Comparative study for analysis of carbohydrates in biological samples

Area of Science:

• Analytical Chemistry
• Chromatography
• Mass Spectrometry

Background:

• Accurate carbohydrate analysis is crucial in various scientific fields.
• Selecting the optimal chromatographic method coupled with mass spectrometry is essential for reliable results.
• Existing methods may have limitations in separation performance, sensitivity, or repeatability.

Purpose of the Study:

• To comparatively evaluate four common chromatographic techniques for carbohydrate analysis.
• To determine the most suitable method for monosaccharide analysis in biological matrices.
• To assess the impact of mass spectrometry working modes on analytical performance.

Main Methods:

• Comparative analysis of four chromatographic methods: supercritical fluid chromatography (SFC), hydrophilic interaction liquid chromatography (HILIC), reversed-phase liquid chromatography (RP-LC), and gas chromatography (GC).
• All methods were coupled with triple quadrupole mass spectrometry (QqQ-MS).
• Investigated different mass spectrometry modes: full scan, single ion monitoring (SIM), and multiple reaction monitoring (MRM).
• Carbohydrates were derivatized using 1-phenyl-3-methyl-5-pyrazolone (PMP) for RP-LC and GC.

Main Results:

• Gas chromatography (GC) and reversed-phase liquid chromatography (RP-LC), after derivatization, demonstrated superior separation performance compared to SFC and HILIC.
• Targeted mass spectrometry analysis (SIM and MRM) significantly improved sensitivity and repeatability, particularly for HILIC.
• RP-LC-MS/MS using PMP derivatization achieved nanomolar detection limits (low µg/L range) for monosaccharides.
• The optimized RP-LC-MS method was successfully applied to diverse biological samples, including herbal liquors, pectins, and a human glycoprotein.

Conclusions:

• Reversed-phase liquid chromatography coupled with mass spectrometry (RP-LC-MS) after PMP derivatization is the most suitable method for monosaccharide analysis.
• The method provides excellent separation, high sensitivity, and good repeatability.
• This validated approach is applicable to the analysis of carbohydrates in complex biological matrices.