Evidence map›Paper›PMID 21451589›Full record

ArticleMolecular systems biology2011

Metabolic modeling of endosymbiont genome reduction on a temporal scale.

Keren Yizhak, Tamir Tuller, Balázs Papp, Eytan Ruppin

Abstract read
In one paragraph

Article in Molecular systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Testing the Domino Theory of Gene Loss inLife (Basel, Switzerland) · 2018
    Article
  9. Article
  10. Modeling cancer metabolism on a genome scale.Molecular systems biology · 2015
    Review
  11. Article
  12. Systems biology perspectives on minimal and simpler cells.Microbiology and molecular biology reviews : MMBR · 2014
    Review
  13. Genome reduction as the dominant mode of evolution.BioEssays : news and reviews in molecular, cellular and developmental biology · 2013
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  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

4 authors.

Keren YizhakThe Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. kerenyiz@post.tau.ac.il
Tamir Tuller
Balázs Papp
Eytan Ruppin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental challenge in Systems Biology is whether a cell-scale metabolic model can predict patterns of genome evolution by realistically accounting for associated biochemical constraints. Here, we study the order in which genes are lost in an in silico evolutionary process, leading from the metabolic network of Escherichia coli to that of the endosymbiont Buchnera aphidicola. We examine how this order correlates with the order by which the genes were actually lost, as estimated from a phylogenetic reconstruction. By optimizing this correlation across the space of potential growth and biomass conditions, we compute an upper bound estimate on the model's prediction accuracy (R=0.54). The model's network-based predictive ability outperforms predictions obtained using genomic features of individual genes, reflecting the effect of selection imposed by metabolic stoichiometric constraints. Thus, while the timing of gene loss might be expected to be a completely stochastic evolutionary process, remarkably, we find that metabolic considerations, on their own, make a marked 40% contribution to determining when such losses occur.

Indexed as

AnimalsAphidsBiological EvolutionBuchneraComputer SimulationDNA, BacterialEscherichia coliGenome, BacterialMetabolic Networks and PathwaysModels, BiologicalPhylogenySelection, GeneticSymbiosisSystems BiologyTime FactorsDNA, Bacterial

Identifiers

PMID21451589
PMCPMC3094061

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LicenceCC BY-NC-SA
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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.