From Single Cells to Microbial Population Dynamics: Modelling in Biotechnology Based on Measurements of Individual Cells

Abstract

The development of dynamic modelling of microbial populations in bioprocesses is reviewed. In the 1960s Arnold Fredrickson established the theoretical basis of such models, and other researchers have subsequently advanced them. This review explores the relationships that describe cell proliferation and evaluates the importance of the application of flow cytometry to the fundamental parameterisation of the models for their use in bioprocess engineering. The section "Individual-Based Modelling" discusses recent theoretical developments. Delay-differential equations are demonstrated to describe accurately temporal variation of the cell proliferation cycle and specialised approaches and related iconography are applied to stochastic and deterministic modelling of stages of cellular development. Synchronised cultures of the bacterium Cupriavidus necator were prepared and monitored using a flow cytometer. The data obtained demonstrate that cell proliferation could be simulated quantitatively using the developed model.

Modeling of plant in vitro cultures: Overview and estimation of biotechnological processes

“…First models were simple in structure or segregation grade and dealt mainly with common microorganisms like bacteria and yeasts (Bailey, ). However, the efficacy of these simple approaches pertained only to small scale cultivations, while the population heterogeneity found in larger, industrial scale operations required the formation of dynamic models (Bley, ). With growing interest in fungi cultivation, biotechnological models became increasingly complex (Krull et al, ): segregated models are obligatory for fungi with hyphae growth and for growth of HR networks (Hjortso, ).…”

“…For single cell analysis of plant cell cultures, the tool of flow cytometry became indispensable. Since its broad implementation in medicinal laboratories and incremental implementation in microbiological and biotechnological laboratories in the mid‐1990s (Kottmeier et al, ), the flow cytometer is perfectly suited for process monitoring [e.g., cell number, viability, detection of inclusion bodies, and expression markers like GFP (Krull et al, ; Müller and Bley, )], and therefore offers a useful method for obtaining data to establish and maintain individual‐based models, especially in dynamic populations (Bley, ). The applicability of flow cytometry to particle size measurements is limited and the size of plant cells as well as fact that they usually occur as aggregates render this approach not applicable for measurements of intact plant cells.…”

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

“…Ultimately, industry needs to be able to engineer heterogeneity to obtain better yields and more robust processes. This requires both quantitative evaluation of the change of individual cells in time and of their interaction with the environment ( Bley, 2011 ; Sauer and Mattanovich, 2012 ). Furthermore, this information needs to be included in mathematical frameworks used for design and control in order to have a realistic representation of the bioprocesses and to improve their performance.…”

Diversity and space–time dynamics of endophytic archaea from sugar beet in the north slope of Tianshan Mountain revealed by 454 pyrosequencing and T-RFLP

“…However, due to the unknown conditions for growth requirements of many archaea and the presence of cells in a viable but non-cultivable state, the proportion of microbial diversity detected by conventional cultivation techniques is less than 1 % of the microbial species present (Amann et al 1995;Bley 2011). Culture-dependent biodiversity studies of the endophytic community are somewhat limited.…”