Evidence map›Paper›PMID 33407079›Full record

ArticleBMC bioinformatics2021

Examination of hydrogen cross-feeders using a colonic microbiota model.

Nick W Smith, Paul R Shorten, Eric Altermann, Nicole C Roy, Warren C McNabb

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Modeling approaches for probing cross-feeding interactions in the human gut microbiome.Computational and structural biotechnology journal · 2022
    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

5 authors.

Nick W SmithSchool of Food and Advanced Technology, Massey University, Palmerston North, New Zealand.
Paul R ShortenRiddet Institute, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand. paul.shorten@agresearch.co.nz.ORCID http://orcid.org/0000-0001-5938-8837
Eric AltermannRiddet Institute, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand.
Nicole C RoyRiddet Institute, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand.
Warren C McNabbRiddet Institute, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing.

resultsAn existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions of the colonic model were developed: one representing the colon with sequential compartments and one utilising a continuous spatial representation. When applied to the colonic environment, the model predicted pH dynamics within the ranges measured in vivo and SCFA ratios comparable to those in the literature. The continuous version of the model simulated relative abundances of microbial functional groups comparable to measured values, but predictions were sensitive to the metabolic parameter values used for each functional group. Sulphate availability was found to strongly influence hydrogenotroph activity in the continuous version of the model, correlating positively with SRB and sulphide concentration and negatively with methanogen concentration, but had no effect in the compartmentalised model version.

conclusionsAlthough the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota.

Indexed as

ColonGastrointestinal MicrobiomeBacteriaHumansHydrogenModels, BiologicalSulfidesHydrogenSulfidesCommunity modellingHydrogen sulphideMethaneMicrobiomemicroPop

Identifiers

PMID33407079
PMCPMC7789523

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.