title: A stochastic model correctly predicts changes in budding yeast cell cycle dynamics upon periodic expression of CLN2.
abstract: In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and cln3 strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a deterministic cell cycle model. Next, in order to test the predictive ability of the stochastic model, we focus on a recent experimental study in which forced periodic expression of CLN2 cyclin (driven by MET3 promoter in cln3 background) has been used to synchronize budding yeast cell colonies. We demonstrate that the model correctly predicts the experimentally observed synchronization levels and cell cycle statistics of mother and daughter cells under various experimental conditions (numerical data that is not enforced in parameter optimization), in addition to correctly predicting the qualitative changes in size control due to forced CLN2 expression. Our model also generates a novel prediction: under frequent CLN2 expression pulses, G1 phase duration is bimodal among small-born cells. These cells originate from daughters with extended budded periods due to size control during the budded period. This novel prediction and the experimental trends captured by the model illustrate the interplay between cell cycle dynamics, synchronization of cell colonies, and size control in budding yeast.
authors.affiliation: Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: Cihan
authors.initials: C
authors.lastname: Oguz
authors.affiliation: Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: Alida
authors.initials: A
authors.lastname: Palmisano
authors.affiliation: Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
authors.forename: Teeraphan
authors.initials: T
authors.lastname: Laomettachit
authors.affiliation: Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Mathematics, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: Layne T
authors.initials: LT
authors.lastname: Watson
authors.affiliation: Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: William T
authors.initials: WT
authors.lastname: Baumann
authors.affiliation: Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: John J
authors.initials: JJ
authors.lastname: Tyson
mesh_terms: D002453:Cell Cycle; D048429:Cell Size; D016213:Cyclins / Q000235:genetics*; D015966:Gene Expression Regulation, Fungal; D008954:Models, Biological; D009154:Mutation; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000235:genetics*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics*; D013269:Stochastic Processes
chemical_list: C082721:CLN2 protein, S cerevisiae; D016213:Cyclins; D029701:Saccharomyces cerevisiae Proteins