ArticleJournal of proteome research2012
Identifying novel protein complexes in cancer cells using epitope-tagging of endogenous human genes and affinity-purification mass spectrometry.
Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 22 citations in OpenAlex.
- Review
- Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms.Nature methods · 2021Review
- Nuclear receptor crosstalk - defining the mechanisms for therapeutic innovation.Nature reviews. Endocrinology · 2020Review
- Identification of Endogenous Adenomatous Polyposis Coli Interaction Partners and β-Catenin-Independent Targets by Proteomics.Molecular cancer research : MCR · 2019Article
- Multiproteomic and Transcriptomic Analysis of Oncogenic β-Catenin Molecular Networks.Journal of proteome research · 2018Article
- Strategy for Identification of Phosphorylation Levels of Low Abundance Proteins in Vivo for Which Antibodies Are not Available.Journal of cardiovascular development and disease · 2017Article
- TALEN-Mediated FLAG-Tagging of Endogenous Histone Methyltransferase DOT1L.Advances in bioscience and biotechnology (Print) · 2017Article
- Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.International journal of molecular sciences · 2016Review
- Studying epigenetic complexes and their inhibitors with the proteomics toolbox.Clinical epigenetics · 2016Review
- A Protein Interaction between β-Catenin and Dnmt1 Regulates Wnt Signaling and DNA Methylation in Colorectal Cancer Cells.Molecular cancer research : MCR · 2015Article
- How do oncoprotein mutations rewire protein-protein interaction networks?Expert review of proteomics · 2015Review
- The Identification of Novel Protein-Protein Interactions in Liver that Affect Glucagon Receptor Activity.PloS one · 2015Article
- Integrated analysis of the Wnt responsive proteome in human cells reveals diverse and cell-type specific networks.Molecular bioSystems · 2014Article
- Characterization of molecules binding to the 70K N-terminal region of fibronectin by IFAST purification coupled with mass spectrometry.Journal of proteome research · 2013Article
- Protein-protein interaction networks: probing disease mechanisms using model systems.Genome medicine · 2013Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Affinity-purification mass spectrometry (AP-MS) is the preeminent technique for identification of eukaryotic protein complexes in vivo. AP-MS workflows typically express epitope-tagged bait proteins, immunopurify, and then identify associated protein complexes using mass spectrometry. However, challenges of existing strategies include the construction of expression vectors for large open reading frames and the possibility that overexpression of bait proteins may result in expression of nonphysiological levels of the bait protein with concomitant perturbation of endogenous protein complexes. To address these issues, we use human cell lines with epitope-tagged endogenous genes as AP-MS substrates to develop a platform that we call "knock-in AP-MS", thereby avoiding the challenges of expression vector construction and ensuring that expression of tagged proteins is driven by endogenous regulatory mechanisms. Using three different bait genes (MRE11A, DNMT1 and APC), we show that cell lines expressing epitope-tagged endogenous genes make good substrates for sensitive and reproducible identification of protein interactions using AP-MS. In particular, we identify novel interactors of the important oncoprotein Adenomatous Polyposis Coli (APC), including an interaction with Flightless-1 homologue (FLII) that is enriched in nuclear fractions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.