Modular Metabolic Engineering for Biobased Chemical Production

Lu, Hsu Feng; Villada, Juan C.; Lee, Patrick K. H.

doi:10.1016/j.tibtech.2018.07.003

Cited by 98 publications

(55 citation statements)

References 68 publications

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“…etabolic engineering is an enabling technology for developing sustainable biomanufacturing processes for chemicals, fuels, and nutraceuticals using renewable feedstock by repurposing cellular metabolism [1][2][3][4] . High-level bioproduction of 1,3-propanediol and 1,4-butanediol demonstrates the success of bio-based chemical production [5][6][7] .…”

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confidence: 99%

Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction

et al. 2020

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Metabolic engineering facilitates chemical biosynthesis by rewiring cellular resources to produce target compounds. However, an imbalance between cell growth and bioproduction often reduces production efficiency. Genetic code expansion (GCE)-based orthogonal translation systems incorporating non-canonical amino acids (ncAAs) into proteins by reassigning non-canonical codons to ncAAs qualify for balancing cellular metabolism. Here, GCE-based cell growth and biosynthesis balance engineering (GCE-CGBBE) is developed, which is based on titrating expression of cell growth and metabolic flux determinant genes by constructing ncAA-dependent expression patterns. We demonstrate GCE-CGBBE in genome-recoded Escherichia coli Δ321AM by precisely balancing glycolysis and N-acetylglucosamine production, resulting in a 4.54-fold increase in titer. GCE-CGBBE is further expanded to non-genome-recoded Bacillus subtilis to balance growth and N-acetylneuraminic acid bioproduction by titrating essential gene expression, yielding a 2.34-fold increase in titer. Moreover, the development of ncAA-dependent essential gene expression regulation shows efficient biocontainment of engineered B. subtilis to avoid unintended proliferation in nature.

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confidence: 99%

Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction

et al. 2020

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“…Although carbon dioxide and formate are usually excreted during aerobic methanotrophy 54 , these metabolites have recently become valuable by-products 55,56 and are used as carbon sources in synthetically constructed methanotrophic modular microbial consortia to produce value-added compounds 57 . In our study, the highest carbon dioxide yield (0.39 mmol mmolCH 4 −1 ) was achieved under culture conditions of 20% methane and 20% oxygen, and the highest formate yield (0.025 mmol mmolCH 4 −1 ) was obtained under conditions of 20% methane and 25% oxygen.…”

Section: Discussionmentioning

confidence: 99%

Integrative genome-scale metabolic modeling reveals versatile metabolic strategies for methane utilization inMethylomicrobium albumBG8

Lim

et al. 2021

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Methylomicrobium album BG8 is an aerobic methanotrophic bacterium that can mitigate environmental methane emission, and is a promising microbial cell factory for the conversion of methane to value-added chemicals. However, the lack of a genome-scale metabolic model (GEM) of M. album BG8 has hindered the development of systems biology and metabolic engineering of this methanotroph. To fill this gap, a high-quality GEM was constructed to facilitate a system-level understanding on the biochemistry of M. album BG8. Next, experimental time-series growth and exometabolomics data were integrated into the model to generate context-specific GEMs. Flux balance analysis (FBA) constrained with experimental data derived from varying levels of methane, oxygen, and biomass were used to model the metabolism of M. album BG8 and investigate the metabolic states that promote the production of biomass and the excretion of carbon dioxide, formate, and acetate. The experimental and modeling results indicated that the system-level metabolic functions of M. album BG8 require a ratio > 1:1 between the oxygen and methane specific uptake rates for optimal growth. Integrative modeling revealed that at a high ratio of oxygen-to-methane uptake flux, carbon dioxide and formate were the preferred excreted compounds; at lower ratios, however, acetate accounted for a larger fraction of the total excreted flux. The results of this study reveal a trade-off between biomass production and organic compound excretion and provide evidence that this trade-off is linked to the ratio between the oxygen and methane specific uptake rates.

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“…Metabolism, the set of biochemical reactions that transform various compounds in living cells and organisms, is one of the core systems responsible for maintaining cellular functions. Metabolic models (reconstructions) of bacteria have been developed to facilitate the study and manipulation of biochemical processes [1], allowing the bio-production of valuable compounds to be optimized through metabolic engineering [2]. The study of human metabolism, on the other hand, is becoming increasingly important for biomedical applications as an approach for understanding health and diseases.…”

Section: Introductionmentioning

confidence: 99%

Discovering Essential Multiple Gene Effects Through Large Scale Optimization: An Application to Human Cancer Metabolism

Occhipinti

Hamadi²,

Kugler

et al. 2021

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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Computational modelling of metabolic processes has proven to be a useful approach to formulate our knowledge and improve our understanding of core biochemical systems that are crucial to maintaining cellular functions. Towards understanding the broader role of metabolism on cellular decision-making in health and disease conditions, it is important to integrate the study of metabolism with other core regulatory systems and omics within the cell, including gene expression patterns.After quantitatively integrating gene expression profiles with a genome-scale reconstruction of human metabolism, we propose a set of combinatorial methods to reverse engineer gene expression profiles and to find pairs and higher-order combinations of genetic modifications that simultaneously optimize multiobjective cellular goals. This enables us to suggest classes of transcriptomic profiles that are most suitable to achieve given metabolic phenotypes.We demonstrate how our techniques are able to compute beneficial, neutral or "toxic" combinations of gene expression levels. We test our methods on nine tissue-specific cancer models, comparing our outcomes with the corresponding normal cells, identifying genes as targets for potential therapies. Our methods open the way to a broad class of applications that require an understanding of the interplay among genotype, metabolism, and cellular behaviour, at scale.

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Modular Metabolic Engineering for Biobased Chemical Production

Cited by 98 publications

References 68 publications

Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction

Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction

Integrative genome-scale metabolic modeling reveals versatile metabolic strategies for methane utilization inMethylomicrobium albumBG8

Discovering Essential Multiple Gene Effects Through Large Scale Optimization: An Application to Human Cancer Metabolism

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