基因组重排选育麦迪霉素高产菌株
Screening and breeding high MDM-producing strains by genome shuffling
朱岩 1宋欣怡 1黄小池 1韩威1
作者信息
- 1. 沈阳药科大学生命科学与生物制药学院,辽宁沈阳110016
- 折叠
摘要
目的 以生米卡链霉菌(Streptomyces mycarofaciens)突变株为研究对象,选育麦迪霉素高产菌株.探索并验证基因组重排技术在菌种选育中的重要作用.方法 通过2轮多亲株灭活原生质体融合技术实现基因组重排.将来自不同育种方法 的5株麦迪霉素高产菌株B64-5、01- GM-1、H-101、H-106和H-108作为第一轮亲本,在质量浓度为3 g·L-1溶菌酶、32℃水浴60 min条件下制备原生质体,分别采用紫外线照射148 s和52℃加热60min灭活原生质体,然后采用质量分数35％ PEG 4000、37℃保温2min诱导原生质体融合.融合子经过初筛和复筛,获得产量进一步提高的重组子作为亲本进行第二轮的多亲株灭活原生质体融合实验.用生物学方法 测定麦迪霉素效价,用HPLC方法 测定麦迪霉素A1含量.结果 与结论 经过2轮基因组重排实验成功选育出3株高产且遗传稳定的麦迪霉素生产菌株.其中1株菌株GSZ2-32发酵前补加前体X-1后摇瓶产量比原始出发菌株Streptomyces mycarofaciens var.464提高1.1倍,麦迪霉素A1(MDMA1)质量分数含量保持在80％以上.
Abstract
Objective To screen and breed high midecamycin-producing strains. To explore and verify the importance of genome shuffling in strain breeding. Methods Genome shuffling was finished by two rounds of inactivated protoplast fusion technology within multi-parental strains. The protoplasts of five high yield mutant strains B64-5,01-GM-l,H-101,H-106 and H-108 with different inheritance background were prepared with lysozyme concentration of 3 g*L~' at 32 t for 60 min,inactivated by ultraviolet irradiation for 148 s and incubated at 52 t for 60 min respectively, and then inactivated protoplasts fusion were carried out with 35% PEG4000 at 37 t for 2 min. After screening,obtained recombinants with further high yield were used according to the above procedure for the next round of inactivated protoplast fusion. Biological method was used to measure the midecamycin biological potency. The midecamycin Al content was analyzed by HPLC. Results and Conclusions Three hereditarily stable and high-midecamycin producing strains are successfully obtained after two rounds of genome shuffling. Total yield is increased by 1. 1 times by using a strain-GSZ2-32,in which precursor is supplied before fermentation,compared with the initial strain,and MD-MA1 content is kept at 80%.
关键词
麦迪霉素/生米卡链霉菌/基因组重排Key words
midecamycin/Streptomyces mycarofaciens/genome shuffling引用本文复制引用
出版年
2011
NETL
NSTL
维普
万方数据