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High-throughput and combinatorial gene expression on a chip for metabolism-induced toxicology screening

Author

Listed:
  • Seok Joon Kwon

    (Rensselaer Polytechnic Institute)

  • Dong Woo Lee

    (Samsung Electro-Mechanics Co, Central R & D Institute)

  • Dhiral A. Shah

    (Rensselaer Polytechnic Institute)

  • Bosung Ku

    (Samsung Electro-Mechanics Co, Central R & D Institute)

  • Sang Youl Jeon

    (Samsung Electro-Mechanics Co, Central R & D Institute)

  • Kusum Solanki

    (Rensselaer Polytechnic Institute)

  • Jessica D. Ryan

    (Solidus Biosciences Inc.)

  • Douglas S. Clark

    (University of California at Berkeley)

  • Jonathan S. Dordick

    (Rensselaer Polytechnic Institute)

  • Moo-Yeal Lee

    (Solidus Biosciences Inc.
    Cleveland State University)

Abstract

Differential expression of various drug-metabolizing enzymes (DMEs) in the human liver may cause deviations of pharmacokinetic profiles, resulting in interindividual variability of drug toxicity and/or efficacy. Here, we present the ‘Transfected Enzyme and Metabolism Chip’ (TeamChip), which predicts potential metabolism-induced drug or drug-candidate toxicity. The TeamChip is prepared by delivering genes into miniaturized three-dimensional cellular microarrays on a micropillar chip using recombinant adenoviruses in a complementary microwell chip. The device enables users to manipulate the expression of individual and multiple human metabolizing-enzyme genes (such as CYP3A4, CYP2D6, CYP2C9, CYP1A2, CYP2E1 and UGT1A4) in THLE-2 cell microarrays. To identify specific enzymes involved in drug detoxification, we created 84 combinations of metabolic-gene expressions in a combinatorial fashion on a single microarray. Thus, the TeamChip platform can provide critical information necessary for evaluating metabolism-induced toxicity in a high-throughput manner.

Suggested Citation

  • Seok Joon Kwon & Dong Woo Lee & Dhiral A. Shah & Bosung Ku & Sang Youl Jeon & Kusum Solanki & Jessica D. Ryan & Douglas S. Clark & Jonathan S. Dordick & Moo-Yeal Lee, 2014. "High-throughput and combinatorial gene expression on a chip for metabolism-induced toxicology screening," Nature Communications, Nature, vol. 5(1), pages 1-12, September.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4739
    DOI: 10.1038/ncomms4739
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