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Keulers, M., Sazuki, T., Satroutdinov, A.D., Kuriyama, H. (1996) Autonomous metabolic oscillations in continuous culture of saccharomyces cerevisiae grown on ethanol, FEMS Micro Letters, 142, 253-258.

has been cited by the following article:

• TITLE: Extending cell cycle synchrony and deconvolving population effects in budding yeast through an analysis of volume growth with a structured Leslie model

  AUTHORS: Chris C. Stowers, Asmita M. Boczko

  KEYWORDS: Quantitative Biology, Systems Biology, Volume Filtration, Cell Cycle

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.10, October 28, 2010

  ABSTRACT: Budding yeast are a fundamental organism at the center of systems biology research. Understanding the physiology and kinetics of their growth and division is fundamental to the design of models of gene regulation and the interpretation of experimental measurements. We have developed a Leslie model with structured volume and age classes to understand population growth and cell cycle synchrony in budding yeast. The model exhibits broad agreement with a variety of experimental data. The model is easily annotated with volume milestones and cell cycle phases and at least three distinct goals are realizable: 1) One can investigate how any single cell property manifests itself at the population level. 2) One can deconvolve observed population averages into individual cell signals structured by volume and age. 3) One can investigate controllability of the population dynamics. We focus on the latter question. Our model was initially designed to answer the question: Can continuous volume filtration extend synchrony? To date, most general experimental methods can produce an initially synchronous population whose synchrony decays rapidly over three or four cell cycles. Our model predicts that continuous volume filtration can extend this maintenance of synchrony by an order of magnitude. Our data inform the development of simple fluidic devices to extend synchrony in continuous culture at all scales from nanophysiometers to bioreactors.