title: Natural biased coin encoded in the genome determines cell strategy.
abstract: Decision making at a cellular level determines different fates for isogenic cells. However, it is not yet clear how rational decisions are encoded in the genome, how they are transmitted to their offspring, and whether they evolve and become optimized throughout generations. In this paper, we use a game theoretic approach to explain how rational decisions are made in the presence of cooperators and competitors. Our results suggest the existence of an internal switch that operates as a biased coin. The biased coin is, in fact, a biochemical bistable network of interacting genes that can flip to one of its stable states in response to different environmental stimuli. We present a framework to describe how the positions of attractors in such a gene regulatory network correspond to the behavior of a rational player in a competing environment. We evaluate our model by considering lysis/lysogeny decision making of bacteriophage lambda in E. coli.
authors.affiliation: Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
authors.forename: Faezeh
authors.initials: F
authors.lastname: Dorri
authors.affiliation: Department of Computer Science, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Hamid
authors.initials: H
authors.lastname: Mahini
authors.affiliation: Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran; Department of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Sharifi-Zarchi
authors.affiliation: Department of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran; Department of Genetics at Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Totonchi
authors.affiliation: School of Computer Science, Institute for Research in Fundamental Sciences, Tehran, Iran.
authors.forename: Ruzbeh
authors.initials: R
authors.lastname: Tusserkani
authors.affiliation: School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran; School of Biological Science, Institute for Research in Fundamental Sciences, Tehran, Iran.
authors.forename: Hamid
authors.initials: H
authors.lastname: Pezeshk
authors.affiliation: National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Sadeghi
mesh_terms: D010582:Bacteriophage lambda / Q000235:genetics*; D003198:Computer Simulation; D004926:Escherichia coli / Q000166:cytology* / Q000821:virology*; D053263:Gene Regulatory Networks; D016679:Genome, Viral; D042541:Intracellular Space / Q000378:metabolism; D008242:Lysogeny / Q000235:genetics; D008954:Models, Biological; D011336:Probability
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