An optimized buffer system for NMR-based urinary metabonomics with effective pH control, chemical shift consistency...

Area of Science:

• Analytical Chemistry
• Metabolomics
• Biochemistry

Background:

• Nuclear Magnetic Resonance (NMR)-based metabonomics is crucial for studying metabolic changes.
• Inter-sample chemical shift variations in metabolites hinder effective data mining in NMR studies.

Purpose of the Study:

• To investigate the impact of pH and ionic strength on metabolite chemical shifts.
• To develop an optimized sample preparation method for NMR-based urinary metabonomics.

Main Methods:

• Systematic investigation of pH and ionic strength effects on 9 urinary metabolites.
• Optimization of buffer composition, concentration, and sample-to-buffer ratio.
• Analysis of chemical shift variations and signal-to-noise ratios.

Main Results:

• Chemical shifts decreased with increasing pH and increased with increasing ionic strength.
• Optimal conditions (pH 7.1-7.7, <0.15 M salt) significantly reduced chemical shift variations (<0.004 ppm).
• A new buffer system (K(2)HPO(4)/NaH(2)PO(4), pH 7.4, 1.5 M) was proposed for human urinary studies.

Conclusions:

• Optimized sample preparation minimizes chemical shift variations in NMR metabonomics.
• The proposed buffer system and correction strategies enhance data reliability for urinary metabonomics.
• This work provides a robust method for improving NMR-based metabolic profiling.