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The potential for non-adaptive origins of evolutionary innovations in central carbon metabolism

Overview of attention for article published in BMC Systems Biology, October 2016
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
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7 tweeters

Citations

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8 Dimensions

Readers on

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39 Mendeley
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Title
The potential for non-adaptive origins of evolutionary innovations in central carbon metabolism
Published in
BMC Systems Biology, October 2016
DOI 10.1186/s12918-016-0343-7
Pubmed ID
Authors

Sayed-Rzgar Hosseini, Andreas Wagner

Abstract

Biological systems are rife with examples of pre-adaptations or exaptations. They range from the molecular scale - lens crystallins, which originated from metabolic enzymes - to the macroscopic scale, such as feathers used in flying, which originally served thermal insulation or waterproofing. An important class of exaptations are novel and useful traits with non-adaptive origins. Whether such origins could be frequent cannot be answered with individual examples, because it is a question about a biological system's potential for exaptation. We here take a step towards answering this question by analyzing central carbon metabolism, and novel traits that allow an organism to survive on novel sources of carbon and energy. We have previously applied flux balance analysis to this system and predicted the viability of 10(15) metabolic genotypes on each of ten different carbon sources. We here use this exhaustive genotype-phenotype map to ask whether a central carbon metabolism that is viable on a given, focal carbon source C - the equivalent of an adaptation in our framework - is usually or rarely viable on one or more other carbon sources C new - a potential exaptation. We show that most metabolic genotypes harbor potential exaptations, that is, they are viable on one or more carbon sources C new . The nature and number of these carbon sources depends on the focal carbon source C itself, and on the biochemical similarity between C and C new . Moreover, metabolisms that show a higher biomass yield on C, and that are more complex, i.e., they harbor more metabolic reactions, are viable on a greater number of carbon sources C new . A high potential for exaptation results from correlations between the phenotypes of different genotypes, and such correlations are frequent in central carbon metabolism. If they are similarly abundant in other metabolic or biological systems, innovations may frequently have non-adaptive ("exaptive") origins.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
United States 1 3%
Germany 1 3%
Unknown 36 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 31%
Researcher 8 21%
Student > Master 6 15%
Student > Postgraduate 4 10%
Student > Bachelor 2 5%
Other 2 5%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 44%
Biochemistry, Genetics and Molecular Biology 8 21%
Immunology and Microbiology 1 3%
Computer Science 1 3%
Social Sciences 1 3%
Other 3 8%
Unknown 8 21%

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 05 October 2017.
All research outputs
#5,970,622
of 11,874,340 outputs
Outputs from BMC Systems Biology
#314
of 995 outputs
Outputs of similar age
#97,270
of 258,594 outputs
Outputs of similar age from BMC Systems Biology
#9
of 18 outputs
Altmetric has tracked 11,874,340 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 995 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 68% 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 258,594 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 61% of its contemporaries.
We're also able to compare this research output to 18 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 50% of its contemporaries.