ArticleJournal of visualized experiments : JoVE2015
Genome-wide protein-protein interaction screening by protein-fragment complementation assay (PCA) in living cells.
Article in Journal of visualized experiments : JoVE, 2015. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed, 27 citations in OpenAlex.
- Uncovering the molecular basis of kinase activity and substrate recognition with phospho-PCA.bioRxiv : the preprint server for biology · 2025Article
- Article
- Dissection of the role of a Src homology 3 domain in the evolution of binding preference of paralogous proteins.Genetics · 2024Article
- Parallel Nonfunctionalization of CK1δ/ε Kinase Ohnologs Following a Whole-Genome Duplication Event.Molecular biology and evolution · 2023Article
- Parallel nonfunctionalization of CK1δ/ε kinase ohnologs following a whole-genome duplication event.bioRxiv : the preprint server for biology · 2023Article
- Intra-Frontiers in genetics · 2023Article
- Barcode fusion genetics-protein-fragment complementation assay (BFG-PCA): tools and resources that expand the potential for binary protein interaction discovery.Nucleic acids research · 2022Article
- Quantification of Protein Expression by Proximity Ligation Assay in the Nonhuman Primate in Response to Estrogen.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Protein context shapes the specificity of SH3 domain-mediated interactions in vivo.Nature communications · 2021Article
- The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs.eLife · 2019Article
- Article
- Profiling theeLife · 2019Article
- Mechanisms of PTPσ-Mediated Presynaptic Differentiation.Frontiers in synaptic neuroscience · 2019Article
- Extended Linkers Improve the Detection of Protein-protein Interactions (PPIs) by Dihydrofolate Reductase Protein-fragment Complementation Assay (DHFR PCA) in Living Cells.Molecular & cellular proteomics : MCP · 2018Article
- Speciation driven by hybridization and chromosomal plasticity in a wild yeast.Nature microbiology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Proteins are the building blocks, effectors and signal mediators of cellular processes. A protein's function, regulation and localization often depend on its interactions with other proteins. Here, we describe a protocol for the yeast protein-fragment complementation assay (PCA), a powerful method to detect direct and proximal associations between proteins in living cells. The interaction between two proteins, each fused to a dihydrofolate reductase (DHFR) protein fragment, translates into growth of yeast strains in presence of the drug methotrexate (MTX). Differential fitness, resulting from different amounts of reconstituted DHFR enzyme, can be quantified on high-density colony arrays, allowing to differentiate interacting from non-interacting bait-prey pairs. The high-throughput protocol presented here is performed using a robotic platform that parallelizes mating of bait and prey strains carrying complementary DHFR-fragment fusion proteins and the survival assay on MTX. This protocol allows to systematically test for thousands of protein-protein interactions (PPIs) involving bait proteins of interest and offers several advantages over other PPI detection assays, including the study of proteins expressed from their endogenous promoters without the need for modifying protein localization and for the assembly of complex reporter constructs.
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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.