Optimization of fermentation process for the production of intracellular polysaccharide from Paecilomyces cicadae and the immuno-stimulating activity of intracellular polysaccharide

Optimization of fermentation process for the production of intracellular polysaccharide (IPS) from the fungus Paecilomyces cicadae and the immuno-stimulating activity of IPS were carried out. The quantitative effects of initial pH, fermentation temperature and time on the yield of IPS content produc...

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Bibliographic Details
Published in:World journal of microbiology & biotechnology 2012-12, Vol.28 (12), p.3293-3299
Main Authors: Cheng, Jun-Wen, Wang, Yan-Bin, He, Liang, Qian, Hua, Fu, Li-Zhong, Li, Hai-Bo
Format: Article
Language:English
Subjects:
Animals
Applied Microbiology
Biochemistry
Biomedical and Life Sciences
Biotechnology
Biotechnology - methods
Cell Line
Cell Proliferation - drug effects
Culture Media - chemistry
Cytokines
Environmental Engineering/Biotechnology
Fermentation
Fungi
Glucose
Hydrogen-Ion Concentration
Immunologic Factors - metabolism
Immunologic Factors - pharmacology
Independent variables
Laboratories
Life Sciences
Macrophage Activation
Macrophages - drug effects
Mice
Microbiology
Optimization
Original Paper
Paecilomyces
Paecilomyces - growth & development
Paecilomyces - metabolism
Polysaccharides - metabolism
Polysaccharides - pharmacology
Regression analysis
Temperature
Variables
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Summary:Optimization of fermentation process for the production of intracellular polysaccharide (IPS) from the fungus Paecilomyces cicadae and the immuno-stimulating activity of IPS were carried out. The quantitative effects of initial pH, fermentation temperature and time on the yield of IPS content produced by P. cicadae in submerged fermentation were investigated separately using response surface methodology (RSM). The three factors chosen for the present investigation were based on the results of a previous Plackett–Burman (PB) design. The experimental data obtained were fitted to a second-order polynomial equation using multiple regression analysis and also analyzed by appropriate statistical methods. RSM analysis showed good correspondence between experimental and predicted values. It was found that three parameters represented significant effect. Probability value ( p  
ISSN:0959-3993
1573-0972
DOI:10.1007/s11274-012-1140-0