Comparative proteomic quantification reveals novel longevity regulators

Ding, L., Lin, H., Huang, C., Vallanadu, V., Ashley, K., Pitts, S. R., Mutlu, A. S., Zhou, Y., Ma, X., Choi, J. M., Jin, F., Wang, J., Wang, M. C.

Janelia Research Campus, Howard Hughes Medical Institute · biorxiv

Paper

Abstract

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.

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Research summary

The paper claims that a systematic cross-method comparison of quantitative proteomics (TMT, LFQ, SILAC) in C. elegans IIS mutants identifies high-confidence, novel protein-level changes and regulators associated with longevity. This is relevant because it directly investigates the molecular mechanisms of lifespan extension in a model organism, providing a systems-level view of the insulin/insulin-like growth factor signaling pathway, although the impact is limited by the use of a standard model organism and the incremental nature of the methodological comparison.

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