A Genetically-Structured Deterministic Chemical Kinetic Simulation of the Life Cycle of the Biotechnologically Important Filamentous Bacteriophage M13

Bacteriophages have been central to the development of molecular biology, serving as model systems for understanding molecular phenomena and as components of important biotechnologies. Phage systems remain at the forefront of research in nanomaterials and nanomedicine and are widely employed component-generating technologies for drug and materials discovery, primarily through phage display. We describe the construction of a genetically-structured, experimentally-based computational simulation of the life cycle of the biotechnologically important filamentous bacteriophage M13. Our simulation integrates 50 years of experimental observations to evaluate and expand the system level understanding of M13. Our deterministic chemical kinetic simulation explicitly includes the molecular details of phage DNA replication, mRNA transcription, protein translation and phage particle assembly, as well as the competing protein-protein, protein-double-stranded DNA, protein-single-stranded DNA, and protein-mRNA interactions that control the timing and extent of phage production. Many aspects of M13 biology are faithfully reproduced by the simulation, including the production levels and timing of the shift between replicative form and preassembly complex DNA, quantities of phage mRNA and proteins, and the time course of assembly and release of progeny phage. The simulation was employed to evaluate the importance of various inherent and dynamic elements in the regulation of the phage life cycle. We describe the relative importance of phage genome structure, promoter and ribosome binding site strengths, and dynamic protein and mRNA levels and binding interactions in controlling the initial phage infection. The simulation that was constructed to describe the course of infection in a single cell over one cell cycle was expanded to provide a picture of the molecular interactions involved in establishing the dynamic steady states that define the persistently infected state of a cell across several cell generations. Our simulation provides a quantitative description of phage biology and highlights gaps in the present understanding of the M13 life cycle. We expect that the simulation will help prioritize future biochemical experiments and be a useful tool in designing new synthetic phage-like systems.