Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreThe development of affinity purification technologies together with mass spectrometric analyses of the purified protein mixtures (AP-MS) has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we have investigated whether ectopic expression of an affinity tagged transcription factor as bait in AP-MS experiments perturbs gene expression in cells resulting in false positive identification of bait associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA-Seq, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then copurify non-specifically and be misidentified as bait associated proteins. Therefore typical controls should be sufficient and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFB1, NFB2, Rel, RelB, IB, IB and IB). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFB family transcription factors. The work here therefore provides a conceptual and experimental framework for analyzing transcription faction protein interactions. SOURCE: Chris,W,Seidel (seidel@phageT4.org) - Seidel Stowers Institute
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team