Enhancement of feather degrading keratinase of Streptomyces swerraensis KN23, applying mutagenesis and statistical optimization to improve keratinase activity

Author:

Abd El-Aziz Nagwa M.,Khalil Bigad E.,Ibrahim Hayam Fouad

Abstract

AbstractIn this study, 25 actinomyces isolates were obtained from 10 different poultry farms and tested for their keratinase activity. The isolate with the highest keratinase activity was identified through molecular identification by PCR and sequencing of the 16S rRNA gene to be Streptomyces spp. and was named Streptomyces werraensis KN23 with an accession number of OK086273 in the NCBI database. Sequential mutagenesis was then applied to this strain using UV, H2O2, and SA, resulting in several mutants. The best keratinolytic efficiency mutant was designated as SA-27 and exhibited a keratinase activity of 106.92 U/ml. To optimize the keratinase expression of mutant SA-27, the Response Surface Methodology was applied using different parameters such as incubation time, pH, carbon, and nitrogen sources. The optimized culture conditions resulted in a maximum keratinase specific activity of 129.60 U/ml. The genetic diversity of Streptomyces werraensis KN23 wild type compared with five mutants was studied using Inter-simple sequence repeat (ISSR). The highest total and polymorphic unique bands were revealed in the S. werraensis KN23 and SA-18 mutant, with 51 and 41 bands, respectively. The dendrogram based on combined molecular data grouped the Streptomyces werraensis and mutants into two clusters. Cluster I included SA-31 only, while cluster II contained two sub-clusters. Sub-cluster one included SA-27, and sub-cluster two included SA-26. The sub-cluster two divided into two sub-sub clusters. Sub-sub cluster one included SA-18, while sub-sub cluster two included one group (SA-14 and S. werraensis KN23).

Funder

National Research Centre Egypt

Publisher

Springer Science and Business Media LLC

Subject

Microbiology (medical),Microbiology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3