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Updated: Jul 28, 2025

A Method to Assess Bacteriocin Effects on the Gut Microbiota of Mice
Published on: July 25, 2017
Assessing the protection mechanisms on Enterobacter aerogenes ATCC 13048 by potentially probiotic strain
Aref Zibaei-Rad1, Mostafa Rahmati-Joneidabad1, Behrooz Alizadeh Behbahani2
1Department of Horticultural Science, Faculty of Agriculture, Agricultural Sciences and Natural Resources University of Khuzestan, P.O. Box: 6341773637, Mollasani, Iran.
Abstract:
In this study, Lacticaseibacillus casei XN18 had a remarkable resistant to simulated gastrointestinal conditions, hydrophobicity (38.60%), auto-aggregation (29.80%), co-aggregation (21.10%), adhesion (9.50%), anti-adhesion (24.40-36.90%), antioxidant activity (46.47%), cholesterol assimilation (41.10%), and antimicrobial effect on some pathogenic microorganisms. The modified double layer method, and Enterobacter aerogenes (inhibition zone (IZ) = 9.10 mm) and Listeria monocytogenes (IZ = 14.60 mm) were the most sensitive and resistant pathogens to the probiotic strain. The Lb. casei was sensitive to ciprofloxacin (IZ = 23 mm) and nitrofurantoin (IZ = 25.10 mm), semi-sensitive to imipenem (IZ = 18.80 mm), erythromycin (IZ = 16.90 mm), and chloramphenicol (IZ = 17.90 mm), and resistant to ampicillin (IZ = 9.60 mm) and nalidixic acid (IZ = 9.90 mm). The Lb. casei showed no haemolytic and DNase properties, and it could therefore be used for health-promoting purposes. In the next section, multilayer perceptron (MLP) neural network (NN) and gaussian process regression (GPR) models with k-fold cross validation method were used for predicting the rate of probiotic viability based on three levels of pH and time. The results showed that GPR has the lowest error. The mean absolute percentage error (MAPE), root mean absolute error (RMSE) and coefficient of determination (R2) for GPR and MLP models were 1.49 ± 0.40, 0.21 ± 0.03, 0.98 ± 0.05 and 6.66 ± 0.98, 0.83 ± 0.23 0.82 ± 0.09, respectively. So, the GPR model can be reliably used as a useful method to predict the probiotic viability in similar cases.
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