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: Disclosed herein are methods of producing glyco-modified viral antigens that provide a shift of the glycosylation profile of recombinant produced viral antigens (e.g. glycoproteins) towards the naturally occurring viral antigens (e.g. glycoproteins). Disclosed are methods of producing a modified viral antigen comprising expressing a viral antigen in a recombinant mammalian cell line having one or more of the endogenous genes Mgat2, Mgat4A, Mgat4B, Mgat5, St3Gal3, St3Gal4, B4galt1, B4galt2, B4galt3, B4galt4, B4galt5, B3gnt2, St3Gal6, SPPL3, and/or FUT8 inactivated and/or downregulated; and optionally a gene ST6Gall inserted. Disclosed are glyco-modified viral antigens produced by the method of using a recombinant mammalian cell line. Disclosed are methods of treating a subject in need thereof comprising administering a composition comprising a therapeutically effective amount of one or more of the glyco-modified viral antigens.

Abstract: A transformative method to profile the glycome in individual cells by leveraging computational biology tools with lectin or similar profiling technologies. Robust and accurate reconstruction glycomes with high-resolution glycan structure information for biological samples, including at the single cell level. Tools such as single-clone analysis andjoint-clone analysis, which may be used to assist researchers in analyzing single cell glycoprofiled samples, which identify how glycosylation variation across cells impact the cellular phenotypes. Single cell glycoprofiling using lectins is practically implemented to provide high resolution of the glycan structure information. Glycan profiling techniques having a wide range of biological applications from embryonic development to cancer and infectious disease due to high throughput, low cost, and robust reliability.

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 significant interferon (IFN) response is induced following treatment of CHO cells with exogenously-added type I IFN or poly I:C. Treatment of the CHO cells with poly I:C prior to infection limited the cytopathic effect from Vesicular stomatitis virus (VSV), Encephalomyocarditis vims (EMCV), and Reovirus-3 vims (Reo) in a STAT1-dependent manner By knocking out two upstream repressors of STAT1: Gfi1 and Trim 24, the engineered CHO cells exhibited increased resistance to virus contaminations. Thus, omics-guided engineering of mammalian cell culture can be deployed to increase safety in biotherapeutic protein production.