Sign in
Systems BiologybioRxiv
Preprint

Engineering the auxin-inducible degron system for tunable in vivo control of organismal physiology

Jeremy VicencioiD, Daisuke ChiharaiD, Matthias EderiD, Julie AhringeriD, Nicholas StroustrupiD

Abstract

The physiological mechanisms governing health and disease exhibit complex interactions between multiple genes and gene products. To study the dynamics of living systems, researchers need experimental methods capable of producing calibrated, quantitative perturbations in vivo -- perturbations that cannot be obtained using classical genetics, RNAi interference, or small molecule drugs. Recently, an auxin-inducible degron (AID) system has been developed to allow targeted degradation of proteins using small-molecule activators, providing spatiotemporal control of protein abundance. However, a better understanding of the biochemical activities of AID system components in their physiological context is needed to design quantitative interventions. Here, we apply engineering approaches to characterize and understand the performance of several AID technologies and then improve this performance in the multicellular animal Caenorhabditis elegans. We 1) develop new technologies that allow for a careful calibration of AID activity for specific purposes; 2) develop new TIR1 enzyme constructs with improved performance over existing constructs; 3) develop an approach to simultaneously and independently degrade target proteins in distinct tissues; and finally, 4) develop an approach for pan-organismal protein degradation by re-engineering the TIR1 enzyme. Taken together, these advances enable new quantitative experimental approaches to study the cellular and systems dynamics of animals.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISNishimura '20Sathyan '19Ogawa '25Hills-Mucke '21Yesbolatova '19Martinez '19
72% semantic matchBioengineering
K. Nishimura, R. Yamada, S. Hagihara+6 more·bioRxiv·Jan 20, 2020