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Structural and functional comparison of Saccharomonospora azurea strains in terms of primycin producing ability
World Journal of Microbiology and Biotechnology ( IF 4.0 ) Pub Date : 2020-09-29 , DOI: 10.1007/s11274-020-02935-x
Márk Kovács , Dénes Seffer , Ágota Pénzes-Hűvös , Ákos Juhász , Ildikó Kerepesi , Kitti Csepregi , Andrea Kovács-Valasek , Csaba Fekete

Emerging and re-emerging microbial pathogens, together with their rapid evolution and adaptation against antibiotics, highlight the importance not only of screening for new antimicrobial agents, but also for deepening knowledge about existing antibiotics. Primycin is a large 36-membered non-polyene macrolide lactone exclusively produced by Saccharomonospora azurea. This study provides information about strain dependent primycin production ability in conjunction with the structural, functional and comparative genomic examinations. Comparison of high- and low-primycin producer strains, transcriptomic analysis identified a total of 686 differentially expressed genes (DEGs), classified into diverse Cluster of Orthologous Groups. Among them, genes related to fatty acid synthesis, self-resistance, regulation of secondary metabolism and agmatinase encoding gene responsible for catalyze conversion between guanidino/amino forms of primycin were discussed. Based on in silico data mining methods, we were able to identify DEGs whose altered expression provide a good starting point for the optimization of fermentation processes, in order to perform targeted strain improvement and rational drug design. Electronic supplementary material The online version of this article (10.1007/s11274-020-02935-x) contains supplementary material, which is available to authorized users.

中文翻译:

天蓝色糖单胞菌菌株在伯霉素生产能力方面的结构和功能比较

新出现和重新出现的微生物病原体,连同它们对抗生素的快速进化和适应,突出了不仅筛选新的抗菌剂而且加深对现有抗生素知识的重要性。Primycin 是一种大型 36 元非多烯大环内酯内酯,由 Saccharomonospora azurea 独家生产。本研究结合结构、功能和比较基因组检查,提供了关于菌株依赖性伯霉素生产能力的信息。比较高和低伯霉素生产菌株,转录组学分析共鉴定了 686 个差异表达基因 (DEG),分为不同的直系同源群。其中,与脂肪酸合成、自抗、讨论了二级代谢的调节和负责催化胍基/氨基形式的伯霉素之间转化的胍丁胺酶编码基因。基于计算机数据挖掘方法,我们能够识别出表达改变的DEG,为优化发酵过程提供了良好的起点,以进行靶向菌株改进和合理的药物设计。电子补充材料本文的在线版本(10.1007/s11274-020-02935-x)包含补充材料,可供授权用户使用。以进行靶向菌株改良和合理的药物设计。电子补充材料本文的在线版本(10.1007/s11274-020-02935-x)包含补充材料,可供授权用户使用。以进行靶向菌株改良和合理的药物设计。电子补充材料本文的在线版本(10.1007/s11274-020-02935-x)包含补充材料,可供授权用户使用。
更新日期:2020-09-29
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