Publications by authors named "Kyung Ae Yang"

Aptamers that undergo large conformational rearrangements at the surface of electrolyte-gated field-effect transistor (EG-FETs)-based biosensors can overcome the Debye length limitation in physiological high ionic strength environments. For the sensitive detection of small molecules, carbon nanotubes (CNTs) that approach the dimensions of analytes of interest are promising channel materials for EG-FETs. However, functionalization of CNTs with bioreceptors using frequently reported surface modification strategies (, π-π stacking), requires highly pristine CNTs deposited through methods that are incompatible with low-cost fabrication methods and flexible substrates.

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Per- and polyfluoroalkyl substances (PFAS) are widely detected environmental contaminants, and there is a great need for development of sensor technologies for rapid and continuous monitoring of PFAS. In this study, we have developed fluorescence based aptasensor that can possibly monitor perfluorooctanoic acid (PFOA) in water with limit of detection (LOD) of 0.17 μM.

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Wearable technologies for personalized monitoring require sensors that track biomarkers often present at low levels. Cortisol—a key stress biomarker—is present in sweat at low nanomolar concentrations. Previous wearable sensing systems are limited to analytes in the micromolar-millimolar ranges.

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Fipronil is a broad-spectrum insecticide widely used in agriculture and residential areas; its indiscriminate use leads to environmental pollution and poses health hazards. Early detection of fipronil is critical to prevent the deleterious effects. However, current insecticide analysis methods such as HPLC, LC/MS, and GC/MS are incompetent; they are costly, immobile, time-consuming, laborious, and need skilled technicians.

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Tracking antimalarial drug use and efficacy is essential for monitoring the current spread of antimalarial drug resistance. However, available methods for determining tablet quality and patient drug use are often inaccessible, requiring well-equipped laboratories capable of performing liquid chromatography-mass spectrometry (LC-MS). Here, we report the development of aptamer-based fluorescent sensors for the rapid, specific detection of the antimalarial compounds piperaquine and mefloquine-two slow-clearing partner drugs in current first-line artemisinin-based combination therapies (ACTs).

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Oligonucleotide receptors (aptamers), which change conformation upon target recognition, enable electronic biosensing under high ionic-strength conditions when coupled to field-effect transistors (FETs). Because highly negatively charged aptamer backbones are influenced by ion content and concentration, biosensor performance and target sensitivities were evaluated under application conditions. For a recently identified dopamine aptamer, physiological concentrations of Mg and Ca in artificial cerebrospinal fluid produced marked potentiation of dopamine FET-sensor responses.

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Digital health promises a paradigm shift for medicine where biomarkers in individuals are continuously monitored to improve diagnosis and treatment of disease. To that end, a technology for minimally invasive quantification of endogenous analytes in bodily fluids will be required. Here, we describe a strategy for designing and fabricating hydrogel microfilaments that can penetrate the skin while allowing for optical fluorescence sensing.

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Determination of the amino acid phenylalanine is important for lifelong disease management in patients with phenylketonuria, a genetic disorder in which phenylalanine accumulates and persists at levels that alter brain development and cause permanent neurological damage and cognitive dysfunction. Recent approaches for treating phenylketonuria focus on injectable medications that efficiently break down phenylalanine but sometimes result in detrimentally low phenylalanine levels. We have identified new DNA aptamers for phenylalanine in two formats, initially as fluorescent sensors and then, incorporated with field-effect transistors (FETs).

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Physical isolation of molecular computing elements holds the potential for increasing system complexity by enabling the reuse of standardized components and by protecting the components from environmental degradation. However, once elements have been compartmentalized, methods for communicating into these compartments are needed. We report the compartmentalization of steroid-responsive DNA aptamers within giant unilamellar vesicles (GUVs) that are permeable to steroid inputs.

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Detection of analytes by means of field-effect transistors bearing ligand-specific receptors is fundamentally limited by the shielding created by the electrical double layer (the "Debye length" limitation). We detected small molecules under physiological high-ionic strength conditions by modifying printed ultrathin metal-oxide field-effect transistor arrays with deoxyribonucleotide aptamers selected to bind their targets adaptively. Target-induced conformational changes of negatively charged aptamer phosphodiester backbones in close proximity to semiconductor channels gated conductance in physiological buffers, resulting in highly sensitive detection.

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Aptamer-based sensors offer a powerful tool for molecular detection, but the practical implementation of these biosensors is hindered by costly and laborious sequence engineering and chemical modification procedures. We report a simple strategy for directly isolating signal-reporting aptamers in vitro through systematic evolution of ligands by exponential enrichment (SELEX) that transduce binding events into a detectable change of absorbance via target-induced displacement of a small-molecule dye. We first demonstrate that diethylthiatricarbocyanine (Cy7) can stack into DNA three-way junctions (TWJs) in a sequence-independent fashion, greatly altering the dye's absorbance spectrum.

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Article Synopsis
  • - The systematic evolution of ligands by exponential enrichment (SELEX) is a technique used to isolate aptamers, which are oligonucleotides with strong affinity for specific targets, but traditional methods are time-consuming and labor-intensive.
  • - A new microfluidic approach simplifies SELEX by integrating the selection and amplification stages, combining bead-based reactions with electrokinetic transfer, allowing for efficient on-chip processing without the need for additional components.
  • - This method enables rapid multi-round enrichment of oligonucleotides with significantly increased binding affinity, exemplified by isolating an aptamer for the protein IgA within about 4 hours.
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Artificial receptors for hydrophobic molecules usually have moderate affinities and limited selectivities. We describe three new classes of high affinity hydrophobic receptors for nonaromatic steroids based on deoxyribonucleotides, obtained through five high stringency selections coupled with tailored counter-selections. The isolation of multiple classes of high affinity steroid receptors demonstrates the surprising breadth of moderately sized hydrophobic binding motifs (<40 nucleotides) available to natural nucleic acids.

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We present a microfluidic approach to integrated isolation of DNA aptamers via systematic evolution of ligands by exponential enrichment (SELEX). The approach employs a microbead-based protocol for the processes of affinity selection and amplification of target-binding oligonucleotides, and an electrophoretic DNA manipulation scheme for the coupling of these processes, which are required to occur in different buffers. This achieves the full microfluidic integration of SELEX, thereby enabling highly efficient isolation of aptamers in drastically reduced times and with minimized consumption of biological material.

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We recently optimized a procedure that directly yields aptameric sensors for small molecules in so-called structure-switching format. The protocol has a high success rate, short time, and is sufficiently simple to be readily implemented in a non-specialist laboratory. We provide a stepwise guide to this selection protocol.

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We present a computational learning method for bio-molecular classification. This method shows how to design biochemical operations both for learning and pattern classification. As opposed to prior work, our molecular algorithm learns generic classes considering the realization in vitro via a sequence of molecular biological operations on sets of DNA examples.

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Oligonucleotide-based receptors or aptamers can interact with small molecules, but the ability to achieve high-affinity and specificity of these interactions depends strongly on functional groups or epitopes displayed by the binding targets. Some classes of targets are particularly challenging: for example, monosaccharides have scarce functionalities and no aptamers have been reported to recognize, let alone distinguish from each other, glucose and other hexoses. Here we report aptamers that differentiate low-epitope targets such as glucose, fructose or galactose by forming ternary complexes with high-epitope organic receptors for monosaccharides.

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Molecular beacons are efficient and useful tools for quantitative detection of specific target nucleic acids. Thanks to their simple protocol, molecular beacons have great potential as substrates for biomolecular computing. Here we present a molecular beacon-based biomolecular computing method for quantitative detection and analysis of target nucleic acids.

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Biomolecules inside a microfluidic system can be used to solve computational problems, such as theorem proving, which is an important class of logical reasoning problems. In this article, the Boolean variables (literals) were represented using single-stranded DNA molecules, and theorem proving was performed by the hybridization and ligation of these variables into a double-stranded "solution" DNA. Then, a novel sequential reaction mixing method in a microfluidic chip was designed to solve a theorem proving problem, where a reaction loop and three additional chambers were integrated and controlled by pneumatic valves.

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We report a straightforward evolutionary procedure to build an optimal sensor array from a pool of DNA sequences oriented toward three-way junctions. The individual sensors were mined from this pool under separate selection pressures to interact with four steroids, while allowing cross-reactivity, in a manner designed to achieve perfect classification of individual steroids. The resulting sensor array had three sensors and displayed discriminatory capacity between steroid classes over full ranges of concentrations.

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The phytocystatins of plants are members of the cystatin superfamily of proteins, which are potent inhibitors of cysteine proteases. The Arabidopsis genome encodes seven phytocystatin isoforms (AtCYSs) in two distantly related AtCYS gene clusters. We selected AtCYS1 and AtCYS2 as representatives for each cluster and then generated transgenic plants expressing the GUS reporter gene under the control of each gene promoter.

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Recent progress in molecular computation suggests the possibility of pattern classification in vitro. Weighted sum is a primitive operation required by many pattern classification problems. Here we present a DNA-based molecular computation method for implementing the weighted-sum operation and its use for molecular pattern classification in a test tube.

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Probe design is one of the most important tasks in successful deoxyribonucleic acid microarray experiments. We propose a multiobjective evolutionary optimization method for oligonucleotide probe design based on the multiobjective nature of the probe design problem. The proposed multiobjective evolutionary approach has several distinguished features, compared with previous methods.

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The use of DNA molecules as a physical computational material has attracted much interest, especially in the area of DNA computing. DNAs are also useful for logical control and analysis of biological systems if efficient visualization methods are available. Here we present a quick and simple visualization technique that displays the results of the DNA computing process based on a colorimetric change induced by gold nanoparticle aggregation, and we apply it to the logic-based detection of biomolecules.

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Many DNA-based technologies, such as DNA computing, DNA nanoassembly and DNA biochips, rely on DNA hybridization reactions. Previous hybridization models have focused on macroscopic reactions between two DNA strands at the sequence level. Here, we propose a novel population-based Monte Carlo algorithm that simulates a microscopic model of reacting DNA molecules.

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