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Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans

Author

Listed:
  • Laura A. Herndon

    (A232 Nelson Biological Laboratories)

  • Peter J. Schmeissner

    (A232 Nelson Biological Laboratories)

  • Justyna M. Dudaronek

    (A232 Nelson Biological Laboratories)

  • Paula A. Brown

    (A232 Nelson Biological Laboratories)

  • Kristin M. Listner

    (A232 Nelson Biological Laboratories)

  • Yuko Sakano

    (A232 Nelson Biological Laboratories)

  • Marie C. Paupard

    (Albert Einstein College of Medicine)

  • David H. Hall

    (Albert Einstein College of Medicine)

  • Monica Driscoll

    (A232 Nelson Biological Laboratories)

Abstract

The nematode Caenorhabditis elegans is an important model for studying the genetics of ageing, with over 50 life-extension mutations known so far. However, little is known about the pathobiology of ageing in this species, limiting attempts to connect genotype with senescent phenotype. Using ultrastructural analysis and visualization of specific cell types with green fluorescent protein, we examined cell integrity in different tissues as the animal ages. We report remarkable preservation of the nervous system, even in advanced old age, in contrast to a gradual, progressive deterioration of muscle, resembling human sarcopenia. The age-1(hx546) mutation, which extends lifespan by 60–100%, delayed some, but not all, cellular biomarkers of ageing. Strikingly, we found strong evidence that stochastic as well as genetic factors are significant in C. elegans ageing, with extensive variability both among same-age animals and between cells of the same type within individuals.

Suggested Citation

  • Laura A. Herndon & Peter J. Schmeissner & Justyna M. Dudaronek & Paula A. Brown & Kristin M. Listner & Yuko Sakano & Marie C. Paupard & David H. Hall & Monica Driscoll, 2002. "Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans," Nature, Nature, vol. 419(6909), pages 808-814, October.
    • Handle: RePEc:nat:nature:v:419:y:2002:i:6909:d:10.1038_nature01135
    DOI: 10.1038/nature01135
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    Citations

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    Cited by:

    1. Christophe Restif & Carolina Ibáñez-Ventoso & Mehul M Vora & Suzhen Guo & Dimitris Metaxas & Monica Driscoll, 2014. "CeleST: Computer Vision Software for Quantitative Analysis of C. elegans Swim Behavior Reveals Novel Features of Locomotion," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
    2. Drew Benjamin Sinha & Zachary Scott Pincus, 2022. "High temporal resolution measurements of movement reveal novel early-life physiological decline in C. elegans," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-17, February.
    3. Maria Gabriella Melchiorre & Marco Socci & Sabrina Quattrini & Giovanni Lamura & Barbara D’Amen, 2022. "Frail Older People Ageing in Place in Italy: Use of Health Services and Relationship with General Practitioner," IJERPH, MDPI, vol. 19(15), pages 1-26, July.
    4. Spencer Farrell & Arnold Mitnitski & Kenneth Rockwood & Andrew D Rutenberg, 2022. "Interpretable machine learning for high-dimensional trajectories of aging health," PLOS Computational Biology, Public Library of Science, vol. 18(1), pages 1-30, January.
    5. Katharina Jovic & Mark G Sterken & Jacopo Grilli & Roel P J Bevers & Miriam Rodriguez & Joost A G Riksen & Stefano Allesina & Jan E Kammenga & L Basten Snoek, 2017. "Temporal dynamics of gene expression in heat-stressed Caenorhabditis elegans," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
    6. Céline N Martineau & André E X Brown & Patrick Laurent, 2020. "Multidimensional phenotyping predicts lifespan and quantifies health in Caenorhabditis elegans," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-14, July.

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