Selective and sensitive detection of nucleic acid biomarkers is of great significance in early-stage diagnosis and targeted therapy. Therefore, the development of diagnostic methods capable of detecting diseases at the molecular level in biological fluids is vital to the emerging revolution in the early diagnosis of diseases. However, the vast majority of the currently available ultrasensitive detection strategies involve either target/signal amplification or involve complex designs. Here, using a p53 tumor suppressor gene whose mutation has been implicated in more than 50% of human cancers, we show a background-free ultrasensitive detection of this gene on a simple platform. The sensor exhibits a relatively static mid-FRET state in the absence of a target that can be attributed to the time-averaged fluorescence intensity of fast transitions among multiple states, but it undergoes continuous dynamic switching between a low-and a high-FRET state in the presence of a target, allowing a high-confidence detection. In addition to its simple design, the sensor has a detection limit down to low femtomolar (fM) concentration without the need for target amplification. We also show that this sensor is highly effective in discriminating against single-nucleotide polymorphisms (SNPs). Given the generic hybridization-based detection platform, the sensing strategy developed here can be used to detect a wide range of nucleic acid sequences enabling early diagnosis of diseases and screening genetic disorders.

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.

Cytosine (C)-rich regions of single-stranded DNA or RNA can fold into a tetraplex structure called i-motifs, which are typically stable under acidic pHs due to the need for protons to stabilize C–C interactions. While new studies have shown evidence for the formation of i-motifs at neutral and even physiological pH, it is not clear whether i-motifs can stably form in cells where DNA experiences topological constraint and crowding. Similarly, several studies have shown that a molecularly crowded environment promotes the formation of i-motifs at physiological pH; however, whether the intracellular crowding counteracts the topological destabilization of i-motifs is yet to be investigated. In this manuscript, using fluorescence resonance energy transfer (FRET)-based single-molecule analyses of human telomeric (hTel) i-motifs embedded in nanocircles as a proof-of-concept platform, we investigated the overall effects of crowding and topological constraint on the i-motif behavior. The smFRET analysis of the nanoassembly showed that the i-motif remains folded at pH 5.5 but unfolds at higher pHs. However, in the presence of a crowder (30% PEG 6000), i-motifs are formed at physiological pH overcoming the topological constraint imposed by the DNA nanocircles. Analysis of FRET-time traces show that the hTel sequence primarily assumes the folded state at pH ≤7.0 under crowding, but it undergoes slow conformational transitions between the folded and unfolded states at physiological pH. Our demonstration that the i-motif can form under cell-mimic crowding and topologically constrained environments may provide new insights into the potential biological roles of i-motifs and also into the design and development of i-motif-based biosensors, therapy, and other nanotechnological applications.