Experimental design and Bayesian networks for enhancement of delta-endotoxin production by Bacillus thuringiensis

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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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
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

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