A hybrid mechanistic-empirical model for in silico mammalian cell bioprocess simulation

In cell culture processes cell growth and metabolism drive changes in the chemical environment of the culture. These environmental changes elicit reactor control actions, cell growth response, and are sensed by cell signaling pathways that influence metabolism. The interplay of these forces shapes the culture dynamics through different stages of cell cultivation and the outcome greatly affects process productivity, product quality, and robustness. Developing a systems model that describes the interactions of those major players in the cell culture system can lead to better process understanding and enhance process robustness. Here we report the construction of a hybrid mechanistic-empirical bioprocess model which integrates a mechanistic metabolic model with subcomponent models for cell growth, signaling regulation, and the bioreactor environment for in silico exploration of process scenarios. Model parameters were optimized by fitting to a dataset of cell culture manufacturing process which exhibits variability in metabolism and productivity. The model fitting process was broken into multiple steps to mitigate the substantial numerical challenges related to the first-principles model components. The optimized model captured the dynamics of metabolism and the variability of the process runs with different kinetic profiles and productivity. The variability of the process was attributed in part to the metabolic state of cell inoculum. The model was then used to identify potential mitigation strategies to reduce process variability by altering the initial process conditions as well as to explore the effect of changing CO₂ removal capacity in different bioreactor scales on process performance. By incorporating a mechanistic model of cell metabolism and appropriately fitting it to a large dataset, the hybrid model can describe the different metabolic phases in culture and the variability in manufacturing runs. This approach of employing a hybrid model has the potential to greatly facilitate process development and reactor scaling.     

Development of a kinetic metabolic model: application to Catharanthus roseus hairy root

A kinetic metabolic model describing Catharanthus roseus hairy root growth and nutrition was developed. The metabolic network includes glycolysis, pentose-phosphate pathway, TCA cycle and the catabolic reactions leading to cell building blocks such as amino acids, organic acids, organic phosphates, lipids and structural hexoses. The central primary metabolic network was taken at pseudo-steady state and metabolic flux analysis technique allowed reducing from 31 metabolic fluxes to 20 independent pathways. Hairy root specific growth rate was described as a function of intracellular concentration in cell building blocks. Intracellular transport and accumulation kinetics for major nutrients were included. The model uses intracellular nutrients as well as energy shuttles to describe metabolic regulation. Model calibration was performed using experimental data obtained from batch and medium exchange liquid cultures of C. roseus hairy root using a minimal medium in Petri dish. The model is efficient in estimating the growth rate.     

Modeling allosteric regulation of de novo pyrimidine biosynthesis in Escherichia coli

With the emergence of multifaceted bioinformatics-derived data, it is becoming possible to merge biochemical and physiological information to develop a new level of understanding of the metabolic complexity of the cell. The biosynthetic pathway of de novo pyrimidine nucleotide metabolism is an essential capability of all free-living cells, and it occupies a pivotal position relative to metabolic processes that are involved in the macromolecular synthesis of DNA, RNA and proteins, as well as energy production and cell division. This regulatory network in all enteric bacteria involves genetic, allosteric, and physiological control systems that need to be integrated into a coordinated set of metabolic checks and balances. Allosterically regulated pathways constitute an exciting and challenging biosynthetic system to be approached from a mathematical perspective. However, to date, a mathematical model quantifying the contribution of allostery in controlling the dynamics of metabolic pathways has not been proposed. In this study, a direct, rigorous mathematical model of the de novo biosynthesis of pyrimidine nucleotides is presented. We corroborate the simulations with experimental data available in the literature and validate it with derepression experiments done in our laboratory. The model is able to faithfully represent the dynamic changes in the intracellular nucleotide pools that occur during metabolic transitions of the de novo pyrimidine biosynthetic pathway and represents a step forward in understanding the role of allosteric regulation in metabolic control.     

Metabolic shifts by nutrient manipulation in continuous cultures of BHK cells

The present work aims at characterizing the regulatory mechanisms of metabolism and product formation of BHK cells producing a recombinant antibody/cytokine fusion protein. This work was carried out through the achievement of several steady-states in chemostat cultures, corresponding to different glucose and glutamine levels in the feed culture medium. Results obtained indicate that both glucose and glutamine consumptions show a Michaelis-Menten dependence on residual glucose and glutamine concentrations, respectively. Similar dependence was also observed for lactate and ammonia productions. K(Glc)(Glc) and K(Gln)(Gln) were estimated to be 0.4 and 0.15 mM, respectively, while q(max)(Glc) and q(max)(Gln) were estimated to be 1.8 and 0.55 nmol 10(-6)cells min(-1), respectively. At very low glucose concentrations, the glucose-to-lactate yield decreased markedly showing a metabolic shift towards lower lactate production; also, the glucose-to-cells yield was increased. At very low-glutamine concentrations, the glutamine-to-ammonia and glutamine-to-cells yields increased, showing a more efficient glutamine metabolism. Overall, amino acid consumption was increased under low glucose or glutamine concentrations. Metabolic-flux analysis confirmed the metabolic shifts by showing increases in the fluxes of the more energetically efficient pathways, at low-nutrient concentrations. No effect of glucose or glutamine concentrations on the cell-specific productivity was observed, even under metabolically shifted metabolism; therefore, it is possible to confine the cells to a more efficient metabolic state maintaining the productivity of the recombinant product of interest, and consequently, increasing final product titers by increasing cell concentration and culture length. This work is intended to be a model approach to characterize cell metabolism in an integrated way; it is highly valuable for the establishment of operating strategies in mammalian cell fermentations in which cell metabolism is to be confined to a desired state.     

Unravelling carbon metabolism in anaerobic cellulolytic bacteria

Carbon metabolism in anaerobic cellulolytic bacteria has been investigated essentially in Clostridium thermocellum, Clostridium cellulolyticum, Fibrobacter succinogenes, Ruminococcus flavefaciens, and Ruminococcus albus. While cellulose depolymerization into soluble sugars by various cellulases is undoubtedly the first step in bacterial metabolisation of cellulose, it is not the only one to consider. Among anaerobic cellulolytic bacteria, C. cellulolyticum has been investigated metabolically the most in the past few years. Summarizing metabolic flux analyses in continuous culture using either cellobiose (a soluble cellodextrin resulting from cellulose hydrolysis) or cellulose (an insoluble biopolymer), this review aims to stress the importance of the insoluble nature of a carbon source on bacterial metabolism. Furthermore, some general and specific traits of anaerobic cellulolytic bacteria trends, namely, the importance and benefits of (i) cellodextrins with degree of polymerization higher than 2, (ii) intracellular phosphorolytic cleavage, (iii) glycogen cycling on cell bioenergetics, and (iv) carbon overflows in regulation of carbon metabolism, as well as detrimental effects of (i) soluble sugars and (ii) acidic environment on bacterial growth. Future directions for improving bacterial cellulose degradation are discussed.     

辅因子在微生物细胞工厂中的代谢调控与应用*

生物体中大部分酶催化反应都需要辅因子参与,辅因子平衡对维持正常的细胞代谢至关重要,而辅因子失衡则会导致细胞生长和生产的紊乱。在微生物细胞工厂的构建中,通过调节辅因子代谢平衡来提高产物合成途径的效率,从而调控细胞生长与产物生产,使代谢流能够最大限度地流向目标产物,已经成为代谢调控的重要手段。目前常见的用于代谢调控的辅因子有NAD(P)H/NAD(P)⁺、辅酶、ATP/ADP等。围绕这几种辅因子的代谢途径及功能分类进行了综述,并总结了微生物中不同产物利用辅因子平衡策略进行合成调控的研究,以期为各类化合物的高效生物合成提供参考。     

ATP调控策略及其在微生物代谢产物合成中的应用

辅因子工程是代谢工程的一个新兴分支领域,主要通过直接调控细胞内关键酶的辅因子,如ATP/ADP、NADH/NAD+、NADPH/NADP+等的浓度和形式来实现代谢流的最大化,快速地将物质流导向目标代谢物。ATP作为一种重要辅因子参与微生物细胞内大量的酶催化反应,将物质代谢途径串联或并联成复杂的网络体系,最终使得物质代谢流的分配受到牵制。因此ATP调控策略有望成为微生物菌株改造的有利工具,用于提高目标代谢物的浓度和生产能力,强化微生物对于环境的耐受以及促进底物利用等。文中将重点论述目前常用的有效ATP调控策略以及ATP调控对于细胞代谢的影响,以期为微生物细胞工厂的高效构建提供参考。     

Evaluating metabolic stress and plasmid stability in plasmid DNA production by Escherichia coli

In the context of recombinant DNA technology, the development of feasible and high-yielding plasmid DNA production processes has regained attention as more evidence for its efficacy as vectors for gene therapy and DNA vaccination arise. When producing plasmid DNA in Escherichia coli, a number of biological restraints, triggered by plasmid maintenance and replication as well as culture conditions are responsible for limiting final biomass and product yields. This termed "metabolic burden" can also cause detrimental effects on plasmid stability and quality, since the cell machinery is no longer capable of maintaining an active metabolism towards plasmid synthesis and the stress responses elicited by plasmid maintenance can also cause increased plasmid instability. The optimization of plasmid DNA production bioprocesses is still hindered by the lack of information on the host metabolic responses as well as information on plasmid instability. Therefore, systematic and on-line approaches are required not only to characterise this "metabolic burden" and plasmid stability but also for the design of appropriate metabolic engineering and culture strategies. The monitoring tools described to date rapidly evolve from laborious, off-line and at-line monitoring to online monitoring, at a time-scale that enables researchers to solve these bioprocessing problems as they occur. This review highlights major E. coli biological alterations caused by plasmid maintenance and replication, possible causes for plasmid instability and discusses the ability of currently employed bioprocess monitoring techniques to provide information in order to circumvent metabolic burden and plasmid instability, pointing out the possible evolution of these methods towards online bioprocess monitoring.     

Application of hybrid cybernetic model in simulating myeloma cell culture co-consuming glucose and glutamine with mixed consumption patterns

A dynamic model called hybrid cybernetic model (HCM) based on structured metabolic network is established for simulating mammalian cell metabolism featured with partially substitutable and partially complementary consumption patterns of two substrates, glucose and glutamine. Benefiting from the application of elementary mode analysis (EMA), the complicated metabolic network is decomposed into elementary modes (EMs) facilitating the employment of the hybrid cybernetic framework to investigate the external and internal flux distribution and the regulation mechanism among them. According to different substrate combination, two groups of EMs are obtained, i.e., EMs associated with glucose uptake and simultaneous uptake of glucose and glutamine. Uptake fluxes through various EMs are coupled together via cybernetic variables to maximize substrate uptake. External fluxes and internal fluxes could be calculated and estimated respectively, by the combination of the stoichiometrics of metabolic networks and fluxes through regulated EMs. The model performance is well validated via three sets of experimental data. Through parameter identification of limited number of experimental data, other external metabolites are precisely predicted. The obtained kinetic parameters of three experimental cultures have similar values, which indicates the robustness of the model. Furthermore, the prediction performance of the model is successfully validated based on identified parameters.     

Elevated pCO2 affects the lactate metabolic shift in CHO cell culture processes

The shift from lactate production to consumption in CHO cell metabolism is a key event during cell culture cultivations and is connected to increased culture longevity and final product titers. However, the mechanisms controlling this metabolic shift are not yet fully understood. Variations in lactate metabolism have been mainly reported to be induced by process pH and availability of substrates like glucose and glutamine. The aim of this study was to investigate the effects of elevated pCO₂ concentrations on the lactate metabolic shift phenomena in CHO cell culture processes. In this publication, we show that at elevated pCO₂ in batch and fed‐batch cultures, the lactate metabolic shift was absent in comparison to control cultures at lower pCO₂ values. Furthermore, through metabolic flux analysis we found a link between the lactate metabolic shift and the ratio of NADH producing and regenerating intracellular pathways. This ratio was mainly affected by a reduced oxidative capacity of cultures at elevated pCO₂. The presented results are especially interesting for large‐scale and perfusion processes where increased pCO₂ concentrations are likely to occur. Our results suggest, that so far unexplained metabolic changes may be connected to increased pCO₂ accumulation in larger scale fermentations. Finally, we propose several mechanisms through which increased pCO₂ might affect the cell metabolism and briefly discuss methods to enable the lactate metabolic shift during cell cultivations.     

A structured kinetic modeling framework for the dynamics of hybridoma growth and monoclonal antibody production in continuous suspension cultures

A structured kinetic model is developed to describe the dynamics of hybridoma growth and the production of monoclonal antibodies and metabolic waste products in suspension culture. The crucial details of known metabolic processes in hybridoma cells are incorporated by dividing the cell mass into four intracellular metabolic pools. The model framework and structure allow the dynamic calculation of the instantaneous specific growth rate of a hybridoma culture. The steady state and dynamic simulations of the model equations exhibit excellent agreement with experimentally observed trends in substrate utilization and product formation. The model represents the first to include any degree of metabolic detail and structure in describing a hybridoma culture. In so doing, it provides the basic modeling framework for incorporating further details of metabolism and can be a useful tool to study various strategies for enhancing hybridoma growth as well as viability and the production of monoclonal antibodies in suspension cultures.     

基于肠道微生态探讨黄连素在代谢性疾病中的抗炎作用

肠道菌群与能量代谢密切相关,其组成和代谢紊乱可通过多种途径导致胰岛素抵抗,肥胖和2型糖尿病。黄连素因具有减重、降糖、调脂等作用被广泛用于肥胖、2型糖尿病及非酒精性脂肪性肝病等代谢性疾病的辅助治疗;研究表明,黄连素可调节肠道菌群的组成和代谢,改善肠道微生态环境,从而改善胰岛素抵抗和代谢。本文综述了黄连素通过肠道菌群-炎症轴在干预代谢性疾病的研究进展,以期为代谢性疾病的治疗寻找新的策略,并为今后该领域的深入研究提供指导意义。     

Predictive macroscopic modeling of cell growth,metabolism and monoclonal antibody production: Case study of a CHO fed-batch production

We describe a systematic approach to establish predictive models of CHO cell growth, cell metabolism and monoclonal antibody (mAb) formation during biopharmaceutical production. The prediction is based on a combination of an empirical metabolic model connecting extracellular metabolic fluxes with cellular growth and product formation with mixed Monod-inhibition type kinetics that we generalized to every possible external metabolite. We describe the maximum specific growth rate as a function of the integral viable cell density (IVCD). Moreover, we also take into account the accumulation of metabolites in intracellular pools that can influence cell growth. This is possible even without identification and quantification of these metabolites as illustrated with fed-batch cultures of Chinese Hamster Ovary (CHO) cells producing a mAb. The impact of cysteine and tryptophan on cell growth and cell productivity was assessed, and the resulting macroscopic model was successfully used to predict the impact of new, untested feeding strategies on cell growth and mAb production. This model combining piecewise linear relationships between metabolic rates, growth rate and production rate together with Monod-inhibition type models for cell growth did well in predicting cell culture performance in fed-batch cultures even outside the range of experimental data used for establishing the model. It could therefore also successfully be applied for in silico prediction of optimal operating conditions.     

Physiology and toxicology of hormone-disrupting chemicals in higher plants

Higher plants are exposed to natural environmental organic chemicals, associated with plant–environment interactions, and xenobiotic environmental organic chemicals, associated with anthropogenic activities. The effects of these chemicals result not only from interaction with metabolic targets, but also from interaction with the complex regulatory networks of hormone signaling. Purpose-designed plant hormone analogues thus show extensive signaling effects on gene regulation and are as such important for understanding plant hormone mechanisms and for manipulating plant growth and development. Some natural environmental chemicals also act on plants through interference with the perception and transduction of endogenous hormone signals. In a number of cases, bioactive xenobiotics, including herbicides that have been designed to affect specific metabolic targets, show extensive gene regulation effects, which are more in accordance with signaling effects than with consequences of metabolic effects. Some of these effects could be due to structural analogies with plant hormones or to interference with hormone metabolism, thus resulting in situations of hormone disruption similar to animal cell endocrine disruption by xenobiotics. These hormone-disrupting effects can be superimposed on parallel metabolic effects, thus indicating that toxicological characterisation of xenobiotics must take into consideration the whole range of signaling and metabolic effects. Hormone-disruptive signaling effects probably predominate when xenobiotic concentrations are low, as occurs in situations of residual low-level pollutions. These hormone-disruptive effects in plants may thus be of importance for understanding cryptic effects of low-dosage xenobiotics, as well as the interactive effects of mixtures of xenobiotic pollutants.     

光遗传学在细菌生产调控中的应用进展

合成生物学的发展使得人们可以根据需求对微生物进行改造,作为“工厂”高效地合成催化所需物质,并通过添加化学诱导物的方式对生命过程进行调控。然而,化学诱导的潜在毒性以及不可逆性等限制其应用。光遗传学技术利用特定波长的光信号实现对细胞生命过程的调控,具有特异性、可逆性、高时空分辨率等特点。近年来,人们对不同来源的光敏蛋白进行改造,开发出各种不同波长、不同效应的光遗传元件用于基因回路的构建,进而实现对细菌蛋白合成、代谢过程的调控。光遗传技术在人与细菌之间搭起了实时的信号沟通桥梁,实现更为精准的物质生产调控:(1)通过光控治疗因子的合成分泌进行药物递送;(2)通过代谢通路的控制提高目的产物的催化效率;(3)通过光诱导控制生物活材料的形成。随着探索的深入,更小体积、更多波长、更高效率的光遗传元件将被开发出来,实现多输入的细菌生命活动调控。     

Segmented linear modeling of CHO fed‐batch culture and its application to large scale production

We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed‐batch cultures. Using the model structure and parameter values from a small‐scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed‐batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785–797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Anti-obesity effects of ginsenoside Rh2 are associated with the activation of AMPK signaling pathway in 3T3-L1 adipocyte

Metabolic disorders such as obesity are major obstacles in improving the average life span. Therefore, a therapeutic approach using natural compounds has been proposed as a novel strategy for preventing metabolic disorders. Ginsenoside Rh2 is one of the ginsenosides that exert anti-diabetes, anti-inflammatory, and anti-cancer effects. However, the anti-obesity effects of Ginsenoside Rh2 remain unclear. Here, we investigated the anti-obesity ability of ginsenoside Rh2 using cell culture systems. Ginsenoside Rh2 effectively inhibited adipocyte differentiation via PPAR-γ inhibition. Next, to find specific target molecules based on this result, we used cell culture systems to examine whether AMPK activation was involved in the anti-obesity ability of ginsenoside Rh2 since several published papers have indicated that AMPK signaling is involved in the regulation of metabolic disorders. Ginsenoside Rh2 significantly activated AMPK in 3T3-L1 adipocytes. In addition, we also examined the effect of AMPK on lipolysis molecules such as CPT-1 and UCP-2 by using an AMPK inhibitor. Ginsenoside Rh2 effectively induced CPT-1 and UCP-2 and this induction was abolished by AMPK inhibitor treatment. Moreover, we observed that ROS is an important upstream signal for AMPK activation during ginsenoside Rh2 treatment.Taken together, these results indicate that ginsenoside Rh2 is the most effective candidate for preventing metabolic disorders such as obesity and that it acts via the AMPK signaling pathway. Thus, AMPK signaling might contribute toward improving human health.