Understanding humoral immune responses to SARS-CoV-2 infection will play a critical role in the development of vaccines and antibody-based interventions. We report systemic and mucosal antibody responses in convalescent individuals who experienced varying severity of disease. Whereas assessment of neutralization and antibody-mediated effector functions revealed polyfunctional antibody responses in serum, only robust neutralization and phagocytosis were apparent in nasal wash samples. Serum neutralization and effector functions correlated with systemic SARS-CoV-2-specific IgG response magnitude, while mucosal neutralization was associated with nasal SARS-CoV-2-specific IgA. Antibody depletion experiments support the mechanistic relevance of these correlations. Associations between nasal IgA responses, virus neutralization at the mucosa, and less severe disease suggest the importance of assessing mucosal immunity in larger natural infection cohorts. Further characterization of antibody responses at the portal of entry may define their ability to contribute to protection from infection or reduced risk of hospitalization, informing public health assessment strategies and vaccine development efforts.

Primary immunodeficiencies (PID) comprise a diverse group of clinical disorders with varied genetic defects. Paradoxically, a substantial proportion of PID patients develop autoimmune phenomena in addition to having increased susceptibility to infections from their impaired immunity. Although much of our understanding comes from data gathered through experimental models, there are several well-characterized PID that have improved our knowledge of the pathways that drive autoimmunity. The goals of this review will be to discuss these immunodeficiencies and to review the literature with respect to the proposed mechanisms for autoimmunity within each put forth to date.

Glycans are found across the tree of life with remarkable structural diversity enabling critical contributions to diverse biological processes, ranging from facilitating host-pathogen interactions to regulating mitosis & DNA damage repair. While functional motifs within glycan structures are largely responsible for mediating interactions, the contexts in which the motifs are presented can drastically impact these interactions and their downstream effects. Here, we demonstrate the first deep learning method to represent both local and global context in the study of glycan structure-function relationships. Our method, glyBERT, encodes glycans with a branched biochemical language and employs an attention-based deep language model to learn biologically relevant glycan representations focused on the most important components within their global structures. Applying glyBERT to a variety of prediction tasks confirms the value of capturing rich context-dependent patterns in this attention-based model: the same monosaccharides and glycan motifs are represented differently in different contexts and thereby enable improved predictive performance relative to the previous state-of-the-art approaches. Furthermore, glyBERT supports generative exploration of context-dependent glycan structure-function space, moving from one glycan to "nearby" glycans so as to maintain or alter predicted functional properties. In a case study application to altering glycan immunogenicity, this generative process reveals the learned contextual determinants of immunogenicity while yielding both known and novel, realistic glycan structures with altered predicted immunogenicity. In summary, modeling the context dependence of glycan motifs is critical for investigating overall glycan functionality and can enable further exploration of glycan structure-function space to inform new hypotheses and synthetic efforts.

Background The bone marrow niche supports hematopoietic cell development through intimate contact with multipotent stromal mesenchymal stem cells; however, the intracellular signaling, function, and regulation of such supportive niche cells are still being defined. Our study was designed to understand how G protein receptor kinase 3 (GRK3) affects bone marrow mesenchymal stem cell function by examining primary cells from GRK3-deficient mice, which we have previously published to have a hypercellular bone marrow and leukocytosis through negative regulation of CXCL12/CXCR4 signaling. Methods Murine GRK3-deficient bone marrow mesenchymal stromal cells were harvested and cultured to differentiate into three lineages (adipocyte, chondrocyte, and osteoblast) to confirm multipotency and compared to wild type cells. Immunoblotting, modified-TANGO experiments, and flow cytometry were used to further examine the effects of GRK3 deficiency on bone marrow mesenchymal stromal cell receptor signaling. Microcomputed tomography was used to determine trabecular and cortical bone composition of GRK3-deficient mice and standard ELISA to quantitate CXCL12 production from cellular cultures. Results GRK3-deficient, bone marrow-derived mesenchymal stem cells exhibit enhanced and earlier osteogenic differentiation in vitro. The addition of a sphingosine kinase inhibitor abrogated the osteogenic proliferation and differentiation, suggesting that sphingosine-1-phosphate receptor signaling was a putative G protein-coupled receptor regulated by GRK3. Immunoblotting showed prolonged ERK1/2 signaling after stimulation with sphingosine-1-phosphate in GRK3-deficient cells, and modified-TANGO assays suggested the involvement of β-arrestin-2 in sphingosine-1-phosphate receptor internalization. Conclusions Our work suggests that GRK3 regulates sphingosine-1-phosphate receptor signaling on bone marrow mesenchymal stem cells by recruiting β-arrestin to the occupied GPCR to promote internalization, and lack of such regulation affects mesenchymal stem cell functionality.

Lectin-glycan interactions facilitate inter- and intracellular communication in many processes including protein trafficking, host-pathogen recognition, and tumorigenesis promotion. Specific recognition of glycans by lectins is also the basis for a wide range of applications in areas including glycobiology research, cancer screening, and antiviral therapeutics. To provide a better understanding of the determinants of lectin-glycan interaction specificity and support such applications, this study comprehensively investigates specificity-conferring features of all available lectin-glycan complex structures. Systematic characterization, comparison, and predictive modeling of a set of 221 complementary physicochemical and geometric features representing these interactions highlighted specificity-conferring features with potential mechanistic insight. Univariable comparative analyses with weighted Wilcoxon-Mann-Whitney tests revealed strong statistical associations between binding site features and specificity that are conserved across unrelated lectin binding sites. Multivariable modeling with random forests demonstrated the utility of these features for predicting the identity of bound glycans based on generalized patterns learned from non-homologous lectins. These analyses revealed global determinants of lectin specificity, such as sialic acid glycan recognition in deep, concave binding sites enriched for positively charged residues, in contrast to high mannose glycan recognition in fairly shallow but well-defined pockets enriched for non-polar residues. Focused fine specificity analysis of hemagglutinin interactions with human-like and avian-like glycans uncovered features representing both known and novel mutations related to shifts in influenza tropism from avian to human tissues. As the approach presented here relies on co-crystallized lectin-glycan pairs for studying specificity, it is limited in its inferences by the quantity, quality, and diversity of the structural data available. Regardless, the systematic characterization of lectin binding sites presented here provides a novel approach to studying lectin specificity and is a step towards confidently predicting new lectin-glycan interactions.