High-confidence single-molecule detection of nucleic acids

Description:
High-confidence detection of biomarkers is critical for the reliable diagnosis of diseases and other biotechnology applications. However, the vast majority of biomarker detection strategies involve either target/signal amplification or complex sensor designs, both of which limit their widespread use. Therefore, there is an increasing demand for simple, adaptable, and amplification-free methods. Using a fluorescence resonance energy transfer (FRET)-based approach, we recently showed a background-free ultrasensitive detection of DNA and miRNA targets on a simple and easily customizable sensing platform. The developed sensors exhibit a relatively static mid-FRET state in the absence of a target but undergo a continuous dynamic switching between a low- and a high-FRET state in the presence of the target - thus enabling a highly reliable detection. In addition, the sensor can fully discriminate single nucleotide polymorphisms (SNPs) which is a requirement for high-specificity sensing of nucleic acid biomarkers. Given the generic hybridization-based detection platform, superior sensitivity, and high-confidence detection, this sensing platform may offer new opportunities in the early diagnosis of diseases and screening of genetic disorders.

We acknowledge the VCU Startup Grant and the VCU’s CTSA (UL1TR002649 from the National Center for Advancing Translational Sciences) and the CCTR Endowment Fund as the source of funding for this work.

Speaker: Soma Dhakal - Virginia Commonwealth University
Dr. Dhakal is an Assistant Professor in the department of chemistry at Virginia Commonwealth University (VCU), Richmond, Virginia. His independent research involves single-molecule analysis of protein-DNA interactions and the development of novel and high-confidence techniques for the detection of nucleic acid and protein biomarkers.