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Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning

55 Pages Posted: 30 Sep 2020 Publication Status: Review Complete

See all articles by Yang Xu

Yang Xu

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Adil Rather

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Shuang Song

Ohio State University (OSU) - Department of Civil, Environmental and Geodetic Engineering

Jen-Chun Fang

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Robert L. Dupont

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Ufuoma I. Kara

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Yun Chang

Purdue University - Davidson School of Chemical Engineering

Joel A. Paulson

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

Rongjun Qin

Ohio State University (OSU) - Department of Civil, Environmental and Geodetic Engineering

Xiaoping Bao

Purdue University - Davidson School of Chemical Engineering

Xiaoguang Wang

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

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Abstract

Rapid, robust virus detection techniques with ultrahigh sensitivity and selectivity are required for the outbreak of the pandemic coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Here, we report that femtomolar concentrations of single-stranded ribonucleic acid (ssRNA) of SARS-CoV-2 trigger ordering transitions in liquid crystal (LC) films decorated with cationic surfactants and complementary 15-mer single-stranded deoxyribonucleic acid (ssDNA) probes. More importantly, the sensitivity of the LC to the severe acute respiratory syndrome (SARS) ssRNA, with a 3 base pair-mismatch compared to the SARS-CoV-2 ssRNA, was measured to decrease by seven orders of magnitude, suggesting that the LC ordering transitions depend strongly on the targeted oligonucleotide sequence. Finally, we designed a LC-based diagnostic kit and a smartphone-based application (App) to enable automatic detection of SARS-CoV-2 ssRNA, which can be used for reliable self-test of SARS-CoV-2 at home without the need for complex equipment or procedures.

Funding: J.P. and X.W. thank the funding support by the startup funds of The Ohio State University (OSU) and X.W. thanks OSU Institute for Materials Research Kickstart Facility Grant. X.B. thanks the funding support by the startup funds of Davidson School of Chemical Engineering at Purdue University. S.S. and R.Q. thanks the funding support by Office of Naval Research (ONR Grant N00014-17-1-2928).

Conflict of Interest: The Ohio State University has filed a patent application (Application Number 63066000) on the work described in this manuscript. The inventors listed on the patent application are X.W., X.B., Q.R., X.Y. and A.M.R. The authors declare no other competing interests.

Keywords: COVID-19, SARS-CoV-2, biosensor, liquid crystals, point-of-care detection kit, machine learning

Suggested Citation

Xu, Yang and Rather, Adil and Song, Shuang and Fang, Jen-Chun and Dupont, Robert L. and Kara, Ufuoma I. and Chang, Yun and Paulson, Joel A. and Qin, Rongjun and Bao, Xiaoping and Wang, Xiaoguang, Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning. Available at SSRN: https://ssrn.com/abstract=3682267 or http://dx.doi.org/10.2139/ssrn.3682267
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Yang Xu

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

United States

Adil Rather

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering ( email )

United States

Shuang Song

Ohio State University (OSU) - Department of Civil, Environmental and Geodetic Engineering

470 Hitchcock Hall
2070 Neil Avenue
Columbus, OH 43210
United States

Jen-Chun Fang

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering ( email )

United States

Robert L. Dupont

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering

United States

Ufuoma I. Kara

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering ( email )

United States

Yun Chang

Purdue University - Davidson School of Chemical Engineering

610 Purdue Mall
West Lafayette, IN 47907
United States

Joel A. Paulson

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering ( email )

United States

Rongjun Qin

Ohio State University (OSU) - Department of Civil, Environmental and Geodetic Engineering ( email )

2070 Neil Avenue, OH 43210
United States

Xiaoping Bao

Purdue University - Davidson School of Chemical Engineering ( email )

610 Purdue Mall
West Lafayette, IN 47907
United States

Xiaoguang Wang (Contact Author)

Ohio State University (OSU) - William G. Lowrie Department of Chemical and Biomolecular Engineering ( email )

United States

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