Evidence map›Paper›PMID 27430744›Full record

ArticleScientific reports2016

Yeast metabolic chassis designs for diverse biotechnological products.

Paula Jouhten, Tomasz Boruta, Sergej Andrejev, Filipa Pereira, Isabel Rocha, Kiran Raosaheb Patil

Abstract read
In one paragraph

Article in Scientific reports, 2016. 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. Article
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  3. Review
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  7. Review
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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

6 authors.

Paula JouhtenEuropean Molecular Biology Laboratory, EMBL, Heidelberg, Germany.
Tomasz BorutaDepartment of Bioprocess Engineering, Lodz University of Technology, Poland.
Sergej AndrejevEuropean Molecular Biology Laboratory, EMBL, Heidelberg, Germany.
Filipa PereiraEuropean Molecular Biology Laboratory, EMBL, Heidelberg, Germany.
Isabel RochaUniversity of Minho, Braga, Portugal.
Kiran Raosaheb PatilEuropean Molecular Biology Laboratory, EMBL, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae - a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains.

Indexed as

Energy MetabolismMetabolic Networks and PathwaysBiotechnologyCluster AnalysisGene DeletionGenes, FungalMetabolic EngineeringMetabolomicsSaccharomyces cerevisiaeSystems Biology

Identifiers

PMID27430744
PMCPMC4949481

What OpenQuestion holds

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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.