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Factors driving metabolic diversity in the budding yeast subphylum

Overview of attention for article published in BMC Biology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

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49 tweeters


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Factors driving metabolic diversity in the budding yeast subphylum
Published in
BMC Biology, March 2018
DOI 10.1186/s12915-018-0498-3
Pubmed ID

Dana A. Opulente, Emily J. Rollinson, Cleome Bernick-Roehr, Amanda Beth Hulfachor, Antonis Rokas, Cletus P. Kurtzman, Chris Todd Hittinger


Associations between traits are prevalent in nature, occurring across a diverse range of taxa and traits. Individual traits may co-evolve with one other, and these correlations can be driven by factors intrinsic or extrinsic to an organism. However, few studies, especially in microbes, have simultaneously investigated both across a broad taxonomic range. Here we quantify pairwise associations among 48 traits across 784 diverse yeast species of the ancient budding yeast subphylum Saccharomycotina, assessing the effects of phylogenetic history, genetics, and ecology. We find extensive negative (traits that tend to not occur together) and positive (traits that tend to co-occur) pairwise associations among traits, as well as between traits and environments. These associations can largely be explained by the biological properties of the traits, such as overlapping biochemical pathways. The isolation environments of the yeasts explain a minor but significant component of the variance, while phylogeny (the retention of ancestral traits in descendant species) plays an even more limited role. Positive correlations are pervasive among carbon utilization traits and track with chemical structures (e.g., glucosides and sugar alcohols) and metabolic pathways, suggesting a molecular basis for the presence of suites of traits. In several cases, characterized genes from model organisms suggest that enzyme promiscuity and overlapping biochemical pathways are likely mechanisms to explain these macroevolutionary trends. Interestingly, fermentation traits are negatively correlated with the utilization of pentose sugars, which are major components of the plant biomass degraded by fungi and present major bottlenecks to the production of cellulosic biofuels. Finally, we show that mammalian pathogenic and commensal yeasts have a suite of traits that includes growth at high temperature and, surprisingly, the utilization of a narrowed panel of carbon sources. These results demonstrate how both intrinsic physiological factors and extrinsic ecological factors drive the distribution of traits present in diverse organisms across macroevolutionary timescales.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 20%
Student > Ph. D. Student 15 19%
Student > Master 11 14%
Student > Bachelor 6 8%
Student > Postgraduate 5 6%
Other 13 16%
Unknown 13 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 37%
Biochemistry, Genetics and Molecular Biology 24 30%
Immunology and Microbiology 2 3%
Chemical Engineering 1 1%
Unspecified 1 1%
Other 4 5%
Unknown 18 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 26 March 2019.
All research outputs
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Outputs from BMC Biology
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Outputs of similar age
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Outputs of similar age from BMC Biology
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Altmetric has tracked 22,860,626 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,000 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.5. This one has done well, scoring higher than 83% 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 330,787 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 34 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 67% of its contemporaries.