Structural-profiling of low molecular weight RNAs by nanopore trapping/translocation using Mycobacterium smegmatis porin A

Yuqin Wang, Xiaoyu Guan, Shanyu Zhang, Yao Liu, Sha Wang, Pingping Fan, Xiaoyu Du, Shuanghong Yan, Panke Zhang, Hong-Yuan Chen, Wenfei Li (), Daoqiang Zhang () and Shuo Huang ()
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Yuqin Wang: Nanjing University
Xiaoyu Guan: Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence
Shanyu Zhang: Nanjing University
Yao Liu: Nanjing University
Sha Wang: Nanjing University
Pingping Fan: Nanjing University
Xiaoyu Du: Nanjing University
Shuanghong Yan: Nanjing University
Panke Zhang: Nanjing University
Hong-Yuan Chen: Nanjing University
Wenfei Li: Nanjing University
Daoqiang Zhang: Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence
Shuo Huang: Nanjing University

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Folding of RNA can produce elaborate tertiary structures, corresponding to their diverse roles in the regulation of biological activities. Direct observation of RNA structures at high resolution in their native form however remains a challenge. The large vestibule and the narrow constriction of a Mycobacterium smegmatis porin A (MspA) suggests a sensing mode called nanopore trapping/translocation, which clearly distinguishes between microRNA, small interfering RNA (siRNA), transfer RNA (tRNA) and 5 S ribosomal RNA (rRNA). To further profit from the acquired event characteristics, a custom machine learning algorithm is developed. Events from measurements with a mixture of RNA analytes can be automatically classified, reporting a general accuracy of ~93.4%. tRNAs, which possess a unique tertiary structure, report a highly distinguishable sensing feature, different from all other RNA types tested in this study. With this strategy, tRNAs from different sources are measured and a high structural conservation across different species is observed in single molecule.

Date: 2021
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DOI: 10.1038/s41467-021-23764-y

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