An atlas of the aging mouse proteome reveals the features of age-related post-transcriptional dysregulation

Masaki Takasugi (), Yoshiki Nonaka, Kazuaki Takemura, Yuya Yoshida, Frank Stein, Jennifer J. Schwarz, Jun Adachi, Junko Satoh, Shinji Ito, Gregory Tombline, Seyed Ali Biashad, Andrei Seluanov, Vera Gorbunova and Naoko Ohtani ()
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Masaki Takasugi: Graduate School of Medicine
Yoshiki Nonaka: Graduate School of Medicine
Kazuaki Takemura: Graduate School of Medicine
Yuya Yoshida: Graduate School of Medicine
Frank Stein: EMBL Heidelberg
Jennifer J. Schwarz: EMBL Heidelberg
Jun Adachi: Health and Nutrition
Junko Satoh: Kyoto University
Shinji Ito: Kyoto University
Gregory Tombline: University of Rochester
Seyed Ali Biashad: University of Rochester
Andrei Seluanov: University of Rochester
Vera Gorbunova: University of Rochester
Naoko Ohtani: Graduate School of Medicine

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract To what extent and how post-transcriptional dysregulation affects aging proteome remains unclear. Here, we provide proteomic data of whole-tissue lysates (WTL) and low-solubility protein-enriched fractions (LSF) of major tissues collected from mice of 6, 15, 24, and 30 months of age. Low-solubility proteins are preferentially affected by age and the analysis of LSF doubles the number of proteins identified to be differentially expressed with age. Simultaneous analysis of proteome and transcriptome using the same tissue homogenates reveals the features of age-related post-transcriptional dysregulation. Post-transcriptional dysregulation becomes evident especially after 24 months of age and age-related post-transcriptional dysregulation leads to accumulation of core matrisome proteins and reduction of mitochondrial membrane proteins in multiple tissues. Based on our in-depth proteomic data and sample-matched transcriptome data of adult, middle-aged, old, and geriatric mice, we construct the Mouse aging proteomic atlas ( https://aging-proteomics.info/ ), which provides a thorough and integrative view of age-related gene expression changes.

Date: 2024
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DOI: 10.1038/s41467-024-52845-x

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