High-density cell arrays for genome-scale phenotypic screening
Due to high associated costs and considerable time investments of cell-based screening, there is a strong demand for new technologies that enable preclinical development and tests of diverse biologicals in a cost-saving and time-efficient manner. For those reasons we developed the high-density cell...
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| Hauptverfasser: | , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
January 25, 2019
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| In: |
SLAS discovery
Year: 2019, Jahrgang: 24, Heft: 3, Pages: 274-283 |
| ISSN: | 2472-5560 |
| DOI: | 10.1177/2472555218818757 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1177/2472555218818757 Verlag, Volltext: https://journals.sagepub.com/doi/10.1177/2472555218818757 
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| Verfasserangaben: | Vytaute Starkuviene, Stefan M. Kallenberger, Nina Beil, Tautvydas Lisauskas, Bastian So-Song Schumacher, Ruben Bulkescher, Piotr Wajda, Manuel Gunkel, Jürgen Beneke, and Holger Erfle |
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| 520 | |a Due to high associated costs and considerable time investments of cell-based screening, there is a strong demand for new technologies that enable preclinical development and tests of diverse biologicals in a cost-saving and time-efficient manner. For those reasons we developed the high-density cell array (HD-CA) platform, which miniaturizes cell-based screening in the form of preprinted and ready-to-run screening arrays. With the HD-CA technology, up to 24,576 samples can be tested in a single experiment, thereby saving costs and time for microscopy-based screening by 75%. Experiments on the scale of the entire human genome can be addressed in a real parallel manner, with screening campaigns becoming more comfortable and devoid of robotics infrastructure on the user side. The high degree of miniaturization enables working with expensive reagents and rare and difficult-to-obtain cell lines. We have also optimized an automated imaging procedure for HD-CA and demonstrate the applicability of HD-CA to CRISPR-Cas9- and RNAi-mediated phenotypic assessment of the gene function. | ||
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