Evidence map›Paper›PMID 34699521›Full record

ArticlePLoS biology2021

On the optimality of the enzyme-substrate relationship in bacteria.

Hugo Dourado, Matteo Mori, Terence Hwa, Martin J Lercher

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.0field-weighted citation impact, top 7% of its field
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

25 citing papers in PubMed, 49 citations in OpenAlex.

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  13. Quantifying microbial guilds.ISME communications · 2024
    Article
  14. Review
  15. Article
  16. Principles of metabolome conservation in animals.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  17. Optimal density of bacterial cells.PLoS computational biology · 2023
    Article
  18. Article
  19. Article
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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 at 2 institutions in 2 countries.

Hugo DouradoInstitute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.ORCID 0000-0003-4851-1355
Matteo MoriDepartment of Physics, University of California at San Diego, La Jolla, California, United States of America.ORCID 0000-0002-6263-8021
Terence HwaDepartment of Physics, University of California at San Diego, La Jolla, California, United States of America.
Martin J LercherInstitute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.ORCID 0000-0003-3940-1621
Heinrich Heine University Düsseldorf · DEUniversity of California San Diego · US

Funding

Quantitative Studies of Bacterial Growth PhysiologyR01GM095903 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HWA, TERENCE · 2011 to 2023
$3.8M
NIGMS NIH HHS R01 GM095903
6 · The paper itself

Abstract

Much recent progress has been made to understand the impact of proteome allocation on bacterial growth; much less is known about the relationship between the abundances of the enzymes and their substrates, which jointly determine metabolic fluxes. Here, we report a correlation between the concentrations of enzymes and their substrates in Escherichia coli. We suggest this relationship to be a consequence of optimal resource allocation, subject to an overall constraint on the biomass density: For a cellular reaction network composed of effectively irreversible reactions, maximal reaction flux is achieved when the dry mass allocated to each substrate is equal to the dry mass of the unsaturated (or "free") enzymes waiting to consume it. Calculations based on this optimality principle successfully predict the quantitative relationship between the observed enzyme and metabolite abundances, parameterized only by molecular masses and enzyme-substrate dissociation constants (Km). The corresponding organizing principle provides a fundamental rationale for cellular investment into different types of molecules, which may aid in the design of more efficient synthetic cellular systems.

Indexed as

EnzymesEscherichia coliKineticsMetabolomeSubstrate SpecificityEnzymes

Identifiers

PMID34699521
PMCPMC8547704
OpenAlexW3209577604

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.