Applications of Catalytic Hairpin Assembly Reaction in Biosensing

Nucleic acids are considered as perfect programmable materials for cascade signal amplification and not merely as genetic information carriers. Among them, catalytic hairpin assembly (CHA), an enzyme-free, high-efficiency, and isothermal amplification method, is a typical example. A typical CHA reaction is initiated by single-stranded analytes, and substrate hairpins are successively opened, resulting in thermodynamically stable duplexes. CHA circuits, which were first proposed in 2008, present dozens of systems today. Through in-depth research on mechanisms, the CHA circuits have been continuously enriched with diverse reaction systems and improved analytical performance. After a short time, the CHA reaction can realize exponential amplification under isothermal conditions. Under certain conditions, the CHA reaction can even achieve 600 000-fold signal amplification. Owing to its promising versatility, CHA is able to be applied for analysis of various markers in vitro and in living cells. Also, CHA is integrated with nanomaterials and other molecular biotechnologies to produce diverse readouts. Herein, the varied CHA mechanisms, hairpin designs, and reaction conditions are introduced in detail. Additionally, biosensors based on CHA are presented. Finally, challenges and the outlook of CHA development are considered.

Molecular dynamics simulation-guided toehold mediated strand displacement probe for single-nucleotide variants detection

Single nucleotide variant (SNV) has become an emerging biomarker for various diseases such as cancers and infectious diseases. Toehold-mediated strand displacement (TMSD), the core reaction of DNA nanotechnology, has been widely leveraged to identify SNVs. However, inappropriate choice of mismatch location results in poor discrimination ability. Here, we comprehensively investigate the effect of mismatch location on TMSD kinetics by molecular dynamic simulation tool oxDNA through umbrella sampling and forward flux sampling disclosing that mismatches at the border of the toehold and branch migration domain yield the lowest TMSD reaction rate. Nine disease-related SNVs (SARS-CoV-2-D614G, EGFR-L858R, EGFR-T790M, KRAS-G12R, etc.) were tested experimentally showing a good agreement with simulation. The best choice of mismatch location enables high discrimination factor with a median of 124 for SNV and wild type. Coupling with a probe-sink system, a low variant allele frequency of 0.1% was detected with 3 S/N. We successfully used the probes to detect SNVs with high confidence in the PCR clones of constructed plasmids. This work provides mechanistic insights into TMSD process at the single-nucleotide level and can be a guidance for the design of TMSD system with fine-tuning kinetics for various applications in biosensors and nanotechnology.

Small RNA Biosensor Design Strategy To Mitigate Off-Analyte Response

Several bottlenecks in the design of current sensor technologies for small noncoding RNA must be addressed. The small size of the sensors and the large number of other nucleotides that may have sequence similarity makes selectivity a real concern. Many of the current sensors have one strand with an exposed region called a toehold. The toehold serves as a place for the analyte nucleic acid strand to bind and initiate competitive displacement of sensors' secondary strands. Since the toehold region is not protected, any endogenous oligonucleotide sequences that are similar or only different by a few nucleic acids will interact with the toehold and cause false signals. To address sensor selectivity, we investigated how the toehold location in the sensor impacts the sensitivity and selectivity for the analyte of interest. We will discuss the differences in sensitivity and selectivity for a miR-146a-5p biosensor in the presence of different naturally occurring mismatch sequences. We found that altering the toehold location lowered the rate of the false signal from off-analyte microRNA by upward of 20 percentage points. Detection limits as low as 56 pM were observed when the sensor concentration was 5 nM. The findings herein are broadly applicable to other small and large RNAs as well as other types of sensing platforms.