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Construction of low-ethanol–wine yeasts through partial deletion of the Saccharomyces cerevisiae PDC2 gene

Overview of attention for article published in AMB Express, March 2017
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Title
Construction of low-ethanol–wine yeasts through partial deletion of the Saccharomyces cerevisiae PDC2 gene
Published in
AMB Express, March 2017
DOI 10.1186/s13568-017-0369-2
Pubmed ID
Authors

Raúl Andrés Cuello, Karina Johana Flores Montero, Laura Analía Mercado, Mariana Combina, Iván Francisco Ciklic

Abstract

We propose an alternative GMO based strategy to obtain Saccharomyces cerevisiae mutant strains with a slight reduction in their ability to produce ethanol, but with a moderate impact on the yeast metabolism. Through homologous recombination, two truncated Pdc2p proteins Pdc2pΔ344 and Pdc2pΔ519 were obtained and transformed into haploid and diploid lab yeast strains. In the pdc2Δ344 mutants the DNA-binding and transactivation site of the protein remain intact, whereas in pdc2Δ519 only the DNA-binding site is conserved. Compared to the control, the diploid BY4743pdc2Δ519 mutant strain reduced up to 7.4% the total ethanol content in lab scale-vinifications. The residual sugar and volatile acidity was not significantly affected by this ethanol reduction. Remarkably, we got a much higher ethanol reduction of 10 and 15% when the pdc2Δ519 mutation was tested in a native and a commercial wine yeast strain against their respective controls. Our results demonstrate that the insertion of the pdc2Δ519 mutation in wine yeast strains can reduce the ethanol concentration up to 1.89% (v/v) without affecting the fermentation performance. In contrast to non-GMO based strategies, our approach permits the insertion of the pdc2Δ519 mutation in any locally selected wine strain, making possible to produce quality wines with regional characteristics and lower alcohol content. Thus, we consider our work a valuable contribution to the problem of high ethanol concentration in wine.

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The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 33%
Student > Ph. D. Student 7 16%
Student > Master 4 9%
Student > Doctoral Student 3 7%
Professor 2 4%
Other 2 4%
Unknown 12 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 31%
Biochemistry, Genetics and Molecular Biology 10 22%
Immunology and Microbiology 2 4%
Computer Science 1 2%
Business, Management and Accounting 1 2%
Other 2 4%
Unknown 15 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 March 2017.
All research outputs
#22,002,486
of 24,547,718 outputs
Outputs from AMB Express
#1,011
of 1,291 outputs
Outputs of similar age
#275,501
of 313,659 outputs
Outputs of similar age from AMB Express
#52
of 54 outputs
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