The number of N-glycans (n) is a distinct feature of each glycoprotein sequence and cooperates with the physical properties of the Golgi N-glycan-branching pathway to regulate surface glycoprotein levels. The Golgi pathway is ultrasensitive to hexosamine flux for the production of tri- and tetra-antennary N-glycans, which bind to galectins and form a molecular lattice that opposes glycoprotein endocytosis. Glycoproteins with few N-glycans (e.g., TbetaR, CTLA-4, and GLUT4) exhibit enhanced cell-surface expression with switch-like responses to increasing hexosamine concentration, whereas glycoproteins with high numbers of N-glycans (e.g., EGFR, IGFR, FGFR, and PDGFR) exhibit hyperbolic responses. Computational and experimental data reveal that these features allow nutrient flux stimulated by growth-promoting high-n receptors to drive arrest/differentiation programs by increasing surface levels of low-n glycoproteins. We have identified a mechanism for metabolic regulation of cellular transition between growth and arrest in mammals arising from apparent coevolution of N-glycan number and branching.

N-Glycan branching in the medial-Golgi generates ligands for lattice-forming lectins (e.g., galectins) that regulate surface levels of glycoproteins including epidermal growth factor (EGF) and transforming growth factor-beta (TGF-beta) receptors. Moreover, functional classes of glycoproteins differ in N-glycan multiplicities (number of N-glycans/peptide), a genetically encoded feature of glycoproteins that interacts with metabolic flux (UDP-GlcNAc) and N-glycan branching to differentially regulate surface levels. Oncogenesis increases beta1,6-N-acetylglucosaminyltransferase V (encoded by Mgat5) expression, and its high-affinity galectin ligands promote surface retention of growth receptors with a reduced dependence on UDP-GlcNAc. Mgat5(-/-) tumor cells are less metastatic in vivo and less responsive to cytokines in vitro, but undergo secondary changes that support tumor cell proliferation. These include loss of Caveolin-1, a negative regulator of EGF signaling, and increased reactive oxygen species, an inhibitor of phosphotyrosine phosphatases. These studies suggest a systems approach to cancer treatment where the surface distribution of receptors is targeted through metabolism and N-glycan branching to induce growth arrest.

How environmental factors combine with genetic risk at the molecular level to promote complex trait diseases such as multiple sclerosis (MS) is largely unknown. In mice, N-glycan branching by the Golgi enzymes Mgat1 and/or Mgat5 prevents T cell hyperactivity, cytotoxic T-lymphocyte antigen 4 (CTLA-4) endocytosis, spontaneous inflammatory demyelination and neurodegeneration, the latter pathologies characteristic of MS. Here we show that MS risk modulators converge to alter N-glycosylation and/or CTLA-4 surface retention conditional on metabolism and vitamin D3, including genetic variants in interleukin-7 receptor-α (IL7RA*C), interleukin-2 receptor-α (IL2RA*T), MGAT1 (IVAVT−T) and CTLA-4 (Thr17Ala). Downregulation of Mgat1 by IL7RA*C and IL2RA*T is opposed by MGAT1 (IVAVT−T) and vitamin D3, optimizing branching and mitigating MS risk when combined with enhanced CTLA-4 N-glycosylation by CTLA-4 Thr17. Our data suggest a molecular mechanism in MS whereby multiple environmental and genetic inputs lead to dysregulation of a final common pathway, namely N-glycosylation.

Summary Modern single-cell technologies allow multiplexed sampling of cellular states within a tissue. However, computational tools that can infer developmental cell-state transitions reproducibly from such single-cell data are lacking. Here, we introduce p-Creode, an unsupervised algorithm that produces multi-branching graphs from single-cell data, compares graphs with differing topologies, and infers a statistically robust hierarchy of cell-state transitions that define developmental trajectories. We have applied p-Creode to mass cytometry, multiplex immunofluorescence, and single-cell RNA-seq data. As a test case, we validate cell state-transition trajectories predicted by p-Creode for intestinal tuft cells, a rare, chemosensory cell type. We clarify that tuft cells are specified outside of the Atoh1-dependent secretory lineage in the small intestine. However, p-Creode also predicts, and we confirm, that tuft cells arise from an alternative, Atoh1-driven developmental program in the colon. These studies introduce p-Creode as a reliable method for analyzing large datasets that depict branching transition trajectories. p-Creode is publicly available for download here: https://github.com/KenLauLab/pCreode.

The association of receptors and solute transporters with components of the endocytic machinery regulates their surface levels, and thereby cellular sensitivity to cytokines, ligands and nutrients in the extracellular environment. Most transmembrane receptors and solute transporters are glycoproteins, and the Asn (N)-linked oligosaccharides (N-glycans) can bind animal lectins, forming multivalent lattices or microdomains that regulate glycoprotein mobility in the plane of membrane. The N-glycan number (sequence-encoded NXS/T) and context-dependent Golgi N-glycan branching cooperate to regulate glycoprotein affinities for the galectin family of lectins. Galectin-3 binding reduces EGF receptor trafficking into clathrin-coated pits and caveolae lipid rafts, decreases ligand-independent receptor activation and promotes α5β1 integrin remodelling in focal adhesions. N-glycan branching in the medial Golgi increases glycan affinity for galectins, and the Golgi pathway is sensitive to uridine diphosphate-Nacetylglucosamine (UDP-GlcNAc) supply, in turn hexosamine pathway metabolites (fructose-6-P, glutamine and acetyl-CoA). Thus, lattice avidity and cellular responsiveness to extracellular cues are regulated in an adaptive manner by metabolism and Golgi modification to glycoproteins. Computational modelling of the hexosamine/Golgi/lattice has provided new insight on cell surface adaptation in cancer and autoimmune disease.

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Highlights d Cell distance distributions define global data structure in native and latent space d Input cell distribution is determinant of dimensionality reduction performance d Modality-specific cell distributions influence degree of structural preservation

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.