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Related Concept Videos

Oligosaccharide Assembly01:24

Oligosaccharide Assembly

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Protein glycosylation starts in the ER lumen and continues in the Golgi apparatus. Glycosyltransferases catalyze the addition of sugar molecules or glycosylation of proteins. Usually, these enzymes add sugars to the hydroxyl groups of selected serine or threonine residues to form O-linked glycans or the amino groups of asparagine residues to form N-linked glycans. Different positions on the same polypeptide chain can contain differently linked glycans.
Multiple sugar molecules that may or may...
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Related Experiment Video

Updated: May 31, 2025

Improved In-gel Reductive &#946;-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry
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Identification of Oligosaccharide Isomers Using Electrostatically Asymmetric OmpF Nanopore.

Fan Gao1, Jia-Hong Wang1, Hui Ma1

  • 1Molecular Sensing and Imaging Center, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.

Angewandte Chemie (International Ed. in English)
|January 24, 2025
PubMed
Summary

A new OmpF nanopore sensor detects neutral oligosaccharides at low concentrations. This sensor accurately identifies differences in glycosidic bonds, crucial for analyzing complex biological samples.

Keywords:
Glycosidic Bond ConfigurationLabel FreeOligosaccharide SensingOmpF NanoporeSingle Molecule

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Area of Science:

  • Carbohydrate Chemistry
  • Analytical Chemistry
  • Biophysics

Background:

  • Oligosaccharides (glycans) present analytical challenges due to their uncharged nature and complex stereoisomeric diversity.
  • Accurate analysis of glycans is crucial for understanding biological processes but is hindered by their structural complexity and lack of charge.

Purpose of the Study:

  • To develop a novel single-molecule sensor for sensitive and stereoselective detection of oligosaccharides.
  • To overcome the limitations of analyzing uncharged and structurally diverse glycans.

Main Methods:

  • Development of a single-molecule oligosaccharide sensor utilizing the OmpF nanopore.
  • Leveraging the natural electroosmotic flow within the OmpF nanopore for driving unlabeled neutral oligosaccharides.
  • Employing the asymmetric constriction zone of OmpF to create a stereoselective recognition site.
  • Integration of machine learning algorithms for data analysis and recognition.

Main Results:

  • Detection of unlabeled neutral oligosaccharides at concentrations as low as 6.4 μM.
  • Sensitive identification of differences in glycosidic bonds within cell lysate samples.
  • Achieved 99.9% recognition accuracy for tetrasaccharides differing by a single glycosidic bond using machine learning.

Conclusions:

  • The OmpF nanopore sensor offers a highly sensitive analytical tool with a broad dynamic range for oligosaccharide analysis.
  • Enables chiral recognition of oligosaccharides at low concentrations.
  • Suitable for analyzing low-abundance and complex biological samples, including cell lysates.