Evidence map›Paper›PMID 29973148›Full record

ArticleBMC genomics2018

Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism.

Adam Amara, Eriko Takano, Rainer Breitling

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Construction and application of the genome-scale metabolic model ofFrontiers in bioengineering and biotechnology · 2023
    Article
  6. Article
  7. Article
  8. Review
  9. Clavulanic Acid Production byAntibiotics (Basel, Switzerland) · 2021
    Review
  10. Comparative Transcriptome Analysis ofFrontiers in bioengineering and biotechnology · 2020
    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

3 authors.

Adam AmaraManchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, School of Chemistry, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.ORCID http://orcid.org/0000-0003-0489-0533
Eriko TakanoManchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, School of Chemistry, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
Rainer BreitlingManchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, School of Chemistry, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK. rainer.breitling@manchester.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/M017702/1
6 · The paper itself

Abstract

backgroundStreptomyces species produce a vast diversity of secondary metabolites of clinical and biotechnological importance, in particular antibiotics. Recent developments in metabolic engineering, synthetic and systems biology have opened new opportunities to exploit Streptomyces secondary metabolism, but achieving industry-level production without time-consuming optimization has remained challenging. Genome-scale metabolic modelling has been shown to be a powerful tool to guide metabolic engineering strategies for accelerated strain optimization, and several generations of models of Streptomyces metabolism have been developed for this purpose.

resultsHere, we present the most recent update of a genome-scale stoichiometric constraint-based model of the metabolism of Streptomyces coelicolor, the major model organism for the production of antibiotics in the genus. We show that the updated model enables better metabolic flux and biomass predictions and facilitates the integrative analysis of multi-omics data such as transcriptomics, proteomics and metabolomics.

conclusionsThe updated model presented here provides an enhanced basis for the next generation of metabolic engineering attempts in Streptomyces.

Indexed as

Models, BiologicalAnti-Bacterial AgentsBacterial ProteinsBiomassGene Expression Regulation, BacterialMetabolic EngineeringProteomicsStreptomyces coelicolorAnti-Bacterial AgentsBacterial ProteinsGenome-scale metabolic modellingNatural productsOmicsSecondary metabolismStreptomycesSynthetic biology

Identifiers

PMID29973148
PMCPMC6040156

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.