Comparative genomic and transcriptomic analysis guides to further enhance the biosynthesis of erythromycin by an overproducer

Autor: Xiaobo Li, Xiang Ke, Lijia Qiao, Yufei Sui, Ju Chu
Rok vydání: 2022
Předmět:
Zdroj: Biotechnology and Bioengineering. 119:1624-1640
ISSN: 1097-0290
0006-3592
Popis: Omics approaches have been applied to understand the boosted productivity of natural products by industrial high-producing microorganisms. Here, with the updated genome sequence and transcriptomic profiles derived from high-throughput sequencing, we exploited comparative omics analysis to further enhance the biosynthesis of erythromycin in an industrial overproducer, Saccharopolyspora erythraea HL3168 E3. By comparing the genome of E3 with the wild type NRRL23338, we identified fragment deletions inside 56 coding sequences and 255 single nucleotide polymorphisms over the genome of E3. Substantial numbers of genomic variations were observed in genes responsible for pathways which were interconnected to the biosynthesis of erythromycin by supplying precursors/cofactors or by signal transduction. Through comparative transcriptomic analysis, L-glutamine/L-glutamate and 2-oxoglutarate were identified as reporter metabolites. Around the node of 2-oxoglutarate, genomic mutations were also observed. Furthermore, the transcriptomic data suggested that genes involved in the biosynthesis of erythromycin were significantly up-regulated constantly, whereas some genes in biosynthesis clusters of other secondary metabolites contained nonsense mutations and were expressed at extremely low levels. Based on the omics association analysis, readily available strategies were proposed to engineer E3 by simultaneously overexpressing sucB (coding for 2-oxoglutarate dehydrogenase E2 component) and sucA (coding for 2-oxoglutarate dehydrogenase E1 component), which increased the erythromycin titer by 71% compared to E3 in batch culture. This work provides more promising molecular targets to engineer for enhanced production of erythromycin by the overproducer.
Databáze: OpenAIRE
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