Journal
MICROORGANISMS
Volume 9, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/microorganisms9030579
Keywords
response surface methodology; artificial neural network; optimization; bacteriocin-like inhibitory substances; Lactococcus lactis Gh1
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Funding
- Ministry of Higher Education (MOHE), Malaysia under Prototype Research Grant Scheme [PRGS/2/2015/SG05/UPM/01/2]
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In this study, the optimal medium formulation for BLIS production by Lactococcus lactis Gh1 was successfully identified using artificial neural network models, resulting in a significant increase in BLIS production.
Bacteriocin-like inhibitory substances (BLIS) produced by Lactococcus lactis Gh1 had shown antimicrobial activity against Listeria monocytogenes ATCC 15313. Brain Heart Infusion (BHI) broth is used for the cultivation and enumeration of lactic acid bacteria, but there is a need to improve the current medium composition for enhancement of BLIS production, and one of the approaches is to model the optimization process and identify the most appropriate medium formulation. Response surface methodology (RSM) and artificial neural network (ANN) models were employed in this study. In medium optimization, ANN (R-2 = 0.98) methodology provided better estimation point and data fitting as compared to RSM (R-2 = 0.79). In ANN, the optimal medium consisted of 35.38 g/L soytone, 16 g/L fructose, 3.25 g/L sodium chloride (NaCl) and 5.40 g/L disodium phosphate (Na2HPO4). BLIS production in optimal medium (717.13 +/- 0.76 AU/mL) was about 1.40-fold higher than that obtained in nonoptimised (520.56 +/- 3.37 AU/mL) medium. BLIS production was further improved by about 1.18 times higher in 2 L stirred tank bioreactor (787.40 +/- 1.30 AU/mL) as compared to that obtained in 250 mL shake flask (665.28 +/- 14.22 AU/mL) using the optimised medium.
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