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Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential
KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO).
2018 (English)In: Metabolic engineering, ISSN 1096-7176, E-ISSN 1096-7184, Vol. 45, p. 223-236Article in journal (Refereed) Published
Abstract [en]

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified. 

Place, publisher, year, edition, pages
Academic Press Inc. , 2018. Vol. 45, p. 223-236
Keywords [en]
E. coli, Max-min driving force analysis, Network-embedded thermodynamic analysis, Pathway enumeration, Pathway thermodynamics, Synechocystis, Amino acids, Biochemistry, Biosynthesis, Carbon, Escherichia coli, Metabolism, Metabolites, Thermoanalysis, Thermodynamic properties, Driving force analysis, Thermo dynamic analysis, Thermodynamics, 2 oxoglutaric acid, acetyl coenzyme A, adenosine triphosphate, coenzyme A, erythrose 4 phosphate, ferulic acid, fructose 6 phosphate, fumaric acid, glyceraldehyde 3 phosphate, glyceraldehyde 3 phosphate dehydrogenase, isoprenoid, lysine, malate dehydrogenase, malic acid, naringenin, nicotinamide adenine dinucleotide, nicotinamide adenine dinucleotide (phosphate) transhydrogenase, oxaloacetic acid, phosphate, reduced nicotinamide adenine dinucleotide phosphate, succinate coenzyme A ligase, succinate dehydrogenase, tricarboxylic acid, unclassified drug, Article, comparative study, computer analysis, concentration process, controlled study, enzyme synthesis, glycolysis, metabolic engineering, metabolomics, nonhuman, photorespiration, photosynthesis, priority journal, prospecting optimal pathway with python, workflow
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-223193DOI: 10.1016/j.ymben.2017.12.011ISI: 000424292100023Scopus ID: 2-s2.0-85040079427OAI: oai:DiVA.org:kth-223193DiVA, id: diva2:1186316
Note

Export Date: 13 February 2018; Article; CODEN: MEENF; Correspondence Address: Hudson, E.P.; Science for Life Laboratory, School of Biotechnology, KTH Royal Institute of Technology, P-Box 1031, Sweden; email: paul.hudson@scilifelab.se; Funding details: 2016-06160, VR, Vetenskapsrådet; Funding details: RBP14-0013, SSF, Stiftelsen för Strategisk Forskning. QC 20180228

Available from: 2018-02-28 Created: 2018-02-28 Last updated: 2018-03-13Bibliographically approved

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