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  • P-III-0880

Deep Interactome Profiling MS (DIP-MS), a novel interaction proteomics method for the deconvolution of immunoprecipitated protein complexes

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Organisation of the Proteome (PPI)

Poster

Deep Interactome Profiling MS (DIP-MS), a novel interaction proteomics method for the deconvolution of immunoprecipitated protein complexes

Thema

  • Organisation of the Proteome (PPI)

Mitwirkende

Fabian Frommelt (Vienna / AT; Zurich / CH), Andrea Fossati (Zurich / CH; San Francisco, CA / US), Federico Uliana (Zurich / CH; Mainz / DE), Fabian Wendt (Zurich / CH), Peng Xue (Zurich / CH; Guang Zhou / CN), Moritz Heusel (Zurich / CH), Bernd Wollscheid (Zurich / CH), Ruedi Aebersold (Zurich / CH), Rodolfo Ciuffa (Zurich / CH), Matthias Gstaiger (Zurich / CH)

Abstract

Proteins organize into dynamic modules to carry out most cellular processes. Ever-advancing analytical capabilities to study modular proteome organization holds great promise to pinpoint molecular lesions driving disease phenotypes.

Affinity purification combined with LC-MS/MS is a powerful method to identify a protein"s set of direct and indirect interaction partners with high sensitivity, but cannot resolve the sum of purified proteins into instances of specific protein complexes within a single AP-MS experiment. We devised an integrated computational/wet lab method Deep Interactome Profiling by Mass Spectrometry (DIP-MS) which identifies distinct protein complexes from an AP sample at high sensitivity, This is accomplished by the integration of targeted affinity enrichment with blue native-PAGE separation, quantitative high-throughput DIA-MS and deep-learning-based signal processing.

96-well based MS-sample processing combined with high-throughput DIA-MS allows protein profiling from up to 70 BN-PAGE fractions within one day. In addition, we introduced PPIprophet for efficient data driven neural network based complex deconvolution from the acquired data.

We applied DIP-MS to probe the modular structure of the human prefoldin (PFD) family of complexes, resolving distinct PFD holo- and sub-complex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated.

When benchmarked against AP-MS and SEC-MS, we could demonstrate the superior resolution and coverage of our approach. DIP-MS identified a novel low abundant PDRG1 based complex isoform of canonical PFD, which we validated by in-silico structural modelling and reciprocal AP-MS. Finally, we found that DIP-MS was sensitive enough to identify folding substrate for the complex-complex interactions of CCT/TRiC-PFD and the PAQosome complex, a super complex involved in the assembly of protein complexes. The results were validated by orthogonal DIP-MS experiments, literature derived and experimental AP-MS data. The exceptional sensitivity, resolution, and speed of DIP-MS promise to significantly advance our ability to link specific proteome organizational states to phenotypic outcomes in healthy and diseased conditions.

Frommelt F, Fossati A, Uliana F, Wendt F, Xue P, Heusel M, Wollscheid B, Aebersold R, Ciuffa R, Gstaiger M. DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes. Nat Methods. 2024 Apr;21(4):635-647. doi: 10.1038/s41592-024-02211-y. Epub 2024 Mar 26. PMID: 38532014; PMCID: PMC11009110.

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