Label-free and high-sensitive detection for genetic point mutation based on hyperspectral interferometry

Rongxin Fu; Qi Li; Junqi Zhang; Ruliang Wang; Xue Lin; Ning Xue; Ya Su; Kai Jiang; Guoliang Huang

doi:10.1117/12.2246119

31 October 2016 Label-free and high-sensitive detection for genetic point mutation based on hyperspectral interferometry

Rongxin Fu, Qi Li, Junqi Zhang, Ruliang Wang, Xue Lin, Ning Xue, Ya Su, Kai Jiang, Guoliang Huang

Author Affiliations +

Proceedings Volume 10024, Optics in Health Care and Biomedical Optics VII; 100243D (2016) https://doi.org/10.1117/12.2246119
Event: SPIE/COS Photonics Asia, 2016, Beijing, China

Abstract

Label free point mutation detection is particularly momentous in the area of biomedical research and clinical diagnosis since gene mutations naturally occur and bring about highly fatal diseases. In this paper, a label free and high sensitive approach is proposed for point mutation detection based on hyperspectral interferometry. A hybridization strategy is designed to discriminate a single-base substitution with sequence-specific DNA ligase. Double-strand structures will take place only if added oligonucleotides are perfectly paired to the probe sequence. The proposed approach takes full use of the inherent conformation of double-strand DNA molecules on the substrate and a spectrum analysis method is established to point out the sub-nanoscale thickness variation, which benefits to high sensitive mutation detection. The limit of detection reach 4pg/mm² according to the experimental result. A lung cancer gene point mutation was demonstrated, proving the high selectivity and multiplex analysis capability of the proposed biosensor.

Citation Download Citation

Rongxin Fu, Qi Li, Junqi Zhang, Ruliang Wang, Xue Lin, Ning Xue, Ya Su, Kai Jiang, and Guoliang Huang "Label-free and high-sensitive detection for genetic point mutation based on hyperspectral interferometry", Proc. SPIE 10024, Optics in Health Care and Biomedical Optics VII, 100243D (31 October 2016); https://doi.org/10.1117/12.2246119

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KEYWORDS

Biosensors

Interferometry

Lung cancer

Genetics

Biological research

Molecules

Spectrum analysis

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