Isolation and characterization of Lactobacillus brevis C23 with ability to secrete antimicrobial substance for the inhibition of a foodborne pathogen Listeria monocytogenes ATCC 7644

Aims@#This study aims to isolate lactic acid bacteria (LAB) from various food sources to obtain a potent strain against Listeria monocytogenes. @*Methodology and results@#A total of 68 LAB isolates were selected to evaluate their antimicrobial activity against L. monocytogenes, a foodborne pathogen and a causative agent of listeriosis. The selected isolate was identified and characterized. The isolate C23 from cabbage showed the highest antimicrobial activity against L. monocytogenes ATCC 7644 with inhibition ability of 73.94%. The isolate was closely related to Lactobacillus brevis by 16S rRNA sequencing and subsequently deposited in GenBank with an accession number of MN880215, named as L. brevis C23. The cell free supernatant (CFS) of L. brevis C23 had high tolerance in low pH and was able to withstand up to 60 °C. The proteinaceous nature of the antimicrobial agent was also confirmed through the enzymatic test. The CFS was stable on different detergents as well as bile salts. Under transmission electron microscopy (TEM), the inhibitory effect of CFS against L. monocytogenes was proven by causing cell lysis.@*Conclusion, significance and impact of study@#Bacteriocin-like inhibitory substances (BLIS) of L. brevis C23 showed very promising potential in food industrial application.

Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using Response Surface Methodology and Artificial Neural Network

Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391, a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%). Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05). In addition the use of RSM and ANN alongside each other provided a proper growth prediction model.