Single-Cell Multimodal Functional Glycan Profiling Identifies Novel T Cell Immunomodulatory Glycan Signatures 2309845

Abstract

Abstract Introduction Glycans are key regulators of immune recognition, yet how endogenous human lectins interpret dynamic glycan changes at single-cell resolution remains poorly understood. Existing single-cell omics platforms do not measure functional glycan-lectin interactions, limiting the discovery of glycan-mediated immunoregulatory programs. To address this gap, we developed scGOAT-seq, a multimodal single-cell method that integrates DNA-barcoded recombinant human lectins with transcriptomic profiling to generate physiologically grounded readouts of functional glycan states across diverse immune contexts. Methods We curated and validated a panel of recombinant human lectins, including Siglec-7, Siglec-9, Siglec-15, Galectin-8/9, DC-SIGN, and MBL, that collectively span major mammalian glycan classes and applied them using scGOAT-seq on PBMCs under different immune perturbations. Results Applied to perturbed peripheral immunity, scGOAT-seq revealed stimulus-specific remodeling of Siglec-ligand landscapes that demarcate discrete immune activation states. In CD4 T cells, Siglec-9L and Siglec-15L distinguished immuno-metabolic, transitional, and effector-like activation programs, whereas Siglec-7L uniquely tracked IL-2-independent activation pathways associated with innate-like stimulation. To probe functional consequences of disrupting these pathways, we blocked Siglec-7/9 receptors during LPS stimulation. Blockade reduced Siglec-ligand display, rewired glycan landscapes across monocytes, NK cells, and T cells, and amplified inflammatory, metabolic, and cytotoxic transcriptional programs. These blockade-induced signatures showed prognostic relevance in TCGA kidney cancer datasets, highlighting their potential translational significance. Conclusion Together, scGOAT-seq defines a powerful framework for functional glycan profiling in single cells, revealing previously unrecognized glycan-defined T cell states and offering new avenues for diagnostic stratification and therapeutic glyco-engineering. Funding Source MIT Koch Institute Traditional Bridge Award, MIT School of Science Research Innovation Award, MIT Koch Institute Graduate Fellowship Topic Categories Technological Innovations in Immunology (TECH)