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Generation of a platform strain for ionic liquid tolerance using adaptive laboratory evolution

Overview of attention for article published in Microbial Cell Factories, November 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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4 tweeters

Citations

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28 Dimensions

Readers on

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50 Mendeley
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Title
Generation of a platform strain for ionic liquid tolerance using adaptive laboratory evolution
Published in
Microbial Cell Factories, November 2017
DOI 10.1186/s12934-017-0819-1
Pubmed ID
Authors

Elsayed T. Mohamed, Shizeng Wang, Rebecca M. Lennen, Markus J. Herrgård, Blake A. Simmons, Steven W. Singer, Adam M. Feist

Abstract

There is a need to replace petroleum-derived with sustainable feedstocks for chemical production. Certain biomass feedstocks can meet this need as abundant, diverse, and renewable resources. Specific ionic liquids (ILs) can play a role in this process as promising candidates for chemical pretreatment and deconstruction of plant-based biomass feedstocks as they efficiently release carbohydrates which can be fermented. However, the most efficient pretreatment ILs are highly toxic to biological systems, such as microbial fermentations, and hinder subsequent bioprocessing of fermentative sugars obtained from IL-treated biomass. To generate strains capable of tolerating residual ILs present in treated feedstocks, a tolerance adaptive laboratory evolution (TALE) approach was developed and utilized to improve growth of two different Escherichia coli strains, DH1 and K-12 MG1655, in the presence of two different ionic liquids, 1-ethyl-3-methylimidazolium acetate ([C2C1Im][OAc]) and 1-butyl-3-methylimidazolium chloride ([C4C1Im]Cl). For multiple parallel replicate populations of E. coli, cells were repeatedly passed to select for improved fitness over the course of approximately 40 days. Clonal isolates were screened and the best performing isolates were subjected to whole genome sequencing. The most prevalent mutations in tolerant clones occurred in transport processes related to the functions of mdtJI, a multidrug efflux pump, and yhdP, an uncharacterized transporter. Additional mutations were enriched in processes such as transcriptional regulation and nucleotide biosynthesis. Finally, the best-performing strains were compared to previously characterized tolerant strains and showed superior performance in tolerance of different IL and media combinations (i.e., cross tolerance) with robust growth at 8.5% (w/v) and detectable growth up to 11.9% (w/v) [C2C1Im][OAc]. The generated strains thus represent the best performing platform strains available for bioproduction utilizing IL-treated renewable substrates, and the TALE method was highly successful in overcoming the general issue of substrate toxicity and has great promise for use in tolerance engineering.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 28%
Researcher 10 20%
Student > Bachelor 6 12%
Student > Master 5 10%
Student > Doctoral Student 2 4%
Other 3 6%
Unknown 10 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 26%
Biochemistry, Genetics and Molecular Biology 13 26%
Chemical Engineering 3 6%
Engineering 3 6%
Immunology and Microbiology 2 4%
Other 4 8%
Unknown 12 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2018.
All research outputs
#6,698,949
of 12,444,666 outputs
Outputs from Microbial Cell Factories
#409
of 906 outputs
Outputs of similar age
#154,617
of 374,443 outputs
Outputs of similar age from Microbial Cell Factories
#25
of 126 outputs
Altmetric has tracked 12,444,666 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 906 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 374,443 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.