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Lipid unsaturation promotes BAX and BAK pore activity during apoptosis

Author

Listed:
  • Shashank Dadsena

    (University of Cologne)

  • Rodrigo Cuevas Arenas

    (Utrecht University)

  • Gonçalo Vieira

    (Universidade Nova de Lisboa)

  • Susanne Brodesser

    (University of Cologne)

  • Manuel N. Melo

    (Universidade Nova de Lisboa)

  • Ana J. García-Sáez

    (University of Cologne
    Max Planck Institute of Biophysics)

Abstract

BAX and BAK are proapoptotic members of the BCL2 family that directly mediate mitochondrial outer membrane permeabilition (MOMP), a central step in apoptosis execution. However, the molecular architecture of the mitochondrial apoptotic pore remains a key open question and especially little is known about the contribution of lipids to MOMP. By performing a comparative lipidomics analysis of the proximal membrane environment of BAK isolated in lipid nanodiscs, we find a significant enrichment of unsaturated species nearby BAK and BAX in apoptotic conditions. We then demonstrate that unsaturated lipids promote BAX pore activity in model membranes, isolated mitochondria and cellular systems, which is further supported by molecular dynamics simulations. Accordingly, the fatty acid desaturase FADS2 not only enhances apoptosis sensitivity, but also the activation of the cGAS/STING pathway downstream mtDNA release. The correlation of FADS2 levels with the sensitization to apoptosis of different lung and kidney cancer cell lines by co-treatment with unsaturated fatty acids supports the relevance of our findings. Altogether, our work provides an insight on how local lipid environment affects BAX and BAK function during apoptosis.

Suggested Citation

  • Shashank Dadsena & Rodrigo Cuevas Arenas & Gonçalo Vieira & Susanne Brodesser & Manuel N. Melo & Ana J. García-Sáez, 2024. "Lipid unsaturation promotes BAX and BAK pore activity during apoptosis," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49067-6
    DOI: 10.1038/s41467-024-49067-6
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    1. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    2. Kim Vriens & Stefan Christen & Sweta Parik & Dorien Broekaert & Kazuaki Yoshinaga & Ali Talebi & Jonas Dehairs & Carmen Escalona-Noguero & Roberta Schmieder & Thomas Cornfield & Catriona Charlton & La, 2019. "Evidence for an alternative fatty acid desaturation pathway increasing cancer plasticity," Nature, Nature, vol. 566(7744), pages 403-406, February.
    3. Mostefa Fodil & Vincent Blanckaert & Lionel Ulmann & Virginie Mimouni & Benoît Chénais, 2022. "Contribution of n-3 Long-Chain Polyunsaturated Fatty Acids to the Prevention of Breast Cancer Risk Factors," IJERPH, MDPI, vol. 19(13), pages 1-19, June.
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