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Gene and transcript abundances of bacterial type III secretion systems from the rumen microbiome are correlated with methane yield in sheep

Overview of attention for article published in BMC Research Notes, August 2017
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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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1 blog
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8 X users

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24 Mendeley
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Title
Gene and transcript abundances of bacterial type III secretion systems from the rumen microbiome are correlated with methane yield in sheep
Published in
BMC Research Notes, August 2017
DOI 10.1186/s13104-017-2671-0
Pubmed ID
Authors

Janine Kamke, Priya Soni, Yang Li, Siva Ganesh, William J. Kelly, Sinead C. Leahy, Weibing Shi, Jeff Froula, Edward M. Rubin, Graeme T. Attwood

Abstract

Ruminants are important contributors to global methane emissions via microbial fermentation in their reticulo-rumens. This study is part of a larger program, characterising the rumen microbiomes of sheep which vary naturally in methane yield (g CH4/kg DM/day) and aims to define differences in microbial communities, and in gene and transcript abundances that can explain the animal methane phenotype. Rumen microbiome metagenomic and metatranscriptomic data were analysed by Gene Set Enrichment, sparse partial least squares regression and the Wilcoxon Rank Sum test to estimate correlations between specific KEGG bacterial pathways/genes and high methane yield in sheep. KEGG genes enriched in high methane yield sheep were reassembled from raw reads and existing contigs and analysed by MEGAN to predict their phylogenetic origin. Protein coding sequences from Succinivibrio dextrinosolvens strains were analysed using Effective DB to predict bacterial type III secreted proteins. The effect of S. dextrinosolvens strain H5 growth on methane formation by rumen methanogens was explored using co-cultures. Detailed analysis of the rumen microbiomes of high methane yield sheep shows that gene and transcript abundances of bacterial type III secretion system genes are positively correlated with methane yield in sheep. Most of the bacterial type III secretion system genes could not be assigned to a particular bacterial group, but several genes were affiliated with the genus Succinivibrio, and searches of bacterial genome sequences found that strains of S. dextrinosolvens were part of a small group of rumen bacteria that encode this type of secretion system. In co-culture experiments, S. dextrinosolvens strain H5 showed a growth-enhancing effect on a methanogen belonging to the order Methanomassiliicoccales, and inhibition of a representative of the Methanobrevibacter gottschalkii clade. This is the first report of bacterial type III secretion system genes being associated with high methane emissions in ruminants, and identifies these secretions systems as potential new targets for methane mitigation research. The effects of S. dextrinosolvens on the growth of rumen methanogens in co-cultures indicate that bacteria-methanogen interactions are important modulators of methane production in ruminant animals.

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X Demographics

The data shown below were collected from the profiles of 8 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 17%
Student > Ph. D. Student 3 13%
Student > Master 3 13%
Student > Doctoral Student 2 8%
Professor 2 8%
Other 3 13%
Unknown 7 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 33%
Unspecified 1 4%
Environmental Science 1 4%
Arts and Humanities 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 3 13%
Unknown 9 38%
Attention Score in Context

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 20 April 2018.
All research outputs
#3,105,844
of 24,093,053 outputs
Outputs from BMC Research Notes
#408
of 4,361 outputs
Outputs of similar age
#56,759
of 321,086 outputs
Outputs of similar age from BMC Research Notes
#20
of 155 outputs
Altmetric has tracked 24,093,053 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 4,361 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has done particularly well, scoring higher than 90% 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 321,086 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 82% of its contemporaries.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.