Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes. While proteomics offers insights into aging mechanisms, prior studies are limited in proteome coverage and lifespan range. To address this, we integrate the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of cortex, hippocampus, striatum and kidney in the C57BL/6JN mice, quantifying 8,954 to 9,376 proteins per tissue (12,749 total). Samples spanned both sexes and three age groups (3, 12, and 20 months), representing early to late adulthood. To improve TMT quantitation accuracy, we develop a peptide-spectrum match-based filtering strategy that leverages resolution and signal-to-noise thresholds. Our analysis uncovers distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney and primarily age-related changes in brain tissues. We also identify both linear and non-linear proteomic trajectories with age, revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlights further divergent age-related trajectories, particularly in synaptic proteins. This study provides a robust data analysis workflow for Orbitrap Astral-based TMT analysis and expands the proteomic understanding of aging across tissues, ages, and sexes.

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Publication Details

Journal
Nature Communications
Published
2025-05-22
DOI
https://doi.org/10.1038/s41467-025-60022-x
Citations
4
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
3.03

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article

Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration

Dina L. Bai, Gregory R. Keele, João A. Paulo, Erin D. Jeffery et al.
4 citations
Nature Communications
Advanced Proteomics Techniques and Applications
3.03
article

Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration

Dina L. Bai, Gregory R. Keele, João A. Paulo, Erin D. Jeffery, Zichen Gao, Steven P. Gygi, Tian Zhang, Yue Dou, Xiao Tian, Seth P. Kodikara, Erik Hultenius
article en
4 citations

Abstract

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes. While proteomics offers insights into aging mechanisms, prior studies are limited in proteome coverage and lifespan range. To address this, we integrate the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of cortex, hippocampus, striatum and kidney in the C57BL/6JN mice, quantifying 8,954 to 9,376 proteins per tissue (12,749 total). Samples spanned both sexes and three age groups (3, 12, and 20 months), representing early to late adulthood. To improve TMT quantitation accuracy, we develop a peptide-spectrum match-based filtering strategy that leverages resolution and signal-to-noise thresholds. Our analysis uncovers distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney and primarily age-related changes in brain tissues. We also identify both linear and non-linear proteomic trajectories with age, revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlights further divergent age-related trajectories, particularly in synaptic proteins. This study provides a robust data analysis workflow for Orbitrap Astral-based TMT analysis and expands the proteomic understanding of aging across tissues, ages, and sexes.

Nature CommunicationsVol. 16(1)
Harvard University (US), RTI International (US), Sanford Burnham Prebys Medical Discovery Institute (US), Discovery Institute (US), University of Virginia (US)
National Institutes of Health, National Institute on Aging, National Cancer Institute, National Institute of General Medical Sciences
Openalex Percentile: Top 9%
Advanced Proteomics Techniques and Applications
3.03
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