A modified TALEN-based system for robust generation of knock-out human pluripotent stem cell lines and disease models
1 Chemical Genomics Centre of the Max Planck Society, Dortmund, Germany
2 Human Stem Cell Pluripotency Group, Max Planck Institute for Molecular Biomedicine, Münster, Germany
3 Institute of Experimental Pathology (ZMBE), University of Münster, 48149 Münster, Germany
4 Interdisciplinary Centre for Clinical Research (IZKF), University of Münster, 48149 Münster, Germany
BMC Genomics 2013, 14:773 doi:10.1186/1471-2164-14-773Published: 9 November 2013
Transcription activator-like effector nucleases (TALENs) have emerged as a tool for enabling targeted gene editing and disruption in difficult systems, such as human pluripotent stem cells (hPSCs). The modular architecture of TAL effectors theoretically enables targeting of any genomic locus and several cloning systems for custom TALEN assembly have recently been established. However, there is a lack of versatile TALEN expression systems applicable to hPSCs.
Here, we extend an existing TALE assembly system by a dual set of expression vectors for efficient application of TALEN technology in hPSCs. This is characterized by improved TALEN architecture as well as antibiotic resistance and fluorescent reporter cassettes, thus enabling enrichment for transfected cells.
Improved functionality of the combined system was demonstrated by targeted disruption of the HPRT1 gene to create isogenic disease models of Lesch-Nyhan-Syndrome. Using female hPSCs, homozygous disruption of HPRT1 occurred at efficiencies of up to 15%. Differentiating isogenic knock-out cells both into central nervous system (CNS) as well as into sensory-like neurons recapitulated previously described phenotypes based on patient-specific induced PSCs and extended these findings to non-CNS neurons, respectively.
The combined vector system allows for flexible and affordable generation of knock-out hPSCs lines, thus enabling investigation of developmental processes as well as the generation of isogenic disease models without the need for patient material.