Skip to main content
Open Access Publications from the University of California

UC Riverside

UC Riverside Previously Published Works bannerUC Riverside

Bait Correlation Improves Interactor Identification by Tandem Mass Tag-Affinity Purification-Mass Spectrometry.

  • Author(s): Mei, Liangyong
  • Montoya, Maureen R
  • Quanrud, Guy M
  • Tran, Minh
  • Villa-Sharma, Athena
  • Huang, Ming
  • Genereux, Joseph C
  • et al.

The quantitative multiplexing capacity of isobaric tandem mass tags (TMT) has increased the throughput of affinity purification mass spectrometry (AP-MS) to characterize protein interaction networks of immunoprecipitated bait proteins. However, variable bait levels between replicates can convolute interactor identification. We compared the Student's t-test and Pearson's R correlation as methods to generate t-statistics and assessed the significance of interactors following TMT-AP-MS. Using a simple linear model of protein recovery in immunoprecipitates to simulate reporter ion ratio distributions, we found that correlation-derived t-statistics protect against bait variance while robustly controlling type I errors (false positives). We experimentally determined the performance of these two approaches for determining t-statistics under two experimental conditions: irreversible prey association to the Hsp40 mutant DNAJB8H31Q followed by stringent washing, and reversible association to 14-3-3ζ with gentle washing. Correlation-derived t-statistics performed at least as well as Student's t-statistics for each sample and with substantial improvement in performance for experiments with high bait-level variance. Deliberately varying bait levels over a large range fails to improve selectivity but does increase the robustness between runs. The use of correlation-derived t-statistics should improve identification of interactors using TMT-AP-MS. Data are available via ProteomeXchange with identifier PXD016613.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
Current View