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Identification of nucleoside monophosphates and their epigenetic modifications using an engineered nanopore
Abstract
RNA modifications play critical roles in the regulation of various biological processes and are associated with many human diseases. Direct identification of RNA modifications by sequencing remains challenging, however. Nanopore sequencing is promising, but the current strategy is complicated by sequence decoding. Sequential nanopore identification of enzymatically cleaved nucleoside monophosphates may simultaneously provide accurate sequence and modification information. Here we show a phenylboronic acid-modified hetero-octameric Mycobacterium smegmatis porin A nanopore, with which direct distinguishing between monophosphates of canonical nucleosides, 5-methylcytidine, N 6-methyladenosine, N 7-methylguanosine, N 1-methyladenosine, inosine, pseudouridine and dihydrouridine was achieved. A custom machine learning algorithm, which reports an accuracy of 0.996, was also applied to the quantitative analysis of modifications in microRNA and natural transfer RNA. It is generally suitable for sensing of a variety of other nucleoside or nucleotide derivatives and may bring new insights to epigenetic RNA sequencing.
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“Contrary to SBS, it is therefore also able to identify modified and unnatural nucleotides such that the readout of data encoded using an expanded molecular alphabet is possible.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [87]
Citations
Cites
Dynamic RNA Modifications in Gene Expression Regulation
Roundtree, I. A., Evans, M., Pan, T., & He, C. (2017) · Cell · doi:10.1016/j.cell.2017.05.045 · Cited by 3,512
Structure of Staphylococcal α-Hemolysin, a Heptameric Transmembrane Pore
Song, L., Hobaugh, M. R., Shustak, C., Cheley, S., Bayley, H., & Gouaux, J. E. (1996) · Science · doi:10.1126/science.274.5294.1859 · Cited by 2,426
Continuous base identification for single-molecule nanopore DNA sequencing
Clarke, J., Wu, H., Jayasinghe, L., Patel, A., Reid, S., & Bayley, H. (2009) · Nature Nanotechnology · doi:10.1038/nnano.2009.12 · Cited by 1,813
MODOMICS: a database of RNA modification pathways. 2017 update
Boccaletto, P., Machnicka, M. A., Purta, E., Piątkowski, P., Bagiński, B., Wirecki, T. K., de Crécy‐Lagard, V., Ross, R. L., Limbach, P. A., Kötter, A., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1030 · Cited by 1,767
Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome
Linder, B., Grozhik, A. V., Olarerin-George, A. O., Meydan, C., Mason, C. E., & Jaffrey, S. R. (2015) · Nature Methods · doi:10.1038/nmeth.3453 · Cited by 1,569
A detailed examination of boronic acid–diol complexation
Springsteen, G., & Wang, B. (2002) · Tetrahedron · doi:10.1016/s0040-4020(02)00489-1 · Cited by 1,483
Role of RNA modifications in cancer
Barbieri, I., & Kouzarides, T. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0253-2 · Cited by 1,350
5-methylcytosine promotes mRNA export — NSUN2 as the methyltransferase and ALYREF as an m5C reader
Yang, X., Yang, Y., Sun, B., Chen, Y., Xu, J., Lai, W., Li, A., Wang, X., Bhattarai, D. P., Xiao, W., et al. (2017) · Cell Research · doi:10.1038/cr.2017.55 · Cited by 1,141
The dynamic N1-methyladenosine methylome in eukaryotic messenger RNA
Dominissini, D., Nachtergaele, S., Moshitch-Moshkovitz, S., Peer, E., Kol, N., Ben-Haim, M. S., Dai, Q., Segni, A. D., Salmon‐Divon, M., Clark, W. C., et al. (2016) · Nature · doi:10.1038/nature16998 · Cited by 1,047
Pseudouridine profiling reveals regulated mRNA pseudouridylation in yeast and human cells
Carlile, T. M., Rojas-Durán, M. F., Zinshteyn, B., Shin, H., Bartoli, K. M., & Gilbert, W. V. (2014) · Nature · doi:10.1038/nature13802 · Cited by 1,042
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Metadata
- Authors
- Wang, Y., Zhang, S., Jia, W., Fan, P., Wang, L., Li, X., Chen, J., Cao, Z., Du, X., Liu, Y., Wang, K., Hu, C., Zhang, J., Hu, J., Zhang, P., Chen, H.-Y., & Huang, S.
- Affiliations
- State Key Laboratory of Analytical Chemistry for Life Science (CN)
- Corresponding author
- Huang, Shuo
- ORCID
- Venue
- Nature Nanotechnology
- Published
- 2022-07-18
- Volume
- 17
- Issue
- 9
- Pages
- 976-983
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W4285728626
- Cited by
- 143
- References
- 51
- Citations by year
- 2026: 30 · 2025: 41 · 2024: 35 · 2023: 32 · 2022: 5
- FWCI
- 8.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Nanotechnology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Oxford
- National Natural Science Foundation of China (31972917, 5431ZZXM2204, ZYJH004, 21675083, 91753108)
- China Postdoctoral Science Foundation (2021M691508)
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province (BK20200009)
- Nanjing University (ZYJH004)
- Fundamental Research Funds for the Central Universities (020514380257, 020514380261)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Nanopore and Nanochannel Transport Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Nucleic Acid Chemistry
- Keywords
- RNA modification, nucleoside monophosphates, 5-methylcytidine, N6-methyladenosine, 7-methylguanosine, N1-methyladenosine, inosine, pseudouridine, dihydrouridine, machine learning classification, microRNA, tRNA, enzymatic cleavage
- MeSH terms
- Humans, Inosine, Nucleosides, Nucleotides, Pseudouridine, RNA, Transfer, Porins, MicroRNAs, Epigenesis, Genetic, Nanopores
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