Flow cytometry gives relevant data on cellular parameters such as DNA, RNA, and protein contents of individual cells and is therefore a powerful tool for analyzing microbial population dynamics. Relevant information about growth dynamics may be obtained from protein distribution. In fact, protein distribution is related to age distribution and depends on the law of growth of the population and the law of growth of the single cell. To extract the available information from protein distribution, we developed a computer algorithm starting from a model for growth of Saccharomyces cerevisiae. This algorithm quantitatively fits experimental protein distributions, allows a deconvolution of these distributions, and thus yields information about temporal parameters of the cell cycle and structure of yeast populations.
|Number of pages||5|
|Publication status||Published - Jan 1984|
ASJC Scopus subject areas
- Cell Biology
- Pathology and Forensic Medicine