Journal
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
Volume 177, Issue -, Pages 211-220Publisher
ELSEVIER
DOI: 10.1016/j.ijbiomac.2021.02.014
Keywords
Bifunctional; Metagenomics big data; In-silico screening; Cellulase; xylanase; Lignocellulosic biomass
Funding
- Agricultural Biotechnology Research Institute of Iran (ABRII)
- Institute of Biochemistry and Biophysics (IBB)
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This study identified a novel stable bifunctional cellulase/xylanase, PersiCelXyn1, from rumen microbiota using a computational approach and demonstrated its stability and degradation capability under harsh conditions.
Due to the importance of using lignocellulosic biomass, it is always important to find an effective novel enzyme or enzyme cocktail or fusion enzymes. Identification of bifunctional enzymes through a metagenomic approach is an efficient method for converting agricultural residues anda beneficial way to reduce the cost of enzyme cocktail and fusion enzyme production. In this study, a novel stable bifunctional cellulase/xylanase, PersiCelXyn1 was identified from the rumen microbiota by the multi-stage in-silico screening pipeline and computationally assisted methodology. The enzyme exhibited the optimal activity at pH 5 and 50 degrees C. Analyzing the enzyme activity at extreme temperature, pH, long-term storage, and presence of inhibitors and metal ions, confirmed the stability of the bifunctional enzyme under harsh conditions. Hydrolysis of the rice straw by PersiCelXyn1 showed its ca-pability to degrade both cellulose and hemicellulose polymers. Also, the enzyme improved the degradation of various biomass substrates after 168 h of hydrolysis. Our results demonstrated the power of the multi-stage in-silico screening to identify bifunctional enzymes from metagenomic big data for effective bioconversion of lig-nocellulosic biomass. (c) 2018 Published by Elsevier B.V.
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