Preprint · CC-BY
via OpenAlex
Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse Caenorhabditis nematodes
Stephen A. Banse, Christine A. Sedore, Anna L Coleman-Hulbert, Erik Johnson, Brian Onken, David Hall, Erik Segerdell, E Grace Jackson, Yuhua Song, Haley C Osman, Jian Xue, Elena Battistoni, Suhzen Guo, Anna Foulger, Madhuri Achanta
eLife · 2024 · ▲ 1 citations
Deregulated nutrient-sensing
Altered intercellular communication
Senolytics
Rapamycin / mTOR inhibition
C. elegans
Abstract
Discovery of new compounds that ameliorate the negative health impacts of aging promises to be of tremendous benefit across a number of age-based comorbidities. One method to prioritize a testable subset of the nearly infinite universe of potential compounds is to use computational prediction of their likely anti-aging capacity. Here, we present a survey of longevity effects for 16 compounds suggested by a previously published computational prediction set, capitalizing upon the comprehensive, multi-species approach utilized by the Caenorhabditis Intervention Testing Program. While 11 compounds (aldosterone, arecoline, bortezomib, dasatinib, decitabine, dexamethasone, erlotinib, everolimus, gefitinib, temsirolimus, and thalidomide) either had no effect on median lifespan or were toxic, 5 compounds (all-trans retinoic acid, berberine, fisetin, propranolol, and ritonavir) extended lifespan in Caenorhabditis elegans . These computer predictions yield a remarkable positive hit rate of 30%. Deeper genetic characterization of the longevity effects of one of the most efficacious compounds, the endogenous signaling ligand all-trans retinoic acid (atRA, designated tretinoin in medical products), demonstrated a requirement for the regulatory kinases AKT-1 and AKT-2. While the canonical Akt-target FOXO/DAF-16 was largely dispensable, other conserved Akt-targets (Nrf2/SKN-1 and HSF1/HSF-1), as well as the conserved catalytic subunit of AMPK AAK-2, were all necessary for longevity extension by atRA. Our results highlight the potential of combining computational prediction of longevity interventions with the power of nematode functional genetics and underscore that the manipulation of a conserved metabolic regulatory circuit by co-opting endogenous signaling molecules is a powerful approach for discovering aging interventions.
◌ CITATION ONLY
Full text is not openly licensed for redistribution here. Read it at the source:
Provenance
- Source
- OpenAlex
- DOI
- 10.7554/elife.104375
- Canonical
- link ↗
- Fetched
- 2026-10-12 MST
Cite this
APA
Banse, S.A., Sedore, C.A., Coleman-Hulbert, A.L., Johnson, E., Onken, B., Hall, D., Segerdell, E., Jackson, E.G., Song, Y., Osman, H.C., Xue, J., Battistoni, E., Guo, S., Foulger, A., Achanta, M., Sheikh, M., Fitzgibbon, T., Willis, J.H., Woodruff, G., & Driscoll, M. (2024). Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse Caenorhabditis nematodes. <em>eLife</em>. https://doi.org/10.7554/elife.104375
Vancouver
Banse SA, Sedore CA, Coleman-Hulbert AL, Johnson E, Onken B, Hall D, et al. Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse Caenorhabditis nematodes. eLife. 2024. doi:10.7554/elife.104375.
BibTeX
@unpublished{stephen2024Comput,
title = {Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse Caenorhabditis nematodes},
author = {Stephen A. Banse and Christine A. Sedore and Anna L Coleman-Hulbert and Erik Johnson and Brian Onken and David Hall and Erik Segerdell and E Grace Jackson and Yuhua Song and Haley C Osman and Jian Xue and Elena Battistoni and Suhzen Guo and Anna Foulger and Madhuri Achanta and Mustafa Sheikh and Theresa Fitzgibbon and John H. Willis and Gavin Woodruff and Monica Driscoll and Gordon J. Lithgow and Patrick C. Phillips},
journal = {eLife},
year = {2024},
doi = {10.7554/elife.104375},
}
Research neighborhood
References, citing works, and semantically nearest findings. Click a node to open it.
Related findings
eLife 2025
Open access · OA
Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse <i>Caenorhabditis</i> nematodes.
eLife 2025
Open access · CC-BY
Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically diverse Caenorhabditis nematodes
2024
Open access · CC-BY
eLife Assessment: Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically-diverse Caenorhabditis nematodes
PLoS Genetics 2011
Open access · CC-BY
The Evolutionarily Conserved Longevity Determinants HCF-1 and SIR-2.1/SIRT1 Collaborate to Regulate DAF-16/FOXO
bioRxiv (Cold Spring Harbor Laboratory) 2021
Preprint · CC-BY
Antioxidants green tea extract and nordihydroguaiaretic acid confer species and strain specific lifespan and health effects in Caenorhabditis nematodes
GeroScience 2023
Open access · CC-BY