Separation and quantification of neoagaro- and agaro-oligosaccharide products generated from agarose digestion by beta-agarase and HCl in liquid chromatography systems.
ABSTRACT A series of neoagaro-oligosaccharides (NAOS) were separated and isolated by beta-agarase digestion and agaro-oligosaccharides (AOS) by HCl hydrolysis from agarose with defined quantity and degree of polymerization (DP). Profiles of the oligomer length in the crude product mixtures were monitored by two high-performance liquid chromatography (HPLC) systems: size-exclusion chromatography (SEC) and NH2-column chromatography (NH2-HPLC), coupled with an evaporative light-scattering detector (ELSD). Calibration curves were established separately to identify the DP and quantify the amount of the oligomer products analyzed in the two systems. Each system was optimized to generate a spectrum of saccharide oligomers with various DP, where the reaction yield for NAOS was 52.7% by 4U/mg beta-agarase and for AOS was 45.6% by 0.4M HCl. SEC resolved the product in size ranges consisting of DP 1-22 for NAOS and DP 1-14 for AOS. NH2-HPLC clearly resolved both distinct saccharide product sizes within DP 12. The optimized system was connected with a fraction collector to isolate and quantify these individually separated products. The total product yields of the recovered NAOS of DP 1-22 and AOS of DP 1-14 by the SEC system were 84.7% and 82.9%, respectively. NH2-HPLC recovered NAOS and AOS, both with a DP of 1-10 with total product yields of 48.9% and 90.0%, respectively. Isolated NAOS and AOS product fractions were inspected by (1)H NMR spectroscopy and ESIMS spectrometry to confirm structure, molecular mass, and purity. This study established feasible systems for the preparation and qualitative and quantitative measurements, as well as for the isolation of various sizes of oligomers generated from agarose.
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ABSTRACT: A series of linear glucan saccharides (GS) with defined quantity and degree of polymerization (DP) were synthesized from α-d-glucose 1-phosphate (α-d-Glc 1-P) by phosphorylase-a. The GS product fractions with average DP 11, 22, 38, 52, 60, 70, and 79 were measured by HPSEC-ELSD system. Then the same seven fractions were resolved into individual peaks with DP: 6–14, 10–32, 27–55, 37–67, 44–75, 49–83 and 53–89 by HPAEC-PAD system. Results showed that measurement of α-d-Glc 1-P amount consuming during GS synthesis by both systems enable calculation of reaction yield. The reaction yield for the 24 h biosynthesis of the GS product was 25.3% (measured by HPSEC-ELSD) or 29.1% (measured by HPAEC-PAD). The HPSEC-ELSD and HPAEC-PAD systems were also successfully used for phosphorylase-a activity measurement in order to perform its kinetic characterization. This study established feasible systems for preparation of various sizes of the GS with defined DP and quantity as well as characterization of phosphorylase-a kinetics.Carbohydrate Polymers 06/2014; 106:209–216. · 3.92 Impact Factor
- Studies in Surface Science and Catalysis - STUD SURF SCI CATAL. 01/2002; 141:395-402.
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ABSTRACT: This study was to investigate near-infrared reflectance spectroscopy (NIRS) application for determination of individual soluble carbohydrate content in soybean seeds for development of high-quality new soybean variety and quality control of soy products. NIRS was used as a rapid and simultaneous analysis method to determine individual soluble carbohydrate content of soybean seeds in Korea. A total of 240 samples (about 2 g) were scanned in the reflectance mode and the reference values for the individual soluble carbohydrate contents were measured by high performance liquid chromatography. Calibration equation for individual soluble carbohydrate contents were developed using modified partial least-squares regression with internal cross validation (n=155). The equation for sucrose content had lower standard error of cross-validation, higher R2 (coefficient of determination in calibration), and higher ratio of unexplained variance divided by variance (1-VR) value than that for raffinose, and stachyose. Prediction of an external validation set (n=85) showed significant correlation between reference value and NIRS estimated value based on the standard error of prediction (SEP), r2 (coefficient of determination in prediction), and the ratio of standard deviation (SD) of reference data to SEP. The model for sucrose had higher value of RSP (ratio of standard deviation for prediction, the ratio of SD of reference data to SEP(C) in the external validation set) and r2 (3.50 and 0.921, respectively), thereby that equation has good quantitative accuracy, whereas those of raffinose, and stachyose had lower value (below 0.89 and 0.45, respectively). These results indicated that NIRS could be used to rapidly determine the content of sucrose in soybean seed samples in the breeding programs for development of high-quality new soybean variety.Journal of the Korean Society for Applied Biological Chemistry 08/2010; 53(4). · 0.54 Impact Factor