A kinetic model development of the M13 bacteriophage life cycle
Date
2014
Authors
Smeal, Steven William, author
Fisk, Nick, advisor
Prasad, Ashok, advisor
Gentry-Weeks, Claudia, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
A kinetic model which can simulate the M13 bacteriophage (a virus which only infects bacteria) life-cycle was created through a set of ordinary differential equations. The M13 bacteriophage is a filamentous phage with a circular single-stranded DNA genome. The kinetic model was developed by converting the biology into ordinary differential equations through careful studying of the existing literature describing the M13 life cycle. Most of the differential equations follow simple mass-action kinetics but some have an additional function, called the Hill Function, to account for special scenarios. Whenever possible, the rate constants associated with each ordinary differential equation were based off of experimentally determined constants. The literature describing M13 viral infection did not provide all of the rate constants necessary for our model. The parameters which were not experimentally determined through literature were estimated in the model based on what is known about the process. At present, no experiments were performed by our lab to verify the model or expand on the information available in the literature. However, the M13 phage model has improved the understanding of phage biology and makes some suggestions about the unknown factors that are most important to quantitatively understanding phage biology. The kinetic model is genetically structured and simulates all well-known and major features of viral phage infection beginning when the first viral ssDNA has entered the cytoplasm and ends right before the cell is ready to divide. The model includes DNA replication, transcription, translation, mRNA processing and degradation, viral protein P2 and viral DNA interaction, viral protein P5 and viral single-strand DNA (ssDNA) interaction, P5 and mRNA interactions, and the assembly of new phage. Additionally, the model has implemented an interaction of P2 and P10, which has not been directly verified through experiments, to account for the negative effect P10 has on DNA replication. The interaction of the host cell and virus infection was not explicitly modeled, but a subset of cellular resources were set aside for phage reproduction based on experimental estimates of the metabolic burden of phage infection. Specifically, limited amount of host resources RNA polymerase, DNA polymerase 3, and ribosomes were allocated to phage reproduction. All other host resources such as nucleotides and amino acids were assumed to be in abundance and did not limit phage replication. The model was verified by comparing the output of the model to a set of existing experimental results in literature. The model reproduced both the experimentally measured levels of phage proteins and mRNA, and the timing and dynamics of virus production for the first cell cycle after infection. All of the unknown parameters were based off the model results at the end of the first cell cycle. When the model was extended to account for phage production through multiple cell divisions, the model predicts the cell has the ability to cure itself from the infection in 7 - 8 cell cycles, which we found literature supporting our results after we made the conclusions. Once the model was created we studied how host resources, RNA polymerase and ribosomes, were distributed during the infection process. We were also able to replicate an experiment describing the effects that the viral DNA binding protein P5 had on the translation of five other viral proteins in-silico. The role of P5 inhibition in the viral life-cycle is unclear and our in-depth analysis of P5 function has revealed a possible explanation of how P5 translational inhibition could be an evolutionary advantage. Additionally, we proposed a mechanism which has not been strongly suggested to exist in literature. We are anticipating the development of the model will aide in the progress of phage display on filamentous phage and we believe the current model can be easily amendable to account for other phage like phages such as Ike filamentous phage. We discuss further additions and modifications to the model that will allow more exact treatment of early events in the phage life-cycle and more explicit coupling of phage life-cycle and host biology.
Description
Rights Access
Subject
M13
bacteriophage
kinetic model
control mechanisms