Evidence map›Paper›PMID 31255177›Full record

ArticleMicrobial cell factories2019

Generation of an E. coli platform strain for improved sucrose utilization using adaptive laboratory evolution.

Elsayed T Mohamed, Hemanshu Mundhada, Jenny Landberg, Isaac Cann, Roderick I Mackie, Alex Toftgaard Nielsen, Markus J Herrgård, Adam M Feist

Abstract read
In one paragraph

Article in Microbial cell factories, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Advances in adaptive laboratory evolution applications forSynthetic and systems biotechnology · 2025
    Review
  5. Effects of Tumor-associatedArchives of Razi Institute · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Adaptive laboratory evolution ofMetabolic engineering communications · 2020
    Article
  19. Review
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

8 authors.

Elsayed T MohamedNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark.
Hemanshu MundhadaNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark.
Jenny LandbergNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark.
Isaac CannDepartment of Animal Sciences, Institute for Genomic Biology and Energy Biosciences Institute, University of Illinois, Urbana, IL, 61801, USA.
Roderick I MackieDepartment of Animal Sciences, Institute for Genomic Biology and Energy Biosciences Institute, University of Illinois, Urbana, IL, 61801, USA.
Alex Toftgaard NielsenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark.
Markus J HerrgårdNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark.
Adam M FeistNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, Lyngby, 2800 Kgs, Denmark. afeist@ucsd.edu.ORCID http://orcid.org/0000-0002-8630-4800

Funding

Novo Nordisk Fonden NNF10CC1016517Novo Nordisk Fonden NNF14OC0011269
6 · The paper itself

Abstract

backgroundSucrose is an attractive industrial carbon source due to its abundance and the fact that it can be cheaply generated from sources such as sugarcane. However, only a few characterized Escherichia coli strains are able to metabolize sucrose, and those that can are typically slow growing or pathogenic strains.

methodsTo generate a platform strain capable of efficiently utilizing sucrose with a high growth rate, adaptive laboratory evolution (ALE) was utilized to evolve engineered E. coli K-12 MG1655 strains containing the sucrose utilizing csc genes (cscB, cscK, cscA) alongside the native sucrose consuming E. coli W.

resultsEvolved K-12 clones displayed an increase in growth and sucrose uptake rates of 1.72- and 1.40-fold on sugarcane juice as compared to the original engineered strains, respectively, while E. coli W clones showed a 1.4-fold increase in sucrose uptake rate without a significant increase in growth rate. Whole genome sequencing of evolved clones and populations revealed that two genetic regions were frequently mutated in the K-12 strains; the global transcription regulatory genes rpoB and rpoC, and the metabolic region related to a pyrimidine biosynthetic deficiency in K-12 attributed to pyrE expression. These two mutated regions have been characterized to confer a similar benefit when glucose is the main carbon source, and reverse engineering revealed the same causal advantages on M9 sucrose. Additionally, the most prevalent mutation found in the evolved E. coli W lineages was the inactivation of the cscR gene, the transcriptional repression of sucrose uptake genes.

conclusionThe generated K-12 and W platform strains, and the specific sets of mutations that enable their phenotypes, are available as valuable tools for sucrose-based industrial bioproduction in the facile E. coli chassis.

Indexed as

Directed Molecular EvolutionEscherichia coliEscherichia coli ProteinsGenetic EngineeringGenome, BacterialGlucoseMembrane Transport ProteinsSucrosecscB protein, E coliEscherichia coli ProteinsGlucoseMembrane Transport ProteinsSucroseAdaptive laboratory evolutionEscherichia coliPlatform strainsRenewable feedstocksSucrose

Identifiers

PMID31255177
PMCPMC6599523

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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.