Cell mass and cell cycle dynamics of an asynchronous budding yeast population: Experimental observations, flow cytometry data analysis, and multi‐scale modeling

Abstract

Despite traditionally regarded as identical, cells in a microbial cultivation present a distribution of phenotypic traits, forming a heterogeneous cell population. Moreover, the degree of heterogeneity is notably enhanced by changes in micro-environmental conditions. A major development in experimental single-cell studies has taken place in the last decades. It has however not been fully accompanied by similar contributions within data analysis and mathematical modeling. Indeed, literature reporting, for example, quantitative analyses of experimental single-cell observations and validation of model predictions for cell property distributions against experimental data is scarce. This study focuses on the experimental and mathematical description of the dynamics of cell size and cell cycle position distributions, of a population of Saccharomyces cerevisiae, in response to the substrate consumption observed during batch cultivation. The good agreement between the proposed multi-scale model (a population balance model [PBM] coupled to an unstructured model) and experimental data (both the overall physiology and cell size and cell cycle distributions) indicates that a mechanistic model is a suitable tool for describing the microbial population dynamics in a bioreactor. This study therefore contributes towards the understanding of the development of heterogeneous populations during microbial cultivations. More generally, it consists of a step towards a paradigm change in the study and description of cell cultivations, where average cell behaviors observed experimentally now are interpreted as a potential joint result of various co-existing single-cell behaviors, rather than a unique response common to all cells in the cultivation.

Exploring the potential of the glycerol-3-phosphate dehydrogenase 2 (GPD2) promoter for recombinant gene expression in Saccharomyces cerevisiae

“…For the wild type reporter strain TMB4140, four typical growth stages [13] of aerobic batch cultivation mode were observed (Fig. 1A), i.e.…”

Microbial heterogeneity affects bioprocess robustness: Dynamic single‐cell analysis contributes to understanding of microbial populations

“…Whereas this technique can be automated for image capture and analysis, it is not applicable for routine analysis of bioprocesses. However, automated FC could be applied for the estimation of the transient dynamics between subpopulation by the application of efficient mathematical algorithm, such as population balance models that have been discussed previously [38,39]. This concept is illustrated in Fig.…”

“…This approach could greatly reduce the computational cost and save resources for the integration of complex biological mechanisms. At this level, some recent efforts have been made for the design of effective population balance models able to simulate the heterogeneity of a microbial population in bioreactors [37][38][39]. Information about environmental fluctuations is of primary importance for population dynamics [40].…”

Modeling population dynamics in a microbial consortium under control of a synthetic pheromone‐mediated communication system

“…The resulting peaks representing cells with a single or duplicated genome are assigned to the G 1 and G 2 , respectively. G 1 is associated with bud formation, therefore, the fraction represents the budding index .…”