From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling

Author:

Cortes Michael G.12,Lin Yiruo3,Zeng Lanying45,Balázsi Gábor16

Affiliation:

1. The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA;

2. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, USA

3. Department of Computer Science and Engineering, Texas A&M University, College Station, Texas 77843, USA

4. Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA;

5. Center for Phage Technology, Texas A&M University, College Station, Texas 77843, USA

6. Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York 11794, USA

Abstract

Cellular decision making is the process whereby cells choose one developmental pathway from multiple possible ones, either spontaneously or due to environmental stimuli. Examples in various cell types suggest an almost inexhaustible plethora of underlying molecular mechanisms. In general, cellular decisions rely on the gene regulatory network, which integrates external signals to drive cell fate choice. The search for general principles of such a process benefits from appropriate biological model systems that reveal how and why certain gene regulatory mechanisms drive specific cellular decisions according to ecological context and evolutionary outcomes. In this article, we review the historical and ongoing development of the phage lambda lysis–lysogeny decision as a model system to investigate all aspects of cellular decision making. The unique generality, simplicity, and richness of phage lambda decision making render it a constant source ofmathematical modeling–aided inspiration across all of biology. We discuss the origins and progress of quantitative phage lambda modeling from the 1950s until today, as well as its possible future directions. We provide examples of how modeling enabled methods and theory development, leading to new biological insights by revealing gaps in the theory and pinpointing areas requiring further experimental investigation. Overall, we highlight the utility of theoretical approaches both as predictive tools, to forecast the outcome of novel experiments, and as explanatory tools, to elucidate the natural processes underlying experimental data.

Publisher

Annual Reviews

Subject

Cell Biology,Biochemistry,Bioengineering,Structural Biology,Biophysics

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