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Efficient Culturing and Genetic Manipulation of Human Pluripotent Stem Cells

Overview of attention for article published in PLOS ONE, December 2011
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Title
Efficient Culturing and Genetic Manipulation of Human Pluripotent Stem Cells
Published in
PLOS ONE, December 2011
DOI 10.1371/journal.pone.0027495
Pubmed ID
Authors

Robert T. Schinzel, Tim Ahfeldt, Frank H. Lau, Youn-Kyoung Lee, Alicia Cowley, Tony Shen, Derek Peters, David H. Lum, Chad A. Cowan

Abstract

Human pluripotent stem cells (hPSC) hold great promise as models for understanding disease and as a source of cells for transplantation therapies. However, the lack of simple, robust and efficient culture methods remains a significant obstacle for realizing the utility of hPSCs. Here we describe a platform for the culture of hPSCs that 1) allows for dissociation and replating of single cells, 2) significantly increases viability and replating efficiency, 3) improves freeze/thaw viability 4) improves cloning efficiency and 5) colony size variation. When combined with standard methodologies for genetic manipulation, we found that the enhanced culture platform allowed for lentiviral transduction rates of up to 95% and electroporation efficiencies of up to 25%, with a significant increase in the total number of antibiotic-selected colonies for screening for homologous recombination. We further demonstrated the utility of the enhanced culture platform by successfully targeting the ISL1 locus. We conclude that many of the difficulties associated with culturing and genetic manipulation of hPSCs can be addressed with optimized culture conditions, and we suggest that the use of the enhanced culture platform could greatly improve the ease of handling and general utility of hPSCs.

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Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Mexico 1 2%
Romania 1 2%
Unknown 61 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 18%
Student > Ph. D. Student 11 17%
Student > Bachelor 8 12%
Other 7 11%
Professor 5 8%
Other 13 20%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 37%
Biochemistry, Genetics and Molecular Biology 15 23%
Medicine and Dentistry 10 15%
Chemical Engineering 2 3%
Computer Science 1 2%
Other 5 8%
Unknown 8 12%