Evidence map›Paper›PMID 31690234›Full record

ArticleJournal of the Royal Society, Interface2019

Modelling microbial communities using biochemical resource allocation analysis.

Suraj Sharma, Ralf Steuer

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Nutrient colimitation is a quantitative, dynamic property of microbial populations.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  2. Deciphering and designing microbial communities by genome-scale metabolic modelling.Computational and structural biotechnology journal · 2024
    Review
  3. Review
  4. Review
  5. Review
  6. Microbial population dynamics decouple growth response from environmental nutrient concentration.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Frontiers in veterinary science · 2022
    Article
  8. 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

2 authors.

Suraj SharmaHumboldt-Universität zu Berlin, Institut für Biologie, FachInstitut für Theoretische Biologie (ITB), Invalidenstr. 110, 10115 Berlin, Germany.
Ralf SteuerHumboldt-Universität zu Berlin, Institut für Biologie, FachInstitut für Theoretische Biologie (ITB), Invalidenstr. 110, 10115 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To understand the functioning and dynamics of microbial communities is a fundamental challenge in current biology. To tackle this challenge, the construction of computational models of interacting microbes is an indispensable tool. There is, however, a large chasm between ecologically motivated descriptions of microbial growth used in many current ecosystems simulations, and detailed metabolic pathway and genome-based descriptions developed in the context of systems and synthetic biology. Here, we seek to demonstrate how resource allocation models of microbial growth offer the potential to advance ecosystem simulations and their parametrization. In particular, recent work on quantitative resource allocation allow us to formulate mechanistic models of microbial growth that are physiologically meaningful while remaining computationally tractable. These models go beyond Michaelis-Menten and Monod-type growth models, and are capable of accounting for emergent properties that underlie the remarkable plasticity of microbial growth. We outline the utility and advantages of using biochemical resource allocation models by considering a coarse-grained model of cyanobacterial growth and demonstrate how the model allows us to address specific questions of relevance for the simulation of marine microbial ecosystems, including the physiological acclimation of protein expression to different environments, the description of co-limitation by several nutrients and the differential use of alternative nutrient sources, as well as the description of metabolic diversity based on our increasing knowledge about quantitative cell physiology.

Indexed as

Models, BiologicalCyanobacteriaMicrobiotacyanobacteriaecosystems biologyflux-balance analysismarine ecologytrait-based modelling

Identifiers

PMID31690234
PMCPMC6893496

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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.