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Design of experiments for enhanced production of bioactive exopolysaccharides from indigenous probiotic lactic acid bacteria

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Title Design of experiments for enhanced production of bioactive exopolysaccharides from indigenous probiotic lactic acid bacteria
 
Creator Bhat, Bilqeesa
Vaid, Surbhi
Habib, Bisma
Bajaj, Bijender Kumar
 
Subject Enterococcus faecium K1
Lactobacillus paracasei M7
Optimization
Probiotics
Response surface methodology
 
Description 539-551
Exopolysaccharides (EPS) produced by several bacteria including the probiotic lactic acid bacteria (LAB) not only help them to execute certain vital life functions, but offers huge potential for applications in sectors like medical/pharmaceutical, food, agriculture, and environmental health. However, low yield of EPS from probiotic LAB has always been a challenge. Previously we have reported that EPS from two LAB probiotic strains i.e. Enterococcus faecium K1 (isolate from kalarei), and Lactobacillus paracasei M7 (isolate from human breast milk) possessed several bioactive functional attributes like hypocholesterolemic activity, antioxidant potential, antibiofilm activity, antimicrobial activity, emulsification ability, and desirable physiochemical properties. However, the EPS yield was low. Current study reports optimization of process variables by Design of Experiments (DoE) to enhance EPS yield from these bacteria. The most effective process variables for EPS production were earmarked for E. faecium K1 (lactose, ammonium citrate, incubation time and pH), and for L. paracasei M7 (glucose, incubation time and pH), by Plackett–Burman design, and the same were optimized using central composite design (CCD) of response surface methodology (RSM). The EPS yield from E. faecium K1 was enhanced by 101.40% at optimal level of variables (lactose 10.07 g/L, ammonium citrate 2.49 g/L, incubation time 94.05 h and pH 5.4). Similarly, EPS yield was enhanced by 79.6% from L. paracasei M7 using optimal level of variables (glucose 10 g/L, incubation time 48 h and pH 7.6). Thus, DoE represents a powerful approach for optimization of process variables.
 
Date 2020-09-30T05:50:08Z
2020-09-30T05:50:08Z
2020-10
 
Type Article
 
Identifier 0975-0959 (Online); 0301-1208 (Print)
http://nopr.niscair.res.in/handle/123456789/55372
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJBB Vol.57(5) [October 2020]