Application of Response Surface Methodology in Medium Optimization for Protease Production by the New Strain of Serratia marcescens SB08 CHIDAMBARAM KULANDAISAMY VENIL* and PERUMALSAMY LAKSHMANAPERUMALSAMY

For production of protease by a new strain, Serratia marcescens SB08, optimization of the fermentation medium and environmental conditions, were carried out by applying factorial design and response surface methodology. The results of factorial design showed that pH, agitation, incubation time and yeast extract were the key factors affecting protease production. The optimal cultural conditions for protease production obtained with response surface methodology were pH 6.0, agitation 100 rpm, incubation time 51.0 h and yeast extract 3.0 g/l. This model was also validated by repeating the experiments under the optimized conditions, which resulted in the maximum protease production of 281.23 U/ml (Predicted response 275.66 U/ml), thus proving the validity of the model. Unexplored Serratia marcescens SB08 strain isolated from enteric gut of sulphur butterfly (Kricogonia lyside) was taken up for this study. This study demonstrates the ability of the new strain, Serratia marcescens SB08, for protease production and also that smaller and less time consuming statistical experimental designs are adequate for the optimization of fermentation processes for maximum protease production. K e y w o r d s: Serratia marcescens SB08, central composite design (CCD), protease production * Corresponding author: C.K. Venil, 13/262 MGR Nagar, Podanur, Coimbatore – 641 023, Tamil Nadu, India; phone: 098426 99688; e-mail: [email protected] 118 Venil C.K. and Lakshmanaperumalsamy P. 2 (Wenster-Botz, 2000). This method is not only laborious and time consuming but also often leads to an incomplete understanding of the system behaviour, resulting in confusion and lack of predictive ability. Limitations and drawbacks of the single factor optimization can be eliminated by employing response surface methodology (RSM) which is used to explain the combined effects of all the factors in a fermentation process (Elibol, 2004). Response surface methodology not only deals with experimental strategies but also deals with mathematical methods and statistical inference for constructing and exploring an approximate functional relationship between a response variable and a set of design variables. Statistical methods have been applied for optimization of enzyme production (Dey et al., 2001; Francis et al., 2002; Ahuja et al., 2004; Kunamneni et al., 2005). No defined medium has been established for the optimum production of enzymes from different microbial sources. Each organism has its own special conditions for maximum enzyme production. The use of a good reliable statistical model is essential to develop better strategies for the optimization of the fermentation process (Ghaly et al., 2005). In the present work, a new strain Serratia marcescens SB08 (GenBank Accession Number: AB061685) has been subjected to special conditions using response surface methodology for enhancing the production of protease with optimum medium factors and conditions.