Evidence map›Paper›PMID 27387069›Full record

ArticleEnvironmental microbiology2016

Stoichiometric modelling of assimilatory and dissimilatory biomass utilisation in a microbial community.

Kristopher A Hunt, Ryan deM Jennings, William P Inskeep, Ross P Carlson

Abstract read
In one paragraph

Article in Environmental microbiology, 2016. 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. Article
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  5. Review
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  7. 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.

Kristopher A HuntCenter for Biofilm Engineering, Montana State University, Bozeman, MT, USA.
Ryan deM JenningsThermal Biology Institute, Montana State University, Bozeman, MT, USA.
William P InskeepThermal Biology Institute, Montana State University, Bozeman, MT, USA.
Ross P CarlsonCenter for Biofilm Engineering, Montana State University, Bozeman, MT, USA.

Funding

Predictive Multiscale Modeling of Microbial Consortia BiofilmsU01EB019416 · NIBIB · MONTANA STATE UNIVERSITY - BOZEMAN · PI CARLSON, ROSS P., FIELDS, MATTHEW W · 2014 to 2017
$1.3M
NIBIB NIH HHS U01 EB019416
6 · The paper itself

Abstract

Assimilatory and dissimilatory utilisation of autotroph biomass by heterotrophs is a fundamental mechanism for the transfer of nutrients and energy across trophic levels. Metagenome data from a tractable, thermoacidophilic microbial community in Yellowstone National Park was used to build an in silico model to study heterotrophic utilisation of autotroph biomass using elementary flux mode analysis and flux balance analysis. Assimilatory and dissimilatory biomass utilisation was investigated using 29 forms of biomass-derived dissolved organic carbon (DOC) including individual monomer pools, individual macromolecular pools and aggregate biomass. The simulations identified ecologically competitive strategies for utilizing DOC under conditions of varying electron donor, electron acceptor or enzyme limitation. The simulated growth environment affected which form of DOC was the most competitive use of nutrients; for instance, oxygen limitation favoured utilisation of less reduced and fermentable DOC while carbon-limited environments favoured more reduced DOC. Additionally, metabolism was studied considering two encompassing metabolic strategies: simultaneous versus sequential use of DOC. Results of this study bound the transfer of nutrients and energy through microbial food webs, providing a quantitative foundation relevant to most microbial ecosystems.

Indexed as

BiomassEcosystemArchaeaBacteriaCarbonEukaryotaFood ChainMicrobial ConsortiaCarbon

Identifiers

PMID27387069
PMCPMC5629010

What OpenQuestion holds

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Registered trials

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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.