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Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires

Overview of attention for article published in Microbiome, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
18 tweeters

Citations

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33 Dimensions

Readers on

mendeley
109 Mendeley
citeulike
1 CiteULike
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Title
Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires
Published in
Microbiome, November 2015
DOI 10.1186/s40168-015-0121-6
Pubmed ID
Authors

Eugen Bauer, Cedric Christian Laczny, Stefania Magnusdottir, Paul Wilmes, Ines Thiele

Abstract

The human gastrointestinal tract harbors a diverse microbial community, in which metabolic phenotypes play important roles for the human host. Recent developments in meta-omics attempt to unravel metabolic roles of microbes by linking genotypic and phenotypic characteristics. This connection, however, still remains poorly understood with respect to its evolutionary and ecological context. We generated automatically refined draft genome-scale metabolic models of 301 representative intestinal microbes in silico. We applied a combination of unsupervised machine-learning and systems biology techniques to study individual and global differences in genomic content and inferred metabolic capabilities. Based on the global metabolic differences, we found that energy metabolism and membrane synthesis play important roles in delineating different taxonomic groups. Furthermore, we found an exponential relationship between phylogeny and the reaction composition, meaning that closely related microbes of the same genus can exhibit pronounced differences with respect to their metabolic capabilities while at the family level only marginal metabolic differences can be observed. This finding was further substantiated by the metabolic divergence within different genera. In particular, we could distinguish three sub-type clusters based on membrane and energy metabolism within the Lactobacilli as well as two clusters within the Bifidobacteria and Bacteroides. We demonstrate that phenotypic differentiation within closely related species could be explained by their metabolic repertoire rather than their phylogenetic relationships. These results have important implications in our understanding of the ecological and evolutionary complexity of the human gastrointestinal microbiome.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Belgium 1 <1%
Iran, Islamic Republic of 1 <1%
Denmark 1 <1%
Korea, Republic of 1 <1%
Switzerland 1 <1%
Unknown 100 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 25%
Researcher 24 22%
Student > Master 18 17%
Student > Bachelor 6 6%
Other 6 6%
Other 17 16%
Unknown 11 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 39%
Biochemistry, Genetics and Molecular Biology 14 13%
Computer Science 9 8%
Medicine and Dentistry 7 6%
Immunology and Microbiology 5 5%
Other 17 16%
Unknown 14 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 29 June 2018.
All research outputs
#2,390,053
of 19,163,209 outputs
Outputs from Microbiome
#856
of 1,157 outputs
Outputs of similar age
#52,971
of 385,248 outputs
Outputs of similar age from Microbiome
#43
of 79 outputs
Altmetric has tracked 19,163,209 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,157 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.1. This one is in the 26th percentile – i.e., 26% 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 385,248 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 86% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.