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Artificial intelligence-enhanced analysis of genomic DNA visualized with nanoparticle-tagged peptides under electron microscopy

Artificial intelligence-enhanced analysis of genomic DNA visualized with nanoparticle-tagged peptides under electron microscopy
Artificial intelligence-enhanced analysis of genomic DNA visualized with nanoparticle-tagged peptides under electron microscopy
DNA visualization has advanced across multiple microscopy platforms, albeit with limited progress in the identification of novel staining agents for electron microscopy (EM), notwithstanding its ability to furnish a broad magnification range and high-resolution details for observing DNA molecules. Herein, a non-toxic, universal, and simple method is proposed that uses gold nanoparticle-tagged peptides to stain all types of naturally occurring DNA molecules, enabling their visualization under EM. This method enhances the current DNA visualization capabilities, allowing for sequence-specific, genomic-scale, and multi-conformational visualization. Importantly, an artificial intelligence (AI)-enabled pipeline for identifying DNA molecules imaged under EM is presented, followed by classification based on their size, shape, or conformation, and finally, extraction of their significant dimensional features, which to the best of authors' knowledge, has not been reported yet. This pipeline strongly improved the accuracy of obtaining crucial information such as the number and mean length of DNA molecules in a given EM image for linear DNA (salmon sperm DNA) and the circumferential length and diameter for circular DNA (M13 phage DNA), owing to its image segmentation capability. Furthermore, it remained robust to several variations in the raw EM images arising from handling during the DNA staining stage.
DNA visualization, artificial intelligence, electron microscopy, gold nanoparticle-tagged peptides, image analysis
1613-6810
Sundharbaabu, Priyannth Ramasami
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Chang, Junhyuck
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Kim, Yunchul
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Shim, Youmin
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Lee, Byoungsang
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Noh, Chanyoung
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Heo, Sujung
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Lee, Seung Seo
ee34fa26-5fb6-48c8-80c2-1f13ec4ccceb
Shim, Sang-Hee
b949a4a1-31cf-4a92-9330-98dd8fb0383d
Lim, Kwang-il
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Jo, Kyubong
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Lee, Jung Heon
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Sundharbaabu, Priyannth Ramasami
3fd72094-904b-40b4-8fea-2f47422910a3
Chang, Junhyuck
4892dfe3-04af-4793-90db-b70d14a1678b
Kim, Yunchul
8c93bd79-6f29-4afe-a40a-86e205b23cf5
Shim, Youmin
b2c68519-68a3-4e68-8941-112e944bdc8f
Lee, Byoungsang
8671d2cd-1597-4b3c-90c5-6507aef47936
Noh, Chanyoung
f4e4f79a-6a0d-41ef-81c6-00e93f47adcc
Heo, Sujung
92d8c6fd-223b-4178-8a85-5f376466758b
Lee, Seung Seo
ee34fa26-5fb6-48c8-80c2-1f13ec4ccceb
Shim, Sang-Hee
b949a4a1-31cf-4a92-9330-98dd8fb0383d
Lim, Kwang-il
12f33e16-3820-497c-bb3a-9af4c7133465
Jo, Kyubong
c4bdb781-b5a3-4454-81ab-b32956e73bab
Lee, Jung Heon
ae0132af-492d-478f-b6e3-de58aa147c05

Sundharbaabu, Priyannth Ramasami, Chang, Junhyuck, Kim, Yunchul, Shim, Youmin, Lee, Byoungsang, Noh, Chanyoung, Heo, Sujung, Lee, Seung Seo, Shim, Sang-Hee, Lim, Kwang-il, Jo, Kyubong and Lee, Jung Heon (2024) Artificial intelligence-enhanced analysis of genomic DNA visualized with nanoparticle-tagged peptides under electron microscopy. Small, [2405065]. (doi:10.1002/smll.202405065).

Record type: Article

Abstract

DNA visualization has advanced across multiple microscopy platforms, albeit with limited progress in the identification of novel staining agents for electron microscopy (EM), notwithstanding its ability to furnish a broad magnification range and high-resolution details for observing DNA molecules. Herein, a non-toxic, universal, and simple method is proposed that uses gold nanoparticle-tagged peptides to stain all types of naturally occurring DNA molecules, enabling their visualization under EM. This method enhances the current DNA visualization capabilities, allowing for sequence-specific, genomic-scale, and multi-conformational visualization. Importantly, an artificial intelligence (AI)-enabled pipeline for identifying DNA molecules imaged under EM is presented, followed by classification based on their size, shape, or conformation, and finally, extraction of their significant dimensional features, which to the best of authors' knowledge, has not been reported yet. This pipeline strongly improved the accuracy of obtaining crucial information such as the number and mean length of DNA molecules in a given EM image for linear DNA (salmon sperm DNA) and the circumferential length and diameter for circular DNA (M13 phage DNA), owing to its image segmentation capability. Furthermore, it remained robust to several variations in the raw EM images arising from handling during the DNA staining stage.

Text
Small - 2024 - Sundharbaabu - Artificial Intelligence‐Enhanced Analysis of Genomic DNA Visualized with Nanoparticle‐Tagged - Version of Record
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e-pub ahead of print date: 9 October 2024
Keywords: DNA visualization, artificial intelligence, electron microscopy, gold nanoparticle-tagged peptides, image analysis

Identifiers

Local EPrints ID: 496064
URI: http://eprints.soton.ac.uk/id/eprint/496064
ISSN: 1613-6810
PURE UUID: d12a60b9-7ccb-4316-a5b7-856c3a086dfc
ORCID for Seung Seo Lee: ORCID iD orcid.org/0000-0002-8598-3303

Catalogue record

Date deposited: 02 Dec 2024 17:47
Last modified: 05 Dec 2024 02:45

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Contributors

Author: Priyannth Ramasami Sundharbaabu
Author: Junhyuck Chang
Author: Yunchul Kim
Author: Youmin Shim
Author: Byoungsang Lee
Author: Chanyoung Noh
Author: Sujung Heo
Author: Seung Seo Lee ORCID iD
Author: Sang-Hee Shim
Author: Kwang-il Lim
Author: Kyubong Jo
Author: Jung Heon Lee

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