Current status and applications of genome-scale metabolic models.

Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for entire metabolic genes in an organism, and can be simulated to predict metabolic fluxes for various systems-level metabolic studies. Since the first GEM for Haemophilus influenzae was reported in 1999, advances have been made to develop and simulate GEMs for an increasing number of organisms across bacteria, archaea, and eukarya. Here, we review current reconstructed GEMs and discuss their applications, including strain development for chemicals and materials production, drug targeting in pathogens, prediction of enzyme functions, pan-reactome analysis, modeling interactions among multiple cells or organisms, and understanding human diseases.

Metabolic engineering of microorganisms for production of aromatic compounds.

Metabolic engineering has been enabling development of high performance microbial strains for the efficient production of natural and non-natural compounds from renewable non-food biomass. Even though microbial production of various chemicals has successfully been conducted and commercialized, there are still numerous chemicals and materials that await their efficient bio-based production. Aromatic chemicals, which are typically derived from benzene, toluene and xylene in petroleum industry, have been used in large amounts in various industries.

Revisiting Statistical Design and Analysis in Scientific Research.

Statistics is essential to design experiments and interpret experimental results. Inappropriate use of the statistical analysis, however, often leads to a wrong conclusion. This concept article revisits basic concepts of statistics and provides a brief guideline of applying the statistical analysis for scientific research from designing experiments to analyzing and presenting the data.

Repurposing type III polyketide synthase as a malonyl-CoA biosensor for metabolic engineering in bacteria.

Malonyl-CoA is an important central metabolite for the production of diverse valuable chemicals including natural products, but its intracellular availability is often limited due to the competition with essential cellular metabolism. Several malonyl-CoA biosensors have been developed for high-throughput screening of targets increasing the malonyl-CoA pool. However, they are limited for use only in and and require multiple signal transduction steps.

Metabolic engineering of Escherichia coli for high-level astaxanthin production with high productivity.

Astaxanthin is a reddish keto-carotenoid classified as a xanthophyll found in various microbes and marine organisms. As a powerful antioxidant having up to 100 times more potency than other carotenoids such as β-carotene, lutein, and lycopene, astaxanthin is a versatile compound utilized in animal feed, food pigment, health promotion and cosmetic industry. Here, we report development of metabolically engineered Escherichia coli capable of producing astaxanthin to a high concentration with high productivity.

Metabolic Engineering of Escherichia coli for Efficient Production of 2-Pyrone-4,6-dicarboxylic Acid from Glucose.

2-Pyrone-4,6-dicarboxylic acid (PDC) is a pseudoaromatic dicarboxylic acid and is a promising biobased building block chemical that can be used to make diverse polyesters with novel functionalities. In this study, Escherichia coli was metabolically engineered to produce PDC from glucose. First, an efficient biosynthetic pathway for PDC production from glucose was suggested by in silico metabolic flux simulation.

Metabolomics for industrial fermentation.

Metabolomics is essential to understand the metabolism and identify engineering targets to improve the performances of strains and bioprocesses. Although numerous metabolomics techniques have been developed and applied to various organisms, the metabolome of Saccharopolyspora erythraea, a native producer of erythromycin, had never been studied. The 2017 best paper of Bioprocess and Biosystems Engineering reports examination of three methods for quenching and extraction to analyze the intracellular metabolome of S.

Gene Expression Knockdown by Modulating Synthetic Small RNA Expression in Escherichia coli.

Escherichia coli gene expression knockdown using synthetic small RNA (sRNA) can be fine-tuned by altering sRNA sequences to modulate target mRNA-binding ability, but this requires thorough checking for off-target effects. Here, we present an sRNA gene expression knockdown system fine-tuned by using different promoters to modulate synthetic sRNA abundance. Our approach entails selecting knockdown target genes resulting from in silico flux response analysis and those related to product biosynthesis then screening strains transformed with a library of synthetic sRNA-promoter combinations for enhanced production.