Biosynthesis, molecular modeling and statistical optimization of xylanase from a mangrove associated actinobacterium Streptomyces variabilis (MAB3) using Box-Behnken design with its bioconversion efficacy Muthusamy Sanjivkumar a , Tamilselvan Silambarasan b , Ramasamy Balagurunathan b , Grasian Immanuel a, ⁎ a MNP laboratory, Centre for Marine Science and Technology, Manonmaniam Sundaranar University, Rajakamangalam 629502, India b Department of Microbiology, Periyar University, Salem, 636011, India abstract article info Article history: Received 16 April 2018 Received in revised form 31 May 2018 Accepted 12 June 2018 Available online 14 June 2018 The present study was undertaken to evaluate the biosynthesis, molecular modeling and statistical optimization of xylanase production through Box-Behnken design by a mangrove associated actinobacterium Streptomyces variabilis (MAB3). Initially, the production of xylanase by the selected strain was carried through submerged fer- mentation using birchwood xylan as substrate. Further the xylanase production was statistically optimized through Box-Behnken design. It showed 5.30 fold increase of xylanase production by the isolate compared to ‘one factor at a time approach’ in the presence of the basal medium containing birchwood xylan (2.0% w/v) at pH 8.2, temperature 46.5 °C, inoculum size of 2% for 68 h. The analysis of variance (ANOVA) revealed high coef- ficient of determination (R 2 = 0.9490) for the respective responses at significant level (P b 0.0001). The xylanase was purified by different purification steps and it resulted 5.30 fold increase with the yield of 21.27% at the final step using sephadex G-75 chromatography. The molecular weight of the purified xylanase was observed as 50 kDa on 10% SDS-PAGE. The homology 3D structure of the purified xylanase protein was predicted and this protein encodes with 420 amino acid residues. The maximum activity of purified xylanase was observed at pH 8, temper- ature 40 °C and the production medium supplemented with 1 mM Ca 2+ metal ion, 2.0% xylan and 1.5% NaCl. The kinetic parameters of the purified xylanase expressed the K m and V max values of 5.23 mg/ml and 152.07 μg/min/ mg, respectively. Finally, the xylanolytic hydrolysis of pretreated agro-residues, especially the rice straw substituted medium yielded maximum (46.28 mg/g) level of reducing sugar and saccharification (63.18%), followed by bioethanol production (3.92g/l) at 72 h of incubation. Based on the results, it could be confirmed that the selected isolate is a potent strain for xylanase production and also it can able to convert the pretreated agro-residues into economically important byproduct like bioethanol. © 2018 Published by Elsevier B.V. Keywords: Streptomyces sp. Xylanase RSM Agro-residues Bioethanol 1. Introduction Xylanase is the major group of hemicellulolytic enzyme, which acts by depolymerizing the xylan molecules in to monomers [1]. In recent years, interest in xylanase has increased markedly due to their usage in the paper and pulp industry [2]. Other potential applications include the clarification of fruit juices and wine, extraction of plant oil, coffee and starch, production of oligosaccharides and improvement of the nu- tritional value of animal feed [3]. The commercial application of xylanase in various industrial processes had limited success due to var- ious factors. These include inaccessibility of substrate to xylanase en- zymes, because of physical limitations, the limited hydrolysis of xylans due to their branched nature, thermal instability, narrow pH range, end product inhibition and cost of enzyme production. The last two problems can be overcome to some extent by the use of cheap sub- strates and by employing the process of submerged fermentation (SmF) [4]. There are two ways by which the problem of fermentation parame- ters may be addressed: classical and statistical. The classical method is based on “one-factor-at-a-time” method in which one independent var- iable is studied while maintaining all the other factors at a fixed level [5]. This method may lead to unreliable results, inaccurate conclusions and requires a considerable amount of work and time. Moreover, it does not guarantee the determination of optimal conditions and is unable to de- tect the frequent interactions occurring between two or more factors. An alternate strategy is a statistical approach, e.g. factorial experimental design and response surface methodology (RSM) [6]. Statistical methods have also been designed for bioprocess optimization [7]. Com- binatorial interactions of process variables with the production of the desired compound are numerous and the optimum processes may be developed using an effective experimental design procedure [8]. International Journal of Biological Macromolecules 118 (2018) 195–208 ⁎ Corresponding author. E-mail address: gimmas@gmail.com (G. Immanuel). https://doi.org/10.1016/j.ijbiomac.2018.06.063 0141-8130/© 2018 Published by Elsevier B.V. Contents lists available at ScienceDirect International Journal of Biological Macromolecules journal homepage: http://www.elsevier.com/locate/ijbiomac