Fast and sensitive multivalent spatial pattern-recognition for circular RNA detection

Zhixin Zhou, Bing Han, Yu Wang, Nina Lin, Zhongqiu Zhou, Yuan Zhang, Ying Bai, Ling Shen, Yanfei Shen, Yuanjian Zhang () and Honghong Yao ()
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Zhixin Zhou: Southeast University
Bing Han: Southeast University
Yu Wang: Southeast University
Nina Lin: Southeast University
Zhongqiu Zhou: Southeast University
Yuan Zhang: Southeast University
Ying Bai: Southeast University
Ling Shen: Southeast University
Yanfei Shen: Southeast University
Yuanjian Zhang: Southeast University
Honghong Yao: Southeast University

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: Abstract While circular RNAs (circRNAs) exhibit lower abundance compared to corresponding linear RNAs, they demonstrate potent biological functions. Nevertheless, challenges arise from the low concentration and distinctive structural features of circRNAs, rendering existing methods operationally intricate and less sensitive. Here, we engineer an intelligent tetrahedral DNA framework (TDF) possessing precise spatial pattern-recognition properties with exceptional sensing speed and sensitivity for circRNAs. The signal output of TDF sensor occurs only when multivalent spatial pattern-recognition of a circRNA in unamplified samples. Using this sensor, we visualize the real-time response of endogenous circRNA expression in vitro neuronal cells and in vivo brain between pre-stroke and post-stroke male mice, identify the patients with acute ischemic stroke in clinical samples, as well as track the delivery of circRNA in photochromic stroked animal model. Thus, the TDF sensor provides a fast and sensitive tool for the detection of circRNA abundance in both physiological and pathophysiological conditions.

Date: 2024
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DOI: 10.1038/s41467-024-55364-x

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