Systems analysis and design for accelerating process and cell line development

This presentation will highlight our work on integrating genomic science with systems analysis for cell culture engineering. Advances in computational and analytical tools in the past fifteen years have altered the landscape of process engineering. The traditional experimentation based process development is greatly augmented by data and model driven approaches. The availability of vast amount of bioprocess manufacturing data allowed us to gain valuable process insight through data mining. Those insights have led to genomic exploration and mathematical model development that provided mechanistic understanding of pivotal process features and aided in devising a better control of the process and product consistency. The data and model driven approach will also play a key role in a design based cell engineering for the development of production cell lines. A scenario of integrating data on genome stability and accessibility with model assisted cell engineering for cell line development will be presented and the potential and limitation of such an approach will be discussed with technical and regulatory considerations

Systems Analysis of N-Glycan Processing in Mammalian Cells

N-glycosylation plays a key role in the quality of many therapeutic glycoprotein biologics. The biosynthesis reactions of these oligosaccharides are a type of network in which a relatively small number of enzymes give rise to a large number of N-glycans as the reaction intermediates and terminal products. Multiple glycans appear on the glycoprotein molecules and give rise to a heterogeneous product. Controlling the glycan distribution is critical to the quality control of the product. Understanding N-glycan biosynthesis and the etiology of microheterogeneity would provide physiological insights, and facilitate cellular engineering to enhance glycoprotein quality. We developed a mathematical model of glycan biosynthesis in the Golgi and analyzed the various reaction variables on the resulting glycan distribution. The Golgi model was modeled as four compartments in series. The mechanism of protein transport across the Golgi is still controversial. From the viewpoint of their holding time distribution characteristics, the two main hypothesized mechanisms, vesicular transport and Golgi maturation models, resemble four continuous mixing-tanks (4CSTR) and four plug-flow reactors (4PFR) in series, respectively. The two hypotheses were modeled accordingly and compared. The intrinsic reaction kinetics were first evaluated using a batch (or single PFR) reactor. A sufficient holding time is needed to produce terminally-processed glycans. Altering enzyme concentrations has a complex effect on the final glycan distribution, as the changes often affect many reaction steps in the network. Comparison of the glycan profiles predicted by the 4CSTR and 4PFR models points to the 4PFR system as more likely to be the true mechanism. To assess whether glycan heterogeneity can be eliminated in the biosynthesis of biotherapeutics the 4PFR model was further used to assess whether a homogeneous glycan profile can be created through metabolic engineering. We demonstrate by the spatial localization of enzymes to specific compartments all terminally processed N-glycans can be synthesized as homogeneous products with a sufficient holding time in the Golgi compartments. The model developed may serve as a guide to future engineering of glycoproteins

Learning mechanistic metabolic models with small datasets

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An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays

BACKGROUND: DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values. RESULTS: We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions. CONCLUSION: Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray assays using genomic DNA as a reference. We conclude that the use of genomic DNA as reference DNA should greatly facilitate comparative transcriptome analysis

The differentiation of pluripotent stem cells to hepatic cells – Parallels between maturation status and metabolic state

Hepatocytes derived from human pluripotent stem cells (PSCs) hold great promise as an unlimited cell source for liver cell therapy and in vitro toxicity studies. Through the treatment of a series of cytokines and growth factors to mimic embryonic development, PSCs can be guided to differentiate through the endodermal and hepatic commitment stages to become hepatocytelike cells (HLCs). As PSCs differentiate toward endoderm, then to hepatic lineage, the glycolysis and amino acid metabolic rate decreased significantly. Flux analysis using a compartmentalized metabolic flux model that considers cytosolmitochondria interactions revealed that the progressive decline in glycolysis flux coincides with an increase in activities of oxidative phosphorylation (OxPhos) and TCA cycle. This increase in OxPhos activity was also accompanied by increased mitochondria activity. Transcriptome analysis showed that the expression of a number of enzymes and transporter in glucose metabolism decreased as PSCs differentiate toward HLCs. Using a kinetic model of energy metabolism, we showed that the decrease in the expression of those genes could account for the metabolic shift during the differentiation. Our results suggest that metabolic shift may play a role in in vitro PSC differentiation to HLC. Consistently, aborting the metabolic shift by culturing differentiating HLCs at a high glucose level showed a decreased degree of maturation. We then asked the question whether such metabolic shift occurred during embryonic liver development. Lacking fetal liver metabolism data, we examined the transcriptome data of developing liver in mouse embryo. We compiled the transcriptome data of human PSCs differentiation to HLCs and mouse embryonic liver development and performed cross-species in vivo vs. in vitro meta-analysis. After batch corrections on the combined data set cells at different stages of HLC differentiation and different embryonic days of mouse liver development aligned chronologically on a unified developmental “time” scale. The results show that in vitro HLC differentiation of human PSCs reached an equivalent period of E(Embryo day)13-E15 in mouse development, but lacked full maturity of hepatocytes. Furthermore, the enzymes of glucose metabolism behaved similarly in embryonic liver development and in HLC differentiation up to E15. In late stages of embryonic liver development, many of the metabolic enzymes subsequently switch their isoforms to those of the mature hepatocyte. The isoform switch of glycolytic enzymes may reflect the final switch to the mature metabolic nature of the liver. Although, we observe many similar trends in our differentiation, failure to switch isoforms in in vitro differentiation is a key contributor to the lack of maturity of HLCs. In conclusion, the energy metabolism undergoes significant changes over the course of in vitro differentiation from PSCs towards hepatocytes. The shift in energy metabolism is the result, but has also been proposed to be a possible driver, of the differentiation. To enhance the maturation of HLCs, correcting the expression of the genes that fail to progress concordantly as in mouse embryonic liver beyond E15 is a tempting proposition. However, this metabolic study also suggests that providing an appropriate environment to elicit a shift toward the metabolic state of mature hepatocytes may be equally important

Designing a soluble factor-based expansion system through mechanistic understanding of feeder cell-mediated NK cell activation

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Role of Intracellular Stochasticity in Biofilm Growth. Insights from Population Balance Modeling.

There is increasing recognition that stochasticity involved in gene regulatory processes may help cells enhance the signal or synchronize expression for a group of genes. Thus the validity of the traditional deterministic approach to modeling the foregoing processes cannot be without exception. In this study, we identify a frequently encountered situation, i.e., the biofilm, which has in the past been persistently investigated with intracellular deterministic models in the literature. We show in this paper circumstances in which use of the intracellular deterministic model appears distinctly inappropriate. In Enterococcus faecalis, the horizontal gene transfer of plasmid spreads drug resistance. The induction of conjugation in planktonic and biofilm circumstances is examined here with stochastic as well as deterministic models. The stochastic model is formulated with the Chemical Master Equation (CME) for planktonic cells and Reaction-Diffusion Master Equation (RDME) for biofilm. The results show that although the deterministic model works well for the perfectly-mixed planktonic circumstance, it fails to predict the averaged behavior in the biofilm, a behavior that has come to be known asstochastic focusing. A notable finding from this work is that the interception of antagonistic feedback loops to signaling, accentuates stochastic focusing. Moreover, interestingly, increasing particle number of a control variable could lead to an even larger deviation. Intracellular stochasticity plays an important role in biofilm and we surmise by implications from the model, that cell populations may use it to minimize the influence from environmental fluctuation