Streamlined gram-scale natural N-glycan production using reversible tagging after oxidative release of natural glycans

The study of natural glycans is fundamental to modern glycomics; however, the functional analysis of these glycans is limited by their low natural abundance, structural heterogeneity, and the absence of efficient preparative-scale isolation methods. Here, we present a streamlined approach for the gram-scale production of complex natural N-glycans in their reducing form by combining oxidative release of natural glycans (ORNG) using household bleach, an innovative cleavable tag chemistry, and optimized multi-dimensional chromatography. Our ORNG process releases N-glycans from kilogram-scale of natural sources containing various glycoproteins, which can be efficiently attached with a 4-aminobenzoate tag, facilitating the selective separation of these glycans from other biomolecules. The tagged glycans can be purified via dry-load HILIC flash chromatography at gram scale followed by reverse-phase HPLC. Treatment with Oxone quantitatively cleaves the tag, regenerating the free reducing N-glycans in high yield. This method provides an accessible, gram-scale source of complex N-glycans, including complex asymmetric structures that are challenging to synthesize through conventional chemoenzymatic approaches. We believe this approach represents a versatile strategy for acquiring complex natural glycans, opening new avenues for the functional exploration of N-glycans in glycoscience.

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Publication Details

Journal
Communications Chemistry
Published
2025-04-04
DOI
https://doi.org/10.1038/s42004-025-01499-x
Primary Topic
Glycosylation and Glycoproteins Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Streamlined gram-scale natural N-glycan production using reversible tagging after oxidative release of natural glycans

Golden Chen, Maodong Yan, Xuezheng Song, Yi Lasanajak et al.
1 links
Communications Chemistry
Glycosylation and Glycoproteins Research
article

Streamlined gram-scale natural N-glycan production using reversible tagging after oxidative release of natural glycans

Golden Chen, Maodong Yan, Xuezheng Song, Yi Lasanajak, Qing Zhang
article en

Abstract

The study of natural glycans is fundamental to modern glycomics; however, the functional analysis of these glycans is limited by their low natural abundance, structural heterogeneity, and the absence of efficient preparative-scale isolation methods. Here, we present a streamlined approach for the gram-scale production of complex natural N-glycans in their reducing form by combining oxidative release of natural glycans (ORNG) using household bleach, an innovative cleavable tag chemistry, and optimized multi-dimensional chromatography. Our ORNG process releases N-glycans from kilogram-scale of natural sources containing various glycoproteins, which can be efficiently attached with a 4-aminobenzoate tag, facilitating the selective separation of these glycans from other biomolecules. The tagged glycans can be purified via dry-load HILIC flash chromatography at gram scale followed by reverse-phase HPLC. Treatment with Oxone quantitatively cleaves the tag, regenerating the free reducing N-glycans in high yield. This method provides an accessible, gram-scale source of complex N-glycans, including complex asymmetric structures that are challenging to synthesize through conventional chemoenzymatic approaches. We believe this approach represents a versatile strategy for acquiring complex natural glycans, opening new avenues for the functional exploration of N-glycans in glycoscience.

Communications ChemistryVol. 8(1)
Emory University (US), Performance Communications (US)
Emory University, National Institutes of Health, School of Medicine, Emory University, National Institute of General Medical Sciences
Openalex Percentile: Top 94%
Glycosylation and Glycoproteins Research
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Streamlined gram-scale natural N-glycan production using reversible tagging after oxidative release of natural glycans — Golden Chen, Maodong Yan, et al. · Communications Chemistry (2025) | TGRS Research Map | TGRS