Evidence map›Paper›PMID 23349810›Full record

ArticlePloS one2013

Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory.

José Manuel Otero, Donatella Cimini, Kiran R Patil, Simon G Poulsen, Lisbeth Olsson, Jens Nielsen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
8.8field-weighted citation impact, top 2% 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

60 citing papers in PubMed, 170 citations in OpenAlex.

  1. Article
  2. Review
  3. Enhanced Succinate Production inBiotech (Basel (Switzerland)) · 2025
    Article
  4. Computational biology predicts metabolic engineering targets for increased production of 103 valuable chemicals in yeast.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Microbial production of advanced biofuels.Nature reviews. Microbiology · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. Genome-scale metabolic reconstruction of the non-model yeastMetabolic engineering communications · 2020
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Evaluation of pyruvate decarboxylase-negativeEngineering in life sciences · 2019
    Article
  20. 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

6 authors at 3 institutions in 3 countries.

José Manuel OteroDepartment of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Donatella Cimini
Kiran R Patil
Simon G Poulsen
Lisbeth Olsson
Jens Nielsen
Technical University of Denmark · DKChalmers University of Technology · SEUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd)-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals.

Indexed as

Aldehyde-LyasesBiomassCitric Acid CycleDirected Molecular EvolutionFermentationIndustrial MicrobiologyMetabolic EngineeringModels, GeneticMutationOligonucleotide Array Sequence AnalysisReproducibility of ResultsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSuccinic AcidSystems BiologyTransaminasesAGX1 protein, S cerevisiaeAldehyde-LyasesGLY1 protein, S cerevisiaeSaccharomyces cerevisiae ProteinsSuccinic AcidTransaminases

Identifiers

PMID23349810
PMCPMC3549990
OpenAlexW1999640817

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.