Contents lists available at ScienceDirect Biocatalysis and Agricultural Biotechnology journal homepage: www.elsevier.com/locate/bab Process optimization for production of a fibrinolytic enzyme from newly isolated marine bacterium Pseudomonas aeruginosa KU1 Swaroop S. Kumar, Madhathilkovilakathu Haridas, Abdulhameed Sabu ⁎ Inter University Centre for Bioscience and Department of Biotechnology & Microbiology, Kannur University, Thalassery Campus, Kannur, Kerala 670661, India ARTICLE INFO Keywords: Fibrinolytic enzyme Pseudomonas aeruginosa KU1 Response surface methodology Box-Behnken design ABSTRACT A potent fibrinolytic enzyme producing bacteria, Pseudomonas aeruginosa KU1 was isolated from marine sedi- ments of Ezhara beach, Kannur, Kerala. Enzyme production was optimized using statistical approach. Placket- Burman factorial design was used in picking key factors (Tryptone, skimmed milk and inoculum size) that influence fibrinolytic enzyme production of the isolate and further optimized using Box-Benhken design. Optimal concentrations for the selected independent variables in the medium were identified to be 0.72% w/v tryptone, 0.09% w/v skimmed milk and 3.95% v/v inoculum size. Peak production was achieved empirically in shake flask culture and it was very close to the projected activity by the response surface model. The Peak production showed 3.25 fold increase over the activity prior to any optimization and a maximum of 1.32 fold increase of one factor at a time optimization. Though many reports are available on fibrinolytic enzyme pro- duction from Pseudomonas sp. media optimization studies for enhancement of fibrinolytic enzyme production has not been performed so far. This may be the first report on statistical optimization of production of a fi- brinolytic enzyme from marine Pseudomonas sp. 1. Introduction Thrombosis is one of the major cardiovascular diseases caused by accumulation of fibrin clot inside the blood vessels and its treatment involves removal of clot. A few of the therapeutic strategies for cardi- ovascular diseases include usage of anticoagulants or antiplatelets. But, they may not directly act on existing clot. Other approaches are, sur- gical treatment or fibrinolytic enzyme therapy by which thrombus could be removed. Hence, thrombolytic enzymes are also known as clot buster enzymes. Some of these enzymes comprise tissue-type plasmi- nogen activator (t-PA) (Collen and Lijnen, 2004), urokinase (Duffy, 2002), nattokinase (Sumi et al., 1987), lumbrokinase (Mihara et al., 1991) etc. Some of such enzymes are FDA approved for treatment of cardiovascular diseases. However, they may cause side effects such as haemorrhage, nausea etc. (Kumar and Sabu, 2017). Though fibrinolytic enzymes are reported from various sources, including microbial pro- teolytic enzymes (Sumi et al., 1995; Agrebi et al., 2009; Deepak et al., 2010) and in the pipeline towards its clinical application, exploration of natural resources for potential microbes with fibrinolytic potential is an impulse to bio-pharmaceutical sector. Cost of enzyme production is one of the challenging factors re- garding industrial sector. Despite availability of many fibrinolytic proteases, the expense of these enzymes with respect to production is the limitation for its widespread use. Optimization of bioprocess para- meters is highly significant in reducing the overall production cost of the enzyme. Traditional one-factor-at-a-time method of optimization is laborious, time consuming. Moreover, interactions among the variables cannot be accounted while applying this method. Alternate approach for the process optimization is statistical methods which can study multiple factors simultaneously for optimization of process. When the response or output is influenced by multiple variables, the optimization can be achieved through a collection of statistical techniques referred to as response surface methodology (RSM). Appropriately planned set of experiments with statistical optimization not only reduces the time and cost but also finds optimum values of the factors under consideration (He et al., 2004; Montogomery and Myers, 2002). Process optimization for fibrinolytic enzyme production using sta- tistical methods was performed in case of a few bacterial species and most of them belong to Bacillus sp. (Wang et al., 2006; Deepak et al., 2008; Mahajan et al., 2012; Vijayaraghavan and Vincent, 2014c; Liu et al., 2005; Mukherjee and Rai, 2011). Statistical techniques applied for optimizing fibrinolytic enzyme production from bacteria, other than Bacillus sp. are Psuedoalteromonas IND11 (Vijayaraghavan and Vincent, 2014b), Proteus penneri (Jhample et al., 2015), Streptomyces sp. (Silva et al., 2015), Paenibacillus sp. (Vijayaraghavan and Vincent, 2014a), Shewanella sp. (Vijayaraghavan and Vincent, 2015), Serratia sp. (Taneja https://doi.org/10.1016/j.bcab.2018.02.001 Received 8 December 2017; Received in revised form 2 February 2018; Accepted 2 February 2018 ⁎ Correspondence to: Department of Biotechnology and Microbiology, School of Life Sciences, Kannur University, Thalassery Campus, Kannur 670661, Kerala, India. E-mail address: drsabu@gmail.com (A. Sabu). Biocatalysis and Agricultural Biotechnology 14 (2018) 33–39 Available online 05 February 2018 1878-8181/ © 2018 Elsevier Ltd. All rights reserved. T