Ennouri, Karim and Ayed, Rayda Ben and Hassen, Hanen Ben and Mazzarello, Maura and Ottaviani, Ennio (2015) Experimental design and Bayesian networks for enhancement of delta-endotoxin production by Bacillus thuringiensis. Acta Microbiologica et Immunologica Hungarica, 62 (4). pp. 379-392. ISSN 1217-8950
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Abstract
Bacillus thuringiensis (Bt) is a Gram-positive bacterium. The entomopathogenic activity of Bt is related to the existence of the crystal consisting of protoxins, also called delta-endotoxins. In order to optimize and explain the production of delta-endotoxins of Bacillus thuringiensis kurstaki, we studied seven medium components: soybean meal, starch, KH<sub>2</sub>PO<sub>4</sub>, K<sub>2</sub>HPO<sub>4</sub>, FeSO<sub>4</sub>, MnSO<sub>4</sub>, and MgSO<sub>4</sub> and their relationships with the concentration of delta-endotoxins using an experimental design (Plackett—Burman design) and Bayesian networks modelling. The effects of the ingredients of the culture medium on delta-endotoxins production were estimated. The developed model showed that different medium components are important for the Bacillus thuringiensis fermentation. The most important factors influenced the production of delta-endotoxins are FeSO<sub>4</sub>, K<sub>2</sub>HPO<sub>4</sub>, starch and soybean meal. Indeed, it was found that soybean meal, K<sub>2</sub>HPO<sub>4</sub>, KH<sub>2</sub>PO<sub>4</sub> and starch also showed positive effect on the delta-endotoxins production. However, FeSO<sub>4</sub> and MnSO<sub>4</sub> expressed opposite effect. The developed model, based on Bayesian techniques, can automatically learn emerging models in data to serve in the prediction of delta-endotoxins concentrations. The constructed model in the present study implies that experimental design (Plackett—Burman design) joined with Bayesian networks method could be used for identification of effect variables on delta-endotoxins variation.
Item Type: | Article |
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Subjects: | Q Science / természettudomány > QR Microbiology / mikrobiológia |
Depositing User: | Ágnes Sallai |
Date Deposited: | 30 Jun 2016 12:40 |
Last Modified: | 31 Dec 2016 00:15 |
URI: | http://real.mtak.hu/id/eprint/36922 |
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