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Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

Overview of attention for article published in Frontiers in Microbiology, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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1 blog
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2 X users

Citations

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38 Dimensions

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104 Mendeley
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Title
Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation
Published in
Frontiers in Microbiology, March 2017
DOI 10.3389/fmicb.2017.00534
Pubmed ID
Authors

Sebastián N. Mendoza, Pablo M. Cañón, Ángela Contreras, Magdalena Ribbeck, Eduardo Agosín

Abstract

Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 <1%
Sweden 1 <1%
Unknown 102 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 20%
Student > Master 12 12%
Student > Bachelor 10 10%
Researcher 9 9%
Professor 6 6%
Other 13 13%
Unknown 33 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 23%
Agricultural and Biological Sciences 21 20%
Engineering 9 9%
Chemical Engineering 7 7%
Computer Science 3 3%
Other 5 5%
Unknown 35 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 March 2018.
All research outputs
#4,194,118
of 24,885,505 outputs
Outputs from Frontiers in Microbiology
#3,941
of 28,434 outputs
Outputs of similar age
#69,628
of 314,104 outputs
Outputs of similar age from Frontiers in Microbiology
#125
of 489 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,434 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 85% 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 314,104 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 489 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.