Literature DB >> 30831513

Mining of camel rumen metagenome to identify novel alkali-thermostable xylanase capable of enhancing the recalcitrant lignocellulosic biomass conversion.

Shohreh Ariaeenejad1, Morteza Maleki1, Elnaz Hosseini2, Kaveh Kavousi2, Ali A Moosavi-Movahedi2, Ghasem Hosseini Salekdeh3.   

Abstract

The aim of this study was to isolate and characterize novel alkali-thermostable xylanase genes from the mixed genome DNA of camel rumen metagenome. In this study, a five-stage computational screening procedure was utilized to find the primary candidate enzyme with superior properties from the camel rumen metagenome. This enzyme was subjected to cloning, purification, and structural and functional characterization. It showed high thermal stability, high activity in a broad range of pH (6-11) and temperature (30-90 °C) and effectivity in recalcitrant lignocellulosic biomass degradation. Our results demonstrated the power of in silico analysis to discover novel alkali-thermostable xylanases, effective for the bioconversion of lignocellulosic biomass.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Alkaline thermostable xylanase; Camel rumen; Metagenome; Recalcitrant compounds

Mesh:

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Year:  2019        PMID: 30831513     DOI: 10.1016/j.biortech.2019.02.059

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  3 in total

1.  Characterization of efficient xylanases from industrial-scale pulp and paper wastewater treatment microbiota.

Authors:  Jia Wang; Jiawei Liang; Yonghong Li; Lingmin Tian; Yongjun Wei
Journal:  AMB Express       Date:  2021-01-19       Impact factor: 3.298

2.  Invitro bioprocessing of corn as poultry feed additive by the influence of carbohydrate hydrolyzing metagenome derived enzyme cocktail.

Authors:  Seyed Hossein Mousavi; Seyedeh Fatemeh Sadeghian Motahar; Maryam Salami; Kaveh Kavousi; Atefeh Sheykh Abdollahzadeh Mamaghani; Shohreh Ariaeenejad; Ghasem Hosseini Salekdeh
Journal:  Sci Rep       Date:  2022-01-10       Impact factor: 4.379

3.  MCIC: Automated Identification of Cellulases From Metagenomic Data and Characterization Based on Temperature and pH Dependence.

Authors:  Mehdi Foroozandeh Shahraki; Shohreh Ariaeenejad; Fereshteh Fallah Atanaki; Behrouz Zolfaghari; Takeshi Koshiba; Kaveh Kavousi; Ghasem Hosseini Salekdeh
Journal:  Front Microbiol       Date:  2020-10-23       Impact factor: 5.640

  3 in total

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