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Isolation of Pneumocandin Bo by Optimization of Downstream Process Parameters using Statistical Approach

Authors(4) :-Umesh Luthra, Yogesh Patel, Nishtha Singh, Dharmendra Singh

Pneumocandin Bo is a lipopeptide antifungal agent that inhibits the synthesis of 1,3-β-d-glucan, an essential cell wall homopolysaccharide found in many pathogenic fungi. It is an industrial product produced as a result of fermentation by fungal strain Zelerion arboricola. The primary objective in industrial fermentation processes is to recover the product efficiently, reproducibly and safely to its required specification, while achieving maximum product yield at minimum recovery cost.Isolation of product from the fermentation broth is a challenging task. In the current study statistical approach was employed to optimize various parameters for downstream processing of Pneumocandin B0. Filtration technique was optimized initially using one variable at a time method. Press filter technique was found most suitable filtration technique. Solvent selection for extraction procedure was carried out using one variable at a time (OVAT). Isobutanol showed maximum product recovery. Further variables: agitation time, solvent volume and solvent wash were studied using full factorial design. Experimental design showed that agitation time and solvent wash had maximum impact on Pneumocandin B0 extraction.
Umesh Luthra, Yogesh Patel, Nishtha Singh, Dharmendra Singh
Pneumocandin Bo, downstream processing, filtration technique, solvent extraction, full factorial design
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Publication Details
  Published in : Volume 2 | Issue 3 | May-June 2016
  Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 39-44
Manuscript Number : IJSRST16235
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Umesh Luthra, Yogesh Patel, Nishtha Singh, Dharmendra Singh, "Isolation of Pneumocandin Bo by Optimization of Downstream Process Parameters using Statistical Approach", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 3, pp.39-44, May-June-2016.
Journal URL : http://ijsrst.com/IJSRST16235

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