Organelle proteomic profiling reveals lysosomal heterogeneity in association with longevity
Abstract
Lysosomes are active sites to integrate cellular metabolism and signal transduction. A collection of proteins associated with the lysosome mediate these metabolic and signaling functions. Both lysosomal metabolism and lysosomal signaling have been linked to longevity regulation; however, how lysosomes adjust their protein composition to accommodate this regulation remains unclear. Using deep proteomic profiling, we systemically profiled lysosome-associated proteins linked with four different longevity mechanisms. We discovered the lysosomal recruitment of AMPK and nucleoporin proteins and their requirements for longevity in response to increased lysosomal lipolysis. Through comparative proteomic analyses of lysosomes from different tissues and labeled with different markers, we further elucidated lysosomal heterogeneity across tissues as well as the increased enrichment of the Ragulator complex on Cystinosin positive lysosomes. Together, this work uncovers lysosomal proteome heterogeneity across multiple scales and provides resources for understanding the contribution of lysosomal protein dynamics to signal transduction, organelle crosstalk and organism longevity.
Data availability
The mass spectrometry data for protein identification have been deposited via the MASSIVE repository (MSV000090909) to the Proteome X change Consortium (http://proteomecentral.proteomexchange.org) with the dataset identifier PXD038865.Analysis code for Figure 6D, 6F and Figure 6-figure supplement 1 is included in the Supplementary code.
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Organelle proteomic profiling reveals lysosomal heterogeneity in association with longevityProteome Xchange Consortium, PXD038865.
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Meng C Wang
National Natural Science Foundation of China (32071146)
- Yong Yu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Kang Shen, Stanford University, United States
Version history
- Preprint posted: October 17, 2022 (view preprint)
- Received: November 28, 2022
- Accepted: January 18, 2024
- Accepted Manuscript published: January 19, 2024 (version 1)
- Version of Record published: February 19, 2024 (version 2)
Copyright
© 2024, Yu 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.
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