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| Funder | NATIONAL HUMAN GENOME RESEARCH INSTITUTE |
|---|---|
| Recipient Organization | University of Toronto |
| Country | Canada |
| Start Date | Sep 21, 2021 |
| End Date | Aug 31, 2023 |
| Duration | 709 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10303722 |
Project Summary Genes mediate their effects through networks of macromolecular interactions. Large-scale studies have mapped protein interactions for humans and several model organisms.
However, even for S. cerevisiae, the most intensively-studied eukaryotic model, knowledge of the protein interaction network remains both incomplete and ?static?, in the sense that each global interaction mapping study has used essentially the same growth environment and genetic background.
Moreover, despite the many known examples of signalling interactions that appear and fade rapidly after an environmental stress, large-scale interaction maps represent the time- average of interaction over many generations of a cell.
We previously extended the yeast two-hybrid (Y2H) interaction assay with a ?barcode fusion genetics? (BFG) strategy, which uses intracellular recombination to form chimeric barcodes that identify bait/prey protein combinations.
This ?BFG-Y2H? method enabled multiplexing of millions of interaction assays, with internal biological replication, all within a single en masse experiment, and has already been used for proteome-scale mapping of yeast interactions under four growth environments.
Here we propose a further extension, in which the promoter that traditionally reports on interaction status is used to transcribe the chimeric bait/prey barcode locus. Sequencing these ?interaction tags? can thus provide a quantitative measure of promoter output.
Importantly, the rapid dynamics of transcript production and degradation have the potential to enable measurement of interaction dynamics with ~10-minute time resolution, at proteome scale, in living cells.
University of Toronto
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