Computational analysis of phenotypic space in heterologous polyketide biosynthesis—Applications to Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae

Combining metabolomics and network analysis to improve tacrolimus production in Streptomyces tsukubaensis using different exogenous feedings

Tacrolimus is widely used as an immunosuppressant in the treatment of various autoimmune diseases. However, the low fermentation yield of tacrolimus has thus far restricted its industrial applications. To solve this problem, the time-series response mechanisms of the intracellular metabolism that were highly correlated with tacrolimus biosynthesis were investigated using different exogenous feeding strategies in S. tsukubaensis. The metabolomic datasets, which contained 93 metabolites, were subjected to weighted correlation network analysis (WGCNA), and eight distinct metabolic modules and seven hub metabolites were identified to be specifically associated with tacrolimus biosynthesis. The analysis of metabolites within each metabolic module suggested that the pentose phosphate pathway (PPP), shikimate and aspartate pathway might be the main limiting factors in the rapid synthesis phase of tacrolimus accumulation. Subsequently, all possible key-limiting steps in the above metabolic pathways were further screened using a genome-scale metabolic network model (GSMM) of S. tsukubaensis. Based on the prediction results, two newly identified targets (aroC and dapA) were overexpressed experimentally, and both of the engineered strains showed higher tacrolimus production. Moreover, the best strain, HT-aroC/dapA, that was engineered to simultaneously enhanced chorismate and lysine biosynthesis was able to produce 128.19 mg/L tacrolimus, 1.64-fold higher than control (78.26 mg/L). These findings represent a valuable addition to our understanding of tacrolimus accumulation in S. tsukubaensis, and pave the way to further production improvements.

Construction of polyketide overproducing Escherichia coli strains via synthetic antisense RNAs based on in silico fluxome analysis and comparative transcriptome analysis

Rapid assessment and optimization of the incompatible metabolic modules remain a challenge. Here, we developed a systematic approach to characterize the module interactions and improve the problematic modules during the 6-deoxyerythronolide B (6dEB) biosynthesis in E. coli. Tremendous differences in the overall trends of flux changes of various metabolic modules were firstly uncovered based on in silico fluxome analysis and comparative transcriptome analysis. Potential targets for improving 6dEB biosynthesis were identified through analyzing these discrepancies. All 25 predicted targets at modules of PP pathway and nucleotide metabolism were firstly tested for improving the 6dEB production in E. coli via synthetic antisense RNAs. Down-regulation of 18 targets genes leads to more than 20% increase in 6dEB yield. Combinatorial repression of targets with greater than 60% increase in 6dEB titer, e.g., anti-guaB/anti-zwf led to a 296.2% increase in 6dEB production (210.4 mg/L in flask) compared to the control (53.1 mg/L). This is the highest yield yet reported for polyketide heterologous biosynthesis in E. coli. This study demonstrates a strategy to enhance the yield of heterologous products in the chassis cell and indicates the effectiveness of antisense RNA for use in metabolic engineering.

Reconstruction of a charge balanced genome-scale metabolic model to study the energy-uncoupled growth of Zymomonas mobilis ZM1

Zymomonas mobilisis an ethanologenic bacterium and is known to be an example microorganism with energy-uncoupled growth. The reconstructed metabolic model indicate that resistance to intracellular pH reduction could be the main reason for uncoupled growth.

Model-driven intracellular redox status modulation for increasing isobutanol production in Escherichia coli

BACKGROUND

Few strains have been found to produce isobutanol naturally. For building a high performance isobutanol-producing strain, rebalancing redox status of the cell was very crucial through systematic investigation of redox cofactors metabolism. Then, the metabolic model provided a powerful tool for the rational modulation of the redox status.

RESULTS

Firstly, a starting isobutanol-producing E. coli strain LA02 was engineered with only 2.7 g/L isobutanol produced. Then, the genome-scale metabolic modeling was specially carried out for the redox cofactor metabolism of the strain LA02 by combining flux balance analysis and minimization of metabolic adjustment, and the GAPD reaction catalyzed by the glyceraldehyde-3-phosphate dehydrogenase was predicted as the key target for redox status improvement. Under guidance of the metabolic model prediction, a gapN-encoding NADP(+) dependent glyceraldehyde-3-phosphate dehydrogenase pathway was constructed and then fine-tuned using five constitutive promoters. The best strain LA09 was obtained with the strongest promoter BBa_J23100. The NADPH/NADP + ratios of strain LA09 reached 0.67 at exponential phase and 0.64 at stationary phase. The redox modulations resulted in the decrease production of ethanol and lactate by 17.5 and 51.7% to 1.32 and 6.08 g/L, respectively. Therefore, the isobutanol titer was increased by 221% to 8.68 g/L.

CONCLUSIONS

This research has achieved rational redox status improvement of isobutanol-producing strain under guidance of the prediction and modeling of the genome-scale metabolic model of isobutanol-producing E. coli strain with the aid of synthetic promoters. Therefore, the production of isobutanol was dramatically increased by 2.21-fold from 2.7 to 8.68 g/L. Moreover, the developed model-driven method special for redox cofactor metabolism was of very helpful to the redox status modulation of other bio-products.

Computational identification of gene over-expression targets for metabolic engineering of taxadiene production

Taxadiene is the first dedicated intermediate in the biosynthetic pathway of the anticancer compound Taxol. Recent studies have taken advantage of heterologous hosts to produce taxadiene and other isoprenoid compounds, and such ventures now offer research opportunities that take advantage of the engineering tools associated with the surrogate host. In this study, metabolic engineering was applied in the context of over-expression targets predicted to improve taxadiene production. Identified targets included genes both within and outside of the isoprenoid precursor pathway. These targets were then tested for experimental over-expression in a heterologous Escherichia coli host designed to support isoprenoid biosynthesis. Results confirmed the computationally predicted improvements and indicated a synergy between targets within the expected isoprenoid precursor pathway and those outside this pathway. The presented algorithm is broadly applicable to other host systems and/or product choices.

Synthetic biology triggers new era of antibiotics development

As a discipline to design and construct organisms with desired properties, synthetic biology has generated rapid progresses in the last decade. Combined synthetic biology with the traditional process, a new universal workflow for drug development has been becoming more and more attractive. The new methodology exhibits more efficient and inexpensive comparing to traditional methods in every aspect, such as new compounds discovery & screening, process design & drug manufacturing. This article reviews the application of synthetic biology in antibiotics development, including new drug discovery and screening, combinatorial biosynthesis to generate more analogues and heterologous expression of biosynthetic gene clusters with systematic engineering the recombinant microbial systems for large scale production.

Engineering antibiotic production and overcoming bacterial resistance

Progress in DNA technology, analytical methods and computational tools is leading to new developments in synthetic biology and metabolic engineering, enabling new ways to produce molecules of industrial and therapeutic interest. Here, we review recent progress in both antibiotic production and strategies to counteract bacterial resistance to antibiotics. Advances in sequencing and cloning are increasingly enabling the characterization of antibiotic biosynthesis pathways, and new systematic methods for de novo biosynthetic pathway prediction are allowing the exploration of the metabolic chemical space beyond metabolic engineering. Moreover, we survey the computer-assisted design of modular assembly lines in polyketide synthases and non-ribosomal peptide synthases for the development of tailor-made antibiotics. Nowadays, production of novel antibiotic can be tranferred into any chosen chassis by optimizing a host factory through specific strain modifications. These advances in metabolic engineering and synthetic biology are leading to novel strategies for engineering antimicrobial agents with desired specificities.

Multi-factorial engineering of heterologous polyketide production in Escherichia coli reveals complex pathway interactions

Polyketides represent a significant fraction of all natural products. Many possess pharmacological activity which makes them attractive drug candidates. The production of the parent macrocyclic aglycones is catalyzed by multi-modular polyketide synthases utilizing short-chain acyl-CoA monomers. When producing polyketides through heterologous hosts, one must not only functionally express the synthase itself, but activate the machinery used to generate the required substrate acyl-CoA's. As a result, metabolic engineering of these pathways is necessary for high-level production of heterologous polyketides. In this study, we over-express three different pathways for provision of the two substrates (propionyl-CoA and (2S)-methylmalonyl-CoA) utilized for the biosynthesis of 6-deoxyerythronolide B (6-dEB; the macrolactone precursor of erythromycin): (1) a propionate → propionyl-CoA → (2S)-methylmalonyl-CoA pathway, (2) a methylmalonate → methylmalonyl-CoA → propionyl-CoA pathway, and (3) a succinate → succinyl-CoA → (2R)-methylmalonyl-CoA → (2S)-methylmalonyl-CoA → propionyl-CoA pathway. The current study revealed that propionate is a necessary component for greater than 5 mg L(-1) titers. Deletion of the propionyl-CoA:succinate CoA transferase (ygfH) or over-expression of the transcriptional activator of short chain fatty acid uptake improved titer to over 100 mg L(-1), while the combination of the two improved titer to over 130 mg L(-1). The addition of exogenous methylmalonate could also improve titer to over 100 mg L(-1). Expression of a Streptomyces coelicolor A3(2) methylmalonyl-CoA epimerase, in conjunction with over-expression of Escherichia coli's native methylmalonyl-CoA mutase, allowed for the incorporation of exogenously fed succinate into the 6-dEB core.