Cell metabolism can vary considerably over the course of a typical fed-batch antibody production process. However, the intracellular pathway alterations associated with various phases of growth and antibody production have yet to be fully elucidated using industrially relevant production hosts. Therefore, we performed (13)C labeling experiments and metabolic flux analysis (MFA) to characterize CHO cell metabolism during four separate phases of a fed-batch culture designed to closely represent industrial process conditions. First, we found that peak specific growth rate was associated with high lactate production and minimal TCA cycling. Conversely, we found that lactate metabolism switched from net production to net consumption as the culture transitioned from peak growth to peak antibody production. During the peak antibody production phase, energy was primarily generated through oxidative phosphorylation, which was also associated with elevated oxidative pentose phosphate pathway (oxPPP) activity. Interestingly, as TCA cycling and antibody production reached their peaks, specific growth rate continued to diminish as the culture entered stationary phase. However, TCA cycling and oxPPP activity remained high even as viable cell density began to decline. Overall, we found that a highly oxidative state of metabolism corresponded with peak antibody production, whereas peak cell growth was characterized by a highly glycolytic metabolic state.

Chinese hamster ovary (CHO) cells are commonly used for industrial production of recombinant proteins in fed batch or alternative production systems. Cells progress through multiple metabolic stages during fed-batch antibody (mAb) production, including an exponential growth phase accompanied by lactate production, a low growth, or stationary phase when specific mAb production increases, and a decline when cell viability declines. Although media composition and cell lineage have been shown to impact growth and productivity, little is known about the metabolic changes at a molecular level. Better understanding of cellular metabolism will aid in identifying targets for genetic and metabolic engineering to optimize bioprocess and cell engineering. We studied a high expressing recombinant CHO cell line, designated high performer (HP), in fed-batch productions using stable isotope tracers and biochemical methods to determine changes in central metabolism that accompany growth and mAb production. We also compared and contrasted results from HP to a high lactate producing cell line that exhibits poor growth and productivity, designated low performer (LP), to determine intrinsic metabolic profiles linked to their respective phenotypes. Our results reveal alternative metabolic and regulatory pathways for lactate and TCA metabolite production to those reported in the literature. The distribution of key media components into glycolysis, TCA cycle, lactate production, and biosynthetic pathways was shown to shift dramatically between exponential growth and stationary (production) phases. We determined that glutamine is both utilized more efficiently than glucose for anaplerotic replenishment and contributes more significantly to lactate production during the exponential phase. Cells shifted to glucose utilization in the TCA cycle as growth rate decreased. The magnitude of this metabolic switch is important for attaining high viable cell mass and antibody titers. We also found that phosphoenolpyruvate carboxykinase (PEPCK1) and pyruvate kinase (PK) are subject to differential regulation during exponential and stationary phases. The concomitant shifts in enzyme expression and metabolite utilization profiles shed light on the regulatory links between cell metabolism, media metabolites, and cell growth.

Glycerol kinase deficiency (GKD) is an X-linked inborn error of metabolism with metabolic and neurological crises. Liver shows the highest level of glycerol kinase (GK) activity in humans and mice. Absence of genotype-phenotype correlations in patients with GKD indicates the involvement of modifier genes, including other network partners. To understand the molecular pathogenesis of GKD, we performed microarray analysis on liver mRNA from neonatal glycerol kinase (Gyk) knockout (KO) and wild-type (WT) mice. Unsupervised learning revealed that the overall gene expression profile of the KO mice was different from that of WT. Real-time PCR confirmed the differences for selected genes. Functional gene enrichment analysis was used to find 56 increased and 37 decreased gene functional categories. PathwayAssist analysis identified changes in gene expression levels of genes involved in organic acid metabolism indicating that GK was part of the same metabolic network which correlates well with the patients with GKD having metabolic acidemia during their episodic crises. Network component analysis (NCA) showed that transcription factors sterol regulatory element-binding protein (SREBP)-1c, carbohydrate response element-binding protein (ChREBP), hepatocyte nuclear factor-4 alpha (HNF-4alpha) and peroxisome proliferative-activated receptor-alpha (PPARalpha) had increased activity in the Gyk KO mice compared with WT mice, whereas SREBP-2 was less active in the Gyk KO mice. These studies show that Gyk deletion causes alterations in expression of genes in several regulatory networks and is the first time NCA has been used to expand on microarray data from a mouse KO model of a human disease.

ZNF804A (Zinc Finger Protein 804A) has been identified as a candidate gene for schizophrenia (SZ), autism spectrum disorders (ASD), and bipolar disorder (BD) in replicated genome wide association studies (GWAS) and by copy number variation (CNV) analysis. Although its function has not been well-characterized, ZNF804A contains a C2H2-type zinc-finger domain, suggesting that it has DNA binding properties, and consequently, a role in regulating gene expression. To further explore the role of ZNF804A on gene expression and its downstream targets, we used a gene knockdown (KD) approach to reduce its expression in neural progenitor cells (NPCs) derived from induced pluripotent stem cells (iPSCs). KD was accomplished by RNA interference (RNAi) using lentiviral particles containing shRNAs that target ZNF804A mRNA. Stable transduced NPC lines were generated after puromycin selection. A control cell line expressing a random (scrambled) shRNA was also generated. Neuronal differentiation was induced, RNA was harvested after 14 days and transcriptome analysis was carried out using RNA-seq. 1815 genes were found to be differentially expressed at a nominally significant level (p<0.05); 809 decreased in expression in the KD samples, while 1106 increased. Of these, 370 achieved genome wide significance (FDR<0.05); 125 were lower in the KD samples, 245 were higher. Pathway analysis showed that genes involved in interferon-signaling were enriched among those that were down-regulated in the KD samples. Correspondingly, ZNF804A KD was found to affect interferon-alpha 2 (IFNA2)-mediated gene expression. The findings suggest that ZNF804A may affect a differentiating neuron’s response to inflammatory cytokines, which is consistent with models of SZ and ASD that support a role for infectious disease, and/or autoimmunity in a subgroup of patients.

Summary Given the success in engineering synthetic phenotypes in microbes and mammalian cells, constructing non-native pathways in mammals has become increasingly attractive for understanding and identifying potential targets for treating metabolic disorders. Here we introduced the glyoxylate shunt into mouse liver to investigate mammalian fatty acid metabolism. Mice expressing the shunt showed resistance to diet-induced obesity on a high fat diet despite similar food consumption. This was accompanied by a decrease in total fat mass, circulating leptin levels, plasma triglyceride concentration, and a signaling metabolite in liver, malonyl-CoA, that inhibits fatty acid degradation. Contrary to plants and bacteria, in which the glyoxylate shunt prevents the complete oxidation of fatty acids, this pathway when introduced in mice increases fatty acid oxidation such that resistance to diet-induced obesity develops. This work suggests that using non-native pathways in higher organisms to explore and modulate metabolism may be a useful approach.

The liver plays a central role in maintaining whole body metabolic and energy homeostasis by consuming and producing glucose and fatty acids. Glucose and fatty acids compete for hepatic substrate oxidation with regulation ensuring glucose is oxidized preferentially. Increasing fatty acid oxidation is expected to decrease lipid storage in the liver and avoid lipid-induced insulin-resistance. To increase hepatic lipid oxidation in the presence of glucose, we previously engineered a synthetic glyoxylate shunt into human hepatocyte cultures and a mouse model and showed that this synthetic pathway increases free fatty acid beta-oxidation and confers resistance to diet-induced obesity in the mouse model. Here we used ensemble modeling to decipher the effects of perturbations to the hepatic metabolic network on fatty acid oxidation and glucose uptake. Despite sampling of kinetic parameters using the most fundamental elementary reaction models, the models based on current metabolic regulation did not readily describe the phenotype generated by glyoxylate shunt expression. Although not conclusive, this initial negative result prompted us to probe unknown regulations, and malate was identified as inhibitor of hexokinase 2 expression either through direct or indirect actions. This regulation allows the explanation of observed phenotypes (increased fatty acid degradation and decreased glucose consumption). Moreover, the result is a function of pyruvate-carboxylase, mitochondrial pyruvate transporter, citrate transporter protein, and citrate synthase activities. Some subsets of these flux ratios predict increases in fatty acid and decreases in glucose uptake after glyoxylate expression, whereas others predict no change. Altogether, this work defines the possible biochemical space where the synthetic shunt will produce the desired phenotype and demonstrates the efficacy of ensemble modeling for synthetic pathway design.