Analytics for Metabolic Engineering

Kim, Young-Mo; Chan, Leanne Jade G.; Nhan, Melissa; Adams, Paul D.

doi:10.3389/fbioe.2015.00135

Cited by 84 publications

(60 citation statements)

References 115 publications

(125 reference statements)

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“…S. cerevisiae is a widely used industrial workhorse for producing a broad spectrum of chemicals that represents over quarter trillion dollars market 38 . The experimental and analytical approaches described here raise the possibility of genome-scale reprogramming of metabolic fluxes, which will dramatically speed up the “design-build-test” cycle in industrial biomanufacturing 39 . We also expect our method could be used to rewire the fate of yeast cells, such as cell cycle, and thus generate new biological insights on the fundamentals of metabolic diseases, aging and apoptosis by using yeast as a disease model.…”

Section: Discussionmentioning

confidence: 99%

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Sheng

Guo

Ash

et al. 2017

Preprint

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Multiplex and multi-directional control of metabolic pathways is crucial for metabolic engineering to improve product yield of fuels, chemicals, and pharmaceuticals. To achieve this goal, artificial transcriptional regulators such as CRISPR-based transcription regulators have been developed to specifically activate or repress genes of interest. Here, we found that by deploying guide RNAs to target on DNA sites at different locations of genetic cassettes, we could use just one synthetic CRISPR-based transcriptional regulator to simultaneously activate and repress gene expressions. By using the pairwise datasets of guide RNAs and gene expressions, we developed a data-driven predictive model to rationally design this system for fine-tuning expression of target genes. We demonstrated that this system could achieve programmable control of metabolic fluxes when using yeast to produce versatile chemicals. We anticipate that this master CRISPR-based transcription regulator will be a valuable addition to the synthetic biology toolkit for metabolic engineering, speeding up the “design-build-test” cycle in industrial biomanufacturing as well as generating new biological insights on the fates of eukaryotic cells.

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Section: Discussionmentioning

confidence: 99%

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Sheng

Guo

Ash

et al. 2017

Preprint

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“…The implemented pathways typically need to be optimized further for economically viable production titers and rates. The optimization is performed through the Design-Built-Test-(Learn) cycle of metabolic engineering [56][57][58] where stoichiometric [59][60][61] and kinetic models [62][63][64][65][66][67][68][69] , genome editing 70,71 and phenotypic characterization 72 are combined to improve recombinant strains for production of biochemicals.…”

Section: Further Experimental Implementation and Pathway Optimizationmentioning

confidence: 99%

“…The highest ranked candidate pathways can then be experimentally implemented in the host organism and can further be optimized through the Design-Built-Test-(Learn) cycle of metabolic engineering. [56][57][58]…”

Section: Experimental Implementation and Pathway Optimizationmentioning

confidence: 99%

Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors

Tokic

Hadadi

Ataman

et al. 2017

Preprint

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The limited supply of fossil fuels and the establishment of new environmental policies shifted research in industry and academia towards sustainable production of the 2 nd generation of biofuels, with Methyl Ethyl Ketone (MEK) being one promising fuel candidate. MEK is a commercially valuable petrochemical with an extensive application as a solvent. However, as of today, a sustainable and economically viable production of MEK has not yet been achieved despite several attempts of introducing biosynthetic pathways in industrial microorganisms. We used BNICE.ch as a retrobiosynthesis tool to discover all novel pathways around MEK. Out of 1'325 identified compounds connecting to MEK with one reaction step, we selected 3oxopentanoate, but-3-en-2-one, but-1-en-2-olate, butylamine, and 2-hydroxy-2methyl-butanenitrile for further study. We reconstructed 3'679'610 novel biosynthetic pathways towards these 5 compounds. We then embedded these pathways into the genome-scale model of E. coli, and a set of 18'622 were found to be most biologically feasible ones based on thermodynamics and their yields. For each novel reaction in the viable pathways, we proposed the most similar KEGG reactions, with their gene and protein sequences, as candidates for either a direct experimental implementation or as a basis for enzyme engineering. Through pathway similarity analysis we classified the pathways and identified the enzymes and precursors that were indispensable for the production of the target molecules. These retrobiosynthesis studies demonstrate the potential of BNICE.ch for discovery, systematic evaluation, and analysis of novel pathways in synthetic biology and metabolic engineering studies.3 Graphical abstract4 Limited reserves of oil and natural gas and the environmental issues associated with their exploitation in the production of chemicals sparked off current developments of processes that can produce the same chemicals from renewable feedstocks using microorganisms. 1-3 A fair amount of these efforts focuses on a sustainable production of the 2 nd generation biofuels.Compared to the currently used fossil fuels and bioethanol, these 2 nd generation biofuels should provide lower carbon emissions, higher energy density, and should be less corrosive to engines and distribution infrastructures. Recently, a large number of potential candidates for the 2 nd generation biofuels has been proposed such as nbutanol 4 , isobutanol 4 , 2-methyl-1-butanol 4 , 3-methyl-1-butanol 4 , C13 to C17 mixtures of alkanes and alkenes 5 , fatty esters, fatty alcohols 1 , and Methyl Ethyl Ketone (MEK) 6 .While some of these compounds were detected in living cells, none was produced by native organisms in appreciable quantities. 7 For chemicals whose natural microbial producers are not known, the feasibility of their bioproduction has to be assessed and potential novel biosynthetic pathways for production of these chemicals are yet to be discovered. 8,9 Even when production pathways for target chemicals are known, it is important to find alternativ...

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“…Still, the examples are all for titres that are well below industrially relevant ones, and it remains to be seen if the dynamic range of these biosensor systems can be stretched to be applied to select for improved strains at those high product concentrations. It is to be expected that the advances in microfluidics and microdroplet technologies will open up new avenues of high-throughput strain selection, including advanced mass spectrometry analytics and single-cell transcriptomics (Petzold et al, 2015;Kou et al, 2016).…”

Section: Testmentioning

confidence: 99%

Bacterial cell factoriest : applying thermophiles to fuel the biobased economy

Kranenburg¹

2017

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Analytics for Metabolic Engineering

Cited by 84 publications

References 115 publications

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors

Bacterial cell factoriest : applying thermophiles to fuel the biobased economy

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