Document Type
Article
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1. NATURAL SCIENCES, 1.2 COMPUTER AND INFORMATION SCIENCE, 1.4 CHEMICAL SCIENCES, 1.6 BIOLOGICAL SCIENCES
Abstract
β-glucosidases are a class of enzyme that are widely distributed in the living world, with examples noted in plants, fungi, animals and bacteria. They offer both hydrolysis and synthesis capacity for a wide range of biotechnological processes. However, the availability of native, or the production of recombinant β-glucosidases, is currently a bottleneck in the widespread industrial application of this enzyme. In this present work, the production of recombinant β-glucosidase from Streptomyces griseus was optimised using a Design of Experiments strategy, comprising a two-stage, multi-model design. Three screening models were comparatively employed: Fractional Factorial, Plackett-Burman and Definitive Screening Design. Four variables (temperature, incubation time, tryptone, and OD600 nm) were experimentally identified as having statistically significant effects on the production of S.griseus recombinant β-glucosidase in E. coli BL21 (DE3). The four most influential variables were subsequently used to optimise recombinant β-glucosidase production, employing Central Composite Design under Response Surface Methodology. Optimal levels were identified as: OD600 nm, 0.55; temperature, 26 °C; incubation time, 12 h; and tryptone, 15 g/L. This yielded a 2.62-fold increase in recombinant β-glucosidase production, in comparison to the pre-optimised process. Affinity chromatography resulted in homogeneous, purified β-glucosidase that was characterised in terms of pH stability, metal ion compatibility and kinetic rates for p-nitrophenyl-β-D-glucopyranoside (pNPG) and cellobiose catalysis
DOI
https://doi.org/10.3390/bioengineering6030061
Recommended Citation
Uhoraningoga, A., Kinsella, G. K., Frias, J. M., Henehan, G. T., & Ryan, B. J. (2019). The Statistical Optimisation of Recombinant β-glucosidase Production through a Two-Stage, Multi-Model, Design of Experiments Approach. Bioengineering 2019, 6, 61; doi:10.3390/bioengineering6030061
Funder
TU Dublin Fiosraigh
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Publication Details
Uhoraningoga, A., Kinsella, G. K., Frias, J. M., Henehan, G. T., & Ryan, B. J. (2019). The Statistical Optimisation of Recombinant β-glucosidase Production through a Two-Stage, Multi-Model, Design of Experiments Approach. Bioengineering, 6(3), 61.