Literature DB >> 29205813

High-Throughput Block Optical DNA Sequence Identification.

Dodderi Manjunatha Sagar1,2, Lee Erik Korshoj1,2, Katrina Bethany Hanson1,2, Partha Pratim Chowdhury1,2, Peter Britton Otoupal1, Anushree Chatterjee1, Prashant Nagpal1,2,3.   

Abstract

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm-1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition.
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  FTIR spectroscopy; Raman spectroscopy; block nucleotide identification; optical DNA sequencing

Mesh:

Substances:

Year:  2017        PMID: 29205813     DOI: 10.1002/smll.201703165

Source DB:  PubMed          Journal:  Small        ISSN: 1613-6810            Impact factor:   13.281


  4 in total

1.  A machine learning approach for accurate and real-time DNA sequence identification.

Authors:  Yiren Wang; Mashari Alangari; Joshua Hihath; Arindam K Das; M P Anantram
Journal:  BMC Genomics       Date:  2021-07-09       Impact factor: 3.969

Review 2.  Microfluidic and Paper-Based Devices for Disease Detection and Diagnostic Research.

Authors:  Joshua M Campbell; Joseph B Balhoff; Grant M Landwehr; Sharif M Rahman; Manibarathi Vaithiyanathan; Adam T Melvin
Journal:  Int J Mol Sci       Date:  2018-09-12       Impact factor: 5.923

3.  FluoroCellTrack: An algorithm for automated analysis of high-throughput droplet microfluidic data.

Authors:  Manibarathi Vaithiyanathan; Nora Safa; Adam T Melvin
Journal:  PLoS One       Date:  2019-05-01       Impact factor: 3.240

4.  Analysis of Identification Method for Bacterial Species and Antibiotic Resistance Genes Using Optical Data From DNA Oligomers.

Authors:  Ryan L Wood; Tanner Jensen; Cindi Wadsworth; Mark Clement; Prashant Nagpal; William G Pitt
Journal:  Front Microbiol       Date:  2020-02-20       Impact factor: 5.640

  4 in total

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