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Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials
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 remai...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5943445/ https://www.ncbi.nlm.nih.gov/pubmed/29743506 http://dx.doi.org/10.1038/s41598-018-25444-2 |
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author | Freeman, Lindsay M. Pang, Lin Fainman, Yeshaiahu |
author_facet | Freeman, Lindsay M. Pang, Lin Fainman, Yeshaiahu |
author_sort | Freeman, Lindsay M. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5943445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59434452018-05-14 Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials Freeman, Lindsay M. Pang, Lin Fainman, Yeshaiahu Sci Rep Article 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. Nature Publishing Group UK 2018-05-09 /pmc/articles/PMC5943445/ /pubmed/29743506 http://dx.doi.org/10.1038/s41598-018-25444-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Freeman, Lindsay M. Pang, Lin Fainman, Yeshaiahu Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5943445/ https://www.ncbi.nlm.nih.gov/pubmed/29743506 http://dx.doi.org/10.1038/s41598-018-25444-2 |
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