ArticleJournal of the American Chemical Society2018
Mechanistic Investigation and Multiplexing of Liposome-Assisted Metabolic Glycan Labeling.
Article in Journal of the American Chemical Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 66 citations in OpenAlex.
- Chemical engineering of γδ T cells with cancer cell-targeting antibodies for enhanced tumor immunotherapy.National science review · 2025Article
- Navigating the Clinical Landscape of Liposomal Therapeutics in Cancer Treatment.Pharmaceutics · 2025Review
- Late-Stage Functionalization of Living Organisms: Rethinking Selectivity in Biology.Chemical reviews · 2024Review
- Leveraging intracellular ALDH1A1 activity for selective cancer stem-like cell labeling and targeted treatment via in vivo click reaction.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Recent advances in developing active targeting and multi-functional drug delivery systems via bioorthogonal chemistry.Signal transduction and targeted therapy · 2022Review
- Cell-type-specific labeling and profiling of glycans in living mice.Nature chemical biology · 2022Article
- Cell membrane-camouflaged liposomes for tumor cell-selective glycans engineering and imaging in vivo.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Design and Synthesis of Metabolic Chemical Reporters for the Visualization and Identification of Glycoproteins.RSC chemical biology · 2021Article
- Harnessing nanotechnology to expand the toolbox of chemical biology.Nature chemical biology · 2021Review
- Metabolic glycan labelling for cancer-targeted therapy.Nature chemistry · 2020Review
- Nongenetic Bioconjugation Strategies for Modifying Cell Membranes and Membrane Proteins: A Review.Bioconjugate chemistry · 2020Review
- Self-triggered click reaction in an Alzheimer's disease model:Chemical science · 2019Article
- Nanopipette-assisted single cell metabolic glycan labeling.RSC advances · 2019Article
- A Sulfonamide Sialoside Analogue for Targeting Siglec-8 and -F on Immune Cells.Journal of the American Chemical Society · 2019Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
Metabolic labeling of glycans with bioorthogonal reporters has been widely used for glycan imaging and glycoproteomic profiling. One of the intrinsic limitations of metabolic glycan labeling is the lack of cell-type selectivity. The recently developed liposome-assisted bioorthogonal reporter (LABOR) strategy provides a promising means to overcome this limitation, but the mechanism of LABOR has not been investigated in detail. In this work, we performed a mechanistic study on LABOR and explored its multiplexing capability. Our studies support an endocytosis-salvage mechanism. The ligand-targeted liposomes encapsulating azidosugars are internalized into the endosome via the receptor-mediated endocytosis. Unlike the conventional drug delivery, LABOR does not rely on the endosomal escape pathways. Rather, the liposomes are allowed to enter the lysosome, inside which the azidosugars are released from the liposomes. The released azidosugars then intercept the salvage pathways of monosaccharides and get transported into the cytosol by lysosomal sugar transporters. Based on this mechanism, we expanded the scope of LABOR by evaluating a series of ligand-receptor pairs for targeting sialoglycans in various cell types. Different ligand types including small molecules, antibodies, aptamers, and peptides could be easily implemented into LABOR. Finally, we demonstrated that the sialoglycans in two distinct cell populations in a co-cultured system could be selectively labeled with two distinct chemical reporters by performing a multiplexed LABOR labeling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.