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Swimming in Light: A Large-Scale Computational Analysis of the Metabolism of Dinoroseobacter shibae

Overview of attention for article published in PLoS Computational Biology, October 2013
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Title
Swimming in Light: A Large-Scale Computational Analysis of the Metabolism of Dinoroseobacter shibae
Published in
PLoS Computational Biology, October 2013
DOI 10.1371/journal.pcbi.1003224
Pubmed ID
Authors

Rene Rex, Nelli Bill, Kerstin Schmidt-Hohagen, Dietmar Schomburg

Abstract

The Roseobacter clade is a ubiquitous group of marine α-proteobacteria. To gain insight into the versatile metabolism of this clade, we took a constraint-based approach and created a genome-scale metabolic model (iDsh827) of Dinoroseobacter shibae DFL12T. Our model is the first accounting for the energy demand of motility, the light-driven ATP generation and experimentally determined specific biomass composition. To cover a large variety of environmental conditions, as well as plasmid and single gene knock-out mutants, we simulated 391,560 different physiological states using flux balance analysis. We analyzed our results with regard to energy metabolism, validated them experimentally, and revealed a pronounced metabolic response to the availability of light. Furthermore, we introduced the energy demand of motility as an important parameter in genome-scale metabolic models. The results of our simulations also gave insight into the changing usage of the two degradation routes for dimethylsulfoniopropionate, an abundant compound in the ocean. A side product of dimethylsulfoniopropionate degradation is dimethyl sulfide, which seeds cloud formation and thus enhances the reflection of sunlight. By our exhaustive simulations, we were able to identify single-gene knock-out mutants, which show an increased production of dimethyl sulfide. In addition to the single-gene knock-out simulations we studied the effect of plasmid loss on the metabolism. Moreover, we explored the possible use of a functioning phosphofructokinase for D. shibae.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 2 5%
Brazil 1 2%
India 1 2%
United Kingdom 1 2%
United States 1 2%
Unknown 35 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 41%
Researcher 9 22%
Student > Master 5 12%
Professor 3 7%
Student > Postgraduate 2 5%
Other 2 5%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 41%
Biochemistry, Genetics and Molecular Biology 8 20%
Immunology and Microbiology 4 10%
Environmental Science 3 7%
Engineering 2 5%
Other 3 7%
Unknown 4 10%
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 08 October 2013.
All research outputs
#19,944,994
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#7,953
of 8,960 outputs
Outputs of similar age
#159,197
of 220,241 outputs
Outputs of similar age from PLoS Computational Biology
#117
of 135 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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 220,241 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.