Evidence map›Paper›PMID 27824342›Full record

ArticleThe ISME journal2017

Systems-level metabolism of the altered Schaedler flora, a complete gut microbiota.

Matthew B Biggs, Gregory L Medlock, Thomas J Moutinho, Hannah J Lees, Jonathan R Swann, Glynis L Kolling, Jason A Papin

Abstract read
In one paragraph

Article in The ISME journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. iScience · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
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  14. Article
  15. Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research.Toxicological sciences : an official journal of the Society of Toxicology · 2022
    Review
  16. Article
  17. Article
  18. Article
  19. The Methanol Extract ofFrontiers in nutrition · 2022
    Article
  20. 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

7 authors.

Matthew B BiggsDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-6492-8180
Gregory L MedlockDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0002-1571-0801
Thomas J MoutinhoDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Hannah J LeesDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College, London, UK.
Jonathan R SwannDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College, London, UK.
Glynis L KollingDivision of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, VA, USA.
Jason A PapinDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.

Funding

BIOTECHNOLOGY TRAINING PROGRAMT32GM008715 · NIGMS · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI LAURIE, GORDON WILLIAM · 2000 to 2019
$6.6M
Interdisciplinary Training in Systems & Biomolecular Data ScienceT32GM145443 · NIGMS · UNIVERSITY OF VIRGINIA · PI Kevin A Janes, Jason Papin · 2022 to 2026
$1.5M
Mapping and predicting metabolic fluxes between the ileal microbiome and hostR01GM108501 · NIGMS · UNIVERSITY OF VIRGINIA · PI PAPIN, JASON · 2014 to 2017
$1.4M
Transdisciplinary Big Data Science Training at UVaT32LM012416 · NLM · UNIVERSITY OF VIRGINIA · PI BROWN, DONALD E, LOUGHRAN, THOMAS P. · 2016 to 2020
$1.3M
Biodefense Short-Term Training for Minority StudentT35AI060528 · NIAID · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI HALME, ADRIAN J, PETRI, WILLIAM A · 2004 to 2024
$1.3M
NIAID NIH HHS T35 AI060528NIGMS NIH HHS R01 GM108501NIGMS NIH HHS T32 GM008715NIGMS NIH HHS T32 GM145443NLM NIH HHS T32 LM012416
6 · The paper itself

Abstract

The altered Schaedler flora (ASF) is a model microbial community with both in vivo and in vitro relevance. Here we provide the first characterization of the ASF community in vitro, independent of a murine host. We compared the functional genetic content of the ASF to wild murine metagenomes and found that the ASF functionally represents wild microbiomes better than random consortia of similar taxonomic composition. We developed a chemically defined medium that supported growth of seven of the eight ASF members. To elucidate the metabolic capabilities of these ASF species-including potential for interactions such as cross-feeding-we performed a spent media screen and analyzed the results through dynamic growth measurements and non-targeted metabolic profiling. We found that cross-feeding is relatively rare (32 of 3570 possible cases), but is enriched between Clostridium ASF356 and Parabacteroides ASF519. We identified many cases of emergent metabolism (856 of 3570 possible cases). These data will inform efforts to understand ASF dynamics and spatial distribution in vivo, to design pre- and probiotics that modulate relative abundances of ASF members, and will be essential for validating computational models of ASF metabolism. Well-characterized, experimentally tractable microbial communities enable research that can translate into more effective microbiome-targeted therapies to improve human health.

Indexed as

AnimalsBacteriaCulture MediaGastrointestinal MicrobiomeHost-Pathogen InteractionsHumansMetagenomeMiceModels, BiologicalCulture Media

Identifiers

PMID27824342
PMCPMC5270571

What OpenQuestion holds

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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.