Evidence map›Paper›PMID 27769243›Full record

ArticleBMC systems biology2016

The potential for non-adaptive origins of evolutionary innovations in central carbon metabolism.

Sayed-Rzgar Hosseini, Andreas Wagner

Abstract read
In one paragraph

Article in BMC systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Evolutionary design principles in metabolism.Proceedings. Biological sciences · 2019
    Review
  6. Article
  7. Article
  8. Non-adaptive origins of evolutionary innovations increase network complexity in interacting digital organisms.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
    Article
  9. 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

2 authors.

Sayed-Rzgar HosseiniInstitute of Evolutionary Biology and Environmental Studies, University of Zurich, Bldg. Y27, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland.ORCID 0000-0002-2308-6754
Andreas WagnerInstitute of Evolutionary Biology and Environmental Studies, University of Zurich, Bldg. Y27, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland. andreas.wagner@ieu.uzh.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiological systems are rife with examples of pre-adaptations or exaptations. They range from the molecular scale - lens crystallins, which originated from metabolic enzymes - to the macroscopic scale, such as feathers used in flying, which originally served thermal insulation or waterproofing. An important class of exaptations are novel and useful traits with non-adaptive origins. Whether such origins could be frequent cannot be answered with individual examples, because it is a question about a biological system's potential for exaptation. We here take a step towards answering this question by analyzing central carbon metabolism, and novel traits that allow an organism to survive on novel sources of carbon and energy. We have previously applied flux balance analysis to this system and predicted the viability of 10

resultsWe here use this exhaustive genotype-phenotype map to ask whether a central carbon metabolism that is viable on a given, focal carbon source C - the equivalent of an adaptation in our framework - is usually or rarely viable on one or more other carbon sources C

conclusionsA high potential for exaptation results from correlations between the phenotypes of different genotypes, and such correlations are frequent in central carbon metabolism. If they are similarly abundant in other metabolic or biological systems, innovations may frequently have non-adaptive ("exaptive") origins.

Indexed as

Computational BiologyEvolution, MolecularAdaptation, PhysiologicalBiomassCarbonGenotypePhenotypeCarbonCentral carbon metabolismExaptationExhaustive genotype-phenotype mappingInnovation

Identifiers

PMID27769243
PMCPMC5073748

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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.