Lateral flow DNA biosensor for visual detection of nucleic acid with triple-helix DNA functionalized carbon nanotube

We describe a novel lateral flow DNA biosensor (LFDB) based on carbon nanotube (CNT) and triple helix DNA (THD). The carboxylated CNT was first conjugated with amine-modified auxiliary single-stranded DNA probe (P1) by dehydration reaction and used as signal probe. A main DNA probe (P0) was introduced to react with the P1 and formed the THD on the CNT surface. Because of the large spatial effect, P1 was in an inactive state and cannot hybridize with the capture DNA probe (P2) fixed on the LFDB test area. When the target DNA was present, P0 in the triple helix DNA hybridized with the target DNA due to the stronger base action, and the decomposition of the triple helix structure exposed P1. Therefore, P1 on CNT surface was activated to hybridize with P2. The CNT along with P1 was thus captured at the test area and accumulated to show a black line, which can be observed by naked eye for qualitative analysis and recorded with a portable grayscale reader for quantitative analysis. Single -stranded DNA was used as a target to prove the feasibility of the model. Under the best experimental conditions, the THD-CNT based LFDB was able to detect the lowest DNA concentration of 15 pM, which is 2.67 times better than that of the traditional duplex CNT-based LFDB. It should be noted that the LFDB based on THD function-alized CNT can differentiate between one-base-mismatched DNA and the complementary target DNA, can detected target DNA in 10% human serum, and can be employed as a versatile platform to detect various target (proteins, small molecular) by changing the sequence of P0. This biosensor platform has enormous potential in the point-of-care detection of a rich diversity of analytes for clinical diagnosis and biomedical research.

Automated summary

We developed a novel lateral flow DNA biosensor based on carbon nanotubes and triple helix DNA. This biosensor can detect DNA with high sensitivity and has the potential for applications in qualitative and quantitative analysis. It has significant implications for clinical diagnosis and biomedical research.