NDLI: Enhancement of fengycin production in Bacillus amyloliquefaciens by genome shuffling and relative gene expression analysis using RT-PCR.

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Enhancement of fengycin production in Bacillus amyloliquefaciens by genome shuffling and relative gene expression analysis using RT-PCR.

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Enhancement of fengycin production in Bacillus amyloliquefaciens by genome shuffling and relative gene expression analysis using RT-PCR.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Zhao, Junfeng Zhang, Chong Lu, Jing Lu, Zhaoxin
Description	Author Affiliation: Zhao J ( a College of Food Science and Engineering, Henan University of Science and Technology, Tianjing Road, Luoyang 471003, People's Republic of China.); Zhang C ( b College of Food Science and Technology, Nanjing Agricultural University, Jiangsu, Nanjing 210095, People's Republic of China.); Lu J ( b College of Food Science and Technology, Nanjing Agricultural University, Jiangsu, Nanjing 210095, People's Republic of China.); Lu Z ( b College of Food Science and Technology, Nanjing Agricultural University, Jiangsu, Nanjing 210095, People's Republic of China.)
Abstract	Genome shuffling is an efficient approach for the rapid engineering of microbial strains with desirable industrial phenotypes. In this study, we used genome shuffling in an attempt to improve fengycin production of the wild-type strain Bacillus amyloliquefaciens ES-2-4. After 2 rounds of genome shuffling, a high-yield recombinant F2-72 (FMB72) strain that exhibited 8.30-fold increases in fengycin production was obtained. Comparative analysis of synthetase gene (fenA) expression was conducted between the initial and shuffled strains using fluorescent quantitation RT-PCR. Delta CT (threshold cycle) relative quantitation analysis revealed that fengycin synthetase gene (fenA) expression at the transcriptional level in the FMB72 strain was 12.77-fold greater than in the ES-2-4 wild type. The shuffled strain has a potential application in food and pharmaceutical industries. At the same time, the analysis of improved phenotypes will provide more valuable data for inverse metabolic engineering.
File Format	HTM / HTML
ISSN	00084166
e-ISSN	14803275
Journal	Canadian Journal of Microbiology
Issue Number	5
Volume Number	62
Language	English
Publisher	Canadian Science Publishing
Publisher Date	2016-05-01
Publisher Place	Canada
Access Restriction	Open
Subject Keyword	Discipline Microbiology
Content Type	Text
Resource Type	Article
Subject	Genetics Medicine Molecular Biology Immunology Microbiology Applied Microbiology and Biotechnology

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