Evidence map›Paper›PMID 26979110›Full record

ReviewGut microbes2016

Investigating a holobiont: Microbiota perturbations and transkingdom networks.

Renee Greer, Xiaoxi Dong, Andrey Morgun, Natalia Shulzhenko

Abstract readReview
In one paragraph

Review in Gut microbes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
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

28 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Biology · 2021
    Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Interspecies Communication in Holobionts by Non-Coding RNA Exchange.International journal of molecular sciences · 2020
    Review
  20. Gut Microbiota and Cancer of the Host: Colliding Interests.Advances in experimental medicine and biology · 2020
    Review
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

4 authors.

Renee Greera College of Veterinary Medicine, Oregon State University , Corvallis , OR , USA.
Xiaoxi Dongb College of Pharmacy, Oregon State University , Corvallis , OR , USA.
Andrey Morgunb College of Pharmacy, Oregon State University , Corvallis , OR , USA.
Natalia Shulzhenkob College of Pharmacy, Oregon State University , Corvallis , OR , USA.

Funding

Gut microbiota mediates the interplay between immunity and glucose metabolismR01DK103761 · NIDDK · OREGON STATE UNIVERSITY · PI SHULZHENKO, NATALIA · 2015 to 2019
$1.7M
Anti-IL-12p40 Treatment of CVID Enteropathy: Gene Expression/Microbiota AnalysisU01AI109695 · NIAID · OREGON STATE UNIVERSITY · PI MORGUN, ANDRIY · 2013 to 2015
$951k
NIAID NIH HHS U01 AI109695NIDDK NIH HHS R01 DK103761
6 · The paper itself

Abstract

The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study. (1) Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems.

Indexed as

AnimalsAnti-Bacterial AgentsBacteriaBacterial InfectionsComputational BiologyHost-Pathogen InteractionsHumansMicrobiotaAnti-Bacterial Agentsantibioticsbipartite betweenness centralitygermfree miceholobiontmetagenomicsmicrobiomemicrobiotasystems biologytranskingdom networks

Identifiers

PMID26979110
PMCPMC4856449

What OpenQuestion holds

Textmetadata
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.