Overcoming the design, build, test bottleneck for synthesis of nonrepetitive protein-RNA cassettes

Noa Katz, Eitamar Tripto, Naor Granik, Sarah Goldberg, Orna Atar, Zohar Yakhini, Yaron Orenstein and Roee Amit ()
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Noa Katz: Technion - Israel Institute of Technology
Eitamar Tripto: Ben-Gurion University of the Negev
Naor Granik: Technion - Israel Institute of Technology
Sarah Goldberg: Technion - Israel Institute of Technology
Orna Atar: Technion - Israel Institute of Technology
Zohar Yakhini: Technion - Israel Institute of Technology
Yaron Orenstein: Ben-Gurion University of the Negev
Roee Amit: Technion - Israel Institute of Technology

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract We apply an oligo-library and machine learning-approach to characterize the sequence and structural determinants of binding of the phage coat proteins (CPs) of bacteriophages MS2 (MCP), PP7 (PCP), and Qβ (QCP) to RNA. Using the oligo library, we generate thousands of candidate binding sites for each CP, and screen for binding using a high-throughput dose-response Sort-seq assay (iSort-seq). We then apply a neural network to expand this space of binding sites, which allowed us to identify the critical structural and sequence features for binding of each CP. To verify our model and experimental findings, we design several non-repetitive binding site cassettes and validate their functionality in mammalian cells. We find that the binding of each CP to RNA is characterized by a unique space of sequence and structural determinants, thus providing a more complete description of CP-RNA interaction as compared with previous low-throughput findings. Finally, based on the binding spaces we demonstrate a computational tool for the successful design and rapid synthesis of functional non-repetitive binding-site cassettes.

Date: 2021
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DOI: 10.1038/s41467-021-21578-6

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