Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials
Abstract The analysis of DNA has led to revolutionary advancements in the fields of medical diagnostics, genomics, prenatal screening, and forensic science, with the global DNA testing market expected to reach revenues of USD 10.04 billion per year by 2020. However, the current methods for DNA analy...
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2018-05-01
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Online Access: | https://doi.org/10.1038/s41598-018-25444-2 |
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doaj-884ad54a1ee3422b8e0aad079d4dcfa52020-12-08T05:36:21ZengNature Publishing GroupScientific Reports2045-23222018-05-01811710.1038/s41598-018-25444-2Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterialsLindsay M. Freeman0Lin Pang1Yeshaiahu Fainman2Department of Electrical and Computer Engineering, University of California San DiegoDepartment of Electrical and Computer Engineering, University of California San DiegoDepartment of Electrical and Computer Engineering, University of California San DiegoAbstract The analysis of DNA has led to revolutionary advancements in the fields of medical diagnostics, genomics, prenatal screening, and forensic science, with the global DNA testing market expected to reach revenues of USD 10.04 billion per year by 2020. However, the current methods for DNA analysis remain dependent on the necessity for fluorophores or conjugated proteins, leading to high costs associated with consumable materials and manual labor. Here, we demonstrate a potential label-free DNA composition detection method using surface-enhanced Raman spectroscopy (SERS) in which we identify the composition of cytosine and adenine within single strands of DNA. This approach depends on the fact that there is one phosphate backbone per nucleotide, which we use as a reference to compensate for systematic measurement variations. We utilize plasmonic nanomaterials with random Raman sampling to perform label-free detection of the nucleotide composition within DNA strands, generating a calibration curve from standard samples of DNA and demonstrating the capability of resolving the nucleotide composition. The work represents an innovative way for detection of the DNA composition within DNA strands without the necessity of attached labels, offering a highly sensitive and reproducible method that factors in random sampling to minimize error.https://doi.org/10.1038/s41598-018-25444-2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lindsay M. Freeman Lin Pang Yeshaiahu Fainman |
spellingShingle |
Lindsay M. Freeman Lin Pang Yeshaiahu Fainman Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials Scientific Reports |
author_facet |
Lindsay M. Freeman Lin Pang Yeshaiahu Fainman |
author_sort |
Lindsay M. Freeman |
title |
Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title_short |
Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title_full |
Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title_fullStr |
Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title_full_unstemmed |
Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title_sort |
self-reference and random sampling approach for label-free identification of dna composition using plasmonic nanomaterials |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2018-05-01 |
description |
Abstract The analysis of DNA has led to revolutionary advancements in the fields of medical diagnostics, genomics, prenatal screening, and forensic science, with the global DNA testing market expected to reach revenues of USD 10.04 billion per year by 2020. However, the current methods for DNA analysis remain dependent on the necessity for fluorophores or conjugated proteins, leading to high costs associated with consumable materials and manual labor. Here, we demonstrate a potential label-free DNA composition detection method using surface-enhanced Raman spectroscopy (SERS) in which we identify the composition of cytosine and adenine within single strands of DNA. This approach depends on the fact that there is one phosphate backbone per nucleotide, which we use as a reference to compensate for systematic measurement variations. We utilize plasmonic nanomaterials with random Raman sampling to perform label-free detection of the nucleotide composition within DNA strands, generating a calibration curve from standard samples of DNA and demonstrating the capability of resolving the nucleotide composition. The work represents an innovative way for detection of the DNA composition within DNA strands without the necessity of attached labels, offering a highly sensitive and reproducible method that factors in random sampling to minimize error. |
url |
https://doi.org/10.1038/s41598-018-25444-2 |
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