Evidence map›Paper›PMID 28789673›Full record

ArticleBMC research notes2017

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

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

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Characteristics of rumen microbiota andFrontiers in microbiology · 2024
    Article
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Janine KamkeAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
Priya SoniAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
Yang LiAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
Siva GaneshAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
William J KellyAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
Sinead C LeahyAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand.
Weibing ShiDepartment of Energy, Joint Genome Institute, Walnut Creek, CA, 94598, USA.
Jeff FroulaDepartment of Energy, Joint Genome Institute, Walnut Creek, CA, 94598, USA.
Edward M RubinDepartment of Energy, Joint Genome Institute, Walnut Creek, CA, 94598, USA.
Graeme T AttwoodAgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North, 4442, New Zealand. graeme.attwood@agresearch.co.nz.ORCID http://orcid.org/0000-0002-6443-8760
AgResearch · NZLawrence Berkeley National Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRuminants 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 CH

methodsRumen 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.

resultsDetailed 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.

conclusionsThis 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.

Indexed as

Gene Expression Regulation, BacterialTranscriptomeAnimalsBacteriaBacterial ProteinsCulture MediaFermentationGastrointestinal MicrobiomeGene OntologyMetabolic Networks and PathwaysMetagenomeMethaneMethanobrevibacterMolecular Sequence AnnotationPhylogenyRumenBacterial ProteinsCulture MediaMethaneType III Secretion SystemsBacterialMethaneRumenSuccinivibrioType III secretion

Identifiers

PMID28789673
PMCPMC5549432
OpenAlexW2742996162

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.