HPLC with charged aerosol detector (CAD) as a quality control platform for analysis of carbohydrate polymers

QC analysis of carbohydrates has been historically cumbersome due to lengthy and laborious derivatization techniques and the requirement of complimentary instrumentation. HILIC-CAD has emerged as an effective platform for direct monosaccharide composition analysis of complex carbohydrates without de...

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Bibliographic Details
Published in:BMC research notes 2019-05, Vol.12 (1), p.268-268, Article 268
Main Authors: Ghosh, Rajarshi, Kline, Paul
Format: Article
Language:English
Subjects:
Acids
Amino sugars
Backup software
Carbohydrate analysis
Carbohydrates
Chromatography
Detection equipment
Fructose
Glycoproteins
Health aspects
Herbal medicine
High performance liquid chromatography
HILIC
HPSEC
Hyaluronic acid
Ions
Medical research
Monosaccharides
Polymer industry
Polymers
Polysaccharides
QC of carbohydrates
Quality control
Research Note
Sensors
Sugar
Uronic acids
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Summary:QC analysis of carbohydrates has been historically cumbersome due to lengthy and laborious derivatization techniques and the requirement of complimentary instrumentation. HILIC-CAD has emerged as an effective platform for direct monosaccharide composition analysis of complex carbohydrates without derivatization. Although, several neutral sugars have been separated and detected using HILIC-CAD, there has not been any report on acidic and amino sugar analysis using this method. In this study, we developed a gradient method for simultaneous analysis of acidic, amino and select neutral monosaccharides. As an application of the HILIC-CAD method, we performed composition analysis of commercially purchased hyaluronic acid products. Additionally, since CAD is suitable for SEC experiments, we tested the homogeneity of hyaluronic acids using a SEC-CAD method. We separated common uronic acids (GlcA, GalA, LIdoA and Neu5Ac), amino sugars (GlcN, GalN and GlcNAc) and select neutral sugars (LRha, LFuc, Man and Gal) using a gradient HILIC-CAD method. The optimized gradient method demonstrated good linearity (R  > 0.99), precision (RSD 
ISSN:1756-0500
1756-0500
DOI:10.1186/s13104-019-4296-y