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http://dx.doi.org/10.5352/JLS.2016.26.5.571

Screening of Non-Biogenic-Amine-Producing Bacillus subtilis and Medium Optimization for Improving Biomass by the Response Surface Methodology  

Yang, Hee-Jong (Microbial Institute for Fermentation Industry (MIFI))
Jeong, Su-Ji (Microbial Institute for Fermentation Industry (MIFI))
Jeong, Seong-Yeop (Microbial Institute for Fermentation Industry (MIFI))
Heo, Ju-Hee (Microbial Institute for Fermentation Industry (MIFI))
Choi, Nack-Shick (Department of Biochemistry and Health Science, Changwon National University)
Jeong, Do-Youn (Microbial Institute for Fermentation Industry (MIFI))
Publication Information
Journal of Life Science / v.26, no.5, 2016 , pp. 571-583 More about this Journal
Abstract
Biogenic amines are produced primarily by microorganisms found in fermented foods and are often implicated in poisoning incidents in humans. In this study, 620 strains of microorganisms were isolated from traditional Korean fermented food in Sunchang in order to screen for non-biogenicamine-producing microorganisms present in these foods. One strain was identified and named Bacillus subtilis SCJ1, by using 16S rRNA sequencing and biochemical characterization. We investigated the cell growth of this organism in order to understand its potential for industrial application. To this end, we optimized the culture medium constituents by using the response surface methodology. The Plackett-Burman experimental design was used for screening of the medium constituents, such as molasses, yeast extract and peptone, for improving cell growth. In order to determine the optimal concentration of each constituent, we used a central composite design. Consequently, the optimized concentrations of molasses, yeast extract and peptone were predicted to be 27.5 g/l, 7.5 g/l and 17.5 g/l, respectively. By model verification, we confirmed that a 1.49-fold increase in dry cell weight compared to the basal medium-from 1.32 g/l, to 1.9722 g/l-was achieved.
Keywords
Bacillus subtilis; biogenic amine; biomass; optimization; response surface methodology;
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