Technological advances allow us to continuously increase the depth of our transcriptome and proteome analyses. Our lab aims to use the most state-of-the-art approaches to provide answers to the biological questions we are focusing on.
Individual proteins often function as part of a protein complex. The identification of interacting proteins is therefore vital to understand the biological role and function of the studied protein. Over the past few years, we have been using IP-MS/MS technology for the in vivo identification of nuclear, cytoplasmic, and membrane-associated protein complexes from plant tissues. By performing quantitative mass spectrometry measurements on biological triplicates, relative abundance of proteins in GFP-tagged complexes compared to background controls can be statistically evaluated to identify high-confidence interactors.
A detailed protocol can be found following this link or is available upon request: Wendrich et al., (2017) Methods in Molecular Biology - PMID:27864765.
Figure: Example of a Volcano plot showing all identified proteins after filtering and statistical analysis of an IP-MS/MS experiment, with their corresponding protein abundance ratios over the T-test p-value. Depicted in red are proteins that are significantly different from the control, with the bait and GFP among the top hit list. Adapted from Wendrich et al., (2017) Methods in Molecular Biology - PMID:27864765.
Published manuscripts describing and using this technology:
- Bontinck et al., 2018. Frontiers in Plant Sciences. PMID: 29868093
- Andrés-Colás et al., (2017). PNAS. PMID: 28761003
- Muñoz A et al., (2017). Plant Cell. PMID: 28223441
- Wendrich JR et al., (2017) Methods in Molecular Biology. PMID: 27864765
- De Rybel B et al., (2013). Developmental Cell. PMID: 23415953