Combining Glucose Units, m/z, and Collision Cross Section Values: Multiattribute Data for Increased Accuracy in Automated Glycosphingolipid Glycan Identifications and Its Application in Triple Negative Breast Cancer.

Glycan head-groups attached to glycosphingolipids (GSLs) found in the cell membrane bilayer can alter in response to external stimuli and disease, making them potential markers and/or targets for cellular disease states. To identify such markers, comprehensive analyses of glycan structures must be undertaken. Conventional analyses of fluorescently labeled glycans using hydrophilic interaction high-performance liquid chromatography (HILIC) coupled with mass spectrometry (MS) provides relative quantitation and has the ability to perform automated glycan assignments using glucose unit (GU) and mass matching. The use of ion mobility (IM) as an additional level of separation can aid the characterization of closely related or isomeric structures through the generation of glycan collision cross section (CCS) identifiers. Here, we present a workflow for the analysis of procainamide-labeled GSL glycans using HILIC-IM-MS and a new, automated glycan identification strategy whereby multiple glycan attributes are combined to increase accuracy in automated structural assignments. For glycan matching and identification, an experimental reference database of GSL glycans containing GU, mass, and CCS values for each glycan was created. To assess the accuracy of glycan assignments, a distance-based confidence metric was used. The assignment accuracy was significantly better compared to conventional HILIC-MS approaches (using mass and GU only). This workflow was applied to the study of two Triple Negative Breast Cancer (TNBC) cell lines and revealed potential GSL glycosylation signatures characteristic of different TNBC subtypes.

Inactivation of GDP-fucose transporter gene (Slc35c1) in CHO cells by ZFNs, TALENs and CRISPR-Cas9 for production of fucose-free antibodies.

Removal of core fucose from N-glycans attached to human IgG1 significantly enhances its affinity for the receptor FcγRIII and thereby dramatically improves its antibody-dependent cellular cytotoxicity activity. While previous works have shown that inactivation of fucosyltransferase 8 results in mutants capable of producing fucose-free antibodies, we report here the use of genome editing techniques, namely ZFNs, TALENs and the CRISPR-Cas9, to inactivate the GDP-fucose transporter (SLC35C1) in Chinese hamster ovary (CHO) cells. A FACS approach coupled with a fucose-specific lectin was developed to rapidly isolate SLC35C1-deficient cells. Mass spectrometry analysis showed that both EPO-Fc produced in mutants arising from CHO-K1 and anti-Her2 antibody produced in mutants arising from a pre-existing antibody-producing CHO-HER line lacked core fucose. Lack of functional SLC35C1 in these cells does not affect cell growth or antibody productivity. Our data demonstrate that inactivating Slc35c1 gene represents an alternative approach to generate CHO cells for production of fucose-free antibodies.