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Updated: Jul 11, 2026

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
Published on: November 15, 2013
Retrospective analysis and decentralized distribution to improve the lifecycle of Ah receptor research assets
Alex C Veith1, Patrick R Carney1, Aijing Wu2
1McArdle Laboratory for Cancer Research, University of Wisconsin School of Medicine and Public Health, Madison, WI 53706, USA.
Abstract:
Scientific progress benefits from the sharing of "research assets" such as data, reagents, models, and experimental samples. To improve asset shareability, we evaluated the availability, quality, and characterization of recombinant DNA molecules, recombinant mouse models, and tissue samples described by our laboratory in ten publications spanning over thirty years. Employing state-of-the-art molecular technologies, we identified existing samples, updated their localization, generated modern sequences and maps of recombinant models, and ported the associated metadata to an internal blockchain-dependent resource using a standardized description for each asset class. We also created non-fungible tokens representing research assets on the public blockchain network Solana. In addition to providing an audit of previously reported shareable assets and improving the value of recombinant models, this re-analysis also provides evidence for the utility of extant tissue samples that may be difficult and expensive to regenerate. The results demonstrate how retrospective analysis can improve and expand upon the spectrum of shareable research assets through updates on molecular characterization and physical location, as well as improving the availability of biological samples of potential high experimental value. Moreover, the development of a decentralized ledger harboring this revised metadata provides a path to the description and tokenization of scientific assets and provides a strategy to extend the life of scientific assets even after laboratories or sources close.
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