An efficient and scalable pipeline for epitope tagging in mammalian stem cells using Cas9 ribonucleoprotein

Pooran Singh Dewari, Benjamin Southgate, Katrina Mccarten, German Monogarov, Eoghan O'Duibhir, Niall Quinn, Ashley Tyrer, Marie-Christin Leitner, Colin Plumb, Maria Kalantzaki, Carla Blin, Rebecca Finch, Raul Bardini Bressan, Gillian Morrison, Ashley M Jacobi, Mark A Behlke, Alex von Kriegsheim, Simon Tomlinson, Jeroen Krijgsveld, Steven M Pollard

Research output: Contribution to journalArticlepeer-review

Abstract

CRISPR/Cas9 can be used for precise genetic knock-in of epitope tags into endogenous genes, simplifying experimental analysis of protein function. However, Cas9-assisted epitope tagging in primary mammalian cell cultures is often inefficient and reliant on plasmid-based selection strategies. Here we demonstrate improved knock-in efficiencies of diverse tags (V5, 3XFLAG, Myc, HA) using co-delivery of Cas9 protein pre-complexed with two-part synthetic modified RNAs (annealed crRNA:tracrRNA) and single-stranded oligodeoxynucleotide (ssODN) repair templates. Knock-in efficiencies of ~5-30%, were achieved without selection in embryonic stem (ES) cells, neural stem (NS) cells, and brain tumour-derived stem cells. Biallelic-tagged clonal lines were readily derived and used to define Olig2 chromatin-bound interacting partners. Using our novel web-based design tool, we established a 96-well format pipeline that enabled V5-tagging of 60 different transcription factors. This efficient, selection-free and scalable epitope tagging pipeline enables systematic surveys of protein expression levels, subcellular localization, and interactors across diverse mammalian stem cells.

Original languageEnglish
JournaleLIFE
Volume7
Early online date11 Apr 2018
DOIs
Publication statusE-pub ahead of print - 11 Apr 2018

Keywords

  • Journal Article

Fingerprint

Dive into the research topics of 'An efficient and scalable pipeline for epitope tagging in mammalian stem cells using Cas9 ribonucleoprotein'. Together they form a unique fingerprint.

Cite this