A TALEN Genome-Editing System for Generating Human Stem Cell-Based Disease Models

Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
Cell stem cell (Impact Factor: 22.15). 12/2012; 12(2). DOI: 10.1016/j.stem.2012.11.011
Source: PubMed

ABSTRACT Transcription activator-like effector nucleases (TALENs) are a new class of engineered nucleases that are easier to design to cleave at desired sites in a genome than previous types of nucleases. We report here the use of TALENs to rapidly and efficiently generate mutant alleles of 15 genes in cultured somatic cells or human pluripotent stem cells, the latter for which we differentiated both the targeted lines and isogenic control lines into various metabolic cell types. We demonstrate cell-autonomous phenotypes directly linked to disease-dyslipidemia, insulin resistance, hypoglycemia, lipodystrophy, motor-neuron death, and hepatitis C infection. We found little evidence of TALEN off-target effects, but each clonal line nevertheless harbors a significant number of unique mutations. Given the speed and ease with which we were able to derive and characterize these cell lines, we anticipate TALEN-mediated genome editing of human cells becoming a mainstay for the investigation of human biology and disease.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The technology to convert adult human non-neural cells into neural lineages, through induced pluripotent stem cells (iPSCs), somatic cell nuclear transfer (SCNT), and direct lineage conversion or transdifferentiation has progressed tremendously in recent years. Reprogramming based approaches aimed at manipulating cellular identity have enormous potential for disease modeling, high throughput drug screening, cell therapy and personalized medicine. Human iPSC- based cellular disease models have provided proof-of-principle evidence of the validity of this system. However, several challenges remain before patient specific neurons produced by reprogramming can provide reliable insights into disease mechanisms or be applied efficiently to drug discovery and transplantation therapy. This review will first discuss limitations of currently available reprogramming-based methods in faithfully and reproducibly recapitulating disease pathology. Specifically, we will address issues such as culture heterogeneity, interline and inter-individual variability, and limitations of two dimensional differentiation paradigms. Second, we will assess recent progress and the future prospects of reprogramming-based neurologic disease modeling. This includes three dimensional disease modeling, advances in reprogramming technology, pre-screening of human iPSCs, creating isogenic disease models using gene editing, and in vivo reprogramming.
    Stem Cells and Development 03/2015; 24(11). DOI:10.1089/scd.2015.0044 · 4.20 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The rapid development of programmable site-specific endonucleases has led to a dramatic increase in genome engineering activities for research and therapeutic purposes. Specific loci of interest in the genomes of a wide range of organisms including mammals can now be modified using zinc-finger nucleases, transcription activator-like effectornucleases, and CRISPR-associated Cas9 endonucleases in a site-specific manner, in some cases requiring relatively modest effort for endonuclease design, construction, and application. While these technologies have made genome engineering widely accessible, the ability of programmable nucleases to cleave off-target sequences can limit their applicability and raise concerns about therapeutic safety. In this chapter, we review methods to evaluate and improve the DNA cleavage activity of programmable site-specific endonucleases and describe a procedure for a comprehensive off-target profiling method based on the in vitro selection of very large (~10(12)-membered) libraries of potential nuclease substrates.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The value of induced pluripotent stem cells (iPSCs) within regenerative medicine is contingent on predictable and consistent iPSC differentiation. However, residual influence of the somatic origin or reprogramming technique may variegate differentiation propensity and confound comparative genotype/phenotype analyses. The objective of this study was to define quality control measures to select iPSC clones that minimize the influence of somatic origin on differentiation propensity independent of the reprogramming strategy. Over 60 murine iPSC lines were derived from different fibroblast origins (embryonic, cardiac, tail tip) via lentiviral integration and doxycycline-induced transgene expression. Despite apparent equivalency according to established iPSC histologic and cytomorphologic criteria, clustering of clonal variability in pluripotency-related gene expression identified transcriptional outliers that highlighted cell lines with unpredictable cardiogenic propensity. Following selection according to a standardized gene expression profile calibrated by embryonic stem cells, the influence of somatic origin on iPSC methylation and transcriptional patterns was negated. Furthermore, doxycycline-induced iPSCs consistently demonstrated earlier differentiation than lentiviral-reprogrammed lines using contractile cardiac tissue as a measure of functional differentiation. Moreover, delayed cardiac differentiation was predominately associated with up-regulation in pluripotency-related gene expression upon differentiation. Starting from a standardized pool of iPSCs, relative expression levels of two pluripotency genes, Oct4 and Zfp42, statistically correlated with enhanced cardiogenicity independent of somatic origin or reprogramming strategy (R2=0.85). These studies demonstrate that predictable iPSC differentiation is independent of somatic origin with standardized gene expression selection criteria, while the residual impact of reprogramming strategy greatly influences predictable output of tissue-specification required for comparative genotype/phenotype analyses. Stem Cells 2014
    Stem Cells 09/2014; 32(9). DOI:10.1002/stem.1734 · 7.70 Impact Factor