Shangzhong Li

Rapid neurogenesis through transcriptional activation in human stem cells

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.

Recon 2.2: from reconstruction to model of human metabolism

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).

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

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 that the metabolic resources in CHO are more than three 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.

Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion

Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production.

Quantitative feature extraction from the Chinese hamster ovary bioprocess bibliome using a novel meta-analysis workflow

The scientific literature concerning Chinese hamster ovary (CHO) cells grows annually due to the importance of CHO cells in industrial bioprocessing of therapeutics. In an effort to start to catalogue the breadth of CHO phenotypes, or phenome, we present the CHO bibliome. This bibliographic compilation covers all published CHO cell studies from 1995 to 2015, and each study is classified by the types of phenotypic and bioprocess data contained therein. Using data from selected studies, we also present a quantitative meta-analysis of bioprocess characteristics across diverse culture conditions, yielding novel insights and addressing the validity of long held assumptions. Specifically, we show that bioprocess titers can be predicted using indicator variables derived from viable cell density, viability, and culture duration. We further identified a positive correlation between the cumulative viable cell density (VCD) and final titer, irrespective of cell line, media, and other bioprocess parameters. In addition, growth rate was negatively correlated with performance attributes, such as VCD and titer. In summary, despite assumptions that technical diversity among studies and opaque publication practices can limit research re-use in this field, we show that the statistical analysis of diverse legacy bioprocess data can provide insight into bioprocessing capabilities of CHO cell lines used in industry. The CHO bibliome can be accessed at http://lewislab.ucsd.edu/cho-bibliome/.

Whole-Genome Sequencing of Invasion-Resistant Cells Identifies Laminin α2 as a Host Factor for Bacterial Invasion

ABSTRACT To understand the role of glycosaminoglycans in bacterial cellular invasion, xylosyltransferase-deficient mutants of Chinese hamster ovary (CHO) cells were created using clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-associated gene 9 (CRISPR-cas9) gene targeting. When these mutants were compared to the pgsA745 cell line, a CHO xylosyltransferase mutant generated previously using chemical mutagenesis, an unexpected result was obtained. Bacterial invasion of pgsA745 cells by group B Streptococcus (GBS), group A Streptococcus, and Staphylococcus aureus was markedly reduced compared to the invasion of wild-type cells, but newly generated CRISPR-cas9 mutants were only resistant to GBS. Invasion of pgsA745 cells was not restored by transfection with xylosyltransferase, suggesting that an additional mutation conferring panresistance to multiple bacteria was present in pgsA745 cells. Whole-genome sequencing and transcriptome sequencing (RNA-Seq) uncovered a deletion in the gene encoding the laminin subunit α2 (Lama2) that eliminated much of domain L4a. Silencing of the long Lama2 isoform in wild-type cells strongly reduced bacterial invasion, whereas transfection with human LAMA2 cDNA significantly enhanced invasion in pgsA745 cells. The addition of exogenous laminin-α2β1γ1/laminin-α2β2γ1 strongly increased bacterial invasion in CHO cells, as well as in human alveolar basal epithelial and human brain microvascular endothelial cells. Thus, the L4a domain in laminin α2 is important for cellular invasion by a number of bacterial pathogens. IMPORTANCE Pathogenic bacteria penetrate host cellular barriers by attachment to extracellular matrix molecules, such as proteoglycans, laminins, and collagens, leading to invasion of epithelial and endothelial cells. Here, we show that cellular invasion by the human pathogens group B Streptococcus, group A Streptococcus, and Staphylococcus aureus depends on a specific domain of the laminin α2 subunit. This finding may provide new leads for the molecular pathogenesis of these bacteria and the development of novel antimicrobial drugs. IMPORTANCE Pathogenic bacteria penetrate host cellular barriers by attachment to extracellular matrix molecules, such as proteoglycans, laminins, and collagens, leading to invasion of epithelial and endothelial cells. Here, we show that cellular invasion by the human pathogens group B Streptococcus, group A Streptococcus, and Staphylococcus aureus depends on a specific domain of the laminin α2 subunit. This finding may provide new leads for the molecular pathogenesis of these bacteria and the development of novel antimicrobial drugs.

Modulating carbohydrate-protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiology.

Diverse glycans on proteins impact cell and organism physiology, along with drug activity. Since many protein-based biotherapeutics are glycosylated and these glycans have biological activity, there is a desire to engineer glycosylation for recombinant protein-based biotherapeutics. Engineered glycosylation can impact the recombinant protein efficacy and also influence many cell pathways by first changing glycan-protein interactions and consequently modulating disease physiologies. However, its complexity is enormous. Recent advances in glycoengineering now make it easier to modulate protein-glycan interactions. Here, we discuss how engineered glycans contribute to therapeutic monoclonal antibodies (mAbs) in the treatment of cancers, how these glycoengineered therapeutic mAbs affect the transformed phenotypes and downstream cell pathways. Furthermore, we suggest how systems biology can help in the next generation mAb glycoengineering process by aiding in data analysis and guiding engineering efforts to tailor mAb glycan and ultimately drug efficacy, safety and affordability.

A reference genome of the Chinese hamster based on a hybrid assembly strategy

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 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 Chinese hamster ovary cell mutations have been detected in draft assembly gaps. This new assembly will be an invaluable resource for continued basic and pharmaceutical research.

Combating viral contaminants in CHO cells by engineering STAT1 mediated innate immunity

Viral contamination in biopharmaceutical manufacturing can lead to shortages in the supply of critical therapeutics. To facilitate the protection of bioprocesses, we explored the basis for the susceptibility of CHO cells, the most commonly used cell line in biomanufacturing, to RNA virus infection. Upon infection with certain ssRNA and dsRNA viruses, CHO cells fail to generate a significant interferon (IFN) response. Nonetheless, the downstream machinery for generating IFN responses and its antiviral activity is intact in these cells: treatment of cells with exogenously-added type I IFN or poly I:C prior to infection limited the cytopathic effect from Vesicular stomatitis virus (VSV), Encephalomyocarditis virus (EMCV), and Reovirus-3 virus (Reo-3) in a STAT1-dependent manner. To harness the intrinsic antiviral mechanism, we used RNA-Seq to identify two upstream repressors of STAT1: Gfi1 and Trim24. By knocking out these genes, the engineered CHO cells exhibited increased resistance to the prototype RNA viruses tested. Thus, omics-guided engineering of mammalian cell culture can be deployed to increase safety in biotherapeutic protein production among many other biomedical applications.

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

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 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.