Response surface methodology for the optimization of α-amylase production by Streptomyces sp. ML12 using agricultural byproducts

Abstract

Amylases constitute one of the most important groups of enzymes for commercial use. In the present study, production of α-amylase was optimized using a newly isolated actinobacterial strain from the coral reef environment of the Gulf of Mannar Biosphere Reserve, India. It was identified as Streptomyces sp. ML12 based on chemotaxonomy, cultural and morphological characteristics, carbon source utilization and 16S rRNA gene sequencing. Fermentation variables were selected in accordance with the Plackett-Burman design and were optimized by response surface methodology. Five significant variables (rice bran and wheat bran -both agricultural byproducts, sodium chloride, magnesium sulphate and incubation period) were selected for the optimization via central composite design. The optimal features were rice bran (5.5 g/100 mL), wheat bran (5.3 g/100 mL), sodium chloride (2.8 g/100 mL), magnesium sulphate (1.4 g/100 mL) and 8 days of incubation period. Optimization of the medium with the above tested features increased the amylase yield by 4.4-fold.

Optimization of fermentation conditions through response surface methodology for Indole-3-acetic acid production by Marine Sponge Callyspongia diffusa associated Pseudomonas fluorescens BCPBMS-1

“…Agro-industrial waste contains high amount of carbohydrates, lipids and hence, can be used as a rich carbon source for microbial metabolite production. Rice bran, wheat bran, lignocellulosic wastes used as substrate for microbial enzyme production (Sivakumar et al .,2012;Annamalai et al ., 2013and Fernández Núñez, et al .,2017. Sugar cane molasses, beet molasses, bagasse of sugarcane considered as a cheaper carbon source for bio surfactant production (Nitschke et al, 2004;Rashedi et al, 2005;Benincasa, 2007).…”

Enhanced butanol production by optimization of medium parameters using Clostridium acetobutylicum YM1

“…RSMs with different designs have been successfully used for optimization in numerous bioprocesses, such as butanol production (Lin et al, 2011, Ranjan et al, 2013b), growth of propionic acid bacteria (Liew et al, 2005), lactic acid production (Dey et al, 2012), α-amylase production (Sivakumar et al, 2012), ethanol production (Ratnam et al, 2003, Wang et al, 2008), acid dye decolonization (Olya et al, 2014), fluoride ion removal in drinking water (Fakhri, 2014), wastewater treatment (Gengec et al, 2012) and biohydrogen production (Mu et al, 2006, Pan et al, 2008).…”

Statistical optimization and anticancer activity of a red pigment isolated from Streptomyces sp. PM4

“…Conventional practice, which allows one variable at a time, does not allow evaluation of the combined effects of all the factors involved in the process and it is a time consuming one. These restrictions can be overcome by the use of Response Surface Methodology (RSM) which can identify and quantify the various interactions among different parameters [8] . In fact, Plackett-Burman design was applied in the first step of optimization to determine the likely effects of medium components on pigment production.…”