Experimental methods and modeling techniques for description of cell population heterogeneity

Subpopulation-proteomics reveal growth rate, but not cell cycling, as a major impact on protein composition in Pseudomonas putida KT2440

Population heterogeneity occurring in industrial microbial bioprocesses is regarded as a putative effector causing performance loss in large scale. While the existence of subpopulations is a commonly accepted fact, their appearance and impact on process performance still remains rather unclear. During cell cycling, distinct subpopulations differing in cell division state and DNA content appear which contribute individually to the efficiency of the bioprocess. To identify stressed or impaired subpopulations, we analyzed the interplay of growth rate, cell cycle and phenotypic profile of subpopulations by using flow cytometry and cell sorting in conjunction with mass spectrometry based global proteomics. Adjusting distinct growth rates in chemostats with the model strain Pseudomonas putida KT2440, cells were differentiated by DNA content reflecting different cell cycle stages. The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery. In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level. In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

Variability in growth/no growth boundaries of 188 different Escherichia coli strains reveals that approximately 75% have a higher growth probability under low pH conditions than E. coli O157:H7 strain ATCC 43888

This study investigated the variation in growth/no growth boundaries of 188 Escherichia coli strains. Experiments were conducted in Luria-Bertani media under 36 combinations of lactic acid (LA) (0 and 25 mM), pH (3.8, 3.9, 4.0, 4.1, 4.2 and 4.3 for 0 mM LA and 4.3, 4.4, 4.5, 4.6, 4.7 and 4.8 for 25 mM LA) and temperature (20, 25 and 30 °C). After 3 days of incubation, growth was monitored through optical density measurements. For each strain, a so-called purposeful selection approach was used to fit a logistic regression model that adequately predicted the likelihood for growth. Further, to assess the growth/no growth variability for all the strains at once, a generalized linear mixed model was fitted to the data. Strain was fitted as a fixed factor and replicate as a random blocking factor. E. coli O157:H7 strain ATCC 43888 was used as reference strain allowing a comparison with the other strains. Out of the 188 strains tested, 140 strains (∼75%) presented a significantly higher probability of growth under low pH conditions than the O157:H7 strain ATCC 43888, whereas 20 strains (∼11%) showed a significantly lower probability of growth under high pH conditions.

Challenges in industrial fermentation technology research

Industrial fermentation processes are increasingly popular, and are considered an important technological asset for reducing our dependence on chemicals and products produced from fossil fuels. However, despite their increasing popularity, fermentation processes have not yet reached the same maturity as traditional chemical processes, particularly when it comes to using engineering tools such as mathematical models and optimization techniques. This perspective starts with a brief overview of these engineering tools. However, the main focus is on a description of some of the most important engineering challenges: scaling up and scaling down fermentation processes, the influence of morphology on broth rheology and mass transfer, and establishing novel sensors to measure and control insightful process parameters. The greatest emphasis is on the challenges posed by filamentous fungi, because of their wide applications as cell factories and therefore their relevance in a White Biotechnology context. Computational fluid dynamics (CFD) is introduced as a promising tool that can be used to support the scaling up and scaling down of bioreactors, and for studying mixing and the potential occurrence of gradients in a tank.

Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains.

Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division

Since their invention in 1994, fluorescent dyes such as carboxyfluorescein diacetate succinimidyl ester (CFSE) are used for cell proliferation analysis in flow cytometry. Importantly, the interpretation of such assays relies on the assumption that the label is divided equally between the daughter cells upon cell division. However, recent experimental studies indicate that division of cells is not perfectly symmetric and there is unequal distribution of protein between sister cell pairs. The uneven partition of protein or mass to daughter cells can lead to an overlap in the generations of CFSE-labelled cells with straightforward consequences for the resolution of individual generations. Numerous mathematical models developed so far for the analysis of CFSE proliferation assay incorporate the premise that the CFSE fluorescence intensity is halved in the two daughter cells. Here, we propose a novel modelling approach for the analysis of the CFSE cell proliferation assays which are characterized by poorly resolved peaks of cell generations in flow cytometric histograms. We formulate a mathematical model in the form of a system of delay hyperbolic partial differential equations which provides a good agreement with the CFSE histograms time-series data and allows an analytical treatment. The model is a further generalization of the recently proposed class of division- and label-structured models as it considers an asymmetric cell division. In addition, the basic structure of the cell cycle, i.e. the resting and cycling cell compartments, is taken into account. The model is used to estimate fundamental parameters such as activation rate, duration of the cell cycle, apoptosis rate, CFSE decay rate and asymmetry factor in cell division of monoclonal T cells during cognate interaction with dendritic cells.

Integration of models and experimentation to optimise the production of potential biotherapeutics

Despite decades of clinical and commercial success, the current paradigm for drug discovery and development is still empirical and costly. The many hundreds of therapeutic proteins (TPs) in the development pipeline and the FDA-led quality-by-design initiative represent opportunities to address this issue. Advances in our understanding of cellular mechanisms as well as the physicochemical and biological characteristics of TPs have enabled researchers to develop computational models that analyse or even predict molecular and cellular behaviour under different conditions. Coupled with new analytical tools, these models are increasingly used to systemise and expedite the design and optimisation of protein production processes throughout the discovery and development stages.

Extreme resistance to weak-acid preservatives in the spoilage yeast Zygosaccharomyces bailii

Weak-acid preservatives, such as sorbic acid and acetic acid, are used in many low pH foods to prevent spoilage by fungi. The spoilage yeast Zygosaccharomyces bailii is notorious for its extreme resistance to preservatives and ability to grow in excess of legally-permitted concentrations of preservatives. Extreme resistance was confirmed in 38 strains of Z. bailii to several weak-acid preservatives. Using the brewing yeast Saccharomyces cerevisiae as a control, tests showed that Z. bailii was ~3-fold more resistant to a variety of weak-acids but was not more resistant to alcohols, aldehydes, esters, ethers, ketones, or hydrophilic chelating acids. The weak acids were chemically very diverse in structure, making it improbable that the universal resistance was caused by degradation or metabolism. Examination of Z. bailii cell populations showed that extreme resistance to sorbic acid, benzoic acid and acetic acid was limited to a few cells within the population, numbers decreasing with concentration of weak acid to <1 in 1000. Re-inoculation of resistant sub-populations into weak-acid-containing media showed that all cells now possessed extreme resistance. Resistant sub-populations grown in any weak-acid preservative also showed ~100% cross-resistance to other weak-acid preservatives. Tests using (14)C-acetic acid showed that weak-acid accumulation was much lower in the resistant sub-populations. Acid accumulation is caused by acid dissociation in the higher pH of the cytoplasm. Tests on intracellular pH (pHi) in the resistant sub-population showed that the pH was much lower, ~ pH5.6, than in the sensitive bulk population. The hypothesis is proposed that extreme resistance to weak-acid preservatives in Z. bailii is due to population heterogeneity, with a small proportion of cells having a lower intracellular pH. This reduces the level of accumulation of any weak acid in the cytoplasm, thus conferring resistance to all weak acids, but not to other inhibitors.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Picoliter nDEP traps enable time-resolved contactless single bacterial cell analysis in controlled microenvironments

We present a lab-on-a-chip device, the Envirostat 2.0, which allows for the first time contactless cultivation of a single bacterial cell by negative dielectrophoresis (nDEP) in a precisely controllable microenvironment. Stable trapping in perfusing growth medium was achieved by a miniaturization of octupole electrode geometries, matching the dimensions of bacteria. Temperature sensitive fluorescent measurements showed that these reductions of microelectrode distances led to reduced Joule heating during cell manipulation. The presented miniaturization is not possible with conventional manufacturing processes. Therefore, we present a novel bonding technology, which permits miniaturization of 3D octupole electrode geometry with biocompatible materials. To exclude the influence of other cells and to enable sampling of perfusion medium from the isolated living bacterium under study, computer aided flow simulations were used to develop a microfluidic nDEP isolation procedure. The developed microchannel and microelectrode design integrates for the first time well characterized nDEP cell sorting mechanisms and time-resolved contactless single bacterial cell cultivation in a 1.7 picoliter bioreactor system. The cell type independent trapping is demonstrated with singularized Bacillus subtilis, Escherichia coli, Corynebacterium glutamicum and other industrially relevant microbes. The static and precisely controlled microenvironment resulted in a consistent and significant faster growth compared to maximal growth rates observed on population level. Preventing the influence of surfaces and cell-cell interactions, the Envirostat 2.0 chip permits total microenvironmental control by the experimenter and therefore provides major opportunities for microfluidic based cell analysis of bacteria and small eukaryotes.

Physiological heterogeneities in microbial populations and implications for physical stress tolerance

BACKGROUND

Traditionally average values of the whole population are considered when analysing microbial cell cultivations. However, a typical microbial population in a bioreactor is heterogeneous in most phenotypes measurable at a single-cell level. There are indications that such heterogeneity may be unfavourable on the one hand (reduces yields and productivities), but also beneficial on the other hand (facilitates quick adaptation to new conditions--i.e. increases the robustness of the fermentation process). Understanding and control of microbial population heterogeneity is thus of major importance for improving microbial cell factory processes.

RESULTS

In this work, a dual reporter system was developed and applied to map growth and cell fitness heterogeneities within budding yeast populations during aerobic cultivation in well-mixed bioreactors. The reporter strain, which was based on the expression of green fluorescent protein (GFP) under the control of the ribosomal protein RPL22a promoter, made it possible to distinguish cell growth phases by the level of fluorescence intensity. Furthermore, by exploiting the strong correlation of intracellular GFP level and cell membrane integrity it was possible to distinguish subpopulations with high and low cell membrane robustness and hence ability to withstand freeze-thaw stress. A strong inverse correlation between growth and cell membrane robustness was observed, which further supports the hypothesis that cellular resources are limited and need to be distributed as a trade-off between two functions: growth and robustness. In addition, the trade-off was shown to vary within the population, and the occurrence of two distinct subpopulations shifting between these two antagonistic modes of cell operation could be distinguished.

CONCLUSIONS

The reporter strain enabled mapping of population heterogeneities in growth and cell membrane robustness towards freeze-thaw stress at different phases of cell cultivation. The described reporter system is a valuable tool for understanding the effect of environmental conditions on population heterogeneity of microbial cells and thereby to understand cell responses during industrial process-like conditions. It may be applied to identify more robust subpopulations, and for developing novel strategies for strain improvement and process design for more effective bioprocessing.

Sampling techniques for single-cell electrophoresis

Cells are extraordinarily complex, containing thousands of different analytes with concentrations spanning at least nine orders of magnitude. Analyzing single cells instead of tissue homogenates provides unique insights into cell-to-cell heterogeneity and aids in distinguishing normal cells from pathological ones. The high sensitivity and low sample consumption of capillary and on-chip electrophoresis, when integrated with fluorescence, electrochemical, and mass spectrometric detection methods, offer an ideal toolset for examining single cells and even subcellular organelles; however, the isolation and loading of such small samples into these devices is challenging. Recent advances have addressed this issue by interfacing a variety of enhanced mechanical, microfluidic, and optical sampling techniques to capillary and on-chip electrophoresis instruments for single-cell analyses.

A disposable picolitre bioreactor for cultivation and investigation of industrially relevant bacteria on the single cell level

In the continuously growing field of industrial biotechnology the scale-up from lab to industrial scale is still a major hurdle to develop competitive bioprocesses. During scale-up the productivity of single cells might be affected by bioreactor inhomogeneity and population heterogeneity. Currently, these complex interactions are difficult to investigate. In this report, design, fabrication and operation of a disposable picolitre cultivation system is described, in which environmental conditions can be well controlled on a short time scale and bacterial microcolony growth experiments can be observed by time-lapse microscopy. Three exemplary investigations will be discussed emphasizing the applicability and versatility of the device. Growth and analysis of industrially relevant bacteria with single cell resolution (in particular Escherichia coli and Corynebacterium glutamicum) starting from one single mother cell to densely packed cultures is demonstrated. Applying the picolitre bioreactor, 1.5-fold increased growth rates of C. glutamicum wild type cells were observed compared to typical 1 litre lab-scale batch cultivation. Moreover, the device was used to analyse and quantify the morphological changes of an industrially relevant l-lysine producer C. glutamicum after artificially inducing starvation conditions. Instead of a one week lab-scale experiment, only 1 h was sufficient to reveal the same information. Furthermore, time lapse microscopy during 24 h picolitre cultivation of an arginine producing strain containing a genetically encoded fluorescence sensor disclosed time dependent single cell productivity and growth, which was not possible with conventional methods.