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Large-scale carbohydrate analysis by capillary array electrophoresis: part 2. Data normalization and quantification.

Julia Khandurina1, Abraham A Anderson, Nels A Olson

  • 1Diversa Corporation, San Diego, CA 92121, USA. jkhandurina@diversa.com.

Electrophoresis
|October 9, 2004
PubMed
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Automated 96-capillary array electrophoresis (CAE) provides high-performance profiling of sugars for bioindustrial labs. New normalization tools ensure reliable data for monitoring enzymatic polysaccharide digestion products.

Area of Science:

  • Analytical Chemistry
  • Biotechnology
  • Biochemistry

Background:

  • Bioindustrial laboratories require high-throughput methods for analyzing carbohydrates.
  • Enzymatic polysaccharide digestion yields complex mixtures of mono- and oligosaccharides.
  • Existing analytical methods may lack the sensitivity or throughput for large-scale applications.

Purpose of the Study:

  • To present an automated 96-capillary array electrophoresis (CAE) methodology for high-performance carbohydrate profiling.
  • To address challenges in data variability for reliable analysis of enzymatic digestion products.
  • To develop robust data processing and quantification tools for bioindustrial applications.

Main Methods:

  • Optimization of mono- and oligosaccharide separations using 96-capillary array electrophoresis.

Related Experiment Videos

  • Implementation of internal fluorescent standards for migration time normalization and trace alignment.
  • Development of data processing, visualization, and programming tools for CAE data analysis.

    • Main Results:

    • Achieved high-performance profiling of oligo- and monosaccharides with sensitivity at low nanomolar concentrations.
    • Demonstrated good resolving power and reliability in CAE experiments.
    • Successfully developed data normalization tools to manage capillary-to-capillary and run-to-run variations.

    Conclusions:

    • The developed CAE methodology is suitable for large-scale, high-performance profiling of carbohydrates in bioindustrial settings.
    • The normalization strategies and developed tools enhance the reliability and applicability of CAE for monitoring enzymatic polysaccharide digestion.
    • This approach supports diverse applications in agricultural, chemical, and food industries.