Proteomic and transcriptomic profiling reveal different aspects of aging in the kidney

  1. Yuka Takemon
  2. Joel M Chick
  3. Isabela Gerdes Gyuricza
  4. Daniel A Skelly
  5. Olivier Devuyst
  6. Steven P Gygi
  7. Gary A Churchill
  8. Ron Korstanje  Is a corresponding author
  1. The Jackson Laboratory, United States
  2. Vividion Therapeutics, United States
  3. University of Zurich, Switzerland
  4. Harvard Medical School, United States

Abstract

Little is known about the molecular changes that take place in the kidney during the aging process. In order to better understand these changes, we measured mRNA and protein levels in genetically diverse mice at different ages. We observed distinctive change in mRNA and protein levels as a function of age. Changes in both mRNA and protein are associated with increased immune infiltration and decreases in mitochondrial function. Proteins show a greater extent of change and reveal changes in a wide array of biological processes including unique, organ-specific features of aging in kidney. Most importantly, we observed functionally important age-related changes in protein that occur in the absence of corresponding changes in mRNA. Our findings suggest that mRNA profiling alone provides an incomplete picture of molecular aging in the kidney and that examination of changes in proteins is essential to understand aging processes that are not transcriptionally regulated.

Data availability

Source data and analysis scripts have been deposited with FigShare (10.6084/m9.figshare. 12894146). In addition, the transcript and protein data are available in an online tool that supports genetic mapping analysis (https://churchilllab.jax.org/qtlviewer/JAC/DOKidney).The RNA-seq data have been deposited in NCBI's Gene Expression Omnibus, accession number GSE121330 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121330). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD023823.

The following data sets were generated

Article and author information

Author details

  1. Yuka Takemon

    The Jackson Laboratory, Bar Harbor, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3538-4409
  2. Joel M Chick

    Proteomics, Vividion Therapeutics, San Diego, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Isabela Gerdes Gyuricza

    The Jackson Laboratory, Bar Harbor, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7969-1910
  4. Daniel A Skelly

    The Jackson Laboratory, Bar Harbor, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2329-2216
  5. Olivier Devuyst

    Institute of Physiology, Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3744-4767
  6. Steven P Gygi

    Department of Cell Biology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Gary A Churchill

    The Jackson Laboratory, Bar Harbor, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9190-9284
  8. Ron Korstanje

    The Jackson Laboratory, Bar Harbor, United States
    For correspondence
    Ron.Korstanje@jax.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2808-1610

Funding

National Institutes of Health (AG038070)

  • Ron Korstanje

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The Jackson Laboratory's Institutional Animal Care and Use Committee approved all reported mouse studies.(AUS#06005).

Copyright

© 2021, Takemon et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 8,632
    views
  • 1,031
    downloads
  • 84
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Yuka Takemon
  2. Joel M Chick
  3. Isabela Gerdes Gyuricza
  4. Daniel A Skelly
  5. Olivier Devuyst
  6. Steven P Gygi
  7. Gary A Churchill
  8. Ron Korstanje
(2021)
Proteomic and transcriptomic profiling reveal different aspects of aging in the kidney
eLife 10:e62585.
https://doi.org/10.7554/eLife.62585

Share this article

https://doi.org/10.7554/eLife.62585

Further reading

    1. Computational and Systems Biology
    2. Physics of Living Systems
    Divyoj Singh, Sriram Ramaswamy ... Mohd Suhail Rizvi
    Research Article Updated

    Planar cell polarity (PCP) – tissue-scale alignment of the direction of asymmetric localization of proteins at the cell-cell interface – is essential for embryonic development and physiological functions. Abnormalities in PCP can result in developmental imperfections, including neural tube closure defects and misaligned hair follicles. Decoding the mechanisms responsible for PCP establishment and maintenance remains a fundamental open question. While the roles of various molecules – broadly classified into ‘global’ and ‘local’ modules – have been well-studied, their necessity and sufficiency in explaining PCP and connecting their perturbations to experimentally observed patterns have not been examined. Here, we develop a minimal model that captures the proposed features of PCP establishment – a global tissue-level gradient and local asymmetric distribution of protein complexes. The proposed model suggests that while polarity can emerge without a gradient, the gradient not only acts as a global cue but also increases the robustness of PCP against stochastic perturbations. We also recapitulated and quantified the experimentally observed features of swirling patterns and domineering non-autonomy, using only three free model parameters - rate of protein binding to membrane, the concentration of PCP proteins, and the gradient steepness. We explain how self-stabilizing asymmetric protein localizations in the presence of tissue-level gradient can lead to robust PCP patterns and reveal minimal design principles for a polarized system.

    1. Computational and Systems Biology
    2. Neuroscience
    Anna Cattani, Don B Arnold ... Nancy Kopell
    Research Article

    The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3–6 Hz), high theta (~6–12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations.