Abstract: A non-naturally occurring cell comprising an inoperative genomic asparaginase (Aspg) gene and an inoperative glutamine synthetase (Gs) gene, wherein the cell has been transfected with a controllably expressed gene encoding an enzyme having asparaginase activity, a controllably expressed gene encoding an enzyme having glutamine synthetase activity, and a controllably expressed gene encoding a heterologous protein of interest.

Abstract: Method for using glycan or glycomics data for classification, diagnosis, prognosis, subject stratification, or therapy decision making based on a sample with glycans or glycosylated molecules.

Abstract: The invention provides gene targets whose restoration leads to genome stabilization in host cells, such as Chinese Hamster Ovary (CHO) cells. Many DNA repair genes are mutated in CHO cells which compromises their ability to repair naturally occurring DNA damage, in particular double-strand breaks (DSBs). Unrepaired DSBs can give rise to chromosomal instability which, in turn, can lead to loss of transgenes from the genome. As a consequence, protein titer can drop significantly, rendering protein production unprofitable. The invention provides a set of mutated DNA repair genes whose restoration yields significant improvement in DSB repair, genome stability, and protein titer.

Abstract: The disclosed technology provides a computational prediction modeling comprising a novel algorithm for prediction of glycosylation or to optimize biopharmaceutical production of proteins of therapeutic relevance. The model of the disclosed technology can be used to predict glycosylation changes based solely on the stating glycoprofiles in any host cells and known or suggested rules on enzyme specificity. Applications of the invention model are also provided.

Abstract: Glycosylated biopharmaceuticals are important in the global pharmaceutical market. Despite the importance of their glycan structures, our limited knowledge of the glycosylation machinery still hinders controllability of this critical quality attribute. To facilitate discovery of glycosyltransferase specificity and predict glycoengineering efforts, here we extend an approach to model biosynthetic pathways for all measured glycans, and the Markov chain modeling is used to learn glycosyltransferase isoform activities and predict glycosylation following glycosyltransferase knock-in/knockout. We apply our methodology to four different glycoengineered therapeutics (i.e., Rituximab, erythropoietin, Enbrel, and alpha-1 antitrypsin) produced in CHO cells, along with o-glycosylation and lipid profiles. Our models accurately predict N-linked glycosylation following glycoengineering and further quantified the impact of glycosyltransferase mutations on reactions catalyzed by other glycosyltransferases.

Abstract: A non-naturally occurring cell comprising an inoperative genomic asparaginase (Aspg) gene and an inoperative glutamine synthetase (Gs) gene, wherein the cell has been transfected with a controllably expressed gene encoding an enzyme having asparaginase activity, a controllably expressed gene encoding an enzyme having glutamine synthetase activity, and a controllably expressed gene encoding a heterologous protein of interest.

Abstract: Provided are mammalian cells devoid of lactate dehydrogenase activity.

Abstract: Provided are mammalian cells devoid of lactate dehydrogenase activity.

Abstract: The disclosed technology provides a computational prediction modeling comprising a novel algorithm for prediction of glycosylation or to optimize biopharmaceutical production of proteins of therapeutic relevance. The model of the disclosed technology can be used to predict glycosylation changes based solely on the stating glycoprofiles in any host cells and known or suggested rules on enzyme specificity. Applications of the invention model are also provided.

Abstract: Embodiments of the present invention generally relate to the computational analysis and characterization biological networks at the cellular level in Chinese Hamster Ovary (CHO) cells. Based on computational methods utilizing a hamster reference genome, the invention provides methods for identifying a CHO cell line having a desired genetic trait, as well as for generating a desired CHO cell line having a genetic basis for a desired phenotype. Additionally, described herein are methods for constructing and analyzing in silico models of biological networks for CHO cells.