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.

Nanopores have been used for direct observation of RNA structure in native environments but have limited RNA differentiation capabilities. Here, the authors report on the use of Mycobacterium smegmatis porin A nanopores for the trapping and translocation identification of microRNA, siRNA, tRNA and ribosomal RNA.

Details

Title
Structural-profiling of low molecular weight RNAs by nanopore trapping/translocation using Mycobacterium smegmatis porin A
Author
Wang, Yuqin 1   VIAFID ORCID Logo  ; Guan Xiaoyu 2 ; Zhang, Shanyu 1 ; Liu, Yao 1   VIAFID ORCID Logo  ; Wang, Sha 1 ; Fan Pingping 1 ; Du, Xiaoyu 1 ; Shuanghong, Yan 1   VIAFID ORCID Logo  ; Zhang Panke 3   VIAFID ORCID Logo  ; Hong-Yuan, Chen 3   VIAFID ORCID Logo  ; Li, Wenfei 4   VIAFID ORCID Logo  ; Zhang Daoqiang 2 ; Huang, Shuo 1   VIAFID ORCID Logo 

 Nanjing University, State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X); Nanjing University, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X) 
 Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, College of Computer Science and Technology, Nanjing, China (GRID:grid.64938.30) (ISNI:0000 0000 9558 9911) 
 Nanjing University, State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X) 
 Nanjing University, Collaborative Innovation Center of Advanced Microstructures, National Laboratory of Solid State Microstructure, Department of Physics, Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2537859124
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.