Comparative Proteomic Quantification Reveals Novel Longevity Regulators
Proteomics is a powerful tool for profiling the protein landscape underlying cellular and physiological processes. Advances in mass spectrometry-based methods, such as tandem mass tags (TMT) isobaric labeling-based proteomics at both MS2 and MS3, label-free quantification (LFQ) with data-dependent acquisition (DDA) or data-independent acquisition (DIA)-based proteomics, and stable isotope labeling with amino acid (SILAC) spike-in-assisted proteomics, enable quantitative proteome comparisons across biological conditions. These five quantitative proteomic methods offer distinct advantages in coverage, throughput, and quantitative reproducibility. Here, we treated them as orthogonal approaches, retaining protein candidates with significant, consistent-direction changes supported across multiple independently instrumented methods to identify high-confidence protein-level changes associated with longevity. Insulin/insulin-like growth factor signaling (IIS) is a highly conserved longevity regulatory pathway from Caenorhabditis elegans to humans. By quantitatively profiling IIS mutants in C. elegans and performing genetic screening, we obtained a systems-view of proteomic changes linked to longevity and identified new longevity regulators. This systematic cross-method comparison also serves as a valuable resource for guiding the selection of quantitative proteomics approaches.
Authors
- Viruthika Vallanadu
- Jong Min Choi (ORCID: https://orcid.org/0000-0002-5282-7697)
- Ayse Sena Mutlu (ORCID: https://orcid.org/0000-0002-2849-7210)
- Yue Zhou (ORCID: https://orcid.org/0000-0002-4339-4519)
- Cuizhen Huang
- Xing Ma (ORCID: https://orcid.org/0000-0001-6914-0173)
- Lang Ding (ORCID: https://orcid.org/0000-0002-5365-9445)
- Kelly Ashley
- Scarlett Rose Pitts (ORCID: https://orcid.org/0009-0006-8046-6370)
- Hanfeng Lin
- Feng Jin
- Meng C. Wang
- Jin Wang
Institutions
- Howard Hughes Medical Institute (US)
- Baylor College of Medicine (US)
- Janelia Research Campus (US)
Publication Details
- Journal
- PROTEOMICS
- Published
- 2026-10-15
- DOI
- https://doi.org/10.1002/pmic.70195
- Primary Topic
- Genetics, Aging, and Longevity in Model Organisms
- Type
- article
- Field-Weighted Citation Impact
- 0.00