Cell cycle synchronization of Cupriavidus necator by continuous phasing measured via flow cytometry

The influence of self-cycling fermentation long- and short-cycle schemes on Saccharomyces cerevisiae and Escherichia coli

Self-cycling fermentation (SCF), a cyclic process in which cells, on average, divide once per cycle, has been shown to lead to whole-culture synchronization and improvements in productivity during bioconversion. Previous studies have shown that the completion of synchronized cell replication sometimes occurs simultaneously with depletion of the limiting nutrient. However, cases in which the end of cell doubling occurred before limiting nutrient exhaustion were also observed. In order to better understand the impact of these patterns on bioprocessing, we investigated the growth of Saccharomyces cerevisiae and Escherichia coli in long- and short-cycle SCF strategies. Three characteristic events were identified during SCF cycles: (1) an optimum in control parameters, (2) the time of completion of synchronized cell division, and (3) the depletion or plateau of the limiting nutrient. Results from this study and literature led to the identification of three potential trends in SCF cycles: (A) co-occurrence of the three key events, (B) cell replication ending prior to the co-occurrence of the other two events, and (C) depletion or plateau of the limiting nutrient occurring later than the co-occurrence of the other two events. Based on these observations, microbial physiological differences were analyzed and a novel definition for SCF is proposed.

From single cells to microbial population dynamics: modelling in biotechnology based on measurements of individual cells

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.

Automated measurement and monitoring of bioprocesses: key elements of the M(3)C strategy

The state-of-routine monitoring items established in the bioprocess industry as well as some important state-of-the-art methods are briefly described and the potential pitfalls discussed. Among those are physical and chemical variables such as temperature, pressure, weight, volume, mass and volumetric flow rates, pH, redox potential, gas partial pressures in the liquid and molar fractions in the gas phase, infrared spectral analysis of the liquid phase, and calorimetry over an entire reactor. Classical as well as new optical versions are addressed. Biomass and bio-activity monitoring (as opposed to "measurement") via turbidity, permittivity, in situ microscopy, and fluorescence are critically analyzed. Some new(er) instrumental analytical tools, interfaced to bioprocesses, are explained. Among those are chromatographic methods, mass spectrometry, flow and sequential injection analyses, field flow fractionation, capillary electrophoresis, and flow cytometry. This chapter surveys the principles of monitoring rather than compiling instruments.

Origin and analysis of microbial population heterogeneity in bioprocesses

Heterogeneity of industrial production cultures is accepted to a certain degree; however, the underlying mechanisms are seldom perceived or included in the development of new bioprocess control strategies. Population heterogeneity and its basics, perceptible in the diverse proficiency of cells, begins with asymmetric birth and is found to recess during the life cycle. Since inefficient subpopulations have significant impact on the productivity of industrial cultures, cellular heterogeneity needs to be detected and quantified by using high speed detection tools like flow cytometry. Possible origins of population heterogeneity, sophisticated fluorescent techniques for detection of individual cell states, and cutting-edge Omics-technologies for extended information beyond the resolution of fluorescent labelling are highlighted.

Application of a short intracellular pH method to flow cytometry for determining Saccharomyces cerevisiae vitality

The measurement of yeast's intracellular pH (ICP) is a proven method for determining yeast vitality. Vitality describes the condition or health of viable cells as opposed to viability, which defines living versus dead cells. In contrast to fluorescence photometric measurements, which show only average ICP values of a population, flow cytometry allows the presentation of an ICP distribution. By examining six repeated propagations with three separate growth phases (lag, exponential, and stationary), the ICP method previously established for photometry was transferred successfully to flow cytometry by using the pH-dependent fluorescent probe 5,6-carboxyfluorescein. The correlation between the two methods was good (r(2) = 0.898, n = 18). With both methods it is possible to track the course of growth phases. Although photometry did not yield significant differences between exponentially and stationary phases (P = 0.433), ICP via flow cytometry did (P = 0.012). Yeast in an exponential phase has a unimodal ICP distribution, reflective of a homogeneous population; however, yeast in a stationary phase displays a broader ICP distribution, and subpopulations could be defined by using the flow cytometry method. In conclusion, flow cytometry yielded specific evidence of the heterogeneity in vitality of a yeast population as measured via ICP. In contrast to photometry, flow cytometry increases information about the yeast population's vitality via a short measurement, which is suitable for routine analysis.

Modeling synchronous growth of bacterial populations in phased cultivation

The phasing technique is a method for synchronizing cell populations in a bioreactor. Periodic changes of substrate supply and depletion can provoke a cell cycle phasing of originally stochastic scattered proliferation patterns. Synchronized cell populations characterized by changes in DNA content distribution can be monitored by flow cytometry. Thus, studies of the dynamics of single cells in specific cell cycle phases are facilitated. Here we present an age structured model framework investigating synchronized populations using delay differential equations. Applying the framework not only cell populations synchronously increasing under balanced growth conditions, but also synchronized cultures growing in continuous phasing experiments can be described. A process model developed for describing phased cultures was fitted to growth data obtained from a synchronous cultivation of Cupriavidus necator. Its potential utility is demonstrated by a quantitative process description and by its ability to identify ways in which the grade of synchrony could be improved.

Modes of cytometric bacterial DNA pattern: a tool for pursuing growth

Analyses of DNA pattern provide an excellent tool to determine activity states of bacteria. Bacterial cell cycle behaviour is generally different from the eukaryotic one and is pre-determined by the bacteria's diversity within the phylogenetic tree, and their metabolic traits. As a result, every species creates its specific proliferation pattern that differs from every other one. Up to now, just few bacterial species have been investigated and little information is available concerning DNA cycling even in already known species. This prevents understanding of the complexity and diversity of ongoing bacterial interactions in many ecosystems or in biotechnology. Flow cytometry is the only possible technique to shed light on the dynamics of bacterial communities and DNA patterns will help to unlock the hidden principles of their life. This review provides basic knowledge about the molecular background of bacterial cell cycling, discusses modes of cell cycle phases and presents techniques to both obtain DNA patterns and to combine the contained information with physiological cell states.

A cytomic approach reveals population heterogeneity ofCupriavidus necator in response to harmful phenol concentrations

The understanding of functions of cells within microbial populations or communities is certainly needed for existing and novel cytomic approaches which grip the individual scale. Population behaviour results from single cell performances and is caused by the individual genetic pool, history, life cycle states and microenvironmental surroundings. Mimicking natural impaired environments, the paper shows that the Gram-negative Betaproteobacterium Cupriavidus necator dramatically altered its population heterogeneity in response to harmful phenol concentrations. Multiparametric flow cytometry was used to follow variations in structural cellular parameters like chromosome contents and storage materials. The functioning of these different cell types was resolved by ensuing proteomics after the cells' spatial separation by cell sorting, finding 11 proteins changed in their expression profile, among them elongation factor Tu and the trigger factor. At least one third of the individuals clearly underwent starving states; however, simultaneously these cells prepared themselves for entering the life cycle again. Using cytomics to recognise individual structure and function on the microbial scale represents an innovative technical design to describe the complexity of such systems, overcoming the disadvantage of small cell volumes and, thus, to resolve bacterial strategies to survive harmful environments by altering population heterogeneity.