SUMMARY Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells, provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show the metabolic resources in CHO are >3 times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-016-1051-4) contains supplementary material, which is available to authorized users.

Advances in cellular reprogramming and stem cell differentiation now enable ex vivo studies of human neuronal differentiation. However, it remains challenging to elucidate the underlying regulatory programs because differentiation protocols are laborious and often result in low neuron yields. Here, we overexpressed two Neurogenin transcription factors in human-induced pluripotent stem cells and obtained neurons with bipolar morphology in 4 days, at greater than 90% purity. The high purity enabled mRNA and microRNA expression profiling during neurogenesis, thus revealing the genetic programs involved in the rapid transition from stem cell to neuron. The resulting cells exhibited transcriptional, morphological and functional signatures of differentiated neurons, with greatest transcriptional similarity to prenatal human brain samples. Our analysis revealed a network of key transcription factors and microRNAs that promoted loss of pluripotency and rapid neurogenesis via progenitor states. Perturbations of key transcription factors affected homogeneity and phenotypic properties of the resulting neurons, suggesting that a systems-level view of the molecular biology of differentiation may guide subsequent manipulation of human stem cells to rapidly obtain diverse neuronal types.

Accurate and complete genome sequences are essential in biotechnology to facilitate genome-based cell engineering efforts. The current genome assemblies for Cricetulus griseus, the Chinese hamster, are fragmented and replete with gap sequences and misassemblies, consistent with most short-read based assemblies. Here, we completely resequenced C. griseus using Single Molecule Real Time (SMRT) sequencing and merged this with Illumina-based assemblies. This generated a more contiguous and complete genome assembly than either technology alone, reducing the number of scaffolds by >28-fold, with 90% of the sequence in the 122 longest scaffolds. Most genes are now found in single scaffolds, including up- and downstream regulatory elements, enabling improved study of noncoding regions. With >95% of the gap sequence filled, important CHO cell mutations have been detected in draft assembly gaps. This new assembly will be an invaluable resource for continued basic and pharmaceutical research.

35Keywords 36 Metabolic network, secretory pathway, biotherapeutic production, systems biotechnology 37Indeed, recent studies have incorporated portions of the secretory pathway in metabolic models of yeast 55 3-5 . Furthermore, Lund and colleagues reconstructed a genetic interaction network of the mouse secretory 56 pathway and the unfolded protein response and analyzed it in the context of CHO cells 6 . However, such a 57 network does not encompass a stoichiometric reconstruction of the biochemical reactions involved in the 58 secretory pathway nor it is coupled to existing metabolic networks of mammalian cells. 59Here we present the first genome-scale stoichiometric reconstructions and computational models of 60 mammalian metabolism coupled to protein secretion. Specifically, we constructed these for human, 61 mouse, and CHO cells, called RECON2.2s, iMM1685s, and iCHO2048s, respectively. We first derive an 62 expression for computing the energetic cost of synthesizing and secreting a product in terms of molecules 63 of ATP equivalents per protein molecule. We use this expression and analyze how the energetic burden 64 of protein secretion has led to an overall suppression of more expensive secreted host cell proteins in 65 mammalian cells. Given its dominant role in biotherapeutic production, we further focus on the 66 biosynthetic capabilities of CHO cells. We then demonstrate that product-specific secretory pathway 67 models can be built to estimate CHO cell growth rates given the specific productivity of the recombinant 68 3 product as a constraint. We identify the features of secreted proteins that have the highest impact on 69 protein cost and productivity rates. Finally, we use our model to identify proteins that compete for cell 70 resources, thereby presenting targets for cell engineering. Through this study we demonstrate that a 71 systems-view of the secretory pathway now enables the analysis of many biomolecular mechanisms 72 controlling the efficacy and cost of protein expression in mammalian cells. We envision our models as 73 valuable tools for the study of normal physiological processes and engineering cell bioprocesses in 74 biotechnology. All models and data used in this study are freely available at 75 https://github.com/LewisLabUCSD/MammalianSecretoryRecon. 76 77 RESULTS 78 A stoichiometric expression of protein secretion energetics 79In any cell, the secretory machinery is concurrently processing thousands of secreted and membrane 80 proteins, which all compete for secretory pathway resources and pose a metabolic burden. To quantify 81 this burden, we estimated the energetic cost of synthesizing and/or secreting 5,641 and 3,538 82 endogenous proteins in the CHO and human secretome and membrane proteome in terms of total 83 number of ATP equivalent molecules consumed (see Methods). These protein costs were compared to 84 the cost of five recombinant proteins commonly produced in CHO cells (Fig. 1a). To refine estimates, we 85 predicted signal peptides 7 , GPI anchor attachment signals 8 , an...

The exoerythrocytic stage of Plasmodium infection is a critical window for prophylactic intervention. Using genome-wide dual RNA sequencing of flow-sorted infected and uninfected hepatoma cells we show that the human mucosal immunity gene, mucin-13 (MUC13), is strongly upregulated during Plasmodium exoerythrocytic hepatic-stage infection. We confirm MUC13 transcript increases in hepatoma cell lines and primary hepatocytes. In immunofluorescence assays, host MUC13 protein expression distinguishes infected cells from adjacent uninfected cells and shows similar colocalization with parasite biomarkers such as UIS4 and HSP70. We further show that localization patterns are species independent, marking both P. berghei and P. vivax infected cells, and that MUC13 can be used to identify compounds that inhibit parasite replication in hepatocytes. This data provides insights into host-parasite interactions in Plasmodium infection, and demonstrates that a component of host mucosal immunity is reprogrammed during the progression of infection.

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

Chinese hamster ovary (CHO) cells are widely used for biopharmaceutical protein production. One challenge limiting CHO cell productivity is apoptosis stemming from cellular stress during protein production. Here we applied CRISPR interference (CRISPRi) to downregulate the endogenous expression of apoptotic genes Bak, Bax, and Casp3 in CHO cells. In addition to reduced apoptosis, mitochondrial membrane integrity was improved and the caspase activity was reduced. Moreover, we optimized the CRISPRi system to enhance the gene repression efficiency in CHO cells by testing different repressor fusion types. An improved Cas9 repressor has been identified by applying C-terminal fusion of a bipartite repressor domain, KRAB-MeCP2, to nuclease-deficient Cas9. These results collectively demonstrate that CHO cells can be rescued from cell apoptosis by targeted gene repression using the CRISPRi system.