4.5 Article

Genome shuffling of Bacillus amyloliquefaciens for improving antimicrobial lipopeptide production and an analysis of relative gene expression using FQ RT-PCR

Journal

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10295-012-1098-9

Keywords

Genome shuffling; Bacillus amyloliquefaciens; Antimicrobial lipopeptide; CT (threshold cycle); Housekeeping gene; The gene of interest

Funding

  1. National Natural Science Foundation of China [30871753]
  2. National Research Program of China [2011BAD23B05]
  3. Priority Academic Program Development of Jiangsu Higher Education Institutions

Ask authors/readers for more resources

Genome shuffling is an efficient approach for the rapid improvement of the yield of secondary metabolites. This study was undertaken to enhance the yield of surfactin produced by Bacillus amyloliquefaciens ES-2-4 using genome shuffling and to examine changes in SrfA expression of the improved phenotype at the transcriptional level. Six strains with subtle improvements in lipopeptide yield were obtained from populations generated by ultraviolet irradiation, nitrosoguanidine, and ion beam mutagenesis. These strains were then subjected to recursive protoplast fusion. A strain library that was likely to yield positive colonies was created by fusing the lethal protoplasts obtained from both ultraviolet irradiation and heat treatments. After two rounds of genome shuffling, a high-yield recombinant F2-38 strain that exhibited 3.5- and 10.3-fold increases in surfactin production in shake flask and fermenter respectively, was obtained. Comparative analysis of synthetase gene expression was conducted between the initial and shuffled strains using FQ (fluorescent quantitation) RT-PCR. Delta CT (threshold cycle) relative quantitation analysis revealed that surfactin synthetase gene (srfA) expression at the transcriptional level in the F2-38 strain was 15.7-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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available