Evidence map›Paper›PMID 30356154›Full record

ArticleNature microbiology2018

Interspecies cross-feeding orchestrates carbon degradation in the rumen ecosystem.

Lindsey M Solden, Adrian E Naas, Simon Roux, Rebecca A Daly, William B Collins, Carrie D Nicora, Sam O Purvine, David W Hoyt, Julia Schückel, Bodil Jørgensen and 7 more

Open access · hybridAbstract read
In one paragraph

Article in Nature microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
31.4field-weighted citation impact, top 1% 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

114 citing papers in PubMed, 211 citations in OpenAlex.

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54 more citing papers are in PubMed but not listed here.

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

17 authors at 8 institutions in 4 countries.

Lindsey M SoldenDepartment of Microbiology, The Ohio State University, Columbus, OH, USA.
Adrian E NaasFaculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
Simon RouxDepartment of Microbiology, The Ohio State University, Columbus, OH, USA.ORCID http://orcid.org/0000-0002-5831-5895
Rebecca A DalyDepartment of Microbiology, The Ohio State University, Columbus, OH, USA.
William B CollinsAlaska Department of Fish and Game, Division of Wildlife Conservation, Palmer, AK, USA.
Carrie D NicoraPacific Northwest National Laboratory, Richland, WA, USA.
Sam O PurvinePacific Northwest National Laboratory, Richland, WA, USA.
David W HoytPacific Northwest National Laboratory, Richland, WA, USA.
Julia SchückelDepartment of Plant and Environmental Sciences, University of Copenhagen, Copenhagen, Denmark.
Bodil JørgensenDepartment of Plant and Environmental Sciences, University of Copenhagen, Copenhagen, Denmark.
William WillatsSchool of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK.
Donald E SpalingerDepartment of Biology, University of Alaska Anchorage, Anchorage, AK, USA.
Jeffrey L FirkinsDepartment of Animal Sciences, The Ohio State University, Columbus, OH, USA.
Mary S LiptonPacific Northwest National Laboratory, Richland, WA, USA.
Matthew B SullivanDepartment of Microbiology, The Ohio State University, Columbus, OH, USA.ORCID http://orcid.org/0000-0001-8398-8234
Phillip B PopeFaculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway. phillip.b.pope@gmail.com.ORCID http://orcid.org/0000-0002-2067-4059
Kelly C WrightonDepartment of Microbiology, The Ohio State University, Columbus, OH, USA. kwrighton@gmail.com.ORCID http://orcid.org/0000-0003-0434-4217
The Ohio State University · USPacific Northwest National Laboratory · USNorwegian University of Life Sciences · NOUniversity of Copenhagen · DKAlaska Department of Fish and Game · USNewcastle University · GBUniversity of Alaska Anchorage · USWright State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because of their agricultural value, there is a great body of research dedicated to understanding the microorganisms responsible for rumen carbon degradation. However, we lack a holistic view of the microbial food web responsible for carbon processing in this ecosystem. Here, we sampled rumen-fistulated moose, allowing access to rumen microbial communities actively degrading woody plant biomass in real time. We resolved 1,193 viral contigs and 77 unique, near-complete microbial metagenome-assembled genomes, many of which lacked previous metabolic insights. Plant-derived metabolites were measured with NMR and carbohydrate microarrays to quantify the carbon nutrient landscape. Network analyses directly linked measured metabolites to expressed proteins from these unique metagenome-assembled genomes, revealing a genome-resolved three-tiered carbohydrate-fuelled trophic system. This provided a glimpse into microbial specialization into functional guilds defined by specific metabolites. To validate our proteomic inferences, the catalytic activity of a polysaccharide utilization locus from a highly connected metabolic hub genome was confirmed using heterologous gene expression. Viral detected proteins and linkages to microbial hosts demonstrated that phage are active controllers of rumen ecosystem function. Our findings elucidate the microbial and viral members, as well as their metabolic interdependencies, that support in situ carbon degradation in the rumen ecosystem.

Indexed as

Microbial ConsortiaRumenAnimalsBacteriaCarbonHost Microbial InteractionsMetabolic Networks and PathwaysMetagenomicsPhylogenyProteomicsRuminantsVirusesWoodCarbon

Identifiers

PMID30356154
PMCPMC6784887
OpenAlexW2896618349

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.