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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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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Average Attention Score compared to outputs of the same age and source

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13 X users

Citations

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117 Mendeley
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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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Switzerland 1 <1%
Belgium 1 <1%
Iran, Islamic Republic of 1 <1%
Korea, Republic of 1 <1%
Denmark 1 <1%
Unknown 108 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 23%
Researcher 25 21%
Student > Master 19 16%
Other 8 7%
Student > Bachelor 7 6%
Other 17 15%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 38%
Biochemistry, Genetics and Molecular Biology 16 14%
Computer Science 9 8%
Medicine and Dentistry 7 6%
Immunology and Microbiology 6 5%
Other 19 16%
Unknown 16 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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
#5,162,395
of 25,452,734 outputs
Outputs from Microbiome
#1,413
of 1,764 outputs
Outputs of similar age
#78,740
of 395,936 outputs
Outputs of similar age from Microbiome
#23
of 33 outputs
Altmetric has tracked 25,452,734 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,764 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.2. This one is in the 19th percentile – i.e., 19% 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 395,936 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 80% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.