Evidence map›Paper›PMID 26215086›Full record

ArticleMicrobial cell factories2015

Metabolic network capacity of Escherichia coli for Krebs cycle-dependent proline hydroxylation.

Eleni Theodosiou, Oliver Frick, Bruno Bühler, Andreas Schmid

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. EngineeringBiotechnology reports (Amsterdam, Netherlands) · 2022
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  3. Frequency and spectrum of MFrontiers in plant science · 2022
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  4. Review
  5. Metabolic engineering communications · 2021
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  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. A new genome-scale metabolic model ofBiotechnology for biofuels · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Eleni TheodosiouDepartment of Biochemical and Chemical Engineering, Laboratory of Chemical Biotechnology, TU Dortmund University, Emil-Figge-Strasse 66, 44227, Dortmund, Germany. eleni.theodosiou@ufz.de.
Oliver FrickDepartment of Solar Materials, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany. oliver.frick@ufz.de.
Bruno BühlerDepartment of Biochemical and Chemical Engineering, Laboratory of Chemical Biotechnology, TU Dortmund University, Emil-Figge-Strasse 66, 44227, Dortmund, Germany. bruno.buehler@ufz.de.
Andreas SchmidDepartment of Solar Materials, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany. andreas.schmid@ufz.de.
Helmholtz Centre for Environmental Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the metabolism of the microbial host is essential for the development and optimization of whole-cell based biocatalytic processes, as it dictates production efficiency. This is especially true for redox biocatalysis where metabolically active cells are employed because of the cofactor/cosubstrate regenerative capacity endogenous in the host. Recombinant Escherichia coli was used for overproducing proline-4-hydroxylase (P4H), a dioxygenase catalyzing the hydroxylation of free L-proline into trans-4-hydroxy-L-proline with a-ketoglutarate (a-KG) as cosubstrate. In this whole-cell biocatalyst, central carbon metabolism provides the required cosubstrate a-KG, coupling P4H biocatalytic performance directly to carbon metabolism and metabolic activity. By applying both experimental and computational biology tools, such as metabolic engineering and (13)C-metabolic flux analysis ((13)C-MFA), we investigated and quantitatively described the physiological, metabolic, and bioenergetic response of the whole-cell biocatalyst to the targeted bioconversion and identified possible metabolic bottlenecks for further rational pathway engineering.

resultsA proline degradation-deficient E. coli strain was constructed by deleting the putA gene encoding proline dehydrogenase. Whole-cell biotransformations with this mutant strain led not only to quantitative proline hydroxylation but also to a doubling of the specific trans-4-L-hydroxyproline (hyp) formation rate, compared to the wild type. Analysis of carbon flux through central metabolism of the mutant strain revealed that the increased a-KG demand for P4H activity did not enhance the a-KG generating flux, indicating a tightly regulated TCA cycle operation under the conditions studied. In the wild type strain, P4H synthesis and catalysis caused a reduction in biomass yield. Interestingly, the ΔputA strain additionally compensated the associated ATP and NADH loss by reducing maintenance energy demands at comparably low glucose uptake rates, instead of increasing the TCA activity.

conclusionsThe putA knockout in recombinant E. coli BL21(DE3)(pLysS) was found to be promising for productive P4H catalysis not only in terms of biotransformation yield, but also regarding the rates for biotransformation and proline uptake and the yield of hyp on the energy source. The results indicate that, upon a putA knockout, the coupling of the TCA-cycle to proline hydroxylation via the cosubstrate a-KG becomes a key factor constraining and a target to further improve the efficiency of a-KG-dependent biotransformations.

Indexed as

Citric Acid CycleMetabolic Networks and PathwaysBacterial ProteinsBiocatalysisEscherichia coliGene Knockdown TechniquesGenetic EngineeringHydroxylationMembrane ProteinsProlineProlyl HydroxylasesRecombinant ProteinsBacterial ProteinsMembrane ProteinsProlineProlyl HydroxylasesPutA protein, BacteriaRecombinant Proteins

Identifiers

PMID26215086
PMCPMC4517350
OpenAlexW1608066004

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.