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...

Full description

Bibliographic Details
Main Authors: Lindsay M. Freeman, Lin Pang, Yeshaiahu Fainman
Format: Article
Language:English
Published: Nature Publishing Group 2018-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-018-25444-2
id doaj-884ad54a1ee3422b8e0aad079d4dcfa5
record_format Article
spelling 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
work_keys_str_mv AT lindsaymfreeman selfreferenceandrandomsamplingapproachforlabelfreeidentificationofdnacompositionusingplasmonicnanomaterials
AT linpang selfreferenceandrandomsamplingapproachforlabelfreeidentificationofdnacompositionusingplasmonicnanomaterials
AT yeshaiahufainman selfreferenceandrandomsamplingapproachforlabelfreeidentificationofdnacompositionusingplasmonicnanomaterials
_version_ 1724391659381194752