Towards high throughput metabolic flux analysis in plants

Research on plant metabolism is currently experiencing the common use of various omics methods creating valuable information on the concentrations of the cell's constituents. However, little is known about in vivo reaction rates, which can be determined by Metabolic Flux Analysis (MFA), a combination of isotope labeling experiments and computer modeling of the metabolic network. Large-scale applications of this method so far have been hampered by tedious procedures of tissue culture, analytics, modeling and simulation. By streamlining the workflow of MFA, the throughput of the method could be significantly increased. We propose strategies for these improvements on various sub-steps which will move flux analysis to the medium-throughput range and closer to established methods such as metabolite profiling. Furthermore, this may enable novel applications of MFA, for example screening plant populations for traits related to the flux phenotype.     

Towards a metabolic and isotopic steady state in CHO batch cultures for reliable isotope-based metabolic profiling

Attaining metabolic and isotopic balanced growth is one critical condition for physiological studies using isotope-labeled tracers, but is very difficult to obtain in batch culture due to the extensive metabolite exchange with the surrounding medium and related physiological changes. In the present study, we investigated metabolic and isotopic behavior of CHO cells in differently designed media. We observed that the assumption of balanced cell growth cannot be justified in batch culture of CHO cells directly using conventional, commercially available media. By systematically redesigning media composition and characterizing metabolic steady state based on mass balances and measurement of labeling dynamics, we achieved balanced cell growth for the main cellular substrates in CHO cells. This was done in a step-by-step analysis of growth and primary metabolism of CHO cells with the use of [U-¹³C]glucose feeding and adjusting concentrations of amino acids in the growth medium. The optimized media obtained at the end of the study provide balanced growth and isotopic steady state or at least asymptotic steady state. As a result, we established a platform to conduct isotope-based physiological studies of mammalian systems more reliably and therefore well suited for later use in metabolic profiling of mammalian systems such as ¹³C-labeled metabolic flux analysis.     

Elucidating the role of copper in CHO cell energy metabolism using 13C metabolic flux analysis

¹³C‐metabolic flux analysis was used to understand copper deficiency‐related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein‐producing CHO cells. Stationary‐phase labeling experiments with U‐¹³C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed‐batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC‐MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux. Fluxes were evaluated 300 times from stoichiometrically feasible random guess values and their confidence intervals calculated by Monte Carlo simulations. Results from metabolic flux analysis exhibited significant carbon redistribution throughout the metabolic network in cells under Cu deficiency. Specifically, glycolytic fluxes increased (25%–79% relative to glucose uptake) whereas fluxes through the TCA and pentose phosphate pathway (PPP) were lower (15%–23% and 74%, respectively) compared with the Cu‐containing condition. Furthermore, under Cu deficiency, 33% of the flux entering TCA via the pyruvate node was redirected to lactate and malate production. Based on these results, we hypothesize that Cu deficiency disrupts the electron transport chain causing ATP deficiency, redox imbalance, and oxidative stress, which in turn drive copper‐deficient CHO cells to produce energy via aerobic glycolysis, which is associated with excessive lactate production, rather than the more efficient route of oxidative phosphorylation. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1179–1186, 2015     

Towards high resolution analysis of metabolic flux in cells and tissues

1. Download : Download high-res image (172KB)
2. Download : Download full-size image

     

Stable isotope-assisted metabolomics to detect metabolic flux changes in mammalian cell cultures

1. Download : Download high-res image (158KB)
2. Download : Download full-size image

Highlights► Stable isotope-assisted metabolomics is powerful to determine metabolic fluxes. ► Stable isotope-assisted metabolomics is more complex for mammalian cell cultures. ► Biotechnological processes can be improved by assessing metabolic flux changes. ► Metabolic flux analysis is an attractive tool for toxicity studies. ► There is a huge potential for future applications on mammalian systems.     

Proteome analysis of antibody-producing CHO cell lines with different metabolic profiles

Two-dimensional gel electrophoresis and tandem mass spectrometry were used to identify proteins associated with a metabolic shift during fed-batch cultures of two recombinant antibody-producing CHO cell lines. The first cell line underwent a marked change in lactate metabolism during culture, initially producing lactate and then consuming it, while the second cell line produced lactate for a similar duration but did not later consume it. The first cell line displayed a declining specific antibody productivity during culture, correlating to the 2-D gel results and the intracellular antibody concentration determined by HPLC. Several statistical analysis methods were compared during this work, including a fixed fold-change criterion and t-tests using standard deviations determined in several ways from the raw data and mathematically transformed data. Application of a variance-stabilizing transformation enabled the use of a global empirical standard deviation in the t-tests. Most of the protein spots changing in each cell line did not change significantly in the other cell line. A substantial fraction of the changing proteins were glycolytic enzymes; others included proteins related to antibody production, protein processing, and cell structure. Enolase, pyruvate kinase, BiP/GRP78, and protein disulfide isomerase were found in spots that changed over time in both cell lines, and some protein changes differed from previous reports. These data provide a foundation for future investigation of metabolism in industrially relevant mammalian cell culture processes, and suggest that along with differences between cell types, the proteins expressed in cultures with low lactate concentrations may depend on how those conditions were generated.     

Thermodynamics-based metabolic flux analysis

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.     

Parameter identification of a dynamic model of CHO cell cultures: an experimental case study

In this paper, we address the problem of parameter identification in dynamic models of animal cultures, and we propose a step-by-step procedure, which gradually considers more detailed models. This procedure allows subsets of parameters to be estimated at each step, which can be used in the initialization of the next identification step. Finally, the full parameter set can be re-estimated starting from the results of the last step. The efficiency of the procedure is illustrated with a simulation case study and with the identification of a dynamic model from experimental data collected in CHO cell culture.     

Simple and efficient control of CHO cell cultures

Cell cultures must tightly be kept under control in order to guarantee a sufficiently small variability in the protein product quality. A simple and efficient technique for CHO-cell cultures is presented that allows keeping the viable cell count X(v) and the specific growth rate μ of the cells on predefined trajectories. As X(v) and μ cannot directly be measured online, they are controlled indirectly via the total mass of oxygen consumed. Online values of the latter can precisely be estimated from off gas analysis, i.e. from the O? volume ratio measured in the vent line and air flow rate measurements. In glutamine-limited fed-batch cultivations, the glutamine feed rate can be manipulated in such a way that the viable cell density and the specific growth rate are kept on predefined profiles for nearly the entire cultivation time. The viability of the cells is not affected by the closed loop control actions. The technique was validated with CHO-cells cultured in a 2.5-L fully instrumented stirred tank bioreactor. It is shown that the controller is able to run the process exactly on predefined tracks with a high batch-to-batch reproducibility. By means of six fed-batch cultivations of CHO cells it was shown that a remarkable reproducibility of viable cell concentration could be achieved throughout 140 h cultivation time.     

Automated flow cytometry for monitoring CHO cell cultures

Flow cytometry has been used to accurately monitor cell events that indicate the spatio-temporal state of a bioreactor culture. The introduction of process analytical technology (PAT) has led to process improvements using real-time or semi real-time monitoring systems. Integration of flow cytometry into an automated scheme for improved process monitoring can benefit PAT in bioreactor-based biopharmaceutical productions by establishing optimum process conditions and better quality protocols. Herein, we provide detailed protocols for establishing an automated flow cytometry system that can be used to investigate and monitor cell growth, viability, cell size, and cell cycle data. A method is described for the use of such a system primarily focused on CHO cell culture, although it is foreseen the information gathered from automated flow cytometry can be applied to a variety of cell lines to address both PAT requirements and gain further understanding of complex biological systems.     

Metabolic flux rewiring in mammalian cell cultures

1. Download : Download high-res image (203KB)
2. Download : Download full-size image

     

Metabolic flux analysis of CHO cell metabolism in the late non‐growth phase

Chinese hamster ovary (CHO) cell cultures are commonly used for production of recombinant human therapeutic proteins. Often the goal of such a process is to separate the growth phase of the cells, from the non‐growth phase where ideally the cells are diverting resources to produce the protein of interest. Characterizing the way that the cells use nutrients in terms of metabolic fluxes as a function of culture conditions can provide a deeper understanding of the cell biology offering guidance for process improvements. To evaluate the fluxes, metabolic flux analysis of the CHO cell culture in the non‐growth phase was performed by a combination of steady‐state isotopomer balancing and stoichiometric modeling. Analysis of the glycolytic pathway and pentose phosphate pathway (PPP) indicated that almost all of the consumed glucose is diverted towards PPP with a high NADPH production; with even recycle from PPP to G6P in some cases. Almost all of the pyruvate produced from glycolysis entered the TCA cycle with little or no lactate production. Comparison of the non‐growth phase against previously reported fluxes from growth phase cultures indicated marked differences in the fluxes, in terms of the split between glycolysis and PPP, and also around the pyruvate node. Possible reasons for the high NADPH production are also discussed. Evaluation of the fluxes indicated that the medium strength, carbon dioxide level, and temperature with dissolved oxygen have statistically significant impacts on different nodes of the flux network. Biotechnol. Bioeng. 2011; 108:82–92. © 2010 Wiley Periodicals, Inc.     

Impact of dynamic online fed-batch strategies on metabolism, productivity and N-glycosylation quality in CHO cell cultures

As we pursue the means to improve yields to meet growing therapy demands, it is important to examine the impact of process control on glycosylation patterns to ensure product efficacy and consistency. In this study, we describe a dynamic on-line fed-batch strategy based on low glutamine/glucose concentrations and its impact on cellular metabolism and, more importantly, the productivity and N-glycosylation quality of a model recombinant glycoprotein, interferon gamma (IFN-gamma). We found that low glutamine fed-batch strategy enabled up to 10-fold improvement in IFN-gamma yields, which can be attributed to reduced specific productivity of ammonia and lactate. Furthermore, the low glutamine concentration (0.3 mM) used in this fed-batch strategy could maintain both the N-glycosylation macro- and microheterogeneity of IFN-gamma. However, very low glutamine (<0.1 mM) or glucose (<0.70 mM) concentrations can lead to decreased sialylation and increased presence of minor glycan species consisting of hybrid and high-mannose types. This shows that glycan chain extension and sialylation can be affected by nutrient limitation. In addition to nutrient limitation, we also found that N-glycosylation quality can be detrimentally affected by low culture viability. IFN-gamma purified at low culture viability had both lower sialylation as well as glycans of lower molecular masses, which can be attributed to extensive degradation by intracellular glycosidases released by cytolysis. Therefore, in order to maintain good N-glycosylation quality, there is a need to consider both culture viability and nutrient control setpoint in a nutrient-limiting fed-batch culture strategy. A greater understanding of these major factors that affect N-glycosylation quality would surely facilitate future development of effective process controls.     

Genetically constrained metabolic flux analysis

Significant progress has been made in using existing metabolic databases to estimate metabolic fluxes. Traditional metabolic flux analysis generally starts with a predetermined metabolic network. This approach has been employed successfully to analyze the behaviors of recombinant strains by manually adding or removing the corresponding pathway(s) in the metabolic map. The current work focuses on the development of a new framework that utilizes genomic and metabolic databases, including available genetic/regulatory network structures and gene chip expression data, to constrain metabolic flux analysis. The genetic network consisting of the sensing/regulatory circuits will activate or deactivate a specific set of genes in response to external stimulus. The activation and/or repression of this set of genes will result in different gene expression levels that will in turn change the structure of the metabolic map. Hence, the metabolic map will automatically "adapt" to the external stimulus as captured by the genetic network. This adaptation selects a subnetwork from the pool of feasible reactions and so performs what we term "environmentally driven dimensional reduction." The Escherichia coli oxygen and redox sensing/regulatory system, which controls the metabolic patterns connected to glycolysis and the TCA cycle, was used as a model system to illustrate the proposed approach.     

Interpreting metabolic complexity via isotope-assisted metabolic flux analysis

Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output). We then describe how iMFA enables analysis of metabolic complexities and discovery of metabolic pathways. Our goal is to expand the use of iMFA in metabolism research, which is essential to maximizing the impact of metabolic experiments and continuing to advance iMFA and biocomputational techniques.     

代谢流量比率分析及其在代谢工程中的应用

细胞内代谢反应流量在系统理解细胞代谢特性和指导代谢工程改造等方面都起着重要的作用。由于代谢流量难以直接测量得到,在很多情况下通过跟踪稳定同位素在代谢网络中的转移并进行相应的模型计算能有效地定量代谢流量。代谢流量比率分析法能够高度体现系统的生物化学真实性、辨别细胞代谢网络的拓扑结构,并且能够相对简单快速地定量反应速率等,因此受到代谢工程研究者越来越多的重视。以下着重介绍并讨论了利用代谢物同位体分布信息分析关键代谢节点合成途径的流量比率、基于流量比率的代谢流量解析、以及应用于代谢工程等的相关原理、实验测量、数据分析、使用条件等,以期充分发挥代谢流量比率分析法的优势,并将其拓展推广至更多细胞体系的代谢特性阐明和代谢工程改造中去。