Search

Identification of single‐nucleotide variants (SNVs) is of great significance in molecular diagnosis. The problem that should not be ignored in the identification process is that the unexpected secondary structure of the target nucleic acid may greatly affect the detection accuracy. Herein, we proposed a conditional domain‐level SNV diagnosis strategy, in which the subsequent SNV detection can only be carried out after eliminating the unexpected secondary structure of target DNA. Specifically, the target DNA is assembled into a rigid double strand, which makes folding the target DNA difficult and the unexpected secondary structure is eliminated. Based on this double‐stranded structure, specially designed probes are used to detect double‐stranded properties and report abundant domain‐level oligonucleotide information to improve the effective information in the detection results and complete domain‐level SNV diagnosis. If the unexpected secondary structure is not eliminated, the detector will first detect it and feed back to us, ensuring the accuracy of the subsequent detection results. With the occurrence (or not) of SNV and the change of the SNV site, in the proof‐of‐concept experiment, we successfully identified the four homologous sequences to be tested related to BRAF gene. [ABSTRACT FROM AUTHOR]

Abstract: Herein we describe a novel “turn-off” biosensing strategy for thrombin detection based on Surface Enhanced Raman scattering (SERS) and the mediation of spacing between 4-mercaptobenzoic acid (4-MBA) labeled gold nanoparticles (AuNPs). The multiple arginine peptides that initiated gold nano-aggregates incorporating Raman reporter molecules due to the formation of “Hot Spots”, are induced to disband by the addition of thrombin in which the peptides are catalytically cleaved into fragments and thus SERS signals of 4-MBA are sharply declined because of the weakened ability of fragments to induce aggregation. Through this strategy, a novel “turn-off” SERS biosensor for thrombin based on enzymatic amplification is established with sensitivity, selectivity and simplicity as AuNPs and peptides are easily accessible. Compared with non-enzymatic amplification based methods, this newly proposed method has improved sensitivity. The limit of detection was 160fM (at the ratio of signal to noise, S/N=3:1). Further, controlled experiments showed that the method exhibited good selectivity over other proteases. The method demonstrated the capability and the potential for application in complex matrix and future biomarker development. The results also presented the potential and superiority of SERS biosensor based on signal amplification. [Copyright &y& Elsevier]

We describe herein a novel' “turn-on” SERS-based strategy for protease detection based on surface enhanced Raman scattering (SERS) and the mediation of spacing between 4-mercaptobenzoic acid (4-MBA) labeled gold nanoparticles (AuNPs) through enzyme assays. The method employed non-cross-linking aggregation of 4-MBA-modified AuNPs by peptides after treatment with target protease. Thus, SERS signals of 4-MBA are sharply increased because of the decreased electrostatic stability of AuNPs that initiated gold nanoaggregates incorporating Raman reporter molecules due to the formation of “Hot Spots”. Through this strategy, a novel and facile “turn-on” SERS biosensor for trypsin and thrombin based on enzymatic cleavage activity is established with sensitivity, selectivity and simplicity as AuNPs and peptides are easily accessible. Compared with other methods, this newly proposed method has improved sensitivity. The limit of detection was 85 fM (at the ratio of signal to noise, S/N=3:1) for trypsin. Controlled experiments showed that the method exhibited good selectivity over other proteases. We also proved that this principle could be easily adapted to detection of other proteases such as thrombin. The method demonstrated the capability for application in complex matrix samples. The results also presented the potential and superiority of SERS biosensor as a general approach for proteases based on enzyme activity. [ABSTRACT FROM AUTHOR]