Evidence map›Paper›PMID 26422514›Full record

ArticleeLife2015

Protein biogenesis machinery is a driver of replicative aging in yeast.

Georges E Janssens, Anne C Meinema, Javier González, Justina C Wolters, Alexander Schmidt, Victor Guryev, Rainer Bischoff, Ernst C Wit, Liesbeth M Veenhoff, Matthias Heinemann

Abstract read
In one paragraph

Article in eLife, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing 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

105 citing papers in PubMed.

  1. Article
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  5. A Renal Clearable Probe for In Vivo Monoamine Oxidase (MAO) Detection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  6. Article
  7. Article
  8. Article
  9. Article
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  14. Dynamic Changes in Gene Expression Through Aging inbioRxiv : the preprint server for biology · 2024
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

45 more citing papers are in PubMed but not listed here.

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

10 authors.

Georges E JanssensEuropean Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Anne C MeinemaMolecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands.
Javier GonzálezProbability and Statistics, Johann Bernoulli Institute of Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands.
Justina C WoltersAnalytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
Alexander SchmidtBiozentrum, University of Basel, Basel, Switzerland.
Victor GuryevEuropean Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Rainer BischoffAnalytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
Ernst C WitProbability and Statistics, Johann Bernoulli Institute of Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands.
Liesbeth M VeenhoffEuropean Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Matthias HeinemannMolecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An integrated account of the molecular changes occurring during the process of cellular aging is crucial towards understanding the underlying mechanisms. Here, using novel culturing and computational methods as well as latest analytical techniques, we mapped the proteome and transcriptome during the replicative lifespan of budding yeast. With age, we found primarily proteins involved in protein biogenesis to increase relative to their transcript levels. Exploiting the dynamic nature of our data, we reconstructed high-level directional networks, where we found the same protein biogenesis-related genes to have the strongest ability to predict the behavior of other genes in the system. We identified metabolic shifts and the loss of stoichiometry in protein complexes as being consequences of aging. We propose a model whereby the uncoupling of protein levels of biogenesis-related genes from their transcript levels is causal for the changes occurring in aging yeast. Our model explains why targeting protein synthesis, or repairing the downstream consequences, can serve as interventions in aging.

Indexed as

Cellular SenescenceGene Expression ProfilingModels, BiologicalProteomeSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsProteomeSaccharomyces cerevisiae Proteinsbiochemistrycomputational biologyproteomereplicative agingS. cerevisiaesystems biologytranscriptome

Identifiers

PMID26422514
PMCPMC4718733

What OpenQuestion holds

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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.