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Denaturing mass photometry for rapid optimization of chemical protein-protein cross-linking reactions

Author

Listed:
  • Hugo Gizardin-Fredon

    (CNRS
    Infrastructure Nationale de Protéomique ProFI – FR2048)

  • Paulo E. Santo

    (Apartado 12, 2781-901
    Universidade Nova de Lisboa, Av. da República, 2780-157)

  • Marie-Eve Chagot

    (Université de Lorraine)

  • Bruno Charpentier

    (Université de Lorraine)

  • Tiago M. Bandeiras

    (Apartado 12, 2781-901
    Universidade Nova de Lisboa, Av. da República, 2780-157)

  • Xavier Manival

    (Université de Lorraine)

  • Oscar Hernandez-Alba

    (CNRS
    Infrastructure Nationale de Protéomique ProFI – FR2048)

  • Sarah Cianférani

    (CNRS
    Infrastructure Nationale de Protéomique ProFI – FR2048)

Abstract

Chemical cross-linking reactions (XL) are an important strategy for studying protein-protein interactions (PPIs), including low abundant sub-complexes, in structural biology. However, choosing XL reagents and conditions is laborious and mostly limited to analysis of protein assemblies that can be resolved using SDS-PAGE. To overcome these limitations, we develop here a denaturing mass photometry (dMP) method for fast, reliable and user-friendly optimization and monitoring of chemical XL reactions. The dMP is a robust 2-step protocol that ensures 95% of irreversible denaturation within only 5 min. We show that dMP provides accurate mass identification across a broad mass range (30 kDa–5 MDa) along with direct label-free relative quantification of all coexisting XL species (sub-complexes and aggregates). We compare dMP with SDS-PAGE and observe that, unlike the benchmark, dMP is time-efficient (3 min/triplicate), requires significantly less material (20–100×) and affords single molecule sensitivity. To illustrate its utility for routine structural biology applications, we show that dMP affords screening of 20 XL conditions in 1 h, accurately identifying and quantifying all coexisting species. Taken together, we anticipate that dMP will have an impact on ability to structurally characterize more PPIs and macromolecular assemblies, expected final complexes but also sub-complexes that form en route.

Suggested Citation

  • Hugo Gizardin-Fredon & Paulo E. Santo & Marie-Eve Chagot & Bruno Charpentier & Tiago M. Bandeiras & Xavier Manival & Oscar Hernandez-Alba & Sarah Cianférani, 2024. "Denaturing mass photometry for rapid optimization of chemical protein-protein cross-linking reactions," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47732-4
    DOI: 10.1038/s41467-024-47732-4
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    References listed on IDEAS

    as
    1. Adar Sonn-Segev & Katarina Belacic & Tatyana Bodrug & Gavin Young & Ryan T. VanderLinden & Brenda A. Schulman & Johannes Schimpf & Thorsten Friedrich & Phat Vinh Dip & Thomas U. Schwartz & Benedikt Ba, 2020. "Quantifying the heterogeneity of macromolecular machines by mass photometry," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Rebecca Beveridge & Johannes Stadlmann & Josef M. Penninger & Karl Mechtler, 2020. "A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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