Evidence map›Paper›PMID 37443156›Full record

ArticleNature communications2023

Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions.

Matteo Mori, Chuankai Cheng, Brian R Taylor, Hiroyuki Okano, Terence Hwa

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Review
  3. Energetic gradients emerge in developing motor-microtubule structures.bioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  6. Glycolytic ATP production enables rapid mammalian cell growth.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Unveiling Metabolic Engineering Strategies by Quantitative Heterologous Pathway Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  16. Flexibility and sensitivity in gene regulation out of equilibrium.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  17. Article
  18. Article
  19. 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

5 authors at 2 institutions in 1 country.

Matteo Mori *Department of Physics, University of California San Diego, 9500 Gilman Dr. La Jolla, San Diego, CA, 92093, USA. mamori@ucsd.edu.ORCID 0000-0002-6263-8021
Chuankai Cheng *Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Brian R TaylorDepartment of Physics, University of California San Diego, 9500 Gilman Dr. La Jolla, San Diego, CA, 92093, USA.ORCID 0000-0002-4557-1048
Hiroyuki OkanoDepartment of Physics, University of California San Diego, 9500 Gilman Dr. La Jolla, San Diego, CA, 92093, USA.
Terence HwaDepartment of Physics, University of California San Diego, 9500 Gilman Dr. La Jolla, San Diego, CA, 92093, USA.ORCID 0000-0003-1837-6842
University of California San Diego · USUniversity of Southern California · 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

Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here we establish a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks. FDM allowed for a detailed quantification of the energy and biosynthesis budget for growing Escherichia coli cells. Surprisingly, the ATP generated during the biosynthesis of building blocks from glucose almost balances the demand from protein synthesis, the largest energy expenditure known for growing cells. This leaves the bulk of the energy generated by fermentation and respiration unaccounted for, thus challenging the common notion that energy is a key growth-limiting resource. Moreover, FDM together with proteomics enables the quantification of enzymes contributing towards each metabolic function, allowing for a first-principle formulation of a coarse-grained model of global protein allocation based on the structure of the metabolic network.

Indexed as

Energy MetabolismProteinsEscherichia coliFermentationMetabolic Networks and PathwaysProteins

Identifiers

PMID37443156
PMCPMC10345195
OpenAlexW4384203067

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.