Literature DB >> 17137668

Towards understanding of the complex structure of growing yeast populations.

Chiara Cipollina1, Marina Vai, Danilo Porro, Christos Hatzis.   

Abstract

In a growing Saccharomyces cerevisiae population, cell size is finely modulated according to both the chronological and genealogical ages. This generates the complex heterogeneous structure typical of budding yeast populations. In recent years, there has been a growing interest in developing mathematical models capable of faithfully describing population dynamics at the single cell level. A multistaged morphologically structured model has been lately proposed based on the population balance theory. The model was able to describe the dynamics of the generation of a heterogeneous growing yeast population starting from a sub-population of daughter unbudded cells. In this work, which aims at validating the model, the simulated experiment was performed by following the release of a homogeneous population of daughter unbudded cells. A biparametric flow cytometric approach allowed us to analyse the time course joint distribution of DNA and protein contents at the single cell level; this gave insights into the coupling between growth and cell cycle progression that generated the final population structure. The comparison between experimental and simulated size distributions revealed a strong agreement for some unexpected features as well. Therefore, the model can be considered as validated and extendable to more complex situations.

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Year:  2006        PMID: 17137668     DOI: 10.1016/j.jbiotec.2006.10.012

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  10 in total

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Journal:  Cell Prolif       Date:  2010-04-14       Impact factor: 6.831

2.  Experimental analysis and modelling of in vitro HUVECs proliferation in the presence of various types of drugs.

Authors:  L Mancuso; M Scanu; M Pisu; A Concas; G Cao
Journal:  Cell Prolif       Date:  2010-12       Impact factor: 6.831

3.  Experimental analysis and modelling of in vitro proliferation of mesenchymal stem cells.

Authors:  L Mancuso; M I Liuzzo; S Fadda; M Pisu; A Cincotti; M Arras; E Desogus; F Piras; G Piga; G La Nasa; A Concas; G Cao
Journal:  Cell Prolif       Date:  2009-07-10       Impact factor: 6.831

Review 4.  Growth and the cell cycle in green algae dividing by multiple fission.

Authors:  Ivan Nedyalkov Ivanov; Milada Vítová; Kateřina Bišová
Journal:  Folia Microbiol (Praha)       Date:  2019-07-25       Impact factor: 2.099

5.  Analysis of the effect of inoculum characteristics on the first stages of a growing yeast population in beer fermentations by means of an individual-based model.

Authors:  M Ginovart; C Prats; X Portell; M Silbert
Journal:  J Ind Microbiol Biotechnol       Date:  2010-09-03       Impact factor: 3.346

6.  Differences in stationary-phase cells of a commercial Saccharomyces cerevisiae wine yeast grown in aerobic and microaerophilic batch cultures assessed by electric particle analysis, light diffraction and flow cytometry.

Authors:  X Portell; M Ginovart; R Carbó; J Vives-Rego
Journal:  J Ind Microbiol Biotechnol       Date:  2010-09-04       Impact factor: 3.346

7.  Optimization of yeast cell cycle analysis and morphological characterization by multispectral imaging flow cytometry.

Authors:  Meredith E K Calvert; Joanne A Lannigan; Lucy F Pemberton
Journal:  Cytometry A       Date:  2008-09       Impact factor: 4.355

8.  Cell size control in yeast.

Authors:  Jonathan J Turner; Jennifer C Ewald; Jan M Skotheim
Journal:  Curr Biol       Date:  2012-05-07       Impact factor: 10.834

9.  Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions.

Authors:  Paul Bogdan; Bridget M Deasy; Burhan Gharaibeh; Timo Roehrs; Radu Marculescu
Journal:  Sci Rep       Date:  2014-04-28       Impact factor: 4.379

10.  Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

Authors:  Marta Ginovart; Rosa Carbó; Mónica Blanco; Xavier Portell
Journal:  Front Microbiol       Date:  2018-01-04       Impact factor: 5.640

  10 in total

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