Reconstruction of a high‐quality metabolic model enables the identification of gene overexpression targets for enhanced antibiotic production in Streptomyces coelicolor A3(2)

Abstract

Streptomycetes are industrially and pharmaceutically important bacteria that produce a variety of secondary metabolites including antibiotics. Streptomycetes have a complex metabolic network responsible for the production of secondary metabolites and the utilization of organic residues present in soil. In this study, we reconstructed a high-quality metabolic model for Streptomyces coelicolor A3(2), designated iMK1208, in order to understand and engineer the metabolism of this model species. In comparison to iIB711, the previous metabolic model for S. coelicolor, the predictive power of iMK1208 was enhanced by the recent insights that enabled the incorporation of an updated biomass equation, stoichiometric matrix, and energetic parameters. iMK1208 was validated by comparing predictions with the experimental data for growth capability in various growth media. Furthermore, we applied a strain-design algorithm, flux scanning based on enforced objective flux (FSEOF), to iMK1208 for actinorhodin overproduction. FSEOF results identified not only previously known gene overexpression targets such as actII-ORF4 and acetyl-CoA carboxylase, but also novel targets such as branched-chain α-keto acid dehydrogenase (BCDH). We constructed and evaluated the BCDH overexpression mutant, which showed a 52-fold increase in actinorhodin production, validating the prediction power of iMK1208. Hence iMK1208 was shown to be a useful and valuable framework for studying the biotechnologically important Streptomyces species using the principles of systems biology and metabolic engineering.

Toward Systems Metabolic Engineering of Streptomycetes for Secondary Metabolites Production

“…Examples of metabolic engineering strategies used for the optimization of secondary metabolite production in streptomycete hosts. [83][84][85] Construction of a mutant strain with improved yields C labeling and MFA to construct metabolic network model 84.8% [70][71][72] EFMA on the ascomycin network model for target predictions Strain engineering by overexpression and inactivation of genes Addition of resin HP20 in the growth medium…”

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites

“…as statistical medium optimization 43 and genome-scale metabolic modeling 44,45 (see next section). Rational approaches are expected to remain dominant due to recent releases of precise gene manipulation tools specically developed for actinomycetes, for instance CRISPR-Cas9.…”

“…Genome-scale metabolic models of S. erythraea and S. spinosa were used to identify the effects of supplementing amino acids in media on production yield, 44,58 while those of A. balhimycina, S. coelicolor and S. tsukubaensis were used to identify gene manipulation targets to enhance target production. 45,60,61 In these metabolic models, only experimentally known secondary metabolite biosynthetic pathways were considered. For example, separate biosynthetic pathways for actinorhodin, undecylprodigiosin, calcium-dependent antibiotic, ectoine, and germicidin were included in the latest version of the S. coelicolor metabolic model, 45 while the S. erythraea metabolic model describes biosynthetic pathways for erythromycin, 2-methylisoborneol, rhamnosylaviolin, and erythrochelin.…”

“…45,60,61 In these metabolic models, only experimentally known secondary metabolite biosynthetic pathways were considered. For example, separate biosynthetic pathways for actinorhodin, undecylprodigiosin, calcium-dependent antibiotic, ectoine, and germicidin were included in the latest version of the S. coelicolor metabolic model, 45 while the S. erythraea metabolic model describes biosynthetic pathways for erythromycin, 2-methylisoborneol, rhamnosylaviolin, and erythrochelin. 44 Now that many BGCs can be effectively detected using so-ware programs (e.g., antiSMASH 53 ), incorporating their corresponding biosynthetic reactions into metabolic models becomes an important task.…”

Genetic Transformation for Quality Improvement in Ornamental Climbers

“…The intermediate enzymatic steps in the secondary metabolite pathway can be knocked out or knocked down by minimising the level of the corresponding mRNA via RNA interference technologies by miRNA , siRNA or antisense technology (Verpoorte and Memelink 2002 ). The enhanced production of important secondary metabolites in the plants may be by the overexpression of responsible genes in the homologous or heterologous plant system as reported by Kim et al ( 2014 ) and Pandey et al ( 2014 ). The most recent technique for the functional analysis of the gene is CRISPR/Cas9, TALEN and ZFN system in which a gene can be knocked out (Gaj et al 2013 ;Shalem et al 2014 ).…”