Elucidation of Strains Grouping and Polysaccharide structural Features by Cluster Analysis and the Relationships of Polysaccharide Structure-Macrophage Stimulatory by Various Statistical Analyses on Ten Regionally Different Strains of Lentinula edodes

• Main Authors: Tiffany Chien Ting Lo, 羅千婷
• Other Authors: C. Allen Chang
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/54588056602086608156

博士 === 國立交通大學 === 生物科技系所 === 95 === In this research, we have made major efforts to isolate polysaccharides from the submerged cultures of ten different strains of Lentinula edodes and have determined their monosaccharide compositions, molecular weights, structural linkage types, immuno-modulating and anti-cancer activities. The isolates had a molecular weight distribution between 1x102 and 3x103 kDa. The monosaccharide composition analysis revealed that these polysaccharides were heterogeneous and contained glucose, mannose, xylose, galactose, fucose, rhamnose and arabinose in different ratios. A major form of polysaccharide linkage with a backbone of alpha-(1-4)-glucan and side chains of beta-(1-6)-glucan has been identified. A method using the pressurized water extraction (PWE) technique (10.1 MPa, 28 °C, 70 min) to improve the extraction efficiency and to retain the general structures and bioactivities of the polysaccharides has also been developed. These polysaccharides were also found to stimulate macrophage cell-cell interactions. The use of multiple linear regression analysis allows the deduction of the correlation between the monosaccharide composition ratios and in vitro macrophage (RAW264.7) stimulatory activities of polysaccharides obtained from different mushroom strains. Arabinose, xylose, mannose, fucose and galactose were identified as the monosaccharides that could be related to macrophage stimulatory activities. In addition, principal component analysis and factor analysis methods were used to find polysaccharide structural characteristics of these L. edodes. Furthermore, investigations by amplified fragment length polymorphism analysis (AFLP) and by statistical cluster analyses of GC-MS linkage data were compared to understand the relationships of genotypes and structural features of these species. The structures and biological activities of these polysaccharides were quite complex and remained to be delineated in the future at the molecular level. The novel feature of using statistical methods to treat limited but complex experimental data in this work represents a new approach in the bioinformatics area and allows the simplification of research problems in the glycobiology field.