Predicting Strain Engineering Strategies Using iKS1317: A Genome‐Scale Metabolic Model ofStreptomyces coelicolor

Abstract

Streptomyces coelicolor is a model organism for the Actinobacteria, a phylum known to produce an extensive range of different bioactive compounds that include antibiotics currently used in the clinic. Biosynthetic gene clusters discovered in genomes of other Actinobacteria can be transferred to and expressed in S. coelicolor, making it a factory for heterologous production of secondary metabolites. Genome‐scale metabolic reconstructions have successfully been used in several biotechnology applications to facilitate the over‐production of target metabolites. Here, the authors present iKS1317, the most comprehensive and accurate reconstructed genome‐scale metabolic model (GEM) for S. coelicolor. The model reconstruction is based on previous models, publicly available databases, and published literature and includes 1317 genes, 2119 reactions, and 1581 metabolites. It correctly predicts wild‐type growth in 96.5% of the evaluated growth environments and gene knockout predictions in 78.4% when comparing with observed mutant growth phenotypes, with a total accuracy of 83.3%. However, using a minimal nutrient environment for the gene knockout predictions, iKS1317 has an accuracy of 87.1% in predicting mutant growth phenotypes. Furthermore, we used iKS1317 and existing strain design algorithms to suggest robust gene‐knockout strategies to increase the production of acetyl‐CoA. Since acetyl‐CoA is the most important precursor for polyketide antibiotics, the suggested strategies may be implemented in vivo to improve the function of S. coelicolor as a heterologous expression host.

Enzyme-constrained models and omics analysis of Streptomyces coelicolor reveal metabolic changes that enhance heterologous production

“…Sco-GEM has been reconstructed by curating the recently published iKS1317 model (Kumelj et al, 2018) to include genes, reactions and metabolites from the equally recently published models iAA1259 (Amara et al, 2018) and Sco4 (Wang et al, 2018). While the curations from iAA1259 were primarily related to coelimycin P1, butyrolactone, xylan and cellulose pathways, the 377 reactions added to Sco-GEM from Sco4 were scattered across a large range of different subsystems, covering both primary and secondary metabolism (Figure S1).…”

“…A relatively lenient threshold of −30 kJ/mol was defined to classify a reaction as irreversible; with the intent not to over-constrain the model (Figure 1E). The proposed changes in reversibility were evaluated against growth and knockout data (Kumelj et al, 2018), discarding 59 of 770 the proposed reactions. Consequentially, the flux bounds of 273 reactions were modified, while all ATP-driven reactions were manually curated and generally assumed irreversible, unless they had an estimated positive change in Gibbs free energy or were known to be reversible.…”

“…Further aided by the publication of its genome sequence (Bentley et al, 2002), the antibiotic coelimycin P1 (yellow), produced from the formerly cryptic polyketide gene cluster known as cpk, was added to this list (Gomez-Escribano et al, 2012), illustrating that even after the antibiotic golden age there still has been much to be discovered in this prolific genus. Today, the widespread use of S. coelicolor continues as a host for heterologous production of biosynthetic gene clusters (BGCs; Castro et al, 2015;Bibb, 2011, 2014;Kumelj et al, 2018;Thanapipatsiri et al, 2015;Yin et al, 2015). Heterologous expression is a powerful strategy for novel compound discovery from BGCs that are either natively silent or originate from an unculturable source (Nepal and Wang, 2019).…”

“…transcriptomics and proteomics (Robinson and Nielsen, 2016). The increased interest in using genome-scale models of S. coelicolor is conspicious: since the first reconstruction in 2005 (Borodina et al, 2005), five GEMs have been published Amara et al, 2018;Kim et al, 2014;Kumelj et al, 2018;Wang et al, 2018), and three of those within 2018: iKS1317 (Kumelj et al, 2018), Sco4 (Wang et al, 2018) and iAA1259 (Amara et al, 2018). Additionally, as a model organism for the Actinomycetes, the GEMs of S. coelicolor are frequently used as template for model development of closely related strains (Mohite et al, 2019), such as S. clavuligerus (Toro et al, 2018), Saccharopolyspora erythraea (Licona-Cassani et al, 2012) and S. lividans (Valverde et al, 2018).…”

“…To increase the rate and quality of model reconstruction, in this study two research groups of the Sco-GEM community, responsible for two of the latest model updates (Kumelj et al, 2018;Wang et al, 2018), have joined forces to merge existing GEMs of S. coelicolor into one consensus-model that is publicly hosted on GitHub and can be continuously updated and improved by all members of the community. Hosting the model on GitHub has many advantages: 1) Open access and contribution; 2) Version control; 3) Continuous quality control with memote (Lieven et al, 2018); 4) Continuous development and improvement; 5) New improvements released instantly (no publication lag time); 6) Complete documentation of model reconstruction.…”