Single-Molecule FRET-Based Multiplexed Detection.

Single-molecule multiplexed detection is a high-promise toolkit for the expanding field of biosensing and molecular diagnostics. Among many single-molecule techniques available today for biomarker sensing including fluorescence, force, electrochemical, spectroscopic, barcoding, and other techniques, fluorescence-based approaches are arguably the most widely used methods due to their high sensitivity, selectivity, and readily available fluorophore-labeling schemes for a wide variety of biomolecules. However, multiplexed imaging using fluorescence techniques has proven to be challenging due to the sophisticated labeling schemes often requiring multiple FRET (fluorescence resonance energy transfer) pairs and/or excitation sources, which lead to overlapping signals and complicate data analysis. Here, we describe a single-molecule FRET method that enables multiplexed analysis while still using only one FRET pair, and thus the described approach is a significant step forward from conventional FRET methods.

Computational generation and characterization of IsdA-binding aptamers with single-molecule FRET analysis.

Staphylococcus aureus is a major foodborne bacterial pathogen. Early detection of S. aureus is crucial to prevent infections and ensure food quality. The iron-regulated surface determinant protein A (IsdA) of S. aureus is a unique surface protein necessary for sourcing vital iron from host cells for the survival and colonization of the bacteria. The function, structure, and location of the IsdA protein make it an important protein for biosensing applications relating to the pathogen. Here, we report an in-silico approach to develop and validate high-affinity binding aptamers for the IsdA protein detection using custom-designed in-silico tools and single-molecule Fluorescence Resonance Energy Transfer (smFRET) measurements. We utilized in-silico oligonucleotide screening methods and metadynamics-based methods to generate 10 aptamer candidates and characterized them based on the Dissociation Free Energy (DFE) of the IsdA-aptamer complexes. Three of the aptamer candidates were shortlisted for smFRET experimental analysis of binding properties. Limits of detection in the low picomolar range were observed for the aptamers, and the results correlated well with the DFE calculations, indicating the potential of the in-silico approach to support aptamer discovery. This study showcases a computational SELEX method in combination with single-molecule binding studies deciphering effective aptamers against S. aureus IsdA, protein. The established approach demonstrates the ability to expedite aptamer discovery that has the potential to cut costs and predict binding efficacy. The application can be extended to designing aptamers for various protein targets, enhancing molecular recognition, and facilitating the development of high-affinity aptamers for multiple uses.

FRET-Based Single-Molecule Detection of Pathogen Protein IsdA Using Computationally Selected Aptamers.

Iron-regulated surface determinant protein A (IsdA) is a key surface protein found in the foodborne bacteria─Staphylococcus aureus (S. aureus)─which is known to be critical for bacterial survival and colonization. S. aureus is pathogenic and has been linked to foodborne diseases; thus, early detection is critical to prevent diseases caused by this bacterium. Despite IsdA being a specific marker for S. aureus and several detection methods have been developed for sensitive detection of this bacteria such as cell culture, nucleic acids amplification, and other colorimetric and electrochemical methods, the detection of S. aureus through IsdA is underdeveloped. Here, by combining computational generation of target-guided aptamers and fluorescence resonance energy transfer (FRET)-based single-molecule analysis, we presented a widely applicable and robust detection method for IsdA. Three different RNA aptamers specific to the IsdA protein were identified and their ability to switch a FRET construct to a high-FRET state in the presence of protein was verified. The presented approach demonstrated the detection of IsdA down to picomolar levels (×10-12 M, equivalent to ∼1.1 femtomoles IsdA) with a dynamic range extending to ∼40 nM. The FRET-based single-molecule technique that we reported here is capable of detecting the foodborne pathogen protein IsdA with high sensitivity and specificity and has a broader application in the food industry and aptamer-based sensing field by enabling quantitative detection of a wide range of pathogen proteins.

Single-Molecule Sensor for High-Confidence Detection of miRNA.

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.

Single-Molecule FRET-Based Dynamic DNA Sensor.

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.

Single-Molecule Analysis of Nanocircle-Embedded I-Motifs under Crowding.

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.