A DOUBLE FLOW CYTOMETRIC TAG ALLOWS TRACKING OF THE DYNAMICS OF CELL-CYCLE PROGRESSION OF NEWBORN SACCHAROMYCES-CEREVISIAE CELLS DURING BALANCED EXPONENTIAL-GROWTH

Citation
D. Porro et al., A DOUBLE FLOW CYTOMETRIC TAG ALLOWS TRACKING OF THE DYNAMICS OF CELL-CYCLE PROGRESSION OF NEWBORN SACCHAROMYCES-CEREVISIAE CELLS DURING BALANCED EXPONENTIAL-GROWTH, Yeast, 11(12), 1995, pp. 1157-1169
Citations number
37
Categorie Soggetti
Microbiology,"Biothechnology & Applied Migrobiology",Biology
Journal title
YeastACNP
ISSN journal
0749503X
Volume
11
Issue
12
Year of publication
1995
Pages
1157 - 1169
Database
ISI
SICI code
0749-503X(1995)11:12<1157:ADFCTA>2.0.ZU;2-2
Abstract
Studies on the dynamics of growth of single eukaryotic cells and their relationships with cell cycle regulations are generally carried out f ollowing cell synchronization procedures or, on a relatively low numbe r of cells, by time-lapse studies. Establishment of both time-lapse st udies and synchronous cell populations usually requires elaborate expe rimental efforts and is prone to perturb the physiological state of th e cell. In this paper we use a new flow cytometric approach which allo ws, in asynchronous growing Saccharomyces cerevisiae populations, tagg ing of both the cell age and the cell protein content of a cohort of d aughter cells at the different cell cycle set points. Since the cell p rotein content is a good estimation of the cell size, it is possible t o follow the kinetics of the cell size increase during cell cycle prog ression. The experimental findings obtained indicate an exponential in crease of the cell size during growth, that the daughter and the paren t subpopulations grow with the same specific growth rate, that the ave rage cell size increase rate of each individual cell is almost identic al to the specific growth rate of the overall population and provide t he opportunity to estimate the cell cycle length for the daughter cell population as well as the identification of the complex structure of asynchronously growing yeast populations.