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Rapid nanopore discrimination between single polynucleotide molecules

Open access
Meller, Amit, Nivon, Lucas, Brandin, Eric, Golovchenko, Jene, Branton, Daniel·2000·Proceedings of the National Academy of Sciences

Abstract

A variety of different DNA polymers were electrophoretically driven through the nanopore of an α-hemolysin channel in a lipid bilayer. Single-channel recording of the translocation duration and current flow during traversal of individual polynucleotides yielded a unique pattern of events for each of the several polymers tested. Statistical data derived from this pattern of events demonstrate that in several cases a nanopore can distinguish between polynucleotides of similar length and composition that differ only in sequence. Studies of temperature effects on the translocation process show that translocation duration scales as ∼ T −2 . A strong correlation exists between the temperature dependence of the event characteristics and the tendency of some polymers to form secondary structure. Because nanopores can rapidly discriminate and characterize unlabeled DNA molecules at low copy number, refinements of the experimental approach demonstrated here could eventually provide a low-cost high-throughput method of analyzing DNA polynucleotides.

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Metadata

Authors
Meller, A., Nivon, L., Brandin, E., Golovchenko, J., & Branton, D.
Venue
Proceedings of the National Academy of Sciences
Published
2000-02
Volume
97
Issue
3
Pages
1079-1084
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1971212710
Cited by
937
References
0
FWCI
22.23
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Rapid nanopore discrimination between single polynucleotide molecules. https://app.cochat.ai/papers/10.1073/pnas.97.3.1079
The paper
Meller, A., Nivon, L., Brandin, E., Golovchenko, J., & Branton, D. (2000). Rapid nanopore discrimination between single polynucleotide molecules. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.97.3.1079

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.