Back

Crowdsourced riboregulators reveal design principles for programmable RNA switching

Robson, J. M.; Moussas, G.; Francis, D.; Green, A. A.

2026-07-09 synthetic biology
10.64898/2026.07.08.737257 bioRxiv
Show abstract

RNA-based sensors offer powerful and programmable control of gene expression, yet our understanding of the structural principles that govern their potential design space remains incomplete. Here, we challenged a community of designers to generate novel riboregulators capable of activating translation in response to specific RNA targets. Participants submitted diverse sequence architectures, which were synthesized and evaluated in a cell-free transcription-translation system. Across 100 designs, community-generated riboregulators displayed wide variability in activation dynamics, fold change, and structural features, outperforming some canonical toehold-switch designs and achieving up to 80-fold activation. Structural ensemble analyses identified accessibility patterns near the ribosome binding site that distinguish high- from low-performing regulators, highlighting the central role of RBS sequestration and release in modulating expression. Together, we demonstrate community-driven design can expand the accessible structural space of riboregulators and uncover mechanistic features governing translational activation. Our findings establish quantitative links between RNA folding energetics and gene expression output, providing design principles for next-generation programmable RNA sensors.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Nature Communications
5641 papers in training set
Top 6%
22.0%
2
Nucleic Acids Research
1281 papers in training set
Top 0.8%
18.2%
3
Cell Systems
201 papers in training set
Top 0.4%
7.8%
4
ACS Synthetic Biology
287 papers in training set
Top 0.8%
4.0%
50% of probability mass above
5
Science
477 papers in training set
Top 3%
3.2%
6
Nature Biotechnology
172 papers in training set
Top 2%
2.6%
7
Nature Chemical Biology
119 papers in training set
Top 1.0%
2.6%
8
Science Advances
1243 papers in training set
Top 14%
2.4%
9
Molecular Cell
350 papers in training set
Top 2%
2.4%
10
Nature Methods
385 papers in training set
Top 4%
2.1%
11
Molecular Systems Biology
162 papers in training set
Top 1%
2.1%
12
Cell
431 papers in training set
Top 5%
2.1%
13
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 26%
1.9%
14
Trends in Biotechnology
12 papers in training set
Top 0.1%
1.7%
15
Nature
645 papers in training set
Top 7%
1.4%
16
Angewandte Chemie International Edition
93 papers in training set
Top 1%
1.3%
17
Communications Chemistry
48 papers in training set
Top 0.8%
1.3%
18
eLife
5828 papers in training set
Top 55%
1.3%
19
Neuron
337 papers in training set
Top 4%
1.3%
20
Cell Chemical Biology
94 papers in training set
Top 1%
1.1%
21
RNA
189 papers in training set
Top 1%
1.1%
22
PLOS Computational Biology
1863 papers in training set
Top 18%
1.0%
23
Nature Machine Intelligence
70 papers in training set
Top 2%
1.0%
24
Advanced Science
286 papers in training set
Top 8%
1.0%
25
Nature Genetics
286 papers in training set
Top 5%
0.8%
26
Cell Reports
1498 papers in training set
Top 27%
0.8%