Ultrasensitive and Selective Detection of SARS-CoV-2 using Thermotropic Liquid Crystals and Image-based Machine Learning

Xu, Yang; Rather, Adil M.; Song, Shuang; Fang, Jen-Chun; Dupont, Robert L.; Kara, Ufuoma I.; Chang, Yun; Paulson, Joel A.; Qin, Rongjun; Bao, Xiaoping; Wang, Xiaoguang

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 the femtomolar concentrations of single-stranded ribonucleic acid (ssRNA) of SARS-CoV-2 trigger ordering transitions in liquid crystal (LC) films decorated with cationic surfactant and complementary 15-mer single-stranded deoxyribonucleic acid (ssDNA) probe. 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, is measured to decrease by seven orders of magnitude, suggesting that the LC ordering transitions depend strongly on the targeted oligonucleotide sequence. Finally, we design a LC-based diagnostic kit and a smartphone-based application (App) to enable automatic detection of SARS-CoV-2 ssRNA, which could be used for reliable self-test of SARS-CoV-2 at home without the need for complex equipment or procedures.