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Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential

Asplund-Samuelsson, Johannes (författare)
KTH,Science for Life Laboratory, SciLifeLab
Janasch, Markus (författare)
KTH,Skolan för bioteknologi (BIO),Science for Life Laboratory, SciLifeLab
Hudson, Elton P. (författare)
KTH,Science for Life Laboratory, SciLifeLab,Skolan för bioteknologi (BIO)
 (creator_code:org_t)
Academic Press Inc. 2018
2018
Engelska.
Ingår i: Metabolic engineering. - : Academic Press Inc.. - 1096-7176 .- 1096-7184. ; 45, s. 223-236
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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. 

Ämnesord

NATURVETENSKAP  -- Biologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

Nyckelord

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

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Janasch, Markus
Hudson, Elton P.
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