Optimized TMT-Based Quantitative Cross-Linking MassSpectrometry Strategy for Large-Scale Interactomic Studies br

Cross-linking mass spectrometry (XL-MS) is a powerful method for theinvestigation of protein-protein interactions (PPI) from highly complex samples. XL-MScombined with tandem mass tag (TMT) labeling holds the promise of large-scale PPIquantification. However, a robust and efficient TMT-based XL-MS quantificationmethod has not yet been established due to the lack of a benchmarking dataset andthorough evaluation of various MS parameters. To tackle these limitations, we generate atwo-interactome dataset by spiking in TMT-labeled cross-linkedEscherichia colilysateinto TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Usingthis benchmarking dataset, we assess the efficacy of cross-link identification and accuracyof cross-link quantification using different MS acquisition strategies. For identification,we compare various MS2- and MS3-based XL-MS methods, and optimize stepped higherenergy collisional dissociation (HCD) energies for TMT-labeled cross-links. Weobserved a need for notably higher fragmentation energies compared to unlabeledcross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3-, and synchronous precursorselection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vastnumber of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexedquantitative PPI characterization from complex biological systems.