Jingkui Chen

Analyzing Clonal Variation of Monoclonal Antibody-Producing CHO Cell Lines Using an In Silico Metabolomic Platform

Monoclonal antibody producing Chinese hamster ovary (CHO) cells have been shown to undergo metabolic changes when engineered to produce high titers of recombinant proteins. In this work, we have studied the distinct metabolism of CHO cell clones harboring an efficient inducible expression system, based on the cumate gene switch, and displaying different expression levels, high and low productivities, compared to that of the parental cells from which they were derived. A kinetic model for CHO cell metabolism was further developed to include metabolic regulation. Model calibration was performed using intracellular and extracellular metabolite profiles obtained from shake flask batch cultures. Model simulations of intracellular fluxes and ratios known as biomarkers revealed significant changes correlated with clonal variation but not to the recombinant protein expression level. Metabolic flux distribution mostly differs in the reactions involving pyruvate metabolism, with an increased net flux of pyruvate into the tricarboxylic acid (TCA) cycle in the high-producer clone, either being induced or non-induced with cumate. More specifically, CHO cell metabolism in this clone was characterized by an efficient utilization of glucose and a high pyruvate dehydrogenase flux. Moreover, the high-producer clone shows a high rate of anaplerosis from pyruvate to oxaloacetate, through pyruvate carboxylase and from glutamate to α-ketoglutarate, through glutamate dehydrogenase, and a reduced rate of cataplerosis from malate to pyruvate, through malic enzyme. Indeed, the increase of flux through pyruvate carboxylase was not driven by an increased anabolic demand. It is in fact linked to an increase of the TCA cycle global flux, which allows better regulation of higher redox and more efficient metabolic states. To the best of our knowledge, this is the first time a dynamic in silico platform is proposed to analyze and compare the metabolomic behavior of different CHO clones.

Immunosuppressive activity enhances central carbon metabolism and bioenergetics in myeloid-derived suppressor cells in vitro models

BackgroundThe tumor microenvironment contains a vast array of pro- and anti-inflammatory cytokines that alter myelopoiesis and lead to the maturation of immunosuppressive cells known as myeloid-derived suppressor cells (MDSCs). Incubating bone marrow (BM) precursors with a combination of granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin-6 (IL-6) generated a tumor-infiltrating MDSC-like population that impaired anti-tumor specific T-cell functions. This in vitro experimental approach was used to simulate MDSC maturation, and the cellular metabolic response was then monitored. A complementary experimental model that inhibited L-arginine (L-Arg) metabolizing enzymes in MSC-1 cells, an immortalized cell line derived from primary MDSCs, was used to study the metabolic events related to immunosuppression.ResultsExposure of BM cells to GM-CSF and IL-6 activated, within 24 h, L-Arg metabolizing enzymes which are responsible for the MDSCs immunosuppressive potential. This was accompanied by an increased uptake of L-glutamine (L-Gln) and glucose, the latter being metabolized by anaerobic glycolysis. The up-regulation of nutrient uptake lead to the accumulation of TCA cycle intermediates and lactate as well as the endogenous synthesis of L-Arg and the production of energy-rich nucleotides. Moreover, inhibition of L-Arg metabolism in MSC-1 cells down-regulated central carbon metabolism activity, including glycolysis, glutaminolysis and TCA cycle activity, and led to a deterioration of cell bioenergetic status. The simultaneous increase of cell specific concentrations of ATP and a decrease in ATP-to-ADP ratio in BM-derived MDSCs suggested cells were metabolically active during maturation. Moreover, AMP-activated protein kinase (AMPK) was activated during MDSC maturation in GM-CSF and IL-6–treated cultures, as revealed by the continuous increase of AMP-to-ATP ratios and the phosphorylation of AMPK. Likewise, AMPK activity was decreased in MSC-1 cells when L-Arg metabolizing enzymes were inhibited. Finally, inhibition of AMPK activity by the specific inhibitor Compound C (Comp-C) resulted in the inhibition of L-Arg metabolizing enzyme activity and abolished MDSCs immunosuppressive activity.ConclusionsWe anticipate that the inhibition of AMPK and the control of metabolic fluxes may be considered as a novel therapeutic target for the recovery of the immunosurveillance process in cancer-bearing hosts.

Impact of epidermal growth factor tethering strategy on cellular response.

In an effort to evaluate the impact of various epidermal growth factor (EGF) grafting strategies upon cell surface receptor activation and cell adhesion, we generated low-fouling surfaces by homogeneously grafting carboxymethylated dextran (CMD) on amino-coated glass substrate. By preventing nonspecific cell adhesion while providing reactive groups facilitating subsequent protein grafting, CMD allowed achieving specific cell/tethered EGF interactions and therefore deriving unambiguous conclusions about various EGF grafting strategies. We demonstrate here that A-431 cell response to immobilized EGF is highly dependent on the bioactivity of the tagged protein being tethered, its proper orientation, and its surface density. Among all the approaches we tested, the oriented tethering of fully bioactive EGF via a de novo-designed coiled-coil capture system was shown to be the most efficient. That is, it led to the most intense and sustained phosphorylation of EGF receptors as well as to strong A-431 cell adhesion, the latter being comparable to that observed with amino-coated surfaces in the absence of CMD.

Identifying conditions for inducible protein production in E. coli: combining a fed-batch and multiple induction approach

BackgroundIn the interest of generating large amounts of recombinant protein, inducible systems have been studied to maximize both the growth of the culture and the production of foreign proteins. Even though thermo-inducible systems were developed in the late 1970s, the number of studies that focus on strategies for the implementation at bioreactor scale is limited. In this work, the bacteriophage lambda PL promoter is once again investigated as an inducible element but for the production of green fluorescent protein (GFP). Culture temperature, induction point, induction duration and number of inductions were considered as factors to maximize GFP production in a 20-L bioreactor.ResultsIt was found that cultures carried out at 37°C resulted in a growth-associated production of GFP without the need of an induction at 42°C. Specific production was similar to what was achieved when separating the growth and production phases. Shake flask cultures were used to screen for desirable operating conditions. It was found that multiple inductions increased the production of GFP. Induction decreased the growth rate and substrate yield coefficients; therefore, two time domains (before and after induction) having different kinetic parameters were created to fit a model to the data collected.ConclusionBased on two batch runs and the simulation of culture dynamics, a pre-defined feeding and induction strategy was developed to increase the volumetric yield of a temperature regulated expression system and was successfully implemented in a 20-L bioreactor. An overall cell density of 5.95 g DW l-1 was achieved without detriment to the cell specific production of GFP; however, the production of GFP was underestimated in the simulations due to a significant contribution of non-growth associated product formation under limiting nutrient conditions.

L-glutamine is a key parameter in the immunosuppression phenomenon

Suppression of tumour-specific T-cell functions by myeloid-derived suppressor cells (MDSCs) is a dominant mechanism of tumour escape. MDSCs express two enzymes, i.e. inducible nitric oxide synthase (iNOS) and arginase (ARG1), which metabolize the semi-essential amino acid L-arginine (L-Arg) whose bioavailability is crucial for T-cell proliferation and functions. Recently, we showed that glutaminolysis supports MDSC maturation process by ensuring the supply of intermediates and energy. In this work, we used an immortalized cell line derived from mouse MDSCs (MSC-1 cell line) to further investigate the role of L-glutamine (L-Gln) in the maintenance of MDSC immunosuppressive activity. Culturing MSC-1 cells in L-Gln-limited medium inhibited iNOS activity, while ARG1 was not affected. MSC-1 cells inhibited Jukat cell growth without any noticeable effect on their viability. The characterization of MSC-1 cell metabolic profile revealed that L-Gln is an important precursor of lactate production via the NADP(+)-dependent malic enzyme, which co-produces NADPH. Moreover, the TCA cycle activity was down-regulated in the absence of L-Gln and the cell bioenergetic status was deteriorated accordingly. This strongly suggests that iNOS activity, but not that of ARG1, is related to an enhanced central carbon metabolism and a high bioenergetic status. Taken altogether, our results suggest that the control of glutaminolysis fluxes may represent a valuable target for immunotherapy.

A Single Dynamic Metabolic Model Can Describe mAb Producing CHO Cell Batch and Fed-Batch Cultures on Different Culture Media.

CHO cell culture high productivity relies on optimized culture medium management under fed-batch or perfused chemostat strategies enabling high cell densities. In this work, a dynamic metabolic model for CHO cells was further developed, calibrated and challenged using datasets obtained under four different culture conditions, including two batch and two fed-batch cultures comparing two different culture media. The recombinant CHO-DXB11 cell line producing the EG2-hFc monoclonal antibody was studied. Quantification of extracellular substrates and metabolites concentration, viable cell density, monoclonal antibody concentration and intracellular concentration of metabolite intermediates of glycolysis, pentose-phosphate and TCA cycle, as well as of energetic nucleotides, were obtained for model calibration. Results suggest that a single model structure with a single set of kinetic parameter values is efficient at simulating viable cell behavior in all cases under study, estimating the time course of measured and non-measured intracellular and extracellular metabolites. Model simulations also allowed performing dynamic metabolic flux analysis, showing that the culture media and the fed-batch strategies tested had little impact on flux distribution. This work thus paves the way to an in silico platform allowing to assess the performance of different culture media and fed-batch strategies.

Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson's Disease

Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level.

Kinetic metabolic modelling for the control of plant cells cytoplasmic phosphate

A previously developed kinetic metabolic model for plant metabolism was used in a context of identification and control of intracellular phosphate (Pi) dynamics. Experimental data from batch flask cultures of Eschscholtiza californica cells was used to calibrate the model parameters for the slow dynamics (growth, nutrition, anabolic pathways, etc.). Perturbation experiments were performed using a perfusion small-scale bioreactor monitored by in vivo(31)P NMR. Parameter identification for Pi metabolism was done by measuring the cells dynamic response to different inputs for extracellular Pi (two pulse-response experiments and a step-response experiment). The calibrated model can describe Pi translocation between the cellular pools (vacuole and cytoplasm). The effect of intracellular Pi management on ATP/ADP and phosphomonoesters concentrations is also described by the model. The calibrated model is then used to develop a control strategy on the cytoplasmic Pi pool. From the identification of the systems dynamics, a proportional-integral controller was designed and tuned. The closed-loop control was implemented in the small-scale NMR bioreactor and experimental results were in accordance with model predictions. Thus, the calibrated model is able to predict cellular behaviour for phosphate metabolism and it was demonstrated that it is possible to control the intracellular level of cytoplasmic Pi in plant cells.

A systems approach to plant bioprocess optimization

A dynamic model for plant cell metabolism was used as a basis for a rational analysis of plant production potential in in vitro cultures. The model was calibrated with data from 3-L bioreactor cultures. A dynamic sensitivity analysis framework was developed to analyse the response curves of secondary metabolite production to metabolic and medium perturbations. Simulation results suggest that a straightforward engineering of cell metabolism or medium composition might only have a limited effect on productivity. To circumvent the problem of the dynamic allocation of resources between growth and production pathways, the sensitivity analysis framework was used to assess the effect of stabilizing intracellular nutrient concentrations. Simulations showed that a stabilization of intracellular glucose and nitrogen reserves could lead to a 116% increase in the specific production of secondary metabolites compared with standard culture protocol. This culture strategy was implemented experimentally using a perfusion bioreactor. To stabilize intracellular concentrations, adaptive medium feeding was performed using model mass balances and estimations. This allowed for a completely automated culture, with controlled conditions and pre-defined decision making algorithm. The proposed culture strategy leads to a 73% increase in specific production and a 129% increase in total production, as compared with a standard batch culture protocol. The sensitivity analysis on a mathematical model of plant metabolism thus allowed producing new insights on the links between intracellular nutritional management and cell productivity. The experimental implementation was also a significant improvement on current plant bioprocess strategies.

Development and validation of isooctane skeletal mechanisms based on LLNL detailed mechanism

This paper describes recent development of isooctane skeletal mechanisms for Homogeneous Charge Compression Ignition (HCCI) engines. Two skeletal mechanisms were constructed: one with 259 species and the other with 291 species. The former was developed for accurate predictions of Start of Combustion (SOC) and the latter aiming at accurate predictions of both SOC and emissions. Evaluations of the performances of these skeletal mechanisms were conducted under extensive conditions. Both skeletal mechanisms are found satisfactory in predicting SOC with a speeding up factor of 15?20. The expanded version is found necessary for accurate predictions of CO and unburned hydrocarbon emissions.