Distinct CD16a features on human NK cells observed by flow cytometry correlate with increased ADCC.

Natural killer (NK) cells destroy tissue that have been opsonized with antibodies. Strategies to generate or identify cells with increased potency are expected to enhance NK cell-based immunotherapies. We previously generated NK cells with increased antibody-dependent cell mediated cytotoxicity (ADCC) following treatment with kifunensine, an inhibitor targeting mannosidases early in the N-glycan processing pathway. Kifunensine treatment also increased the antibody-binding affinity of Fc γ receptor IIIa/CD16a. Here we demonstrate that inhibiting NK cell N-glycan processing increased ADCC. We reduced N-glycan processing with the CRIPSR-CAS9 knockdown of MGAT1, another early-stage N-glycan processing enzyme, and showed that these cells likewise increased antibody binding affinity and ADCC. These experiments led to the observation that NK cells with diminished N-glycan processing capability also revealed a clear phenotype in flow cytometry experiments using the B73.1 and 3G8 antibodies binding two distinct CD16a epitopes. We evaluated this "affinity profiling" approach using primary NK cells and identified a distinct shift and differentiated populations by flow cytometry that correlated with increased ADCC.

Avian influenza A viruses exhibit plasticity in sialylglycoconjugate receptor usage in human lung cells.

IMPORTANCE: It is well known that influenza A viruses (IAV) initiate host cell infection by binding to sialic acid, a sugar molecule present at the ends of various sugar chains called glycoconjugates. These sugar chains can vary in chain length, structure, and composition. However, it remains unknown if IAV strains preferentially bind to sialic acid on specific glycoconjugate type(s) for host cell infection. Here, we utilized CRISPR gene editing to abolish sialic acid on different glycoconjugate types in human lung cells, and evaluated human versus avian IAV infections. Our studies show that both human and avian IAV strains can infect human lung cells by utilizing any of the three major sialic acid-containing glycoconjugate types, specifically N-glycans, O-glycans, and glycolipids. Interestingly, simultaneous elimination of sialic acid on all three major glycoconjugate types in human lung cells dramatically decreased human IAV infection, yet had little effect on avian IAV infection. These studies show that avian IAV strains effectively utilize other less prevalent glycoconjugates for infection, whereas human IAV strains rely on a limited repertoire of glycoconjugate types. The remarkable ability of avian IAV strains to utilize diverse glycoconjugate types may allow for easy transmission into new host species.

Fucosylated glycoproteins and fucosylated glycolipids play opposing roles in cholera intoxication.

Cholera toxin (CT) is the etiological agent of cholera. Here we report that multiple classes of fucosylated glycoconjugates function in CT binding and intoxication of intestinal epithelial cells. In Colo205 cells, knockout of B3GNT5, the enzyme required for synthesis of lacto- and neolacto-series glycosphingolipids (GSLs), reduces CT binding but sensitizes cells to intoxication. Overexpressing B3GNT5 to generate more fucosylated GSLs confers protection against intoxication, indicating that fucosylated GSLs act as decoy receptors for CT. Knockout (KO) of B3GALT5 causes increased production of fucosylated O-linked and N-linked glycoproteins, and leads to increased CT binding and intoxication. Knockout of B3GNT5 in B3GALT5 KO cells eliminates production of fucosylated GSLs but increases intoxication, identifying fucosylated glycoproteins as functional receptors for CT. These findings provide insight into molecular determinants regulating CT sensitivity of host cells.

Toward Automatic Inference of Glycan Linkages Using MSn and Machine Learning─Proof of Concept Using Sialic Acid Linkages.

Glycosidic linkages in oligosaccharides play essential roles in determining their chemical properties and biological activities. MSn has been widely used to infer glycosidic linkages but requires a substantial amount of starting material, which limits its application. In addition, there is a lack of rigorous research on what MSn protocols are proper for characterizing glycosidic linkages. In this work, to deliver high-quality experimental data and analysis results, we propose a machine learning-based framework to establish appropriate MSn protocols and build effective data analysis methods. We demonstrate the proof-of-principle by applying our approach to elucidate sialic acid linkages (α2'-3' and α2'-6') in a set of sialyllactose standards and NIST sialic acid-containing N-glycans as well as identify several protocol configurations for producing high-quality experimental data. Our companion data analysis method achieves nearly 100% accuracy in classifying α2'-3' vs α2'-6' using MS5, MS4, MS3, or even MS2 spectra alone. The ability to determine glycosidic linkages using MS2 or MS3 is significant as it requires substantially less sample, enabling linkage analysis for quantity-limited natural glycans and synthesized materials, as well as shortens the overall experimental time. MS2 is also more amenable than MS3/4/5 to automation when coupled to direct infusion or LC-MS. Additionally, our method can predict the ratio of α2'-3' and α2'-6' in a mixture with 8.6% RMSE (root-mean-square error) across data sets using MS5 spectra. We anticipate that our framework will be generally applicable to analysis of other glycosidic linkages.

Site specific N- and O-glycosylation mapping of the spike proteins of SARS-CoV-2 variants of concern.

The glycosylation on the spike (S) protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, modulates the viral infection by altering conformational dynamics, receptor interaction and host immune responses. Several variants of concern (VOCs) of SARS-CoV-2 have evolved during the pandemic, and crucial mutations on the S protein of the virus have led to increased transmissibility and immune escape. In this study, we compare the site-specific glycosylation and overall glycomic profiles of the wild type Wuhan-Hu-1 strain (WT) S protein and five VOCs of SARS-CoV-2: Alpha, Beta, Gamma, Delta and Omicron. Interestingly, both N- and O-glycosylation sites on the S protein are highly conserved among the spike mutant variants, particularly at the sites on the receptor-binding domain (RBD). The conservation of glycosylation sites is noteworthy, as over 2 million SARS-CoV-2 S protein sequences have been reported with various amino acid mutations. Our detailed profiling of the glycosylation at each of the individual sites of the S protein across the variants revealed intriguing possible association of glycosylation pattern on the variants and their previously reported infectivity. While the sites are conserved, we observed changes in the N- and O-glycosylation profile across the variants. The newly emerged variants, which showed higher resistance to neutralizing antibodies and vaccines, displayed a decrease in the overall abundance of complex-type glycans with both fucosylation and sialylation and an increase in the oligomannose-type glycans across the sites. Among the variants, the glycosylation sites with significant changes in glycan profile were observed at both the N-terminal domain and RBD of S protein, with Omicron showing the highest deviation. The increase in oligomannose-type happens sequentially from Alpha through Delta. Interestingly, Omicron does not contain more oligomannose-type glycans compared to Delta but does contain more compared to the WT and other VOCs. O-glycosylation at the RBD showed lower occupancy in the VOCs in comparison to the WT. Our study on the sites and pattern of glycosylation on the SARS-CoV-2 S proteins across the VOCs may help to understand how the virus evolved to trick the host immune system. Our study also highlights how the SARS-CoV-2 virus has conserved both N- and O- glycosylation sites on the S protein of the most successful variants even after undergoing extensive mutations, suggesting a correlation between infectivity/ transmissibility and glycosylation.

Cellular glycan modification by B3GAT1 broadly restricts influenza virus infection.

Communicable respiratory viral infections pose both epidemic and pandemic threats and broad-spectrum antiviral strategies could improve preparedness for these events. To discover host antiviral restriction factors that may act as suitable targets for the development of host-directed antiviral therapies, we here conduct a whole-genome CRISPR activation screen with influenza B virus (IBV). A top hit from our screen, beta-1,3-glucuronyltransferase 1 (B3GAT1), effectively blocks IBV infection. Subsequent studies reveal that B3GAT1 activity prevents cell surface sialic acid expression. Due to this mechanism of action, B3GAT1 expression broadly restricts infection with viruses that require sialic acid for entry, including Victoria and Yamagata lineage IBVs, H1N1/H3N2 influenza A viruses (IAVs), and the unrelated enterovirus D68. To understand the potential utility of B3GAT1 induction as an antiviral strategy in vivo, we specifically express B3GAT1 in the murine respiratory epithelium and find that overexpression is not only well-tolerated, but also protects female mice from a lethal viral challenge with multiple influenza viruses, including a pandemic-like H1N1 IAV. Thus, B3GAT1 may represent a host-directed broad-spectrum antiviral target with utility against clinically relevant respiratory viruses.