In addition, studies using this method to predict phage endolysin and non endolysins proteins predicted overall accuracy of 86.8%. All of these results indicate that our prediction method can be further controlled studies of bacteria and antimicrobial drugs provide effective information and help.

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