title: Modeling epigenetic regulation of PRC1 protein accumulation in the cell cycle.
abstract: BACKGROUND
  Epigenetic regulation contributes to many important processes in biological cells. Examples include developmental processes, differentiation and maturation of stem cells, evolution of malignancy and other. Cell cycle regulation has been subject of mathematical modeling by a number of authors that resulted in many interesting models and application of analytic techniques ranging from stochastic processes to partial differential equations and to integral, functional and operator equations. In this paper we address the question of how the regulation of protein contents influences the long-term dynamics of the population. To accomplish this, we follow the philosophy of a 1984 model by Kimmel et al., but adjust the details to fit the experimental data on protein PRC1 from a more recent paper.
  
  
  RESULTS
  We built a model of cell cycle dynamics of the PRC1 and fitted it to the data made available by Cohen and his co-authors. We have run the model for a large number of cell generations, recording the PRC1 contents in all cells of the resulting pedigree, at constant time intervals. During cell division the PRC1 is unequally divided between daughter cells. The picture emerging from simulations of Data set 1 is that of a very well-tuned regulatory circuit that provides a stable distribution of PRC1 contents and interdivision times. Data set 2 seems qualitatively different, with more variation in cell cycle duration.
  
  
  CONCLUSIONS
  The main question we address is whether the regulatory feedbacks deduced from single cell cycle data provide epigenetic regulation of cell characteristics in long run. PRC1 is a good candidate because of its role in setting timing of division. Findings of the current paper include tight regulation of the cell cycle (particularly the timing of the cell cycle) even that PRC1 is only one of the players in cell dynamics. Understanding that association, even close, does not necessarily imply causation, we consider this an interesting and important result.
authors.affiliation: Systems Engineering Group, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland. marzena.dolbniak@polsl.pl.
authors.forename: Marzena
authors.initials: M
authors.lastname: Dolbniak
authors.affiliation: Systems Engineering Group, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland. kimmel@rice.edu.|Departments of Statistics and Bioengineering, Rice University, MS 138, 6100 Main, Houston, TX, 77005, USA. kimmel@rice.edu.
authors.forename: Marek
authors.initials: M
authors.lastname: Kimmel
authors.affiliation: Systems Engineering Group, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland. jaroslaw.smieja@polsl.pl.
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Smieja
mesh_terms: D002453:Cell Cycle; D018797:Cell Cycle Proteins / Q000235:genetics* / Q000378:metabolism; D044127:Epigenesis, Genetic; D005786:Gene Expression Regulation; D006801:Humans; D008957:Models, Genetic
chemical_list: D018797:Cell Cycle Proteins; C116662:PRC1 protein, human